Methods and devices for vectorial targeting of the human central thalamus to guide deep brain stimulation therapy - Patents.com

Abstract

Methods and devices are disclosed for vector targeting of the human central thalamus (CT) to guide deep brain stimulation (DBS). In some embodiments, electrodes are provided, each with a plurality of contacts. A three-dimensional orientation of the main axis of the central lateral nucleus-medial component of the dorsal tegmental tract (CL / DTTm) fiber bundle of a human subject is determined. The contacts of the electrode are positioned within the CT fibers of the subject in substantial alignment with the three-dimensional orientation. Electrical stimulation is applied to the contacts to selectively activate the CT fibers. The positioning and application are performed to maximize activation of the central lateral nucleus-dorsomedial tegmental tract fiber pathway in the subject and minimize activation of the central median nucleus-parafascicular nucleus fiber pathway in the subject. Methods and devices for surgical planning involving vector targeting of human CT to guide DBS are also disclosed. TIFF2024535859000003.tif123128

Description

[Technical field]

[0001] This invention was made with Government support under Grant No. UH3 NS095554 awarded by the National Institutes of Health-National Institute of Neurological Disorders and Stroke. The Government has certain rights in this invention.

[0002] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 244,589, filed September 15, 2021, which is incorporated by reference in its entirety.

[0003] Field The present technology relates to methods and devices, including systems and non-transitory computer-readable media, for vector-based targeting of the human central thalamus to guide deep brain stimulation therapy. [Background technology]

[0004] background The central thalamus (CT) is a key node in the mammalian brain's arousal regulatory network, hypothesized to modulate large-scale activity patterns throughout the anterior forebrain in response to internal and external demands during wakefulness. Damage to the CT in humans, for example due to traumatic brain injury (TBI) or stroke, results in persistent cognitive deficits in attention allocation, concentration and sustained attention, working memory, impulse control, processing speed, and motivation. Furthermore, the CT shows extensive point-to-point connections throughout the cortico-thalamic system and also to the striatum, and because of the geometric properties of neurons in the CT, cognitive dysfunction (typically in the form of executive dysfunction) and arousal regulation resulting from loss of neurons within the CT are a common consequence of multifocal brain injury, typical of traumatic brain injury; anoxia; hypoxic-ischemic encephalopathy; vasospasm (e.g., due to aneurysmal hemorrhage, vasculitis, or other causes); or multifocal ischemic insults sustained by toxic-metabolic, post-infectious, autoimmune, or a wide range of other causes.

[0005] Current therapies are ineffective in treating these cognitive deficits, so central thalamic deep brain stimulation (DBS) (CT-DBS) has been proposed as a treatment option to artificially reconstruct arousal regulation to re-establish and / or generally support cognitive function in TBI subjects. By targeting the "wings" of the central lateral (CL) nucleus and its axonal projection fiber bundles, CT-DBS may result in significant and cumulative improvements in responsiveness, communication, and motor function in subjects after very severe TBI. However, the mechanism that produces this outcome remains unclear, depending on the location of the DBS lead (e.g., electrodes and / or associated contacts) and the method of neural activation.

[0006] The use of DBS to treat very severe TBI subjects has a long history of failure; primarily due to poor subject selection and hypothesis-free DBS targeting. The primary target for DBS in these subjects has been the centromedian-parafascicular complex (Cm-Pf) of the thalamus, a relatively large and prominent nucleus located near the CL nucleus. To date, however, clinical outcomes in this subject population have been highly variable due to multiple factors, including the etiology of the disease being investigated; the ability to successfully target and obtain the CM-Pf during lead implantation; and the underlying rate of spontaneous recovery from TBI within one year after injury.

[0007] Although clinical outcomes in very severe brain trauma are variable, preclinical evidence for enhancing wakefulness and behavioral performance in intact animals during electrical stimulation of the CL is more extensive. Recent studies have confirmed that electrical stimulation of the CL can effectively enhance wakefulness and performance in healthy rodents and in rodent models of two pathologies: epilepsy and TBI. In anesthetized animals, optogenetic stimulation of the CL in mice and electrical stimulation of the CL in rodents and non-human primates (NHPs) have shown widespread cortical and subcortical activation.

[0008] A recent study in healthy behaving non-human primates (NHPs) extended these results to examine the behavioral and physiological effects of different methods of CT-DBS while the animals were performing a more complex visuomotor task. A unique aspect of this study was the use of two closely spaced DBS leads placed within the CT, and the finding that both the precise location of the leads within the CT and the orientation of the electric field established between the two leads were critical parameters for improved performance and enhanced fronto-striatal activity patterns.

[0009] In a more recent study, positioning DBS electrodes to maximize activation of the lateral central nucleus-dorsomedial tegmental tract (CL / DTTm) fiber pathway in a subject and minimize activation of the median central nucleus-parafascicular nucleus fiber pathway in a subject, as described in U.S. Patent No. 9,592,383 (Patent Document 1) and PCT Application No. PCT / US2021 / 023648 (Patent Document 2), each of which is incorporated herein by reference in its entirety, resulted in favorable outcomes. In this study, field-shaping within the central thalamus (fsCT-DBS), which utilizes at least two stimulators to control thalamic fibers, was used to selectively target activation and avoidance within the mammalian thalamus, and was implemented in direct measurements from experiments conducted in non-human primates. Thus, by applying CT-DBS to subjects with moderate to severe traumatic brain injury, improved wakefulness regulation has been shown to correlate with activation of CL / DTTm.

