Systems and methods for monitoring neural activity

Abstract

A method for monitoring neural activity responsive to a stimulus in the brain of a subject under general anesthesia, the method comprising: applying the stimulus to one or more of at least one electrode implanted in a target neural structure of the brain; detecting, at one or more of the at least one electrode in or near the target neural structure of the brain, a resonance response from the target neural structure induced by the stimulus; and determining one or more waveform characteristics of the detected resonance response.

Description

Technical Field

[0001] The present disclosure relates to deep brain stimulation (DBS), and more particularly, to methods and systems for monitoring neural activity in response to DBS. Background Art

[0002] Deep brain stimulation (DBS) is an established therapy for movement disorders and other neurological disorders, including epilepsy, obsessive-compulsive disorder, and depression. DBS is typically administered to patients whose symptoms cannot be adequately controlled by medications alone. DBS involves surgically implanting electrodes into or near specific neural structures in the brain, typically the subthalamic nucleus (STN), the globus pallidus internus (GPi), and / or the thalamus. The electrodes are connected to a neurostimulator that is typically implanted inside the body and configured to deliver electrical pulses to the target area. It is believed that this electrical stimulation interrupts abnormal brain activity associated with the patient's symptoms. The stimulation parameters can be adjusted using a controller outside the body that is remotely connected to the neurostimulator.

[0003] Although established DBS techniques have been shown to be effective in alleviating movement disorder symptoms, existing technology devices still have several limitations. In particular, established techniques for intraoperative testing of DBS electrodes to ensure correct positioning in the brain, such as x-ray imaging, microelectrode recording, and clinical evaluation, may be inaccurate. As a result, the electrodes are often implanted in suboptimal positions, which leads to diminished therapeutic effects and adverse side effects. After implantation, DBS devices require manual adjustment by a clinician. This typically involves the clinician adjusting the parameters of the stimulation based on a largely subjective assessment of immediate or short-term improvement in the patient's symptoms. Since the therapeutic effects may occur slowly and since the DBS parameter space is large, the task of finding a set of optimal parameters is time- and cost-inefficient and can lead to suboptimal therapeutic effects. In addition, continuously applying electrical stimulation using conventional DBS can also lead to suboptimal treatment outcomes, including adverse side effects and shortened battery life of the DBS stimulator. Summary of the Invention

[0004] According to a first aspect of the present disclosure, there is provided a method for monitoring neural activity in a subject's brain in response to a stimulus, the method comprising: inducing general anesthesia in the subject; applying the stimulus to one or more of at least one electrode implanted in the brain; detecting, at one or more of the at least one electrode in or near a target neural structure of the brain, a resonance response from the target neural structure induced by the stimulus; and determining one or more waveform characteristics of the detected resonance response.

[0005] According to another aspect of the present disclosure, there is provided a method for monitoring neural activity responsive to a stimulus in the brain of a subject under general anesthesia, the method comprising: inducing general anesthesia in the subject; applying the stimulus to one or more of at least one electrode implanted in the brain; detecting, at one or more of the at least one electrode in or near a target neural structure of the brain, a resonance response from the target neural structure induced by the stimulus; and determining one or more waveform characteristics of the detected resonance response.

[0006] The one or more waveform characteristics may be determined based on at least a portion of a second or subsequent cycle in the detected resonance response.

[0007] The one or more waveform characteristics may include one or more of the following: a) the frequency of the resonance response; b) the temporal envelope of the resonance response; c) the amplitude of the resonance response; d) the fine structure of the resonance response; e) the decay rate of the resonance response; f) the delay between the onset of the stimulus and the onset of the temporal characteristics of the resonance response.

[0008] The stimulus may include a plurality of pulses.

[0009] The step of determining the one or more waveform characteristics may include comparing a first characteristic within two or more cycles of the detected resonance response. The step of determining the one or more waveform characteristics may include determining the change in the first characteristic within the two or more cycles. The step of determining the one or more waveform characteristics may include determining the rate of change of the first characteristic within the two or more cycles.

[0010] The resonance response may include a plurality of resonance components. One or more of the plurality of resonance components may originate from neural structures different from the target neural structure.

[0011] The method may further comprise: adjusting the position of one or more of the at least one electrode based on the one or more determined waveform characteristics.

[0012] The method may further comprise: adapting the stimulus based on the one or more determined waveform characteristics of the resonance response. The adaptation may include adjusting one or more of the frequency, amplitude, pulse width, electrode configuration, or morphology of the stimulus.

[0013] The method may further comprise: correlating the detected resonance response with a template resonance response; and adapting the stimulus based on the correlation. The method may further comprise: correlating the one or more determined waveform characteristics with one or more predetermined thresholds; and adapting the stimulus based on the correlation.

[0014] The stimulation can be non-therapeutic or therapeutic.

[0015] The stimulation can include a patterned signal that includes a plurality of bursts spaced apart by a first time period, each burst including a plurality of pulses spaced apart by a second time period, where the first time period is greater than the second time period, and where the detection is performed during one or more of the first time periods. The first time period can be greater than or equal to the second time period. The plurality of pulses within at least one of the bursts can have different amplitudes. The different amplitudes can be selected to produce an amplitude ramp of sequential pulses in the at least one of the bursts. The final pulse in each of the plurality of bursts can be substantially the same.

[0016] The method can further include: estimating a patient's state based on the determined one or more waveform characteristics. In such a case, the method can further include: diagnosing the patient and / or generating one or more alerts associated with the estimated patient state based on the estimation of the patient's state; and outputting the one or more alerts.

[0017] The method can further include: applying a second stimulation to a target neural structure in the brain; at one or more of the at least one electrode implanted in or near the target neural structure, detecting a second resonance response from the target neural structure induced by the second stimulation; and determining one or more second waveform characteristics of the detected second resonance response.

[0018] The method can further include: estimating the degree of progression of a disease associated with the patient based on the one or more first waveform characteristics and the one or more second waveform characteristics.

[0019] The method can further include: determining the effectiveness of a therapy provided to the patient based on the one or more first waveform characteristics and the one or more second waveform characteristics. The therapy can be medication or deep brain stimulation.

[0020] The at least one electrode can include two or more electrodes located within different neural structures in the brain. The at least one electrode can include two or more electrodes located within different hemispheres of the brain.

[0021] The method can further include: determining whether one or more of the at least one electrode is positioned within the target neural network based on the detected resonance response. The method can further include: moving one or more of the first electrode and the second electrode based on the detected resonance response.

[0022] The steps of applying the stimulus, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response may be repeated one or more times such that a series of resonance responses are detected, each resonance response in response to the application of a separate signal. These steps may be repeated until it is determined that one or more of the at least one electrode are positioned within the target nerve structure.

[0023] The method may further include: comparing common waveform characteristics between two or more detected resonance responses.

[0024] The method may further include: comparing the degree of change of common characteristics between two or more detected resonance responses.

[0025] The method may further include: determining the rate of change of common characteristics between two or more detected resonance responses.

[0026] The method may further include: selecting one or more of the at least one electrode to be used for therapeutic stimulation of the target nerve structure based on the one or more waveform characteristics; and applying therapeutic stimulation to the target nerve structure through the selected one or more of the at least one electrode.

[0027] The method may further include: inserting the at least one electrode into the brain along a predetermined trajectory; wherein while inserting the at least one electrode, the steps of applying the stimulus, determining the resonance response, and determining one or more waveform characteristics of the detected resonance response are repeated to generate a resonance response profile relative to the predetermined trajectory and the target nerve structure.

[0028] The resonance response profile may be used to determine the position of the one or more electrodes relative to the target nerve structure.

[0029] The at least one electrode may include a plurality of electrodes, and wherein different combinations of the at least one electrode may be used to repeat the steps of applying the stimulus, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response to generate a resonance response profile.

[0030] The method may further include: selecting one or more of the at least one electrode based on the nerve response profile; and applying therapeutic stimulation to the selected one or more of the at least one electrode. The selected one or more of the at least one electrode may include a plurality of electrodes.

[0031] The one or more of the at least one electrode used to apply the stimulus may include at least two electrodes. Similarly, the one or more of the at least one electrode used to detect the resonance response may include at least two electrodes.

[0032] The neural target structure can be part of the cortico-basal ganglia-thalamo-cortical circuit.

[0033] The neural target structure can be the subthalamic nucleus, the internal globus pallidus, the substantia nigra reticulata, the pedunculopontine nucleus.

[0034] According to another aspect of the present disclosure, there is provided a neural stimulation system, comprising: a lead having at least one electrode adapted to be implanted in or near a target nerve structure in the brain; a signal generator selectively coupled to one or more of the at least one electrode and configured to generate a stimulation for stimulating the target nerve structure; a measuring device selectively coupled to one or more of the at least one electrode and configured to detect a resonance response from the target nerve structure induced by the stimulation; and a processing unit coupled to the measuring device and configured to determine one or more waveform characteristics of the detected resonance response.

[0035] The one or more waveform characteristics can be determined based on at least a portion of a second or subsequent cycle in the detected resonance response.

[0036] The one or more waveform characteristics include one or more of the following: a) the frequency of the resonance response; b) the temporal envelope of the resonance response; c) the amplitude of the resonance response; d) the fine structure of the resonance response; e) the decay rate of the resonance response; f) the delay between the onset of the stimulation and the onset of the temporal characteristics of the resonance response.

[0037] The stimulation can include a plurality of pulses.

[0038] When determining the one or more waveform characteristics, the processing unit can be configured to correlate a first characteristic within two or more cycles of the detected resonance response.

[0039] When determining the one or more waveform characteristics, the processing unit can be configured to determine the degree of change of the first characteristic within the two or more cycles.

[0040] When determining the one or more waveform characteristics, the processing unit can be configured to determine the rate of change of the first characteristic within the two or more cycles.

[0041] The resonance response can be detected at one or more electrodes different from the one or more electrodes applying the stimulation.

[0042] The resonance response can include a plurality of resonance components.

[0043] The processing unit may be coupled to the signal generator and configured to selectively control the output of the signal generator.

[0044] The processing unit may be configured to: control the signal generator to adjust the stimulus based on the one or more determined waveform characteristics of the resonance response.

[0045] The processing unit may further be configured to: associate the detected resonance response with a template resonance response; and control the signal generator to adjust the stimulus based on the association.

[0046] The processing unit may be configured to: associate the one or more determined waveform characteristics with one or more predetermined thresholds; and control the signal generator to adjust the stimulus based on the association.

[0047] The adjustment may include adjusting one or more of the frequency, amplitude, pulse width, electrode configuration, or morphology of the stimulus.

[0048] The stimulus may be non-therapeutic or therapeutic.

[0049] The stimulus may include a patterned signal that includes a plurality of bursts spaced apart by a first time period, each burst including a plurality of pulses spaced apart by a second time period, where the first time period is greater than the second time period, and where the detection is performed during one or more of the first time periods. The first time period is greater than or equal to the second time period. The plurality of pulses within at least one of the bursts may have different amplitudes.

[0050] The different amplitudes may be selected to produce an amplitude ramp of sequential pulses in the at least one of the bursts.

[0051] The final pulse in each of the plurality of bursts is preferably substantially the same.

[0052] The processing unit may be configured to: estimate a patient's state based on the determined one or more waveform characteristics.

[0053] The processing unit may be configured to: diagnose the patient based on the estimate of the patient's state.

[0054] The processing unit may be configured to: generate one or more alerts associated with the estimated patient state; and output the one or more alerts.

[0055] The processing unit may be configured to: estimate the degree of progression of a disease associated with the patient or the effectiveness of a therapy provided to the patient based on the one or more waveform characteristics and the one or more second waveform characteristics, the one or more second waveform characteristics being determined based on a second resonance response detected after the resonance response.

[0056] The therapy may be medication or deep brain stimulation.

[0057] The system may further include: a second lead having at least one second electrode adapted to be implanted in or near a second target structure in the brain; wherein the signal generator is selectively coupled to one or more of the at least one second electrode and is configured to generate a stimulation for stimulating the second target nerve structure; wherein the measuring device is selectively coupled to one or more of the at least one second electrode and is configured to detect a resonance response from the second target nerve structure induced by the stimulation; a processing unit coupled to the measuring device and configured to determine one or more waveform characteristics of the detected resonance response from the second target nerve structure.

[0058] The lead and the second lead may be located within or near different nerve structures in the brain. The lead and the second lead may be located within different hemispheres of the brain.

[0059] The processing unit may be configured to: determine whether one or more of the at least one electrode are positioned within the target neural network based on the detected resonance response.

[0060] The signal generator, the measuring device, and the processing unit may be configured to repeat the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response. In this case, the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response may be repeated until the processing unit determines that one or more of the at least one electrode are positioned within the target nerve structure.

[0061] The processing unit may be configured to control the signal generator: select one or more of the at least one electrode to be used for therapeutic stimulation of the target nerve structure based on the one or more waveform characteristics; and apply therapeutic stimulation to the target nerve structure through the selected one or more of the at least one electrode.

[0062] The steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response may be repeated while inserting the at least one electrode; and the processing unit may further be configured to generate a resonance response profile with respect to the predetermined trajectory and the target nerve structure.

[0063] The processing unit may be configured to determine the position of the one or more electrodes relative to the target nerve structure based on the resonance response profile.

[0064] The at least one electrode may include a plurality of electrodes. In such a case, different combinations of the at least one electrode may be used to repeat the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response to generate a resonance response profile.

[0065] The processing unit may be configured to: select one or more of the at least one electrode based on the nerve response profile; and control the signal generator to apply a therapeutic stimulation to the selected one or more of the at least one electrode.

[0066] The selected one or more of the at least one electrode may include a plurality of electrodes.

[0067] One or more of the at least one electrode for applying the stimulation may include at least two electrodes, and / or one or more of the at least one electrode for detecting the resonance response includes at least two electrodes.

[0068] The nerve target structure may be part of the cortico-basal ganglia-thalamo-cortical circuit.

[0069] The nerve target structure may be the subthalamic nucleus, the internal globus pallidus, the substantia nigra reticulata, the pedunculopontine nucleus.

[0070] According to another aspect of the present disclosure, a method for monitoring neural activity in a subject's brain in response to a stimulation is provided, the method comprising:

[0071] a. Inducing general anesthesia in the subject;

[0072] b. Applying a stimulation to a target nerve structure in the brain; and

[0073] c. Detecting a neural response evoked by the stimulation at an electrode implanted in or near the target nerve structure.

[0074] Wherein the stimulation includes a patterned signal, the patterned signal includes a plurality of bursts spaced apart by a first time period, each burst includes a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

[0075] According to another aspect of the present disclosure, there is provided a method for monitoring neural activity in the brain of a subject under general anesthesia in response to a stimulus, the method comprising:

[0076] a. applying a stimulus to a target neural structure in the brain; and

[0077] b. detecting a neural response evoked by the stimulus at an electrode implanted in or near the target neural structure,

[0078] Wherein the stimulation includes a patterned signal, the patterned signal includes a plurality of bursts spaced apart by a first time period, each burst includes a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

[0079] The first time period is preferably greater than or equal to the second time period.