[0010] This application relates to further enhancements to deep brain stimulation techniques. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] U.S. Patent No. 9,592,383 [Patent Document 2] PCT Application No. PCT / US2021 / 023648 Summary of the Invention

[0012] overview In some aspects, the disclosed technology relates to targeting the human central thalamus to achieve target activation and successful target avoidance of regions of the human intra-thalamic pathway in the central thalamus to achieve vector-based placement of deep brain stimulation electrodes. In some examples, the technology facilitates target capture and avoidance of the human intra-thalamic pathway in a human subject based on imaging, thalamic segmentation protocols, and predictive biophysical models that estimate activation of projection fibers to accurately determine a vector corresponding to the central lateral nucleus-medial component of the dorsal tegmental tract (CL / DTTm) fiber bundle, and to position contacts of deep brain stimulation (DBS) electrodes in substantial alignment with the determined vector and / or dominant axis.

[0013] One aspect of the present technology relates to a method for vector targeting the human central thalamus to guide deep brain stimulation (DBS). The method involves providing one or more electrodes, each with a plurality of contacts. The three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. The plurality of contacts of the one or more electrodes are then positioned in the central thalamus fibers of the human subject in substantial alignment with the three-dimensional orientation of the main axis of the determined CL / DTTm fiber bundle. Electrical stimulation is then applied to the positioned plurality of contacts of the one or more electrodes to treat the human subject for arousal dysregulation. The positioning and application are performed to maximize the activation of the fiber pathway of the lateral central nucleus-dorsomedial tegmental tract in the human subject, and minimize the activation of the fiber pathway of the median central nucleus-parafascicular nucleus in the human subject.

[0014] Another aspect of the present technology relates to a method for treating a pathological condition characterized by arousal dysregulation in a human subject. The method involves the steps of selecting a human subject having arousal dysregulation. One or more electrodes, each with a plurality of contacts, are provided. The three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. The plurality of contacts of the one or more electrodes are then positioned in the central thalamic fibers of the human subject in substantial alignment with the three-dimensional orientation of the main axis of the determined CL / DTTm fiber bundle. Electrical stimulation is then applied to the positioned plurality of contacts of the one or more electrodes to selectively activate the central thalamic fibers of the human subject. The positioning and application are performed to maximize the activation of the fiber pathway of the lateral central nucleus-dorsomedial tegmental tract in the human subject and minimize the activation of the fiber pathway of the median central nucleus-parafascicular nucleus in the human subject.

[0015] A further aspect of the present technology relates to a method for surgical planning involving vector-based targeting of the human central thalamus to guide DBS, the method being implemented by one or more surgical computing devices. The method involves segmenting the central thalamus in an image of the human subject's brain to create a segmented brain model. One or more fiber pathways are modeled in the segmented brain model. Based on the modeling, a three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. An initial model position and orientation in the segmented brain model for one or more electrodes is generated based at least in part on the determined three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject. Based on the modeling and generation, a stimulation map is created. To selectively activate the central thalamus fibers of the human subject, positions and orientations of a plurality of contacts of the one or more electrodes on the central thalamus fibers of the human subject and electrical stimulation conditions for the positioned and oriented contacts of the one or more electrodes are identified. This allows maximizing the activation of the lateral centrolateral-dorsomedial tegmental pathway fiber pathway in human subjects and minimizing the activation of the median centrolateral-parafascicular nucleus fiber pathway in human subjects based on the generated simulation maps.

[0016] Yet another aspect of the present technology relates to a non-transitory computer-readable medium having stored thereon instructions for surgical planning involving vector-based targeting of the human thalamus center to guide DBS. The non-transitory computer-readable medium includes executable code that, when executed by one or more processors, causes the one or more processors to segment the thalamus center in an image of the human subject's brain to create a segmented brain model. One or more fiber pathways are modeled in the segmented brain model. Based on the modeling, a three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. Based at least in part on the determined three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject, an initial model position and orientation in the segmented brain model is generated for one or more electrodes. Based on the modeling and generation, a stimulation map is created. Based on the created simulation map, positions and orientations for multiple contacts of the one or more electrodes on the central thalamic fibers of the human subject and electrical stimulation conditions for the positioned and oriented multiple contacts of the one or more electrodes are identified to selectively activate the central thalamic fibers of the human subject such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized.

[0017] Another aspect of the present technology relates to a surgical computing device. The surgical computing device includes a memory having program instructions stored therein; and one or more processors coupled to the memory and configured to execute the stored program instructions. The stored program instructions include segmenting a thalamic center in an image of a human subject's brain to create a segmented brain model. One or more fiber pathways are modeled in the segmented brain model. Based on the modeling, a three-dimensional orientation of a major axis of a CL / DTTm fiber bundle of the human subject is determined. Initial model positions and orientations are generated in the segmented brain model for one or more electrodes based at least in part on the determined three-dimensional orientation of a major axis of a CL / DTTm fiber bundle of the human subject. Based on the modeling and generation, a stimulation map is created. Based on the created simulation map, positions and orientations for multiple contacts of the one or more electrodes on the central thalamic fibers of the human subject and electrical stimulation conditions for the positioned and oriented multiple contacts of the one or more electrodes are identified to selectively activate the central thalamic fibers of the human subject such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized.

[0018] A further aspect of the present technology relates to a system for vector-based targeting of the human central thalamus to guide DBS. The system includes the surgical computing device of the present technology. The system also includes an imaging device operatively connected to a surgical planning system, and one or more electrodes. An electrical stimulator is connected to the surgical computing device and the one or more electrodes to enable electrical activation of the electrodes based on a command from the surgical computing device.

[0019] The present technology advantageously provides methods and systems for treatment via vector targeting of the human central thalamus to guide DBS to support forebrain arousal regulation via activation of fibers emanating from the central lateral nucleus (CL) and the surrounding medial dorsal tegmental tract (DTTm). The CL / DTTm target can be optimally activated by shaping the applied electric field by utilizing one or more leads or stimulators with multiple electrode contacts placed in substantial alignment with the orientation of the major axes of the CL / DTTm fiber bundles as determined from fiber pathway modeling.

[0020] Key targets for stimulation are local fiber tracts that cross the CT, such as the dorsomedial tegmental tract (DTTm), a component of the ascending reticular activating system that passes through the CL and enters the thalamic reticular nucleus (TRN), which projects broadly to the cortex and striatum. The DTTm also extends glutamatergic efferents from the CL nucleus to the TRN, cortex, and striatum. For many TBI subjects, precise therapeutic DBS targets may be difficult to determine, given the widespread structural damage present in this population, including substantial deformation and atrophy of thalamic nuclei. However, subjects with higher levels of consciousness and less structural damage in the thalamus, frontal lobe, and striatum are predicted to be ideal candidates for DBS therapy, as they often suffer from persistent cognitive dysfunction. However, in such individuals, targeting and improved activation of wakefulness-related pathways that minimize off-target side effects is crucial for the development of this promising treatment, as has been shown in recent years. The DTTm fiber pathway is an optimal DBS target for promoting performance in healthy NHPs, which directly informs current and future clinical studies using DBS to treat the persistent fatigue and cognitive dysfunction experienced by the majority of TBI subjects. The techniques described and illustrated herein improve activation of targeted regions of the CL / DTTm fiber bundles based on substantially aligning the orientation of the contacts of the inserted electrodes with the major axis of the CL / DTTm fiber bundles.

[0021] Central thalamic deep brain stimulation (CT-DBS) is an investigational therapy to treat persistent cognitive dysfunction in humans after traumatic brain injury (TBI). However, the mechanisms by which CT-DBS may promote cognitive re-establishment are unknown, and the heterogeneity of etiology and recovery profiles in TBI subjects will likely result in variable outcomes and difficult interpretations. CT-DBS activation patterns in the central thalamus (CT) of healthy non-human primates (NHPs) have been modeled and experimentally validated as NHPs perform a range of visuomotor tasks. Selective activation of a specific fiber pathway, the DTTm, and limited activation of the nearby centromedian-parafascicular (Cm-Pf) pathway results in robust behavioral facilitation. Modeling of CT-DBS within these two nearby thalamic pathways is consistent with behavioral effects observed across a range of animals. Empirical validation of the biophysical modeling approach in intact, behaving NHP will directly inform current and future clinical investigations using conventional and novel modalities of CT-DBS to effectively treat the persistent cognitive dysfunction experienced by the majority of TBI subjects for which no treatment currently exists.

[0022] Both CL and Cm-Pf have been reported to be associated with some enhancement of arousal and behavioral facilitation, but the quality of localization in human clinical studies varies, making direct comparisons uncertain. The selective effects of CL / DTTm fibers shown here are consistent with these projections providing broad excitatory inputs across frontal cortical and striatal regions. Limited coactivation of Cm-Pf->TRN fibers limited facilitation, whereas equivalent coactivation of these fibers had an inhibitory effect, suggesting a key role for known anatomical and physiological differences between CL neurons and neurons in the parafascicular (Pf) and centromedian (Cm) nuclei.

[0023] Studies of both cortical and striatal activation provide the basis for the selective behavioral effects associated with CL / DTTm activation. CL / DTTm regulates frontal cortical regions (Baker, et al., “Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates.” J. Neurophysiol. 116:2383-2404 (2016)), the disclosure of which is incorporated herein by reference in its entirety) and striatal regions (Liu, et al., “Frequency-Selective Control of Cortical and Subcortical Networks by Central Thalamus. Elife. 4, 1-27 (2016)), the disclosure of which is incorporated herein by reference in its entirety). (2015)), there are differences in the local microcircuit effects of CL / DTTm and Cm-Pf stimulation in the striatum. Medium spiny neurons (MSNs), the main output neurons of the striatum, are activated by either CL or Pf afferents, but CL afferents have been shown to be more effective at driving MSN action potentials. On the other hand, Pf afferents act via NMDA receptors to generate long-term depression through mechanisms of synaptic plasticity (Ellender, et al., “Heterogeneous Properties of Central Lateral and Parafascicular Thalamic Synapses in the Striatum.” J. Physiol. 591, 257-72 (2013), the entire disclosure of which is incorporated herein by reference). These physiological differences likely contribute to the reduced behavioral facilitation produced when CL / DTTm and Cm-Pf->TRN fibers are coactivated.