[0080] The stimulation is preferably biphasic. The plurality of pulses in a burst may have different amplitudes. The different amplitudes may be selected to produce a ramp. The final pulse in each of the plurality of bursts may be substantially the same. The stimulation may be patterned to be non-therapeutic or therapeutic.

[0081] In any of the above aspects, general anesthesia in the subject may be induced using a reagent selected from propofol, thiopental, etomidate, methohexital, ketamine, and sevoflurane.

[0082] In any of the above aspects, general anesthesia in the subject may be maintained using a reagent selected from isoflurane, sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide, and xenon.

[0083] In any of the above aspects, general anesthesia in the subject may be maintained using fentanyl, fentanyl derivatives, barbiturates, or benzodiazepines.

[0084] In any of the above aspects, general anesthesia in the subject may be maintained using fentanyl, remifentanil, or fentanyl derivatives.

[0085] In any of the above aspects, general anesthesia in the subject may be induced using propofol and maintained using a combination of sevoflurane and remifentanil. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Embodiments of the present disclosure will now be described by way of non - limiting examples with reference to the accompanying drawings, in which:

[0087] Figure 1 is a diagram showing resonance from a neural structure in response to a deep brain stimulation (DBS) signal;

[0088] Figure 2 is a diagram showing resonance from a neural structure in response to a patterned DBS signal;

[0089] Figure 3 is a diagram showing evoked resonance in response to 10 consecutive pulses of a DBS signal;

[0090] Figure 4 is a diagram showing the range and variance of the peak amplitude of the resonance response to continuous and patterned DBS;

[0091] FIG. 5a is a diagram showing neural resonance induced by a continuous non - therapeutic patterned DBS signal;

[0092] FIG. 5b is a diagram showing neural resonance induced by a continuous therapeutic patterned DBS signal;

[0093] FIG. 5c is a diagram showing neural resonance after transitioning from a continuous therapeutic DBS signal to a non - therapeutic DBS signal;

[0094] FIG. 5d is a diagram showing the estimated frequency of evoked resonance in response to a non - therapeutic DBS signal;

[0095] FIG. 5e is a diagram showing the estimated frequency of evoked resonance in response to a therapeutic DBS signal;

[0096] FIG. 5f is a diagram showing the estimated frequency of evoked resonance in response to a transition between a therapeutic DBS signal and a non - therapeutic DBS signal;

[0097] FIG. 6a is a diagram showing neural resonance induced by a continuous non - therapeutic patterned DBS signal;

[0098] FIG. 6b is a diagram showing neural resonance induced by a continuous therapeutic patterned DBS signal;

[0099] FIG. 6c is a diagram showing neural resonance after transitioning from a continuous therapeutic DBS signal to a non - therapeutic DBS signal;

[0100] FIG. 6d is a diagram showing the estimated frequency of evoked resonance in response to a non - therapeutic DBS signal;

[0101] FIG. 6e is a diagram showing the estimated frequency of evoked resonance in response to a therapeutic DBS signal;

[0102] FIG. 6f is a graph showing the estimated frequency of the evoked resonance in response to the transition between the therapeutic DBS signal and the non-therapeutic DBS signal;

[0103] FIG. 7a is a graph showing the evoked resonance that begins to diverge into two peaks in response to patterned DBS with an amplitude of 1.5 mA;

[0104] FIG. 7b is a graph showing the evoked resonance that diverges into two peaks in response to patterned DBS with an amplitude of 2.25 mA;

[0105] FIG. 7c is a graph showing two separate evoked resonance peaks in response to patterned DBS with an amplitude of 3.375 mA;

[0106] Figure 8 is a schematic diagram of the tip of an electrode lead for implantation in the brain;

[0107] Figure 9 is a schematic diagram of an electrode lead implanted in the subthalamic nucleus of the brain;

[0108] Figure 10 is a schematic diagram of a system for managing DBS;

[0109] Figure 11 is a flowchart showing the process of positioning a DBS electrode in the brain;

[0110] Figure 12 is a flowchart showing the process of monitoring and processing resonance responses in response to stimulation at multiple electrodes at multiple electrodes;

[0111] Figure 13 is according to Figure 12 the resonance response to the stimulation signal measured at different electrodes implanted in the brain shown in the process;

[0112] Figure 14 is according to Figure 12 the resonance response to the stimulation signals applied at different electrodes measured at different electrodes implanted in the brain shown in the process;

[0113] Figure 15 is a flowchart showing the process of determining the parameters of the DBS stimulation signal based on the patient's medication;

[0114] Figure 16 is a flowchart showing the process of generating a stimulation signal with closed-loop feedback based on the evoked resonance at the target nerve structure;

[0115] Figure 17 is a flowchart showing another process of generating a stimulation signal with closed-loop feedback based on the evoked resonance at the target nerve structure;

[0116] Figure 18 Graphically shows the switching between therapeutic and non-therapeutic stimulation periods of the resonance activity characteristics of a process according to Figure 17 with respect to the evoked response;

[0117] FIG. 19a shows a patterned stimulation signal according to an embodiment of the present disclosure;

[0118] FIG. 19b shows another patterned stimulation signal according to an embodiment of the present disclosure;

[0119] Figure 20 Shows the results of a motor function test of a patient receiving DBS;

[0120] FIGS. 21a to 21g are diagrams showing the neural resonance evoked by a continuous therapeutic patterned DBS signal;

[0121] Figure 22 is a three-dimensional reconstruction of an electrode array implanted in the STN (smaller mass) and substantia nigra (larger mass) of a patient;

[0122] FIG. 23 is a combined scan of an MRI and a CT of a patient's brain, which shows the positioning of the electrode array;

[0123] Figure 24 Graphically shows the change of ERNA amplitude with respect to the electrode position;

[0124] Figure 25A Graphically shows the ERNA frequency of 19 cerebral hemispheres versus the DBS amplitude;

[0125] Figure 25B Graphically shows the ERNA amplitude of 19 cerebral hemispheres versus the DBS amplitude;

[0126] Figure 25C Graphically shows the relative β (RMS 13-30Hz / RMS 4-45Hz ) of 19 cerebral hemispheres versus the DBS amplitude;

[0127] Figure 25D Graphically shows the relative β associated with the ERNA frequency (ρ = 0.601, p < 0.001) of 19 cerebral hemispheres;

[0128] Figure 26A Graphically shows the washout of the ERNA frequency within 15 s continuously after DBS and in the last 15 s before DBS in 19 cerebral hemispheres;

[0129] Figure 26B Graphically shows the washout of the ERNA amplitude of 19 cerebral hemispheres;

[0130] Figure 26C Graphically show the relative β washout of 19 cerebral hemispheres; and

[0131] Figure 26D Graphically show the washout of 19 cerebral hemispheres in the 200 - 400 Hz HFO frequency band

[0132] Figure 27 Is a diagram of ERNA in the brains of patients under awake and general anesthesia in response to DBS stimulation;

[0133] Figure 28 Is a graph showing the changes in ERNA at four electrodes in the electrode array at the time of implantation (awake) and 560 days after general anesthesia;

[0134] Figure 29 Is a diagram of ERNA measured at different electrodes in the left STN of the brain of a patient under general anesthesia in response to stimulation signals applied at different electrodes;

[0135] Figure 30 Is a diagram of ERNA measured at different electrodes in the right STN of the brain of a patient under general anesthesia in response to stimulation signals applied at different electrodes;

[0136] Figure 31 Is a diagram of ERNA measured at different electrodes in the left STN of the brain of a patient under general anesthesia in response to stimulation signals applied at different electrodes;

[0137] Figure 32 Is a diagram of ERNA measured at different electrodes in the right STN of the brain of a patient under general anesthesia in response to stimulation signals applied at different electrodes;

[0138] Figure 33 Is a diagram of ERNA measured at different electrodes in the left STN of the brain of a patient under general anesthesia in response to stimulation signals applied at different electrodes;

[0139] Figure 34 Is a graph showing the range, median, and interquartile range of ERNA amplitudes measured at different electrodes in the STN of the brains of patients under awake and general anesthesia in response to stimulation signals applied at different electrodes;

[0140] Figures 35A to 35B Is a rank graph showing the correlation between ERNA amplitudes measured at electrodes in the STN of the brains of patients under awake and general anesthesia in response to stimulation signals applied at different electrodes;

[0141] Figure 36Illustration of ERNA measured at a single electrode in the STN of the brain of a patient under general anesthesia in response to a stimulation signal;

[0142] Figures 37a and 37b are graphs showing the range, median, and interquartile range of the inter-peak latency of ERNA measured at electrodes in 36 STNs of the brains of patients under awake and general anesthesia induced by propofol and sevoflurane in response to stimulation signals applied at different electrodes;

[0143] Figures 38 to 40 Illustration of ERNA measured in the STN of the brain of a sheep under general anesthesia at 3.375 mA, 5.063 mA, and 7.594 mA, respectively, in response to stimulation signals applied at different electrodes;

[0144] Figures 41 to 43 Illustration of ERNA measured in the STN of the brain of a sheep under general anesthesia at 3.375 mA, 5.063 mA, and 7.594 mA, respectively, in response to stimulation signals applied at different electrodes. Detailed Description

[0145] Embodiments of the present disclosure relate to improvements in neural stimulation in the brain. DBS devices typically apply a constant amplitude stimulation to a target region of the brain at a constant frequency of 130 Hz. The inventors have determined not only that applying such stimulation elicits a neural response from the target region of the brain, but also that the neural response includes a resonant component that has not been previously recognized. Continuous DBS at conventional frequencies does not allow for a long enough time window to observe resonant activity. However, by monitoring the neural response after the stimulation has ceased (by patterning the stimulation signal or otherwise), resonant activity can be monitored. In addition, the inventors have recognized that embodiments of the present invention have applications both for reducing the physical effects associated with movement disorders and the adverse effects of other neurological conditions, neuropsychiatric disorders, sensory disorders, and pain.

[0146] In addition to the above, the inventors have also recognized that neuronal oscillations, as reflected by local field potentials measured, for example, by implanted electrodes, by EEG, or by MEG, are also affected by both DBS and certain medications used to treat movement disorders. In particular, it has been found that high-frequency oscillations (HFOs) in the range of 200 Hz to 400 Hz measured in local field potentials by DBS electrodes implanted in the subthalamic nucleus (STN) of the brain can be modulated by both DBS and by using medications such as levodopa. This recognition has motivated the inventors to develop novel techniques for selecting optimal DBS treatment parameters based on the modulation of the measured HFOs. Figure 1Graphically shown is the response of a neural circuit stimulated by a 130 Hz signal delivered by a neural stimulator through an electrode lead (such as the 3387 electrode lead manufactured by Medtronic®) implanted in the subthalamic nucleus (STN) of a patient with Parkinson's disease (PD). Each response to a stimulus pulse includes an evoked compound action potential (ECAP) component and an evoked resonant neural activity (ERNA) component that occurs after the ECAP. The ECAP typically occurs within 1 - 2 milliseconds of the stimulus pulse. The figure shows the responses to the last three consecutive pulses of a 60 - second continuous stimulation period, followed by a stimulation - free period. It can be seen that, by the occurrence of the next stimulus pulse, the evoked resonant response to each of the first two stimulus pulses shown can be shortened such that only a single secondary peak is detected. However, the evoked resonant response to the third (and last) pulse is able to resonate for a longer time and thus can be clearly seen in the form of a decaying oscillation with at least seven peaks for a post - stimulus period of about 30 milliseconds. Figure 1 The evoked resonant response to each of the first two stimulus pulses shown can be shortened such that only a single secondary peak is detected. However, the evoked resonant response to the third (and last) pulse is able to resonate for a longer time and thus can be clearly seen in the form of a decaying oscillation with at least seven peaks for a post - stimulus period of about 30 milliseconds.

[0147] As mentioned above, it is known that clinicians control and adjust DBS parameters to cause a therapeutic effect in a patient. The inventors have recognized that by controlling the DBS parameters in certain ways, non - therapeutic stimulation can be administered that evokes a resonant neural response (ERNA) in the patient without any therapeutic conflict or causing adverse side effects. Such non - therapeutic stimulation can be used to reliably measure the ERNA without causing a sustained change in the resonant neural circuit or the patient's symptomatic state. The non - therapeutic stimulation is preferably achieved by administering a stimulation that includes short pulse bursts followed by a stimulation - free period, and the ERNA is measured during this stimulation - free period. By doing so, the total charge or energy delivered to the patient is below the therapeutic threshold, and the measured ERNA provides information about the patient's natural (untreated) state. In an alternative embodiment, the total charge or energy delivered to the patient can be reduced by reducing the amplitude of the stimulation signal to below the therapeutic threshold. However, doing so may also reduce the amplitude of the peaks in the ERNA, making it more difficult to observe.

[0148] In addition to the above, the inventors have determined that during therapeutic stimulation of a patient, patterned stimulation can be used to monitor and analyze the evoked resonant neural activity. By patterning the stimulation signal, therapeutic stimulation can be maintained while providing a time window in which the resonant response beyond the first resonant peak or more preferably beyond two or more resonant peaks is monitored.

[0149] Figure 2Graphically illustrates exemplary therapeutic patterned DBS stimulation 20 and associated evoked resonance responses according to embodiments of the present disclosure. The patterned stimulation 20 is shown above the curve to illustrate the association between the stimulation and the response. In the patterned stimulation, a single pulse has been omitted from an otherwise continuous 130 Hz pulse train. Thus, the pulse train includes multiple consecutive stimulation pulse bursts, each burst separated by a first time period t 1 , each of the multiple pulses separated by a second time period t 2 . Stimulation continues before and after the omitted pulse (or more than one pulse) to maintain the therapeutic nature of DBS, while the omitted pulse can monitor the resonance of ERNA within several (3 in this example) resonance cycles before the next stimulation pulse interrupts this resonance.

[0150] In summary, by patterning non-therapeutic and therapeutic stimuli, evoked responses can be monitored over a longer time period compared to conventional non-patterned stimuli. Thus, preferably, the stimulation is applied as multiple pulse bursts, each burst separated by a first time period t 1 without stimulation, and each pulse separated by a second time period t 2 . For example, the stimulation signal can include a series of 10 pulse bursts at 130 Hz. To increase the repeatability of the results, the multi-pulse bursts can be repeated after a predetermined non-stimulation period. For example, the multi-pulse bursts can be repeated once per second. The duration of the first time period t 1 is greater than the duration of the second time period t 2 . The ratio between the duration of the burst and the duration between bursts can be selected to ensure that the relevant properties of ERNA can be easily and efficiently monitored. In some embodiments, the duration of each burst is selected to be between 1% and 20% of the non-stimulation duration between bursts.