[0024] The increased feedback inhibition from TRN to CL due to the addition of Cm-Pf->TRN activation may also contribute to the reduced CL excitatory effect on frontal lobe function when both pathways are stimulated. In the neocortex, extensive innervation of supragranular and infragranular layers by CL afferents is associated with supralinear summation of effects across cortical columns (Llinas, et al., "Temporal Binding Via Cortical Coincidence Detection of Specific and Nonspecific Thalamocortical Inputs: A Voltage-Dependent Dye-Imaging Study in Mouse Brain Slices." Proc. Natl. Acad. Sci. US 816 A. 99, 449-454 (2002), the entire disclosure of which is incorporated herein by reference).local synaptic effects within the striatum (innervation of the Cm and Pf is patchy, as disclosed in Smith, et al., "The Thalamostriatal Systems: Anatomical and Functional Organization in Normal and Parkinsonian States." Brain Res. Bull. 78, 60-68 (2009) and Ellender, et al., "Heterogeneous Properties of Central Lateral and Parafascicular Thalamic Synapses in the Striatum." J. Physiol. 591, 257-72 (2013), the disclosures of which are incorporated by reference in their entireties); and feedback inhibition from the TRN (Crabtree, et al., "New Intrathalamic Pathways Allowing Modality-Related and Cross Modality Switching in the Dorsal Thalamus." J. Neurosci. 22, 8754-8761, the disclosures of which are incorporated by reference in their entireties). It is likely that encroachment of activation to Cm-Pf reduces this selective activation both through potent inhibition of cell bodies in the thalamic regions of the CL and in the paralaminar thalamic regions (Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, (2007) and Munkle, et al., “The Distribution of Calbindin, Calretinin and Parvalbumin Immunoreactivity in the Human Thalamus.” J. Chem. Neuroanat. 19, 155-173 (2000)), the entire disclosures of which are incorporated herein by reference; and through potent inhibition of cell bodies in the thalamic regions of the CL and in the paralaminar thalamic regions (Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, (2007) and Munkle, et al., “The Distribution of Calbindin, Calretinin and Parvalbumin Immunoreactivity in the Human Thalamus.” J. Chem. Neuroanat. 19, 155-173 (2000)), the entire disclosures of which are incorporated herein by reference. [Brief description of the drawings]

[0025] [Figure 1] FIG. 1 is a block diagram of an exemplary system of the present technology for vector-based targeting of the human central thalamus to guide deep brain stimulation therapy, including a surgical computing device. [Diagram 2] FIG. 1 is a partial side view and partial block diagram of an exemplary deep brain stimulation device of the present technology. [Figure 3A] FIG. 1 is a partial side view and partial block diagram of one embodiment of a deep brain stimulation device of the present technology implanted in the brain. [Figure 3B] FIG. 3B is a perspective view of a portion of a deep brain stimulation device implanted as shown in FIG. 3A to activate central thalamic fibers in a subject. [Figure 4] FIG. 3B is a block diagram of the adaptive feedback controller illustrated in FIG. 3A. [Diagram 5] 1 is a flowchart of an exemplary method for surgical planning involving vector-based targeting of the human central thalamus to guide deep brain stimulation therapy. [Figure 6] 1 illustrates a method used for image-guided surgical planning to facilitate vector-based targeting of the human central thalamus to guide deep brain stimulation therapy. [Figure 7] Illustrated is a white matter null (WMn) image showing contrast within the thalamus to allow identification of individual thalamic nuclei. [Figure 8] Illustrates the combination of WMn and diffusion tensor imaging (DTI) imaging to provide both target and avoided nuclei, and target and avoided fiber tracts, used to define vector targeting that takes into account both the position and trajectory (i.e., orientation) of the DBS lead (e.g., electrode contacts) relative to the target projection from the nucleus and the fiber tracts emanating from this nucleus. [Figure 9] 9A and 9B illustrate a conceptual overview showing the arrangement of vectors in a three-dimensional assembly of fibers that are tuned for bulk activation of fibers in a CL / DTTm structure. [Figure 10] Illustrated are two thalamic nuclei (activation targets) and the centromedian nucleus (avoidance target), a targeted DTTm fiber bundle, and a volume rendering of a DBS lead with an active electrode. [Figure 11] FIG. 11 illustrates another volume rendering of the two thalamic nuclei of FIG. 10, isolating the fibers activated by the applied electric field. [Figure 12] Illustrates multiple target activation (CL, PPN) and avoidance pathways (MD, VPM, CM) within the human central thalamus. [Figure 13] FIG. 1 illustrates fiber activation profiles, including histograms of activation percentages of target activation and target avoidance regions for a general thalamic model system. [Figure 14] 14 illustrates the change in fiber activation achieved by adjusting electrode positions from that illustrated in FIG. 13. [Figure 15] Illustrates human thalamus imaging data from a human subject with traumatic brain injury (TBI), including activation percentages of CL and PPN targets, as well as other thalamic nuclei (VPM, CM, MD) in avoidance subjects. [Figure 16] FIG. 5 illustrates the results of a study on five subjects who underwent DBS based on vector targeting of the human central thalamus. [Figure 17] An exemplary approach for target acquisition from a representative human subject is illustrated along with activation results from both hemispheres. [Figure 18] Another exemplary approach for target acquisition from another representative human subject is illustrated with activation results from both hemispheres. [Figure 19] 1 illustrates the placement of active contacts for multiple human subjects in a common synthetic atlas space. [Figure 20] Cortical evoked potentials obtained across a 128-channel EEG array are illustrated for activation across two active contacts using 2 Hz duty cycle stimulation. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] Detailed Description The present technology relates to a method for vector targeting the human central thalamus to guide deep brain stimulation (DBS).The present technology also relates to a method, device, system, and non-transitory computer readable medium for surgical planning for vector targeting the human central thalamus to guide DBS.More specifically, the present technology relates to a method for targeting the human central thalamus to achieve targeted activation and successful target avoidance of regions of human intrathalamic pathways in the central thalamus to achieve vector placement of deep brain stimulation electrodes.