[0151] In other embodiments, the duration of each burst can be selected to minimize the effect of the stimulation on the measured ERNA or to emphasize specific features of the measured ERNA. Figure 3 Graphically illustrates how applying 10 pulses at 130 Hz affects ERNA. The response to the first pulse has a wide low-amplitude first peak. For subsequent pulses, the first peak becomes larger and sharper and also migrates to an earlier time. In some embodiments, the optimal number of pulses included in a burst can be selected to maximize the amplitude of the resonance while minimizing the time shift of the peak in ERNA across the burst (e.g., the fourth pulse). In other embodiments, the rate of change of the ERNA characteristics (e.g., amplitude, onset delay) of consecutive pulses across the burst can be used as a defining characteristic. For example, the rate of change across the burst can be used to determine electrode position, optimal parameters, patient status, etc. and / or as a closed-loop control signal.

[0152] The use of burst (e.g., 10 pulses) stimulation provides a high-amplitude evoked neural response, making it easier to measure compared to the response to more continuous DBS. Figure 4 Graphically shown are the range and variance of the first peak amplitude of the ERNA in response to more continuous DBS, where one pulse is skipped per second (left) and burst DBS (right) (only 10 pulses per second). It can be seen that the average peak amplitude of the ERNA in response to burst DBS is approximately 310 μV, while the average peak amplitude of the ERNA in response to more continuous DBS is approximately 140 μV. Additionally, by using burst stimulation, the evoked resonance response can be monitored over several oscillation periods (20 milliseconds or longer).

[0153] By analyzing the characteristics of the ERNA, the inventors have determined that the waveform characteristics of the ERNA (natural frequency, damping coefficient, envelope, fine structure, firing latency, rate of change, etc.) depend on various physiological conditions of the patient. For example, it has been found that therapeutic DBS reduces the resonance frequency of the target neural circuit.

[0154] ERNA changes related to DBS stimulation

[0155] Figures 5a, 5b, and 5c show the frequency changes of the ERNA during non-therapeutic stimulation (Figure 5a), therapeutic stimulation (Figure 5b), and after the stimulation changes from therapeutic to non-therapeutic stimulation (Figure 5c). The resonance frequency of the ERNA is measured by calculating the reciprocal of the time delay between the maxima of two peaks of the ERNA. In other embodiments, the resonance frequency can be calculated as the reciprocal of the average time delay between the maxima of all detected peaks of the ERNA. In other embodiments, the resonance frequency can be calculated by fitting a damped oscillator model to the resonant activity and extracting the natural frequency or by performing spectral analysis (e.g., Fourier transform, wavelet transform). Other techniques for frequency estimation (such as estimating the time between zero crossings in the waveform or using other features of the waveform) can also be used for this purpose.

[0156] In the example shown, in relation to the reference Figure 1 and Figure 2The patterned stimulation is administered to the patient in the same manner. FIGS. 5a and 5b respectively show the responses to patterned non-therapeutic DBS stimulation and therapeutic DBS stimulation. In this example, the non-therapeutic stimulation includes 10 pulse bursts delivered at a frequency of 130 Hz over a 1-second period, with the remaining 120 pulses (which occur during continuous stimulation) skipped. The horizontal dashed line represents the typical observable window of the response (during continuous (non-patterned) DBS). It can be seen that in the case of patterned non-therapeutic stimulation, the amplitude and frequency of the ERNA remain relatively constant, indicating that the stimulation does not strongly affect the resonant state of the target nerve structure over time. Additionally, in the typical observable window of non-patterned stimulation, two resonant peaks of the ERNA (shown in black) can be seen. Then, FIG. 5b shows the response to therapeutic patterned DBS stimulation at 3.375 mA, where 129 pulses are delivered per second at a rate of 130 Hz, with the remaining 1 pulse skipped.

[0157] The therapeutic signal causes a decrease in the frequency of the ERNA, potentially causing the second resonant peak of the ERNA to shift outside the typical observable window of continuous (non-patterned) stimulation. However, by patterning the stimulation by skipping one or more pulses, the resonant properties of the ERNA can continue to be measured, as well as subsequent peaks during the omitted stimulation pulses. Additionally, it can be seen that the amplitudes of the third and fourth resonant peaks are increased compared to the non-therapeutic response.

[0158] In addition to simply omitting pulses in a periodic pulse train, alternative methods of patterning the stimulation can improve the monitoring of the ERNA. For example, conventional therapeutic stimulation (e.g., at a frequency of 130 Hz) can be interleaved with bursts of stimulation having a lower frequency (e.g., 90 Hz). The frequency of these interleaved bursts is preferably low enough to allow the observation of multiple ERNA peaks. Similarly, the frequency of these interleaved bursts is preferably high enough to be within the therapeutic frequency range for DBS. The transition between frequencies can be sharp, or alternatively, the change in frequency can be gradual. It may be advantageous to apply a ramp to the frequency of the pulses to avoid a sharp step change in frequency.

[0159] As a supplement or alternative to adjusting the frequency of the applied stimulation, the amplitude of the pulses can be modulated over time. This can include applying ramps for increasing the pulse amplitude over several pulses within a burst and / or for decreasing the pulse amplitude over several pulses within a burst. To enhance the monitoring of the ERNA, it may be advantageous to apply a fixed amplitude to the pulses prior to the observation window and, if this amplitude is different from the amplitude applied at other times (e.g., to maximize the therapeutic benefit), apply a ramp to the amplitude of the pulses to avoid a sharp step change in amplitude.

[0160] Then, FIG. 5c shows the response after switching back to non-therapeutic patterned stimulation. In this case, the therapeutic effect of the patterned therapeutic stimulation "washes out", and the ERNA returns to its baseline state. It can be seen that the first peak of the resonance activity in all conditions (all conditions that can typically be measured using conventional continuous DBS) does not change significantly with therapeutic DBS. However, the characteristics of the subsequent part of the ERNA waveform that can be measured by patterning the stimulation show greater changes in frequency and amplitude. Therefore, monitoring the response over a longer period enables the analysis of information regarding the frequency, amplitude, envelope, and fine structure of time-varying oscillations.

[0161] This effect is further illustrated in FIGS. 5d, 5e, and 5f. FIG. 5d shows that the resonance frequency of the ERNA during the non-therapeutic stimulation period is approximately 400 - 450 Hz. Clinically effective stimulation (stimulation that can be operated to actively relieve the patient's disease symptoms) can reduce the frequency of the ERNA to approximately 300 - 350 Hz, as shown in FIG. 5e. FIG. 5f shows the transition of the resonance frequency from 300 - 350 Hz back to approximately 400 - 450 Hz after replacing the therapeutic stimulation with non-therapeutic stimulation.

[0162] FIGS. 6a, 6b, and 6c show another example of the changes in the ERNA during non-therapeutic patterned stimulation (FIG. 6a), during therapeutic patterned stimulation (FIG. 6b), and after transitioning from therapeutic stimulation to non-therapeutic stimulation (FIG. 6c) from different patients. In this example, the patterned stimulation was applied to the patients in the same manner as described with reference to FIGS. 5a - 5e. As in the previous example, it can be seen that the initial non-therapeutic stimulation (FIG. 6a) did not cause a significant change in the ERNA, and the therapeutic stimulation (FIG. 6b) resulted in a decrease in the resonance frequency, which returned to the baseline level after the stimulation was switched back to non-therapeutic patterned stimulation (FIG. 6c). However, in this example, the change in the resonance frequency under therapeutic stimulation was accompanied by an increase in the delay between each stimulation pulse and the onset of resonance. This increase in the onset delay shifted the second resonance peak such that it appeared outside the typical observable window of conventional (non-patterned) DBS. By patterning the stimulation such that the measurement window was long enough to observe three resonance peaks, the ERNA could be characterized. Additionally, contrary to the previous example, the amplitude of the resonance decreased due to the therapeutic stimulation.

[0163] Figures 6d, 6e, and 6f further illustrate the decrease in resonant frequency under therapeutic stimulation in this example. The resonant frequency is estimated by calculating the reciprocal of the time delay between the maxima of two peaks of the ERNA. In Figure 6d, it can be seen that the ERNA frequency measured using non-therapeutic patterned stimulation is approximately 350 Hz. Application of therapeutic patterned stimulation in Figure 6e causes the frequency to decrease to approximately 250 Hz. In Figure 6f, it can be seen that after switching back to non-therapeutic patterned stimulation, the frequency can recover to its baseline level.

[0164] ERNA including multiple resonances

[0165] The inventors have determined that not only does the evoked neural response to the applied stimulation exhibit resonant activity, but in some cases the evoked activity includes multiple resonances. Figures 7a, 7b, and 7c respectively illustrate the ERNA in response to continuous DBS at 1.5 mA, 2.25 mA, and 3.375 mA. At 1.5 mA, the resonant ERNA starts with a single peak, and it can be seen that the single peak begins to slightly disperse into two peaks. At 2.25 mA, the dominance switches to the later of the two peaks. However, the earlier peak that was dominant at 1.5 mA continues at a lower amplitude. At 3.375 mA, there are two peaks, with the later peak being dominant. It is believed that these multiple resonant peaks correspond to activity in different neural circuits. The relative amplitude (or other characteristics, such as temporal or spectral properties) between these resonant responses can be an indicator of the therapeutic state.

[0166] ERNA measurements from long-term implanted electrodes

[0167] Figures 20 to 2 3 provides additional evidence of the positive effects of DBS on patient symptoms and ERNA-related changes. The data shown in these figures were collected from Parkinson's disease patients implanted with electrode arrays. The electrode arrays were implanted long-term, and measurements of ERNA and motor status were made several months after implantation. By measuring ERNA and motor status at this time, it can be inferred that the electrode arrays and their neural environment are stable. Therefore, the established relationship between ERNA and motor status is more representative of the patient's long-term condition compared to those measured during acute intraoperative procedures or studies conducted within a few days of electrode insertion. It has been found that findings from such short-term studies may be confounded by the "stunning effect", which is characterized by a temporary reduction in motor deficits in Parkinson's disease, presumably related to the surgical implantation procedure rather than to the application of therapeutic DBS itself.

[0168] ERNA measurements were collected in a manner similar to that described above with reference to Figures 5a to 6f. Measurements of the patient's motor function were also collected. These measurements included estimates of muscle stiffness, finger tapping speed, and the ease of opening and closing the hand.

[0169] DBS at different stimulation amplitudes was applied to the implanted electrode array in a manner similar to that described above. The stimulation amplitudes included zero, 0.667 mA, 1 mA, 1.5 mA, 2.25 mA, and 3.375 mA. Non-therapeutic burst stimulations were also provided before and after the regular DBS sessions.

[0170] Figure 20 The results of the motor function tests are shown graphically. The observations of stiffness, finger tapping, and patient hand opening / closing are shown separately, with the mean values of these metrics shown in bold. The observations of patient impairment were scored from 0 (zero) to 4, where 4 indicates the greatest impairment and zero indicates the least (or no) movement. This scale is provided on Figure 20 the vertical axis.

[0171] From Figure 20 it is evident that DBS improved all motor scores, with the mean scores showing significant benefits, particularly at the highest levels of DBS (2.25 mA and 3.375 mA). During the final burst washout period, the patient's movement began to return to the pre-DBS condition, during which the stimulation parameters were chosen not to produce a therapeutic effect.

[0172] Figures 21a, 21b, 21c, 21d, and 21e respectively show data extracted from the ERNA waveforms recorded during patterned therapeutic stimulations at amplitudes of 0.667 mA, 1 mA, 1.5 mA, 2.25 mA, and 3.375 mA. In particular, this data represents the ERNA waveforms recorded in response to the final stimulation pulse before the no-stimulation (skipped pulse) period as described above (refer to Figure 1 and Figure 2 ). The patterned stimulation was applied over several minutes (represented on the horizontal axis). The peaks of the ERNA waveforms are represented by darker dots. The valleys of the ERNA waveforms are represented by lighter dots. Figures 21f and 21g show the ERNA before and after continuous DBS during the burst (non-therapeutic) stimulation period.

[0173] Taken together, Figure 20 the results shown in

[0174] and Figure 21 indicate a clear association between ERNA and the effectiveness of DBS in alleviating motor disorders. Thus, these results provide further evidence that the characteristics of ERNA can be used to control DBS parameter settings to optimize therapy for individual patients. For example, if the measured ERNA waveform has a peak at approximately 7 ms and an adjacent peak just below 11 ms (as shown in Figures 21d and 21e), it can be hypothesized that DBS is effective in alleviating symptoms. The peaks at these times only occur when the stimulation is applied at 2.25 mA and 3.375 mA, which correspond to the DBS conditions where the patient's motor function is less impaired (seeFigure 20 )。In this case, the DBS waveform can be adjusted to reduce the energy applied to the brain. Such adjustments can include adjusting one or more of the frequency, amplitude, pulse width, net charge, or morphology of the stimulation. Such adjustments can minimize battery usage, reduce adverse side effects associated with DBS, and improve the safety of long-term stimulation. Otherwise, if the measured ERNA waveform has corresponding adjacent peaks that occur below 7 ms and 11 ms respectively, it can be assumed that the DBS is ineffective, and the amplitude of the DBS should be increased. For example, FIG. 21c shows adjacent peaks at approximately 6 ms and 9 ms in response to a stimulation amplitude of 1.5 mA, which amplitude is not effective in alleviating motor dysfunction, as Figure 20 shown.

[0175] In another example, if there are two adjacent peaks in the ERNA waveform and they are separated in time by more than approximately 3.5 ms (as shown in FIGS. 21d and 21e), it can be assumed that the DBS is effective. On the other hand, if the time difference between the corresponding adjacent peaks is less than 3.5 ms (as in the cases shown in FIGS. 21a and 21b), it can be assumed that the DBS is ineffective. Then, the DBS waveform can be controlled to maintain the DBS parameters (e.g., frequency, amplitude, pulse width, net charge, or morphology) at a level that can provide effective symptom relief while preferably also minimizing battery usage, reducing adverse side effects associated with DBS, and improving the safety of long-term stimulation.

[0176] Although Figure 20 the results shown in and FIG. 21 particularly illustrate the relationship between the measured ERNA and the DBS amplitude, it should be understood that there is a relationship between the measured ERNA and any other parameter of the DBS waveform, including but not limited to frequency, amplitude, pulse width, total net charge, and morphology.

[0177] It should also be understood that the delay of the initial peak in the ERNA waveform and the delay between ERNA peaks can be patient-specific. Advantageously, any reliance on such data for controlling DBS stimulation will be based on the initial characteristics of the ERNA waveform and the motor impairment associated with each patient in order to generate a stimulation control (e.g., closed-loop control) scheme.

[0178] As briefly mentioned above with respect to Figure 20 and FIG. 21, the identification of the association between changes in the resonant behavior of the stimulated neural circuit and the patient's disease symptoms provides several opportunities for improving various aspects of DBS therapy, including but not limited to techniques for the initial implantation and subsequent repositioning of DBS electrodes, and techniques for setting the parameters of DBS stimulation and using feedback to adjust the DBS parameters in real time while DBS therapy is in progress.