[0027] A device and system for vector targeting of the human central thalamus to guide DBS is described herein, comprising a surgical computing device. One aspect of the present technology relates to a system for vector targeting of the human central thalamus to guide DBS. The system comprises the surgical computing device of the present technology. The system also comprises a photographing device and one or more electrodes that are functionally connected to the surgical computing device. An electrical stimulator is connected to the surgical computing device and the one or more electrodes to enable electrical activation of the electrodes based on a command from the surgical computing device.

[0028] 1 illustrates an environment including a system 12 for vector-based targeting of the human central thalamus to guide DBS. System 12 includes a surgical computing device 14, an imaging device 16, and a DBS apparatus 18, but may include other elements or components in other combinations, such as additional computing devices. System 12 enables treatment via selective activation of structures within the central thalamus to support forebrain arousal regulation via activation of the central lateral nucleus (CL) of the central thalamus and the surrounding fibers (CL / DTTm) emanating from the medial dorsal tegmental tract (DTTm).

[0029] The surgical computing device 14 of the system 12 includes a processor 20, a memory 22, and a communication interface 24 coupled together by a bus 26 or other communication link, although it may include other types and / or numbers of elements in other configurations. The processor 20 of the surgical computing device 14 may execute program instructions stored in the memory 22 for any number of functions or other operations as illustrated and described by way of example herein, including surgical planning for vector-based targeting of the human central thalamus to guide DBS. The processor 20 of the surgical computing device 14 may include, for example, one or more graphic processing units (GPUs), a central processing unit (CPU), or a general-purpose processor with one or more processing cores, although other types of processors may also be used.

[0030] The memory 22 of the surgical computing device 14 stores these program instructions for one or more aspects of the technology as illustrated and described herein, although some or all of the program instructions may be stored elsewhere. A variety of different types of memory storage devices may be used for the memory 22, such as random access memory (RAM), read only memory (ROM), solid state drive (SSD), flash memory, or other computer readable media that is read and written by a magnetic, optical, or other read / write system coupled to the processor 20.

[0031] Thus, the memory 22 of the surgical computing device 14 may store applications that may include executable instructions that, when executed by the surgical computing device 14, cause the surgical computing device 14 to perform an operation, such as performing a method for vector-based targeting of the human central thalamus to guide DBS as illustrated and described herein by way of example, as in FIG. 5. Applications may be implemented as modules or components of other applications. Additionally, applications may be implemented as an extension, module, plug-in, or the like of an operating system.

[0032] The communications interface 24 of the surgical computing device 14 operatively couples and enables communication between the surgical computing device 14, the imaging device 16, and the DBS device 18; all of which are coupled together by one or more communications networks 28, although other types and / or numbers of connections and / or configurations to other devices and / or elements may be used. The communications network 28 may include any number and / or types of communications networks, such as a local area network (LAN) or a wide area network (WAN), and / or a wireless network, although other types and / or numbers of protocols and / or communications networks may be used.

[0033] Although aspects of the surgical computing device 14 are described and illustrated herein, the surgical computing device 14 may be implemented on any suitable computing system or device. It should be understood that the devices and systems described herein are for illustrative purposes, and that many variations in the specific hardware and software are possible, as will be recognized by those skilled in the art.

[0034] In addition, two or more computing systems or devices may be substituted for any one of the systems described above. Thus, principles and advantages of distributed processing, such as redundancy and repetition, may also be implemented as desired to increase the robustness and performance of the devices and systems described above. Aspects of the present application may also be implemented on one or more computer systems extending across any suitable network using any suitable interface mechanisms and communication technologies; such mechanisms and technologies include, by way of example only, telecommunications in any suitable form (e.g., voice and modem), wireless communication media, wireless communication networks, cellular communication networks, G3 communication networks, public switched telephone networks (PSTN), packet data networks (PDN), the Internet, intranets, and combinations thereof.

[0035] The imaging device 16 may be any suitable imaging device for obtaining images of the subject's brain, including devices suitable for computed tomography, although other suitable imaging devices may be used. The imaging device 16 is coupled to the surgical computing device 14 to provide images of the subject's brain for further analysis according to the methods disclosed herein.

[0036] 2 is a perspective view and functional block diagram of a DBS device 18. The DBS device 18 includes first and second stimulators 30 coupled to a stimulation signal generator 32. Although the DBS device 18 is described with respect to the first and second stimulators 30, it should be understood that the DBS device 18 may include additional stimulators. Additionally, although a DBS device 18 is described, it should be understood that other types of stimulation devices may be used in the methods of the present technology, including stimulation devices that use other energy modalities.

[0037] The first and second stimulators 30 include at least one electrode 32 mounted on a shank 34. In one embodiment, multiple electrodes 32 are mounted on the shank 34 such that the stimulator 30 is a "multipolar electrode" in which each electrode can be controlled separately. In this example, four electrodes 32 are located on each shank 34 to provide multiple spaced contacts, although other numbers of electrodes may be utilized. The electrodes 34 are connected to one (or separate) insulated conductor that passes through the shank 34. The insulated conductor connects the electrodes 32 to a voltage controller 36 and a stimulation signal generator 38. The voltage controller 36 and stimulation signal generator 38 may be separate from one another or may be part of a single unit. The connections referred to herein may be wired or wireless.

[0038] The electrodes 32 are made from a conductive material, which may be an alloy such as platinum / iridium, with an impedance known in the art, for example, about 100-150 kΩ. The electrodes 32 are about 0.5 mm in length. In one embodiment where multiple electrodes 32 are mounted on the shank 34, the separation between the electrodes 32 may be variable or constant and may be about 0.5 mm.

[0039] The shank 34 is configured to be implanted in the brain of a subject. The shank 34 may be configured as a cylinder, a square, a spiral, or other geometric shape known in the art, as is suitable for implementation. In one embodiment, the shank 34 is implanted in the central thalamus of a subject to selectively activate central thalamic fibers in the subject, as described herein.

[0040] The stimulation signal generator 38 provides the selected pulse train. In one embodiment, the stimulation signal generator 38 can separately drive each electrode 32 in the multi-electrode system through various channels. In this embodiment, the stimulation signal generator 38 may functionally select any one electrode 32 to provide the stimulation signal to. The stimulation signal generator 38 may provide stimulation with various parameters, such as waveform frequency, across multiple electrodes 32 simultaneously and independently.

[0041] The stimulation signal generator 38 can generate voltage wave trains of any desired shape (monophasic or biphasic sine, square, spike, rectangular, triangular, ramp, etc.) at selectable voltage amplitudes in the range of about 0.1 volts to about 10.5 volts or about 0.1 mA to about 25.0 mA, and at selectable frequencies in the range of about 1 Hz to about 10 kHz. In one embodiment, the stimulation signal generator 38 can generate a constant current across at least one pair of electrodes 30, where either electrode of the pair is assigned as a cathode or an anode, although the stimulation signal generator 38 may generate a constant current across two pairs of electrodes, four pairs of electrodes, or six pairs of electrodes, where either electrode of the pair may be assigned as a cathode or an anode. The compliance voltage of the stimulation signal generator 38 can handle resistive loads in the range of 0.5 kOhm to 10 kOhm across any electrode pair. Each channel (cathode / anode pair) can deliver up to approximately 25.0 mA.

[0042] The stimulation signal generator 38 contains circuitry that allows monitoring of the current delivered across each channel. In one embodiment, the stimulation signal generator 38 is programmable in that the pulse shape, sequence, and frequency of pulses can be designed in software on a computer, such as the surgical computing device 14, and uploaded upon command to the stimulation signal generator 38 for delivery to the electrodes 32. The cathode-anode output from each channel may be used to provide bipolar constant current stimulation at the intralaminar nucleus through any pair of electrode contacts across the implanted stimulator 30.

[0043] The voltage controller 36 provides the selected current amplitude or voltage to the pulse train waves. In practice, the pulse trains and voltage amplitudes used are selected on a trial and error basis by evaluating the subject's response to various types and amplitudes of electrical stimulation over a time course of about 1 to about 12 months. For example, after implantation of the stimulator 30 in the subject's thalamic nucleus, stimulation is applied for about 8 to about 12 hours per day at a voltage in the range of about 0.1 to about 10.5 volts or higher and at a rate in the range of about 1 Hz to about 10 kHz. The voltage controller 36 may provide continuous, periodic, or intermittent stimulation. In one embodiment, the voltage controller 36 provides electrical stimulation that is performed using one or more stimulation programs that are interleaved in time.

[0044] 3A and 3B, in one embodiment, the DBS device 18 includes one or more sensors 40 connected to an adaptive feedback controller 42. The sensors 40 are configured to detect neuronal activity in one or more cortical and / or subcortical tissues of the selected subject's brain by means known in the art, although electrodes 32 may be utilized to detect neuronal activity. In one embodiment, the sensors 40 are integrated into the stimulator 30, although sensors 40 not integrated into the stimulator, referred to herein as "extra-stimulator sensors," may be utilized. Extra-stimulator sensors may be implanted in cortical or subcortical regions or may be located on the scalp surface of the subject's head. The sensors 40 collect neuronal data, for example in the form of single unit activity, local field potentials, and / or electrocorticogram ("EcoG") activity. The connection between the sensors 40 and the brain tissue may be electrical, electromagnetic (wireless), or optical to one or multiple targets, as determined by availability and the involvement of a specific pattern of brain trauma.

[0045] In one embodiment, the sensor 40 includes computer and logic circuitry, although the computer and logic circuitry associated with the sensor 40 may be distributed among other components, such as incorporated within the adaptive feedback controller 42 or within the stimulation signal generator 38, and / or within one or more other devices that may be implanted within the subject or external to the subject. In one embodiment, cortical placement of the sensor 40 may detect the occurrence of a failure of human control, and the adaptive feedback 42 controller may adjust stimulation of thalamic targets in synchronization with processing occurring within the deep brain stimulation device 18.

[0046] 3A, 3B, and 4, in one embodiment, the adaptive feedback controller 42 includes a neuronal recording module 44, a state monitoring module 46, a performance monitoring module 48, a processing module 50, and a transmission module 52. The modules described herein for the adaptive feedback controller 42 may be located within one physical device or distributed among multiple devices, including the surgical computing device 14, and may be incorporated into other components or devices described herein. For example, and without limitation, the neuronal recording module 44 may be located within the same device as the extra-stimulator sensor, and the device has appropriate transmission paths for sending and receiving information to other components of the DBS device 18, the subject, and / or an external system; an external system is a system used to maintain, control, or service the deep brain stimulation device 18 or the subject, including the surgical computing device 14.