[0179] ERNA measurements in subjects under general anesthesia

[0180] In addition to confirming the effect of DBS on patients with long-term implanted electrodes, the inventors have also determined that ERNA responsive to DBS exists and is measurable in patients under general anesthesia. Figures 27 to 33 Provide a comparison of ERNA recorded with the patient awake and under general anesthesia. For each of these figures, the implanted electrodes were stimulated with monopolar symmetric biphasic pulses that were patterned in time into bursts of ten consecutive pulses per second with an amplitude of 3.38 mA, a frequency of 130 Hz, and a phase of 60 μs. The electrodes were implanted as described above. ERNA was measured in the left and right STNs of 21 human patients under awake and general anesthesia using various induction agents and maintenance agents as listed in Table 1 below.

[0181]

[0182]

[0183]

[0184] Table 1

[0185] Figure 27 and Figure 28 Provide a comparison of ERNA measured in a patient at the time of electrode implantation (black) and in the same patient under general anesthesia 560 days after implantation. This patient was not included in the table above. The data shown in these figures were collected from Parkinson's disease patients implanted with electrode arrays. The electrode arrays were implanted long-term, and measurements of ERNA and motor status were made at the time of implantation and 560 days after implantation. At 560 days after implantation, general anesthesia was induced with a 130 mg propofol bolus and remifentanil at 0.2 μg / kg / min, and maintained with remifentanil at 0.2 μg / kg / min and isoflurane at 0.6% end-tidal. Figure 27 Is a figure showing ERNA measured during implantation (black) and under general anesthesia (gray). Figure 28 Is a figure showing the change in ERNA across four electrodes (numbered 1, 2, 3, and 4) in an array (such as the Medtronic 3387 electrode array) at the time of implantation (black) and 560 days after implantation under general anesthesia. These results indicate that, despite long-term electrode implantation and the presence of general anesthesia, the amplitude and location changes of ERNA observed in the patient are comparable to those recorded when the patient is awake (not under general anesthesia). Additionally, it can be seen that general anesthesia has some effect on the morphology and amplitude of ERNA in the patient, most notably resulting in a slight decrease in the amplitude of ERNA, but the overall trend of the response across the electrodes to the stimulation conditions remains substantially similar.

[0186] Figure 29 and Figure 30 Comparison of ERNA measured in patients who were awake (black) and under general anesthesia (gray) shortly after electrode implantation when electrodes were implanted into the left subthalamic nucleus (STN) and the right ( Figure 29 ) STN ( Figure 30 ). ERNA was measured for the first time immediately after electrode implantation. General anesthesia was then induced with an 80 mg bolus of propofol and maintained with 0.8 minimum alveolar concentration (MAC) of sevoflurane and 0.08 / μg / kg / min of remifentanil. Under general anesthesia, further measurements of ERNA were made via the implanted electrodes.

[0187] Reference Figure 29 and Figure 30 In each of the four curves in each graph, the ERNA measured at four electrodes (numbered 1, 2, 3, and 4) in the Medtronic 3387 electrode array is shown. Each column shows this ERNA in response to DBS stimulation at a different one of the four electrodes. The stimulated electrode is indicated at the top of each column (electrode stimulation 1, electrode stimulation 2, electrode stimulation 3, and electrode stimulation 4). These curves show that when the patient was under general anesthesia, the ERNA detected at the electrodes in response to DBS stimulation (especially at electrodes 2, 3, and 4) still existed and had an amplitude similar to that of the ERNA detected when the patient was awake.

[0188] Figure 31 and Figure 32 Provide a further comparison of the presence of awake and general anesthesia ERNA in patient ID number I042 as shown in Table 1. Measure the ERNA of the patient when awake (black) and under general anesthesia (gray) shortly after electrode implantation in both the left ( Figure 31 ) subthalamic nucleus (STN) and the right ( Figure 32 ) STN. For the patients ( Figure 31 and Figure 32 subjects), general anesthesia was induced with a 60 mg bolus of propofol and maintained with 0.5 MAC of sevoflurane and 0.15 - 0.2 μg / kg / min of remifentanil.

[0189] In Figure 31 and Figure 32 In each of the four curves in each, the ERNA measured at four electrodes (numbered 1, 2, 3, and 4) in the Medtronic 3387 electrode array is shown. Each column shows the ERNA in response to DBS stimulation at a different one of the four electrodes. The stimulated electrode is indicated at the top of each column (electrode stimulation 1, electrode stimulation 2, electrode stimulation 3, and electrode stimulation 4). As forFigure 29 and 30 like the patient, Figures 31 to 32 showed that when the patient was under general anesthesia, the ERNA detected at the electrodes in response to DBS stimulation (especially at electrodes 2, 3, and 4) still existed and had an amplitude similar to that of the ERNA detected when the patient was awake. Additionally, these results demonstrated that changes in the anesthesia dosage regimen did not appear to substantially affect the measured ERNA.

[0190] Figure 33 Provide a further comparison of the presence of awake and general anesthesia ERNA in patient ID number I040 shown in Table 1. Measure the ERNA of the patient when awake (black) with electrodes implanted in the left subthalamic nucleus (STN) and when under general anesthesia (gray) shortly after electrode implantation. For the patient ( Figure 33 subject), general anesthesia was induced and maintained by target-controlled infusion of propofol at 3.0 μg / ml and remifentanil at 0.6 μg / kg / min.

[0191] In Figure 33 each column of the four curves, the ERNA measured at four electrodes (numbered 1, 2, 3, and 4) in the Medtronic 3387 electrode array is shown, and each column shows the ERNA in response to DBS stimulation at different electrodes among the four electrodes. The stimulated electrode is indicated at the top of each column (electrode stimulation 1, electrode stimulation 2, electrode stimulation 3, and electrode stimulation 4). These data further demonstrated that when the patient was under general anesthesia, the ERNA detected at the electrodes in response to DBS stimulation (especially at electrodes 2, 3, and 4) still existed. Additionally, these results demonstrated that ERNA was measurable in the presence of various drugs and anesthetics.

[0192] The above results indicate that ERNA can be used to guide electrodes to the most beneficial stimulation sites in anesthetized patients as well as patients who remain awake during implantation surgery. Furthermore, the results indicate that various drugs and drug regimens commonly used in anesthesia can be used during such implantation surgery without adversely affecting the presence and use of ERNA for guiding electrodes.

[0193] Figure 34It is a box-and-whisker plot showing the median, range, and interquartile range of ERNA amplitudes measured at four electrodes (numbered E1, E2, E3, and E4) of the Medtronic 3387 electrode array implanted in the body of 21 patients shown in Table 1 in both the awake and general anesthesia (sleep) states. This figure shows that for the electrodes (E2 and E3) targeting the STN of the subject (which have larger ERNA), the ERNA amplitude decreases significantly under general anesthesia. Electrodes E1 and E4 are usually located outside the STN, and the ERNA is small or absent.

[0194] Figures 35a to 35c show the ERNA rank plots of 21 patients from awake to general anesthesia. For each STN of the 21 patients, the electrodes are ranked from 1 to 4 according to the amplitude of the measured ERNA, with rank 1 being the highest amplitude ERNA and rank 4 being the lowest amplitude. The shading of each square represents the percentage match, where the electrodes measure the ERNA amplitude at the same rank in both the awake and anesthetic states. A 100% match is represented by a black square. A 0% match is represented by a white square. Figure 35a includes data for all 21 patients (2 STNs per patient). Figure 35b includes data for those patients induced with propofol anesthesia (9 patients, 18 STNs). Figure 35c includes data for those patients induced with sevoflurane anesthesia (11 patients, 22 STNs).

[0195] Among all the tested STNs, the electrodes that measured the maximum ERNA (rank 1) in the awake state also measured the maximum ERNA amplitude (rank 1) in the sleep state for 32 out of 42 STNs. For the remaining 10 of the 42 STNs, the electrodes that measured the maximum ERNA amplitude (rank 1) in the awake state also measured the second largest ERNA amplitude (rank 2) in the sleep state. This shows that for most of the tested STNs, the electrodes that measured the maximum ERNA amplitude in the awake state also measured the maximum ERNA amplitude under general anesthesia. This further shows that for all the tested STNs, the electrodes that measured the maximum ERNA amplitude in the awake state measured the maximum ERNA amplitude or the second largest ERNA amplitude under general anesthesia. From the comparison of Figures 35a to 35c, it can also be seen that the above pattern is basically correlated across all anesthetics.

[0196] Figure 36 Provide a further comparison of the awake (black) and general anesthesia (gray) ERNA of patient ID041 in Table 1. It can be seen that general anesthesia causes an inflection point in the first peak of the resonance response. It is suspected that this inflection point may be the result of the superposition of two responses combined with each other in the measured ERNA. It is suggested that general anesthesia may affect these responses in different ways, thus causing Figure 36 the shown inflection point. Figure 36The result of the inflection point shown is that, for a patient under general anesthesia, the duration between the first ERNA peak and the second ERNA peak in the measured response may be significantly the same as the duration between the second ERNA peak and the third ERNA peak (and the durations between subsequent peaks (third and fourth, fifth, sixth, etc.)). When using ERNA for diagnosis and control, especially in patients under general anesthesia, measuring / monitoring the inter-peak duration / delay may be preferred compared to measuring the resonance response frequencies within multiple peaks. For example, in addition to the duration between the second and third peaks in ERNA, it may be preferred to measure the duration between the first and second peaks in this ERNA.

[0197] Figure 37a is a graph showing the median, range, and interquartile range of the ERNA inter-peak delay between the first and second peaks of the maximum graded amplitude (grade 1) ERNA of 36 STNs in the brain of the patients shown in Table 1 in both the awake and general anesthesia (sleep) conditions. Figure 37b is a graph showing the median, range, and interquartile range of the ERNA inter-peak delay between the second and third peaks of the maximum graded amplitude (grade 1) ERNA of 36 STNs in the brain of the patients shown in Table 1 in both the awake and general anesthesia (sleep) conditions. Note that for the remaining 6 STNs out of the 42 STNs (21 patients) tested, the inter-peak delay could not be measured, resulting in a sample size of n = 36 STNs in Figures 37a and 37b.

[0198] In both Figures 37a and 37b, the ERNA inter-peak delays are shown separately for all patients, propofol-induced patients, and sevoflurane-induced patients. It can be seen that for all patients, the inter-peak delays of patients under general anesthesia increase (between the first and second peaks and between the second and third peaks). This indicates that general anesthesia increases the inter-peak delay, i.e., slows down the average response frequency. It can also be seen from the above figures that for awake patients, the delay from peak 1 to peak 2 is shorter than the delay from peak 2 to peak 3, while for patients under general anesthesia, it is the opposite; the delay from peak 1 to peak 2 is longer than the delay from peak 2 to peak 3.

[0199] From the above, it can be determined that ERNA exists in human subjects under general anesthesia. It can also be determined that the inter-peak duration or delay of ERNA can be used to identify the optimal location of therapeutic stimulation.

[0200] The inventors have also determined that ERNA exists in sheep, as Figures 28 to 43As shown. Adult female sheep were anesthetized with a continuous flow of isoflurane (about 2%) in air, and vital signs (heart rate, end-tidal CO2, pulse oximetry, eyelid reflex) were monitored during the duration of the surgery. Neural activity was evoked by stimulating a single toroidal electrode in the electrode array, and recorded from 11 other channels by combining toroidal and wire electrodes. The electrode array was implanted into the STN region of the sheep. Figures 38 to 43 The recorded ERNA shown was measured from the toroidal electrode adjacent to the stimulating electrode at a center-to-center distance of 1.5 mm.

[0201] At a frequency of 130 Hz with a 60 μs phase at amplitudes of 3.375 mA ( Figure 38 and Figure 41 ), 5.063 mA ( Figure 39 and Figure 42 ) and 7.594 mA ( Figure 40 and Figure 43 ), monopolar symmetric biphasic pulses were used to stimulate the implanted electrodes. The stimulation was patterned in time as a burst of ten consecutive pulses per second. At each amplitude, a total of 10 bursts of ten consecutive pulses were administered.

[0202] Figures 38 to 40 Shows the resulting ERNA of the first sheep subject in response to the above stimuli d at amplitudes of 3.375 mA, 5.063 mA, and 7.594 mA, respectively. Figures 41 to 43 Shows the resulting ERNA of the second sheep subject also in response to the above stimuli at amplitudes of 3.375 mA, 5.063 mA, and 7.594 mA, respectively. These figures illustrate that resonant neural activity is evoked by deep brain stimulation despite the sheep being under general anesthesia. Additionally, these results suggest that at least in sheep subjects, the use of inhaled isoflurane as an anesthetic does not affect the presence of ERNA.

[0203] Now several practical applications of the above-evoked resonant neural activity will be discussed with reference to several embodiments. In an embodiment, one or more electrode leads can be used to stimulate one or more neural structures within one or both hemispheres of the brain, each lead including one or more electrodes located near the tip of each lead. Each electrode can be used for stimulation, monitoring, or both stimulation and monitoring. One or more of these electrodes can be implanted. The implanted electrodes can be used alone or supplemented with one or more electrodes placed outside the brain or skull.

[0204] Figure 8Illustrated is a typical DBS electrode lead tip 70, such as that incorporated in the Medtronic® DBS lead model 3387. The lead tip 70 includes a first electrode 72a, a second electrode 72b, a third electrode 72c, and a fourth electrode 72d. Once implanted in the brain, each of the electrodes 72a, 72b, 72c, 72d can be used to apply stimulation to one or more neural structures or to monitor and optionally record the evoked response (including ERNA) of the neural circuitry to the stimulation. In other embodiments, leads with more electrodes or electrodes of different sizes or topologies may be used. Additionally, when one or more electrodes on the DBS lead are activated for stimulation or for signal monitoring, one or more reference electrodes may be located at a remote site and used to complete the circuit.

[0205] The target location of the lead tip 70 varies depending on the neural structure. Exemplary target structures include, but are not limited to, the subthalamic nucleus (STN), the substantia nigra pars reticulata (SNr), and the globus pallidus internus (GPi).

[0206] Figure 9 Illustrated is the lead tip 70 implanted in the brain at the target structure, in this case the subthalamic nucleus (STN) 82. It should be appreciated that intersecting the electrode tip 70 with the subthalamic nucleus (STN) 82, which typically has a diameter of 5 to 6 mm, can be a very difficult surgical task. Current techniques such as stereotactic imaging, microelectrode recording, intraoperative x-ray imaging, and applying therapeutic stimulation while monitoring the patient's symptoms are used to locate the electrode tip 70. However, these methods may lack accuracy. Additionally, existing methods typically require the patient to remain awake during the procedure because the patient's spontaneous response can be used to confirm that the electrode is in the proper position relative to the target structure in the brain. As a result, many potential DBS treatment recipients reject this option because they are uncomfortable with having to be awake during the surgical procedure.

[0207] By using a series of patterned stimulations to generate and measure the evoked resonance response from the neural target, the accuracy of positioning the electrodes of the electrode tip 70 within the target structure can be significantly improved. Such techniques can eliminate the need for the patient to be awake during the implantation procedure because the electrodes can be more accurately positioned within the brain and at the correct location relative to the target neural structure. This means that the patient can be sedated or under general anesthesia during the surgery because the electrodes can be positioned to a satisfactory accuracy without the need for patient feedback.

[0208] In Figure 10 is illustrated an exemplary DBS delivery system 90 according to an embodiment of the present disclosure. The system 90 includes Figure 8a lead end 70, the lead end 70 including a plurality of integrated electrodes 72a, 72b, 72c, 72d, as well as a processing unit 92, a signal generator 94, a measurement circuit 96, and an optional multiplexer 98. The processing unit includes a central processing unit (CPU) 100, a memory 102, and an input / output (I / O) bus 104 communicatively coupled to one or more of the CPU 100 and the memory 102.

[0209] In some embodiments, a multiplexer 98 is provided to control whether the electrodes 72a, 72b, 72c, 72d are connected to the signal generator 94 and / or the measurement circuit 96. In other embodiments, a multiplexer may not be required. For example, the electrodes 72a, 72b, 72c, 72d may alternatively be directly connected to both the signal generator 94 and the measurement circuit 96. Although in Figure 10 all of the electrodes 72a, 72b, 72c, 72d are connected to the multiplexer 98, in other embodiments, only one or some of the electrodes 72a, 72b, 72c, 72d may be connected.

[0210] The measurement circuit 96 may include one or more amplifiers and digital signal processing circuitry, including but not limited to sampling circuitry for measuring a neural response to a stimulus (including ERNA). In some embodiments, the measurement circuit 96 may also be configured to extract other information from the received signal, including local field potentials. The measurement circuit 96 may also be used in combination with the signal generator 94 to measure electrode impedance. The measurement circuit 96 may be located external to the processing unit 92 or integrated therein. Communication between the measurement circuit 96 and / or the signal generator 94 on one hand and the I / O port on the other hand may be wired or may be via a wireless link, such as via inductive coupling, Wi-Fi (RTM), Bluetooth (RTM), etc. Power may be supplied to the system 90 by at least one power source 106. The power source 106 may include a battery such that the components of the system 90 can maintain power when implanted within a patient.

[0211] The signal generator 94 is coupled to one or more of the electrodes 72a, 72b, 72c, 72d via the multiplexer 98 and is operable to deliver an electrical stimulus to the corresponding electrode based on a signal received from the processing unit 92. To this end, the signal generator 94, the multiplexer 98, and the processing unit 92 are also communicatively coupled such that information can be transmitted between them. Although the signal generator 94, the multiplexer 98, and the processing unit 92 are shown as separate units in Figure 10 in other embodiments, the signal generator 94 and the multiplexer may be integrated into the processing unit 92. Additionally, any one of the units may be implanted or located outside the patient.

[0212] System 90 may also include one or more input devices 108 and one or more output devices 110. The input devices 108 may include, but are not limited to, one or more of a keyboard, a mouse, a touchpad, and a touchscreen. Examples of output devices include a display, a touchscreen, a light indicator (LED), a sound generator, and a haptic generator. The input device 108 and / or the output device 110 may be configured to provide feedback (e.g., visual, auditory, or haptic feedback) to a user related to, for example, the characteristics of the ERNA or subsequently derived indicators (such as the proximity of the electrode 70 relative to the neural structure in the brain). To this end, one or more of the input devices 108 may also be an output device 110, for example, a touchscreen or a haptic joystick. The input device 108 and the output device 110 may also be connected to the processing unit 92, either wired or wirelessly. The input device 108 and the output device 110 may be configured to provide control of the device to the patient (i.e., a patient controller) or to allow a clinician to program the stimulation settings and receive feedback on the effect of the stimulation parameters on the ERNA characteristics.

[0213] One or more elements of the system 90 may be portable. One or more elements may be implanted in a patient. For example, in some embodiments, the signal generator 94 and the lead 70 may be implanted in the patient, and the processing unit 92 may be located outside the patient's skin and may be configured to communicate wirelessly with the signal generator via RF transmission (e.g., inductive, Bluetooth (RTM), etc.). In other embodiments, the processing unit 92, the signal generator 94, and the lead 70 may all be implanted in the patient. In any case, the signal generator 94 and / or the processing unit 92 may be configured to communicate wirelessly with a controller (not shown) located outside the patient.

[0214] One embodiment of the present disclosure provides a system and method for using the measured ERNA to position the lead tip 70 within a target structure of the brain. During the operation of implanting the lead tip 70 into the brain, instead of relying on the low-accuracy positioning techniques described above to estimate the position of the electrode relative to the neural structure within the brain, the system 90 may be used to provide real-time feedback to the surgeon based on characteristics such as the intensity and quality of the evoked response signals received from one or more electrodes of the lead tip 70. This feedback may be used to estimate the position within the target structure in three dimensions and to inform the decision of whether to reposition the electrode along a different trajectory or to remove and re-implant the electrode.

[0215] Figure 11 A general example of such a process is shown. The process begins at step 112, where, during the surgery, a reference such as Figure 8The electrode lead tip advances towards the target nerve structure along a predetermined trajectory. The step size (or spatial resolution) of the electrode lead advancement can be selected by the surgeon and / or clinician. In some embodiments, the step size is 1 mm. At step 114, an evoked response, including ERNA, is measured by applying patterned stimulation, such as that described above, to the electrodes of the lead tip 70. The stimulation can be applied continuously while the lead tip 70 is being implanted. Alternatively, the patterned signal can be repeated a predetermined number of times, such as 10 times. The evoked response can be measured at the same electrodes used to apply the stimulation, or at one or more different electrodes. By doing so, a more accurate estimate of the position of each electrode relative to the target nerve structure can be provided. Steps 112 and 114 are repeated until the electrode lead tip has been inserted to the maximum allowable depth, which can be within or slightly beyond the target nerve structure.

[0216] By repeating steps 112 and 114, a profile or map of the evoked responses at different positions along the insertion trajectory can be generated. The profile of the evoked response can include measurements from multiple electrodes or from only one electrode. The profiles of the evoked responses at different depths can be output to one or more output devices 110. Then, at step 118, the profiles of the evoked responses are compared to determine whether a preferred electrode position can be identified. The identification of the preferred electrode position can be based on different ERNA characteristics, including the relative differences or their spatial derivatives between amplitude, decay rate, rate of change, and frequency at different insertion positions (e.g., the position that produces the maximum resonance).

[0217] The identification of the preferred electrode position can also be based on a comparison with a template ERNA activity, where the template has been derived from records of other patients. The profile of the evoked response can also be used to estimate the trajectory of the electrode lead 70 through the target nerve structure, including the boundaries and intersecting regions of the structure (e.g., the trajectory through the medial or lateral regions). In the case where the target structure does not intersect the insertion trajectory, the profile of the evoked response can also be used to estimate the proximity to the target structure.

[0218] If a preferred electrode position can be identified at step 120, the electrode lead tip 70 can be repositioned at step 122 so that the electrode is located at the preferred position. Alternatively, for embodiments including an electrode lead tip with a large number of electrodes, the electrode located closest to the preferred position can be nominated for subsequent use in applying therapeutic stimulation. If a preferred position cannot be identified at step 120, the surgeon and / or clinician can choose to remove the electrode and re-implant it along a different trajectory.

[0219] Another embodiment of the present disclosure provides a system and method for determining the relative position of an electrode array with respect to a target nerve structure and then selecting a preferred electrode to be used for applying therapeutic stimulation. This process can be performed during an electrode implantation procedure to assist in the positioning of the electrodes or can be used with previously implanted electrodes when programming the device to deliver therapeutic stimulation. Stimulation can be applied at more than one electrode in the array; for example, in the case of electrode array 70, it can be applied at two or more of electrodes 72a, 72b, 72c, 72d. In the case of using a patterned stimulation protocol, sequential bursts of the stimulation pattern can be applied to different ones of electrodes 72a, 72b, 72c, 72d. Alternatively, a complete stimulation pattern can be applied at one electrode and then another complete stimulation pattern can be applied at another electrode. By doing so, it can be determined which electrode in the electrode array is optimally positioned to provide therapeutic stimulation to one or more target nerve structures; for example, which one of electrodes 72a, 72b, 72c, 72d is optimally positioned within the target nerve structure.

[0220] Figure 12 An exemplary process 130 for measuring evoked responses from a multi-electrode array is shown. At step 132, a stimulation is applied to a first electrode in the X electrode array (electrode 72a in the case of lead tip 70). The applied stimulation can be a burst patterned stimulation as described above. At step 134, evoked responses from the target nerve structure are measured at one or more electrodes in the array. In the case of lead tip 70, for example, when stimulating the first electrode 72a, evoked responses can be measured at the second electrode 72b, the third electrode 72c, and the fourth electrode 72d. In some embodiments, the evoked response received at the stimulating electrode can also be recorded and optionally stored in a memory. Once evoked responses have been measured at each electrode, another electrode is selected for stimulation. This can be achieved by incrementing a counter as shown in step 138 after the process has checked in step 136 to see if all electrodes in the X electrode array have been stimulated, i.e., if the process has cycled through all electrodes in the system. If there are still electrodes to be stimulated, the process is repeated, thereby applying stimulation to the next selected electrode in the array. If all electrodes in the array have been stimulated and the evoked responses to the stimulation have been measured and recorded at each electrode, then the resulting measured evoked responses are processed at step 140.

[0221] Processing the evoked response can involve comparing different ERNA features (including relative differences between amplitude, decay rate, rate of change, and frequency or their spatial derivatives) across different electrode combinations used for stimulation and measurement. For example, the processing can involve identifying the electrodes that measure the maximum evoked resonance amplitude for each stimulation condition. Identification of the preferred electrode locations can also be based on comparison with template ERNA activity. The template can be derived from recordings of other patients, or from one or more models or simulations. The processing can equivalently involve determining the inter-peak latency between peaks in the response, such as the duration between the first and second peaks in the response, the duration between the second and third peaks in the response, or a combination of both. The relative inter-peak latency can be used to identify the optimal stimulation electrodes.

[0222] Based on the processing of the evoked response, the preferred electrodes to be used for therapeutic stimulation can be selected at step 142. The results of the ERNA processing and the recommendation for the preferred electrodes can be output to one or more output devices 110. If the procedure has been performed during surgery, the results of the ERNA processing can also be used to determine which electrodes are within the target nerve structure and whether to reposition the electrode array. The results can also be used to generate one or more templates for future processing of the evoked response in the same or different patients.

[0223] Figure 13 An example of the evoked response measured at each of the first electrode 72a, the second electrode 72b, and the fourth electrode 72d based on the patterned stimulation applied to the third electrode 72c is shown. This example corresponds to Figure 12 one iteration of steps 132 and 134 of the process 130 shown. The electrode 72c being stimulated is represented by the cross hatch. First, it is shown that the resonance response over multiple cycles can be measured using the novel patterned stimulation. Second, it can be seen that the response at the second electrode 72b has the maximum amplitude, the response at the fourth electrode 72d has the minimum amplitude, and the amplitude of the evoked response at the first electrode 72a is substantially less than that at the second electrode 72b but slightly greater than that at the fourth electrode 72d. These results indicate that the second electrode 72b is closest to or within the target nerve structure, and the first electrode 72a and the fourth electrode 72d are outside the target nerve structure.

[0224] Although the evoked response was measured at three electrodes in the above example, in other embodiments, the evoked response can be measured at one or two or any number of electrodes in any configuration. For example, ERNA can be measured and / or recorded from different combinations of electrodes. Additionally or alternatively, the measurement electrodes can be implanted in and / or located outside the brain or skull.

[0225] Figure 14 Graphically shown in accordance with the application to Figure 10 the lead tip 70 of the system 90 shown Figure 12Exemplary evoked responses to stimuli in process 130. Each column of the figure represents one of four stimulus conditions, where the electrodes for stimulation are represented by the cross panels, i.e., each column is an iteration of steps 132 and 134 of process 130. Figure 14 The data shown were measured by positioning the second electrode 72c and the third electrode 72d within the subthalamic nucleus (STN) of the patient's brain. It can be seen that when the other of the second electrode 72b and the third electrode 72c is stimulated, a maximum evoked response is observed at each of the second electrode 72b and the third electrode 72c. Thus, by comparing the evoked responses measured at each electrode in response to stimulation at the other electrode, it is possible to first determine whether any electrodes are positioned within the target nerve structure, second determine whether any electrodes are positioned at the optimal location within the target nerve structure, and third determine the orientation and / or distance of a particular electrode relative to the target nerve structure. In some embodiments, one or more of the presence, amplitude, natural frequency, damping, rate of change, envelope, and fine structure of the evoked resonance response to stimulation can be used to identify the most effective electrodes in the electrode array. Additionally, it can be seen that the evoked response varies depending on the position of the electrode used for stimulation, demonstrating the feasibility of using the Figure 11 process shown to position the electrodes within the target nerve structure.

[0226] In step 132, the process 130 can be repeated using different stimulation parameters (e.g., using different stimulation amplitudes or frequencies) or with more than one stimulation electrode (e.g., stimulation applied simultaneously by multiple electrodes on one or more electrode leads). The response characteristics obtained can be used to assist with current steering (e.g., setting the current distribution across simultaneously active electrodes) and active electrode selection (e.g., which electrodes are to be used for stimulation). For example, the response characteristics can be used to estimate the spatial spread of activation relative to the target region. Using this information, the stimulation profile can be shaped using two or more electrodes to direct the stimulation to a particular region of the brain, i.e., towards the target structure, and away from regions that the clinician does not wish to stimulate. Figure 12 In another embodiment, ERNA can also be used to optimize the stimulation parameters for various medical conditions. For example, once the electrode array (such as the lead tip 70) has been accurately positioned within the target nerve structure, measuring the ERNA can assist with setting the stimulation parameters for therapeutic DBS, improving accuracy, time efficiency, and cost efficiency, and reducing adverse side effects.

[0227]

[0228] ​Changes in resonant activity caused by different stimulation parameters can be used to optimize the stimulation settings. Such processes can enable the therapy to adapt to the individual needs of the patient and can be performed with minimal clinical intervention. In some embodiments, the presence, amplitude, natural frequency, inter-peak time delay (between two peaks or multiple sets of two or more peaks), damping, rate of change, envelope, and fine structure of the evoked resonant response to the stimulation can be used to optimize the stimulation. Such response characteristics can be used to adjust the amplitude, frequency, pulse width, and shape of the stimulation waveform.

[0229] A parameter of the therapeutic stimulation that is particularly difficult to set using the prior art is the stimulation frequency. This is partly because the optimal stimulation frequency can vary from patient to patient; it typically ranges from about 90 Hz to about 185 Hz. In embodiments of the present disclosure, one or more of the above-described characteristics of the ERNA can be used to set the stimulation frequency (e.g., the time period t between pulses in a burst 2 ). For example, the stimulation frequency can be selected to approximate a multiple or submultiple of a frequency component of the ERNA, such as the estimated fundamental frequency of the ERNA.

[0230] It should be understood that some or all of the parameters listed above can have synergistic or adverse effects on each other, resulting in a therapeutic effect. Thus, in some embodiments, known optimization techniques such as machine learning or particle swarm can be implemented to find the optimal set of parameter values within a multi-dimensional parameter space. Such techniques can involve an iterative process of attempting to select different parameter settings to determine the most effective parameter values based on the monitored ERNA.