[0047] The neuronal recording module 44 receives and stores various items of information from the sensors 40, such as subject-specific electrical waveform pattern data. In one embodiment, the neuronal recording module 44 stores information received from the sensors 40 in real-time during use of the DBS device 18. In one embodiment, the neuronal recording module 44 includes output means to allow capture of the stored signals during offline operation of the DBS device 18.

[0048] The state monitoring module 46 is coupled to the sensor 40 and is configured to store and process a first set of variables related to the state of the detected neuronal activity, in particular the spectral content of the local neuronal activity, especially the total power in the frequency ranges of 10-15 Hz, 15-20 Hz, 20-25 Hz, 25-30 Hz, and 10-30 Hz; all of which have been empirically identified to be increased in neuronal populations of the cortex, basal ganglia, and thalamus during either effective multi-site stimulation or alert cognitive function. The state monitoring module 46 may be used to sample average characteristics of the neuronal activity over time from the sensor 40 or from an external brain source that collects neuronal signals for this purpose, and provide real-time characteristics of the signals as feedback via a direct or wireless (Bluetooth) connection. In one embodiment, the state monitoring module 46 includes internal memory and computational resources for extracting features of the neuronal signals.

[0049] A performance monitoring module 48 is coupled to the sensor 40 and configured to store and process a second set of variables related to the modulation of the frequency of locally detected neuronal activity. The performance monitoring module 48 is used to monitor the performance attributes of the stimulation in producing an increase in the spectral power of the local population in a pre-specified frequency range (e.g., 15-25 Hz). In one embodiment, the performance monitoring module 48 includes internal memory and computational resources for extracting features of the neuronal signals.

[0050] The processing module 50 is coupled to the state monitoring module 46 and the performance monitoring module 48. In one embodiment, the processing module 50 may be configured to extract a feature vector based on the first and second sets of processed variables, and to calculate an optimal response stimulation signal based on a comparison between the extracted feature vector and a pre-stored feature vector corresponding to a local spectrum of neuronal activity for the subject recording site. The transmission module 52 is configured to transmit the optimal response stimulation signal calculated by the processing module 50 to the implanted stimulation signal generator 38 to adjust the neuronal activity of the subject's arousal level.

[0051] Based on the respective sets of stored and / or measured variables, the performance monitoring module 48 and the state monitoring module 46 may be used to extract feature vectors from the variables using computer and logic circuits. The feature vectors represent a nearly complete mathematical description of the electrical signals resulting from neuronal activity. The calculated feature vectors may be used for further processing and, if necessary, to synthesize a feedback signal. The feedback signal may be output via a transmission path, which may be wired, wireless, or optical, as known to those skilled in the art. The same or a separate component of the DBS device 18 calculates the output signal and transmits it to the stimulator 30 placed in the brain for adjusting its output in response to the ongoing analysis provided by the internal monitoring system.

[0052] 3A and 4, an embodiment of the present application is shown in which the DBS device 18 includes a sensor 40 interfaced with an adaptive feedback controller 42, which in turn interfaces with a stimulation signal generator 38. The stimulation signal generator 38 is configured to provide feedback control of electrical stimulation of targeted brain regions, such as CL / DTTm fiber pathways. Upon receiving signals via a transmission path, which may be wired, wireless, or optical, the stimulation signal generator 38 provides corresponding stimulation to these regions of the brain via at least one stimulator 12 to modulate or maintain the subject's wakefulness. The operating characteristics of the DBS device 18 may be automatically adjusted using the adaptive feedback controller 42. In other embodiments, the sensor 40, or components of the adaptive feedback controller 42, may store information for ingestion by an external system or physician, or may be used by a physician / programmer to adjust the settings of the DBS device 18. The settings may be adjusted by the DBS device 18 itself, or by a physician / programmer, to increase arousal levels or to affect local signal power.

[0053] One aspect of the present technology relates to a method for vector targeting the human central thalamus to guide deep brain stimulation (DBS). The method involves providing one or more electrodes, each with a plurality of contacts. The three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. The plurality of contacts of the one or more electrodes are then positioned in the central thalamus fibers of the human subject in substantial alignment with the three-dimensional orientation of the main axis of the determined CL / DTTm fiber bundle. Electrical stimulation is then applied to the positioned plurality of contacts of the one or more electrodes to treat the human subject for arousal dysregulation. The positioning and application are performed to maximize the activation of the fiber pathway of the lateral central nucleus-dorsomedial tegmental tract in the human subject, and minimize the activation of the fiber pathway of the median central nucleus-parafascicular nucleus in the human subject.

[0054] In a first step, one or more electrodes are provided, each with one or more contacts. In one embodiment, a deep brain stimulator 18 with electrodes 32 is used, although other devices for activating the central thalamus of a subject may be used, such as a fiber optic optogenetics ("FOG") system, a BION system, or ultrasound. The one or more electrodes are configured to allow selective activation of the central thalamus fibers of a subject, as described below. The technology may be used with single-lead systems with multiple electrical contacts, single-lead systems with multiple split contacts, and multiple-lead systems with any combination of multi-contact electrodes, including split-band contacts. Importantly, the system can accommodate any combination of anodes and cathodes across the lead contacts.