[0231] To further optimize therapeutic DBS, the above-described ERNA monitoring and DBS parameter optimization techniques can be performed on a patient before and after administering a drug to alleviate the symptoms of the disorder. For example, the ERNA recordings of a particular patient with or without such a drug can be used as a baseline for the evoked resonant response that provides the greatest benefit to the patient, such that the parameters can be tuned to attempt to replicate such an evoked response state. Figure 15 A method for determining stimulation parameters based on the ERNA in response to stimulation of a medicated patient is schematically shown. At step 144, before administering any drug, a stimulation is applied to an implanted electrode in the target nerve structure of the patient, and at step 146, the ERNA from the stimulation is measured and recorded. The patient is then medicated at step 148. For example, a clinician can administer a dose of a drug (e.g., levodopa) to the patient. The processes of stimulation and measurement of the resonant response are repeated at steps 150 and 152. The ERNA before and after administering the drug is then used to determine the stimulation parameters that approximate those of the patient's medicated state. In particular, the DBS parameter settings can be selected that, when administered, replicate or approximate the transition from the uncontrolled symptom ERNA to the controlled symptom ERNA.

[0232] In some embodiments, the optimization process may be performed by a clinician while the system 90 is being installed or during a visit to a medical center. Additionally or alternatively, the optimization may be run by the patient or may be automatically instigated by the system 90. For example, the system 90 may periodically (e.g., daily, weekly, or monthly) implement the optimization process. In other embodiments, in the case where the power supply 106 includes a battery, the optimization process may be initiated when the battery is replaced or charged. Other conditions that may trigger the optimization process include changes in the patient's state, such as whether the patient is engaged in a fine motor task, a gross motor task, speaking, sleeping, or sedentary.

[0233] In some embodiments, the system 90 may store a series of previously optimized settings in the memory 102. These stored settings may correspond to optimized settings for different patient states (e.g., fine or gross motor activation, sleep or sedentary) and may include stimulation applied to different target nerve structures. By using the patient controller, the patient may be given the ability to select which of the stored stimulation settings they wish to use at any given time. Alternatively, the system 90 may automatically select which stored stimulation settings to use based on measurements of the patient's state from electrophysiological signals (e.g., ERNA or local field potentials) that the system 90 records from the electrodes 70 or from measurements made with the input device 108 (e.g., accelerometer) of the system 90.

[0234] In addition to improving the accuracy of localizing DBS electrodes in the brain, selecting electrode configurations for stimulation, and optimizing stimulation parameters, ERNA may also be used to generate feedback for controlling the stimulation of the electrodes. In some embodiments, the feedback may be implemented using Figure 10 the system 90 shown.

[0235] In one embodiment, the system 90 may use waveform templates corresponding to preferred patient states. Previous recordings of ERNA in patients with symptom alleviation may be used to generate the templates. For example, ERNA templates recorded from medicated patients or patients receiving effective stimulation therapy may be used. Alternatively, ERNA templates recorded from healthy patients, such as patients without movement disorders, may be used. The templates may be constructed based on the average of many recordings from one or several patients. In some embodiments, instead of the complete template, selected features of the ERNA waveform may be used. For example, parameters of the ERNA (such as the dominant frequency and amplitude components and / or temporal features) may be used to achieve improved electrode placement and therapeutic stimulation control. In some embodiments, preferred ranges of different ERNA characteristics may be defined (e.g., control the stimulation such that the ERNA frequency remains within 250 - 270 Hz).

[0236] Reference Figure 10 and Figure 16, the processing unit 92 can send instructions / signals to the signal generator 94 to generate a patterned stimulation signal, which may or may not be pre-calibrated according to the above embodiments. Then, the signal generator 94 can generate a signal at step 160 and apply it to one of the electrodes 72a, 72b, 72c, 72d of the lead tip 70 (step 162). Then, the processing unit 92 can measure the ERNA and monitor one or more parameters (or characteristics) of the ERNA (step 164). Then, the processing unit 92 can process the received ERNA data (step 166). In some embodiments, the processing unit 92 can compare the ERNA (or one or more of its parameters) with the resonance response (or one or more of its parameters) associated with an effective therapy. Based on the ERNA data, the processing unit 92 can then instruct the signal generator to adjust one or more parameters of the stimulation signal applied to one of the electrodes 72a, 72b, 72c, 72d (step 168).

[0237] In some embodiments, stimulation bursts (such as those described above) combined with the monitoring of ERNA can be used to identify a therapeutic resonance state (e.g., a state associated with good symptom suppression, having minimal side effects and / or minimal electrical power consumption). Based on this information, the therapeutic stimulation parameters required to produce a preferred therapeutic state can be identified. In some embodiments, these stimulation parameters can be used to apply continuous therapeutic DBS to the target nerve structure.

[0238] Probing bursts used to identify resonant activity can be interleaved with therapeutic DBS to re-evaluate the resonance state. These probing bursts can be implemented periodically (e.g., every 10 seconds). In one embodiment, every 10 seconds, a probing burst can be applied for 1 second (e.g., 10 pulses at 130 Hz), and the ERNA can be evaluated. Then, the therapeutic stimulation parameters can be adjusted or maintained based on the ERNA. For example, if there is a change in the ERNA relative to the last probing burst, the stimulation parameters can be adjusted such that the ERNA is comparable to the previously measured ERNA and / or a template ERNA, and / or the ERNA characteristics are within the desired range.

[0239] There are various ways to adjust the therapeutic stimulation based on the measured ERNA. In some embodiments, if the resonant circuit is in a preferred resonance state, e.g., if the measured ERNA substantially matches a template, or if the ERNA characteristics are within the desired range, the amplitude of the therapeutic stimulation can be decreased by the signal generator 94 in response to an instruction from the processing unit 92. Conversely, if the nerve circuit is not in a preferred resonance state, the signal generator 94 can increase the amplitude of the therapeutic stimulation.

[0240] In some embodiments, if a therapeutic resonance is detected, DBS stimulation can be turned off completely, or until the next probing burst is applied to generate a measurable ERNA. Then, when the next probing burst is applied, if the resonance is no longer therapeutic, DBS stimulation can be turned back on.

[0241] In some embodiments, comparison of multiple resonance components in a single measured evoked response can be used as a measure of stimulation efficacy and as a control variable for controlling stimulation parameters.

[0242] In some embodiments, the length of consecutive stimulation blocks (between probing bursts) and the duration of the probing bursts can be adjusted to optimize the ERNA. Longer consecutive stimulation periods or blocks between probing bursts will reduce the computational load on the processing unit 92, thus improving power efficiency, but can also result in a greater difference between the ERNA and the preferred ERNA, thereby reducing the therapeutic effect.

[0243] An inherent requirement of implantable and portable DBS devices is to provide optimal symptom treatment while minimizing side effects and power consumption. In one embodiment, a method for operating system 90 using closed-loop feedback is provided, wherein the duty cycle of the stimulation is modulated with the aim of minimizing the stimulation on-time. Figure 17 A process that can be executed by system 90 is shown. At step 170, a stimulation signal is generated. The parameters of the stimulation signal are selected to optimize the ERNA to a preferred resonance state. Then at step 172, the electrodes of lead tip 70 are stimulated for a period T. Period T can be a fixed period. Preferably, the stimulation is applied continuously or periodically until the preferred ERNA state is reached. Then the therapeutic stimulation is stopped, and the evoked response is measured at one or more electrodes, where the evoked response is for a probing stimulus that includes one or more pulse bursts applied to the stimulation electrodes (at step 174). In some embodiments, the probing stimulus can be applied to more than one electrode. In some embodiments, instead of or in addition to one or more other electrodes, the stimulation electrodes can be used to measure the ERNA. Then the system is maintained in this monitoring state until the ERNA becomes undesirable. In some embodiments, the determination of whether the ERNA is in a preferred or therapeutic state can be performed by comparing the measured response to a template ERNA response or by comparing the measured ERNA characteristics to a desired range. Once the state is considered undesirable at step 176, a stimulation signal is generated again at step 170 and the stimulation signal is applied at 172.

[0244] Figure 18A stimulation scheme 178 is graphically compared to a corresponding characteristic (e.g., resonant frequency) 180 of an ERNA, wherein the stimulation scheme 178 includes a patterned therapeutic stimulation signal 182 followed by a non-therapeutic patterned stimulation signal (including one or more pulse bursts) 184, and the corresponding characteristic 180 of the ERNA varies between a preferred state 186 and a less preferred state 188.

[0245] There are several different ways to implement the patterned signals of the embodiments described herein. Figures 19a and 19b show two exemplary patterned profiles. In Figure 19a, the patterned profile includes a non-stimulation period 192 after a continuous stimulation block 190, followed by a pulse burst 194 and another non-stimulation period 196. During the non-stimulation period, ERNA can be measured and the therapeutic stimulation signal can be adjusted (if necessary).

[0246] In an alternative embodiment, the system may monitor ERNA after the final continuous stimulation pulse 198, as shown in FIG19b. After the monitoring period 200, the therapeutic stimulation may then be adjusted for a period 202, after which the therapeutic stimulation 198 may be applied with the adjusted parameters. This scheme may also be considered continuous stimulation with periodic missing pulses. For this purpose, the continuous stimulation may be considered as a burst of pulses, and the no stimulation period may be considered as described above with reference to FIG19b. Figure 2 The first time period t 1 .

[0247] In other embodiments, instead of omitting stimulation during the monitoring period 200, the parameters that can be changed to maintain stimulation, as previously described with reference to Figures 5a and 5b. For example, conventional therapeutic stimulation at a frequency of, for example, 130 Hz can be applied during the therapeutic stimulation period 198. Then, during the monitoring period 200, stimulation with a different frequency can be applied. The stimulation applied during the monitoring period can be lower than the stimulation applied during the stimulation period. For example, the stimulation frequency during this period can be in the range of 90 Hz. The frequency of this stimulation during the monitoring period 200 may be low enough to allow multiple ERNA peaks to be observed. Similarly, the frequency of the stimulation applied during the monitoring period 200 may be high enough to be within the therapeutic frequency range of DBS. As mentioned above, the transition between frequencies can be sudden, or alternatively, the change in frequency can be gradual. It may be advantageous to apply a ramp to the frequency of the pulse to avoid sudden step changes in frequency.

[0248] Additionally or alternatively, the amplitude of the stimulus applied during the monitoring period 200 may be different from the amplitude of the stimulus applied during the treatment period 198. For example, the amplitude of the stimulus applied during the monitoring period 200 may be less than the amplitude of the stimulus applied during the therapeutic stimulus 198. An amplitude ramp may be applied to transition the stimulus between the treatment period 198 and the monitoring period 200 over a number of pulses to avoid a sudden step change in amplitude.

[0249] In some embodiments, characteristics of the stimulus other than amplitude and frequency may be different between the stimulation period 198 and the monitoring period. Examples of such characteristics include, but are not limited to, the frequency, amplitude, pulse width, net charge, electrode configuration, or morphology of the stimulus.

[0250] The presence and amplitude of ERNA may depend on the stimulus amplitude. Thus, to maintain consistency in ERNA measurements, it may be preferred to always use the same pulse parameter settings, particularly the same amplitude, for the pulses used to measure ERNA. Thus, the last pulse before a no-stimulus period may be at a fixed amplitude that is independent of the amplitude of the stimulus applied by other pulses (e.g., therapeutic stimuli) to minimize any effects due to resonance dependence on stimulus amplitude or other pulse parameters.

[0251] While in the above-described embodiments, a single electrode array is used both for stimulation and recording of the evoked neural response, in other embodiments, electrodes may be distributed on multiple probes or leads in one or more target structures in one or both cerebral hemispheres. Similarly, electrodes implanted or positioned outside the brain may be used for stimulation or recording or both stimulation and recording of the evoked neural response. In some embodiments, a combination of both microelectrodes and macroelectrodes may be used in any foreseeable manner.

[0252] In a further application of embodiments of the present invention, ERNA measurement constructs may be recorded and tracked over time to monitor the progression or remission of a disease or syndrome, or used as a diagnostic tool (e.g., to classify a patient's neurological condition). In the case where the patient's state (as determined by ERNA) deteriorates towards an undesirable or critical state (e.g., a Parkinson's disease crisis), such embodiments may also be used to provide a medical alert to the patient, caregiver, or clinician.

[0253] In yet another application, ERNA may be used to monitor the effect of a drug over time, including the effect of adjusting the drug dosage, etc. Such embodiments may also be used to provide a drug alert to the patient to remind them of when a dose is due or when to skip a dose. Tracking drug effects with ERNA can also provide information to the clinician regarding whether the drug is being taken as prescribed, whether the drug efficacy is decreasing, and whether a dose adjustment is needed.

[0254] In any of the embodiments described herein, the patient may be awake or under general anesthesia. Figures 27 to 43 As discussed, the inventors determined that ERNA is still present in patients under general anesthesia, and therefore ERNA can be used during surgical procedures in which the patient is under general anesthesia. In addition, since various properties of ERNA change under general anesthesia, such properties can be used to determine the effect of general anesthesia on ERNA and therapeutic stimulation. In addition, by comparing the ERNA of awake patients with the same patient during induction and maintenance of anesthesia, ERNA can provide a supportive indication of patient consciousness, which is generally beneficial during general anesthesia.

[0255] General anesthesia can be induced in any manner known in the art. Examples of intravenous induction agents that can be used to induce general anesthesia include propofol, sodium thiopental, etomidate, methoxetine, and ketamine. An example of an inhalation induction agent that can be used to induce general anesthesia is sevoflurane.

[0256] General anesthesia can be maintained in any manner known in the art by inhalation, intravenous means or their combination. The example of suitable inhalation anesthetics includes isoflurane, sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide and xenon. Other inhalation anesthetics that may be suitable include ethyl chloride (ethyl chloride), chloroform, frozen halothane, cyclopropane, diethyl ether, pentane, ethylene, polyethylene ether, methoxypropane, trichloroethylene and vinyl ether. Inhalants can be supplemented by intravenous anesthetics (such as opioids (for example, fentanyl or fentanyl derivatives such as remifentanil) and / or sedatives (such as propofol or benzodiazepines, for example, midazolam) and / or barbiturates (such as thiopental sodium)).

[0257] Further analysis of ERNA and interpretation of results

[0258] DBS induces resonant neural activity

[0259] Neural activity induced by DBS pulses is studied to determine if there are evoked responses that could potentially be used as biomarkers. To preserve evoked activity, stimulation is performed using a wide recording bandwidth as well as symmetrical biphasic pulses, rather than conventional asymmetrical pulses with a very long second phase to minimize the duration of stimulation artifacts.

[0260] Since PD is a major application of DBS, recordings were performed immediately after implantation of DBS electrodes in the STN of PD patients while they were still awake on the operating table. In addition, the modulatory role of the STN in motor, limbic, and associative functions makes it a neural target relevant for a variety of different applications, including DBS treatment of dystonia, essential tremor, epilepsy, and obsessive-compulsive disorder.

[0261] It was found that STN-DBS typically induces large peaks approximately 4 ms after each pulse. By examining the activity after the last pulse before DBS was stopped, it was found that this peak was the first peak with a gradually decreasing amplitude in the sequence. Since this response has the form of a damped oscillation, it was described as evoked resonant neural activity (ERNA).

[0262] To further study ERNA, the standard 130 Hz DBS pattern was temporally patterned to allow multiple peaks to be observed. Two novel patterns were employed: skipping one pulse per second and applying ten-pulse bursts per second. The "skipped pulse" pattern was expected to have a therapeutic effect comparable to that of standard 130 Hz DBS, since over time, the "skipped pulse" pattern results in only a 0.77% reduction in the total number of pulses. In contrast, the "burst" pattern was expected to have minimal therapeutic effect relative to continuous DBS, since only 7.7% of the pulses are delivered, making it a useful probe for studying activity in the absence of therapy. The evoked response tended to increase in amplitude and sharpen across consecutive pulses of the burst and reached a steady state under longer-duration stimulation.

[0263] Burst stimulation was applied to the STN of 12 PD patients (n = 23 hemispheres) who had undergone DBS implantation surgery, and ERNA with a similar morphology was observed in all cases, indicating that ERNA is a robust and reliable signal that can be measured across patient populations. As a control to ensure that ERNA was not a suspected artifact, burst stimulation was also applied to 3 essential tremor patients (n = 6 hemispheres) in whom the electrodes were implanted in the posterior subthalamic area (PSA) (i.e., the white matter area medial to the STN). No ERNA was observed in the PSA, indicating that it is an electrophysiological response that can be localized to the STN.

[0264] ERNA can be localized to the STN

[0265] To confirm that ERNA varies with electrode position relative to the STN, 10 s of burst stimulation was continuously applied to each of four DBS electrodes while recording from three unstimulated electrodes. The DBS implantation surgery was designed to position two of the four electrodes within the STN, with one electrode in the dorsal STN where DBS typically has the greatest benefit and the other electrode in the ventral STN. This variation in electrode position helped to compare the ERNA responses in different regions of the STN with those outside the nucleus. In 8 STN-PD patients (n = 16 hemispheres), it was found that both the amplitude and morphology of ERNA varied according to the stimulating and recording electrode positions. Figure 14Exemplary ERNA showing the last pulse of each burst from one hemisphere, where the responses with the largest amplitude and the most distinct damped oscillatory morphology occur at two intermediate electrodes at the target STN location. As a control, stimulation was also applied to two essential tremor patients (n = 4 hemispheres) using implantation trajectories that were intended to position the distal electrode within the PSA and the proximal electrode within the ventral intermediate nucleus of the thalamus (another tremor target previously shown not to elicit evoked activity beyond ~2 ms).

[0266] Since the change in ERNA amplitude is the most prominent feature, it was used for further analysis. Since not all recordings were in the STN and contained distinct resonant activity, to quantify the ERNA amplitude, the root mean square (RMS) voltage was calculated over 4 - 20 milliseconds. To estimate the implanted electrode position relative to the STN, postoperative CT scans merged with preoperative MRI (Figure 23) were used to generate 3D reconstructions ( Figure 22 ). Based on blind measurements relative to the red nucleus, the electrodes were classified as being above, below, or within the STN. Electrodes within the STN were then further classified as dorsal or ventral.

[0267] ERNA amplitude varied significantly with electrode position (Kruskal - Wallis, H(4) = 45.73, p < 0.001), where only the inferior electrodes were not significantly different from the PSA region (p = 0.370)( Figure 24 ). Although dorsal electrodes tended to be higher than ventral and superior ones, they were not significantly different from each other in amplitude. To account for patient - to - patient amplitude differences due to variations in electrode positioning in the medial - lateral and posterior - anterior planes and underlying differences in patient physiology, recordings from STN - DBS electrodes were re - analyzed after normalizing the responses of the total ERNA amplitude across each hemisphere. After normalization, post - hoc comparisons revealed a significant difference in amplitude between dorsal and ventral STN (Kruskal - Wallis, H(3) = 14.94, p = 0.002; post - hoc with Dunn's method, dorsal vs ventral: p = 0.043, dorsal vs superior: p = 0.081, dorsal vs inferior: p = 0.002).

[0268] These results suggest that ERNA can be localized to the STN and varies across the STN, thus establishing its utility as a feedback signal for guiding electrode implantation to the most beneficial stimulation sites. In addition, although amplitude variation is the most prominent feature, other ERNA properties (such as frequency, time delay, and rate of change) also have potential utility in discriminating STN regions.

[0269] Modulation of ERNA by DBS

[0270] To investigate whether ERNA is modulated by DBS that is therapeutically effective, skip pulse stimulation with gradually increasing current amplitude (ranging from 0.67 - 3.38 mA) in 60 - 90 s blocks was applied to 10 STN - PD patients (n = 19 hemispheres). Generally, it was found that the second and subsequent peaks of ERNA were consistently observed to gradually increase in latency and further disperse with increasing time and stimulus amplitude, which is consistent with a decrease in the resonance activity frequency (Figures 5, 6, 21a to 21e). In many cases, the latency of the first peak also increased, but this change was not consistent across all recordings. The amplitude of the peaks was also commonly observed to vary, usually being larger at the start of each stimulus block and then gradually decreasing.

[0271] To quantify these effects, the reciprocal of the latency difference between the first and second peaks was calculated as a representative measure of ERNA frequency. The amplitude difference between the first peak and the first trough was also calculated as a representative measure of ERNA amplitude. Then, the mean value of the 45 - 60 s period for each condition was used as an estimate of the progressive ERNA value for analysis.

[0272] The ERNA frequency decreased significantly across conditions (one - way repeated measures (RM) ANOVA, F(4,94) = 45.79, p < 0.001). Post - hoc comparisons (Holm - Sidak) showed that the ERNA frequency decreased significantly with each increasing step of DBS amplitude ( Figure 25A ), except for 2.25 mA to 3.38 mA (p = 0.074). The median frequency was 256 Hz at 3.38 mA, approximately twice the 130 Hz stimulation rate. It has been proposed that STN - DBS may act by forming a pacing effect at twice the stimulation rate within the globus pallidus, which is attributed to the immediate excitation of STN axons and the inhibition / recovery time course of the STN soma.

[0273] The ERNA amplitude also differed significantly across conditions (Friedman, x 2 (4) = 41.31, p < 0.001). Post - hoc comparisons with Tukey tests showed that the ERNA amplitude initially increased with DBS amplitude and then stabilized at levels above 1.5 mA ( Figure 25B ). Although these effects may be related to the therapeutic effects of DBS, they may alternatively or additionally be attributed to the saturation of neural firing in the STN. Therefore, subsequent focus was on the association between ERNA frequency and therapeutic effects.

[0274] Association between ERNA and therapeutic effects

[0275] The clinical efficacy of the stimulation was confirmed by assessing limb bradykinesia and rigidity according to the Unified Parkinson’s Disease Rating Scale (UPDRS; items 22 and 23) before and 60 s after stimulation at 2.25 mA. Both clinical signs were significantly improved at 2.25 mA, indicating that DBS was therapeutic (Wilcoxon signed-rank test, bradykinesia: Z = -3.62, p < 0.001, rigidity: Z = -3.70, p < 0.001).

[0276] However, time constraints precluded clinical examination of the stimulation intensity at each step. Therefore, to relate ERNA modulation to the patient state, spontaneous LFP activity in the beta band (13 - 30 Hz) was used. Excessive synchronization of oscillations within the beta band is closely related to the pathophysiology of PD, and its suppression has been associated with improvement of bradykinesia and rigidity dyskinesias.

[0277] Using short-time Fourier transform, “relative beta” was calculated, which is the RMS amplitude within the 13 - 30 Hz band divided by the RMS amplitude within 5 - 45 Hz, as a representative measure of beta activity. Then, the mean value was taken over the 45 - 60 s period across each stimulation amplitude condition, and significant changes in the relative beta values were found (one-way RM ANOVA, F(4,89) = 18.11, p < 0.001). Post hoc tests (Holm-Sidak) showed significant suppression at 3.38 mA compared to all other conditions, and significant suppression at 2.25 mA compared to 0.67 and 1 mA ( Figure 25C ). These results were consistent with previous studies, thus indicating that the beta activity suppression caused by DBS is associated with improvement of clinical signs and demonstrating that stimulation is therapeutically effective at 2.25 mA and above.

[0278] To further relate the ERNA frequency to beta activity and therapeutic efficacy, the mean values of 15 s non-overlapping blocks were compared across various conditions ( Figure 25B ). The ERNA frequency was significantly associated with relative beta (Pearson product-moment, ρ = 0.601, n = 90, p < 0.001).

[0279] These results indicate that ERNA is a clinically relevant biomarker. Additionally, its large amplitude in the range of 20 μVp-p to 681 μVp-p (median 146 μVp-p) is several orders of magnitude larger than spontaneous βLFP activity, the absolute value of which ranges from 0.9 to 12.5 μVRMS (median 2.2 μVRMS). The robustness of ERNA and its unique gradually modulated morphology (Figures 5, 6, 7, 21) contrast sharply with the inherent variability of β-band activity in patients and the noisy burst on-off nature of β spectral band signals. Thus, compared to noisy low-amplitude LFP metrics, ERNA is a more controllable signal for use with fully implantable DBS devices.

[0280] ERNA modulates DBS following washout

[0281] Immediately before and after therapeutic skip pulse stimulation, a 60 s burst stimulation (hereinafter referred to as the pre-DBS and post-DBS conditions) was also applied to monitor activity changes caused by washout of the therapeutic effect.

[0282] Typically, ERNA remained relatively stable before DBS, indicating minimal modulation effect of the burst stimulation. However, immediately following DBS, ERNA peaks appeared with a longer latency and then gradually returned to their pre-DBS state. To quantify these effects, the ERNA frequency and amplitude were averaged within 15 s non-overlapping blocks after DBS and compared to the ERNA frequency and amplitude in the 15 s before DBS. Across all hemispheres tested (N = 19), a difference in ERNA frequency was found (Friedman, χ 2 (4) = 70.23, P < 0.001), where the frequency was significantly reduced at all time points compared to the pre-DBS frequency, except for the last 45 - 60 s block (Tukey, p = 0.73) ( Figure 26A ). The ERNA amplitude also changed significantly across time points (Friedman, χ 2 (4) = 31.37, P < 0.001), where the difference between amplitudes at post-DBS time points indicated washout of the amplitude suppression caused by the therapeutic stimulation ( Figure 26B ). Since the burst stimulation applied across the pre-DBS and post-DBS conditions was constant, the observed changes in ERNA frequency and amplitude can be directly attributed to changes in the state of the STN neural circuit due to washout of the DBS effect. Thus, therapeutically effective DBS modulates ERNA frequency and amplitude, indicating that ERNA has multiple properties that may serve as a biomarker and a tool for probing mechanisms of action.

[0283] Relative β activity was then evaluated before and after DBS and was found to be significantly different across time points (Friedman, χ 2 (4)＝ 24.55, P < 0.001). Consistent with previous reports, relative β decreased significantly immediately after DBS and washed out to pre-DBS levels after 30 s ( Figure 26C ). ERNA frequency supported the skip pulse results, being significantly associated with relative β before and after DBS (Pearson product-moment, ρ = 0.407, n = 152, p < 0.001). ERNA amplitude was also associated with relative β (Pearson product-moment, ρ = 0.373, n = 152, p < 0.001), suggesting that it may also have clinical and mechanistic associations.

[0284] Spontaneous LFP activity in the high-frequency oscillation (HFO) band (200 - 400 Hz) was also analyzed, which overlapped with the observed ERNA frequency. Changes in the HFO band were associated with motor state and effective drug therapy, particularly with β activity, and were closely related to the mechanism of action of DBS. Concurrent ERNA and HFO analysis could be achieved by using burst stimulation, as the data could be segmented to include only the activity between bursts, providing LFP epochs free from stimulus artifacts that could otherwise disrupt the HFO band.

[0285] Since HFO activity is typically characterized by broadband peaks in frequency, multi-taper spectral estimation results were calculated and then the frequencies and amplitudes of the peaks occurring between 200 - 400 Hz were determined. Comparisons were made across 15-s non-overlapping blocks ( Figure 26D ), and it was found that the HFO peak frequency decreased significantly after DBS (Friedman, χ 2 (4) ＝ 45.18, P < 0.001), until the final 45 - 60 s block (Tukey, p = 0.077). This washout trend matched the washout trend of ERNA frequency, although at a lower frequency, and there was a significant association between the two (Pearson product-moment, ρ = 0.546, n = 152, p < 0.001). The median HFO peak frequency immediately following DBS was 253 Hz, comparable to the median ERNA frequency (256 Hz) in the therapeutic 3.38 mA condition, suggesting that during more continuous skip pulse stimulation, HFO activity occurred at the same frequency as ERNA.

[0286] No significant differences were found in HFO peak amplitude (Friedman, χ 2 (4) ＝ 2.11, P = 0.72), but it was significantly associated with ERNA amplitude (Pearson product-moment, ρ = 0.429, N = 152). It is possible that the extremely small amplitude (< 1 μV) of the HFO peak caused any modulation effects to be masked by noise in the recordings.

[0287] Those skilled in the art will appreciate that numerous variations and / or modifications can be made to the above-described embodiments without departing from the broad general scope of the disclosure. Accordingly, the embodiments of the invention are to be considered in all respects as illustrative and not restrictive.

[0288] The following is a list of numbered clauses that define particular embodiments of the disclosure. If a numbered clause refers to an earlier numbered clause, those clauses may be considered in combination.

[0289] 1. A method of monitoring neural activity in a subject's brain in response to a stimulus, the method comprising:

[0290] a. inducing general anesthesia in the subject;

[0291] b. applying the stimulus to one or more of at least one electrode implanted in a target neural structure of the brain;

[0292] c. detecting, at one or more of the at least one electrode in or near the target neural structure of the brain, a resonance response from the target neural structure induced by the stimulus; and

[0293] d. determining one or more waveform characteristics of the detected resonance response.

[0294] 2. A method of monitoring neural activity in a subject's brain in response to a stimulus under general anesthesia, the method comprising:

[0295] a. applying the stimulus to one or more of at least one electrode implanted in a target neural structure of the brain;

[0296] b. detecting, at one or more of the at least one electrode in or near the target neural structure of the brain, a resonance response from the target neural structure induced by the stimulus; and

[0297] c. determining one or more waveform characteristics of the detected resonance response.

[0298] 3. The method according to clause 1 or 2, wherein the one or more waveform characteristics are determined based on at least a portion of a second or subsequent cycle in the detected resonance response.

[0299] 4. The method according to any one of clauses 1 to 3, wherein the one or more waveform characteristics include one or more of the following:

[0300] a) the frequency of the resonance response;

[0301] b) the temporal envelope of the resonance response;

[0302] c) the amplitude of the resonance response;

[0303] d) The fine structure of the resonance response;

[0304] e) The decay rate of the resonance response;

[0305] f) The delay between the initiation of the stimulus and the initiation of the temporal characteristics of the resonance response;

[0306] g) The duration between two peaks in the resonance response.

[0307] 5. The method according to any one of the preceding clauses, wherein the stimulus comprises a plurality of pulses.

[0308] 6. The method according to any one of the preceding clauses, wherein determining the one or more waveform characteristics comprises comparing a first characteristic within two or more cycles of the detected resonance response.

[0309] 7. The method according to clause 6, wherein the step of determining the one or more waveform characteristics comprises determining the variation of the first characteristic within the two or more cycles.

[0310] 8. The method according to clause 6 or 7, wherein the step of determining the one or more waveform characteristics comprises determining the rate of change of the first characteristic within the two or more cycles.

[0311] 9. The method according to any one of the preceding clauses, wherein the resonance response comprises a plurality of resonance components.

[0312] 10. The method according to any one of the preceding clauses, wherein one or more of the plurality of resonance components originate from a nerve structure different from the target nerve structure.

[0313] 11. The method according to clause 8, further comprising: adjusting the position of one or more of the at least one electrode based on the one or more determined waveform characteristics.

[0314] 12. The method according to any of the preceding clauses, further comprising:

[0315] Adapting the stimulus based on the one or more determined waveform characteristics of the resonance response.

[0316] 13. The method according to clause 12, wherein the adaptation comprises adjusting one or more of the frequency, amplitude, pulse width, net charge, electrode configuration or modality of the stimulus.

[0317] 14. The method according to clause 12 or 13, further comprising:

[0318] Associating the detected resonance response with a template resonance response; and

[0319] Adjust the stimulation based on the association.

[0320] 15. The method according to any one of clauses 12 to 14, further comprising:

[0321] Associate the one or more determined waveform characteristics with one or more predetermined thresholds; and

[0322] Adjust the stimulation based on the association.

[0323] 16. The method according to any one of the preceding clauses, wherein the stimulation is non - therapeutic or therapeutic.

[0324] 17. The method according to any one of the preceding clauses, wherein the stimulation comprises a patterned signal, the patterned signal comprising a plurality of bursts spaced apart by a first time period, each burst comprising a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

[0325] 18. The method according to clause 17, wherein at least one of the plurality of pulses within a burst has a different amplitude.

[0326] 19. The method according to clause 18, wherein the different amplitudes are selected to produce an amplitude ramp of sequential pulses in at least one of the bursts.

[0327] 20. The method according to any one of clauses 17 to 19, wherein the final pulse in each of the plurality of bursts is substantially the same.

[0328] 21. The method according to any one of clauses 17 to 20, wherein during the first time period, the stimulation comprises continuous therapeutic stimulation.

[0329] 22. The method according to clause 21, wherein the frequency of the stimulation during the first time period is greater than the frequency of the stimulation during the second time period.

[0330] 23. The method according to any one of the preceding clauses, further comprising:

[0331] Apply a second stimulation to the target nerve structure in the brain;

[0332] Detect, at one or more of the at least one electrode implanted in or near the target nerve structure, a second resonance response from the target nerve structure induced by the second stimulation;

[0333] Determine one or more second waveform characteristics of the detected second resonance response.

[0334] 24. The method as described in clause 23, further comprising:

[0335] Determining the effectiveness of the therapy provided to the patient based on the one or more first waveform characteristics and the one or more second waveform characteristics.

[0336] 25. The method as described in any one of clauses 23 to 24, wherein the at least one electrode comprises two or more electrodes located within different neural structures in the brain.

[0337] 26. The method as described in clause 25, wherein the at least one electrode comprises two or more electrodes located within different hemispheres of the brain.

[0338] 27. The method as described in any one of the foregoing clauses, further comprising:

[0339] Determining whether one or more of the at least one electrode are located in the target neural network based on the detected resonance response.

[0340] 28. The method as described in clause 27, further comprising: moving one or more of the first electrode and the second electrode based on the detected resonance response.

[0341] 29. The method as described in any one of the foregoing clauses, further comprising:

[0342] Repeating the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response.

[0343] 30. The method as described in clause 29, further comprising: comparing the common waveform characteristics between two or more detected resonance responses.

[0344] 31. The method as described in clause 29 or 30, further comprising: comparing the degree of change in the common characteristics between two or more detected resonance responses.

[0345] 32. The method as described in any one of clauses 29 to 31, further comprising: determining the rate of change in the common characteristics between two or more detected resonance responses.

[0346] 33. The method as described in any one of clauses 30 to 32, wherein the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response are repeated until it is determined that one or more of the at least one electrode are located in the target neural structure.

[0347] 34. The method as described in any one of the foregoing clauses, further comprising:

[0348] select one or more of the at least one electrode to be used for therapeutically stimulating the target nerve structure based on the one or more waveform characteristics; and

[0349] apply a therapeutic stimulation to the target nerve structure through the selected one or more of the at least one electrode.

[0350] 35. The method according to clause 29, further comprising:

[0351] insert the at least one electrode into the brain along a predetermined trajectory;

[0352] wherein while inserting the at least one electrode, the steps of repeatedly applying the stimulation, determining the resonance response, and determining one or more waveform characteristics of the detected resonance response are repeated to generate a resonance response profile with respect to the predetermined trajectory and the target nerve structure.

[0353] 36. The method according to clause 35, wherein the resonance response profile is used to determine the position of the one or more electrodes relative to the target nerve structure.

[0354] 37. The method according to clause 29, wherein the at least one electrode includes a plurality of electrodes, and wherein the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response are repeated using different combinations of the at least one electrode to generate a resonance response profile.

[0355] 38. The method according to clause 36 or 37, further comprising:

[0356] select one or more of the at least one electrode based on the nerve response profile; and

[0357] apply a therapeutic stimulation to the selected one or more of the at least one electrode.

[0358] 39. The method according to clause 38, wherein the selected one or more of the at least one electrode includes a plurality of electrodes.

[0359] 40. The method according to any one of the preceding clauses, wherein the one or more of the at least one electrode for applying the stimulation includes at least two electrodes, and / or wherein the one or more of the at least one electrode for detecting the resonance response includes at least two electrodes.

[0360] 41. The method according to any one of the preceding clauses, wherein the nerve target structure is part of a cortico-basal ganglia-thalamo-cortical circuit.

[0361] 42. The method according to any one of the preceding clauses, wherein the target nerve structure is the subthalamic nucleus, the internal globus pallidus, the substantia nigra reticulata, the pedunculopontine nucleus.

[0362] 43. A method of monitoring neural activity in a subject's brain in response to a stimulus under general anesthesia, the method comprising:

[0363] a. applying the stimulus to a target nerve structure in the brain; and

[0364] b. detecting, at an electrode implanted in or near the target nerve structure, a neural response evoked by the stimulus,

[0365] wherein the stimulus comprises a patterned signal, the patterned signal comprising a plurality of bursts spaced apart by a first time period, each burst comprising a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

[0366] 44. A method of monitoring neural activity in a subject's brain in response to a stimulus, the method comprising:

[0367] a. inducing general anesthesia in the patient;

[0368] b. applying the stimulus to a target nerve structure in the brain; and

[0369] c. detecting, at an electrode implanted in or near the target nerve structure, a neural response evoked by the stimulus,

[0370] wherein the stimulus comprises a patterned signal, the patterned signal comprising a plurality of bursts spaced apart by a first time period, each burst comprising a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

[0371] 45. The method according to clause 43 or 44, wherein the first time period is greater than or equal to the second time period.

[0372] 46. The method according to any one of clauses 43 to 45, wherein the stimulus is biphasic.

[0373] 47. The method according to any one of clauses 43 to 46, wherein the plurality of pulses within a burst have different amplitudes.

[0374] 48. The method according to clause 47, wherein the different amplitudes are selected to produce a ramp.

[0375] 49. The method according to any one of clauses 43 to 48, wherein the final pulse in each of the plurality of bursts is substantially the same.

[0376] 50. The method according to any one of clauses 43 to 49, wherein the stimulation is patterned to be non-therapeutic or therapeutic.

[0377] 51. The method according to any one of the preceding clauses, wherein general anesthesia in the subject is induced using a reagent selected from propofol, thiopental, etomidate, methohexital, ketamine, and sevoflurane.

[0378] 52. The method according to any one of the preceding clauses, wherein general anesthesia in the subject is maintained using a reagent selected from isoflurane, sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide, and xenon.

[0379] 53. The method according to any one of the preceding clauses, wherein general anesthesia in the subject is maintained using a fentanyl derivative, a barbiturate, or a benzodiazepine.

[0380] 54. The method according to any one of the preceding clauses, wherein general anesthesia in the subject is induced using propofol and maintained using a combination of sevoflurane and remifentanil.

Claims

1. A system for monitoring neural activity in the brain of a subject under general anesthesia, comprising: a lead having at least one electrode adapted to be implanted in or near a target nerve structure in the brain; a signal generator selectively coupled to one or more of the at least one electrode and configured to generate a stimulus for stimulating the target nerve structure; a measuring device selectively coupled to one or more of the at least one electrode and configured to detect a resonance response from the target nerve structure induced by the stimulus; a processing unit coupled to the measuring device and configured to determine one or more waveform characteristics of the detected resonance response, wherein the one or more waveform characteristics include the duration between two peaks in the resonance response; wherein the processing unit is configured to determine whether one or more of the at least one electrode are positioned in the target nerve structure based on the one or more waveform characteristics including the duration between a first peak and a second peak in the detected resonance response and / or the duration between a second peak and a third peak in the detected resonance response, wherein the duration between the first peak and the second peak is different from the duration between the second peak and the third peak.

2. The system according to claim 1, wherein, the one or more waveform characteristics are determined based on at least a portion of a second or subsequent cycle of the detected resonance response.

3. The system according to claim 1 or 2, wherein, the one or more waveform characteristics include one or more of the following: a) the frequency of the resonance response; b) the temporal envelope of the resonance response; c) the amplitude of the resonance response; d) the fine structure of the resonance response; e) the decay rate of the resonance response; f) the delay between the initiation of the stimulus and the initiation of the temporal characteristics of the resonance response.

4. The system according to claim 1 or 2, wherein, the processing unit is configured to: control the signal generator to adapt the stimulus based on the one or more determined waveform characteristics of the resonance response.

5. The system according to claim 1 or 2, wherein, the stimulus may include a patterned signal including a plurality of bursts spaced apart by a first time period, each burst including a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

6. The system according to claim 1 or 2, wherein, the processing unit is configured to: control the signal generator to apply a second stimulus to the target nerve structure in the brain; control the measuring device to detect a second resonance response from the target nerve structure induced by the second stimulus at one or more of the at least one electrode implanted in or near the target nerve structure; and determine one or more second waveform characteristics of the detected second resonance response.

7. The system according to claim 1 or 2, Characterized in that, the signal generator, the measuring device, and the processing unit are configured to: repeat the steps of applying the stimulus, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response.

8. The system according to claim 1 or 2, characterized in that, one or more electrodes for applying the stimulus in the at least one electrode include at least two electrodes, and / or one or more electrodes for detecting the resonance response in the at least one electrode include at least two electrodes.

9. A non-therapeutic method for monitoring neural activity in a subject's brain in response to a stimulus under general anesthesia, the method comprising: a. applying the stimulus to one or more of at least one electrode implanted in a target nerve structure of the brain; b. detecting, at one or more of the at least one electrode in or near the target nerve structure of the brain, a resonance response from the target nerve structure induced by the stimulus; c. determining one or more waveform characteristics of the detected resonance response, wherein the one or more waveform characteristics include the time elapsed between two peaks of the resonance response; and d. determining whether one or more of the at least one electrode are located in the target nerve structure based on the one or more waveform characteristics including the duration between a first peak and a second peak in the detected resonance response and / or the duration between a second peak and a third peak in the detected resonance response, wherein the duration between the first peak and the second peak is different from the duration between the second peak and the third peak.

10. The method according to claim 9, wherein the one or more waveform characteristics are determined based on at least a portion of a second or subsequent cycle in the detected resonance response.

11. The method according to any one of claims 9 to 10, wherein the one or more waveform characteristics include one or more of the following: a) the frequency of the resonance response; b) the time envelope of the resonance response; c) the amplitude of the resonance response; d) the fine structure of the resonance response; e) the decay rate of the resonance response; f) the delay between the initiation of the stimulus and the initiation of the time characteristics of the resonance response.

12. The method according to any one of claims 9 to 10, which further comprises: adapting the stimulus based on the one or more determined waveform characteristics of the resonance response.

13. The method according to any one of claims 9 to 10, wherein the stimulus comprises a patterned signal, the patterned signal comprising a plurality of bursts spaced apart by a first time period, each burst comprising a plurality of pulses spaced apart by a second time period, wherein the first time period is greater than the second time period, and wherein the detection is performed during one or more of the first time periods.

14. The method according to any one of claims 9 to 10, which further comprises: applying a second stimulus to the target nerve structure in the brain; At one or more of the at least one electrode implanted in or near the target nerve structure, detecting a second resonance response from the target nerve structure induced by the second stimulation; Determining one or more second waveform characteristics of the detected second resonance response.

15. The method according to any one of claims 9 to 10, further comprising: Repeating the steps of applying the stimulation, detecting the resonance response, and determining one or more waveform characteristics of the detected resonance response.

16. The method according to any one of claims 9 to 10, wherein one or more of the at least one electrode for applying the stimulation comprise at least two electrodes, and / or wherein one or more of the at least one electrode for detecting the resonance response comprise at least two electrodes.

17. The method according to claim 13, wherein the first time period is greater than or equal to the second time period.

18. The method according to claim 17, wherein the final pulse in each of the plurality of bursts is substantially the same.

19. The method according to any one of claims 17 to 18, wherein general anesthesia in the subject is induced using a reagent selected from propofol, thiopental, etomidate, methohexital, ketamine, and sevoflurane.

20. The method according to any one of claims 17 to 18, wherein one or more of the following apply: a) General anesthesia in the subject is induced using propofol and maintained using a combination of sevoflurane and remifentanil; b) General anesthesia in the subject is maintained using a reagent selected from isoflurane, sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide, and xenon; c) General anesthesia in the subject is maintained using a fentanyl derivative, a barbiturate, or a benzodiazepine.

21. A non-transitory computer-readable storage medium storing instructions that can be executed by a processor to: a. Apply a stimulation to one or more of at least one electrode implanted in a target nerve structure of a subject under general anesthesia; b. Detect, at one or more of the at least one electrode in or near the target nerve structure of the brain, a resonance response from the target nerve structure induced by the stimulation; c. Determine one or more waveform characteristics of the detected resonance response, wherein the one or more waveform characteristics include the time elapsed between two peaks of the detected resonance response; and d. Determine whether one or more of the at least one electrode are positioned in the target nerve structure based on the one or more waveform characteristics including the duration between a first peak and a second peak and / or the duration between a second peak and a third peak in the detected resonance response, wherein the duration between the first peak and the second peak is different from the duration between the second peak and the third peak.

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