[0055] The one or more electrodes, such as electrode 32, are then positioned in the central thalamic fibers of the subject. In one embodiment, once the relevant subject is selected, a stimulator 30 as described above is implanted in the central thalamus of the subject as illustrated in FIG. 3B to maximize activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the subject and minimize activation of the medial central nucleus-parafascicular nucleus fiber pathway in the subject. Zones of activation and inhibition are illustrated in FIG. 5. As described above, the stimulator 30 includes one or more electrodes 32. In some embodiments, multiple electrodes 32 are provided. The one or more electrodes 32 have multiple spaced contacts. CL / DTTm targets can be optimally activated by shaping the applied electric field by utilizing first and second stimulators 12 with multiple electrode 32 contacts, as described below. As shown in the figure, this is accomplished by positioning the majority of the electrodes 32 on the stimulator 30 to contact the lateral central nucleus-dorsomedial tegmental tract fibers, while few, if any, of the electrodes 32 on the stimulator 30 contact the medial central nucleus-parafascicular nucleus fibers.

[0056] In carrying out the above-described methods, the subject may be conscious through administration of local anesthesia or mild sedation. If the subject is not sufficiently cooperative to remain conscious during the procedure, the above-described approaches may be modified in a manner known in the art to allow the operation to be completed under general anesthesia.

[0057] The subject includes any animal, including human.Non-human animals include all vertebrates, such as mammals and non-mammals, such as non-human primates, sheep, dogs, cats, cows, horses, chickens, amphibians, and reptiles, but preferably mammals, such as non-human primates, sheep, dogs, cats, cows, and horses.The subject may also be livestock, such as cows, pigs, sheep, poultry, and horses, or pets, such as dogs and cats.

[0058] The methods described herein may be used with subjects of any species, gender, age, ethnic group, or genotype. Thus, the term subject includes males and females, and includes elderly subjects, adult subjects at the transition age from adult to elderly, subjects at the transition age from pre-adult to adult, and pre-adult subjects including adolescents, children, and infants. In one embodiment, the subject is an adult subject in his / her 20s to 40s, who would benefit most from treatment and would have the greatest social costs if left untreated. Examples of human ethnic groups include Caucasian, Asian, Hispanic, African, African American, Native American, Semitic, and Pacific Islander. The term subject also includes subjects of any genotype or phenotype, so long as they require treatment as described herein. In addition, subjects may have any genotype or phenotype for hair color, eye color, skin color, or any combination thereof. The term subject includes subjects of any height or weight, or subjects whose organs or body parts are any size or shape.

[0059] In one embodiment, the stimulator 30 is introduced through a burr hole in the skull, although multiple stimulators may be used in other embodiments. Generally, prior to introduction of the stimulator 30, detailed mapping with microelectrodes and microstimulation is performed according to standard methods, as described in Tasker et al., “The Role of the Thalamus in Functional Neurosurgery,” Neurosurgery Clinics of North America 6(1):73-104 (1995), the entire disclosure of which is incorporated herein by reference. An imaging device 16 may be used to image the subject's brain. The system allows a user to plan the implantation of a stimulator system, such as the stimulator 30, in an individual subject using neuroimaging data from the imaging device 16.

[0060] The imaging data is used to model thalamic nuclei, white matter fiber tracts and connections, and the effects of electric field activation within the thalamus by directly modeling the relative activation of CL / DTTm→TRN, Cm-Pf→TRN, and other nearby thalamic pathways. The technology allows for biophysical modeling of precise placement of single or multiple lead systems to selectively activate CL / DTTm and avoid coactivation of Cm-Pf fiber bundles. The system includes modeling of thalamic nuclei; modeling of specific white matter fiber pathways in the brain; modeling of bioelectric fields; and probabilistic mapping of target activation and target avoidance achieved by various configurations of lead contact placement, cathode and anode geometry, pulse shape, pulse width, and frequency of stimulation.

[0061] In one aspect, a segmented brain model of the central thalamus of a subject may be created using known techniques. Model electrode positions and electrical stimulation conditions may be identified using the segmented brain model that maximize activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the subject while minimizing activation of the medial central nucleus-parafascicular nucleus fiber pathway in the subject. A stimulation map is created based on the identified electrode positions and electrical stimulation conditions. The stimulation map is then used to perform the actual positioning of a system such as the stimulator 30. The stimulation map may also be used in some embodiments to determine the application of stimulation as described further below.

[0062] Electrical stimulation is then applied to the positioned electrode or electrodes 32 to selectively activate the central thalamic fibers of the subject. Electrical stimulation may be performed in a variety of conditions to maximize activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the subject and minimize activation of the medial central nucleus-parafascicular nucleus fiber pathway in the subject. For example, electrical stimulation may be applied at .1 to 25.0 milliamps or 0.1 to 10.5 volts, selected independently for each electrode. Electrical stimulation may be applied using continuous, intermittent, or periodic stimulation. Electrical stimulation may be applied using substantially in-phase or substantially out-of-phase stimulation on each electrode 32. Electrical stimulation may be configured to be up- or down-gradient at different rate rates to enhance selective activation. Electrical stimulation may be performed using voltage wave trains having monophasic or biphasic sine, square, spike, rectangular, triangular, and ramp configurations. The electrical stimulation may be applied at one or more frequencies between 1 Hz and 10 kHz. Additionally, the electrical stimulation may be performed using one or more stimulation programs that are interleaved in time.

[0063] The devices and systems of the present technology allow for precise placement of single or multiple leads to selectively target CL / DTTm fibers and minimize nearby off-target fibers that originate and pass through the centromedial-parafascicular complex (Cm-Pf), which also projects to the thalamic reticular nucleus (TRN), as shown in Figure 3B. The one or more electrodes 32 are positioned to maximize activation of the lateral centromedial-dorsomedial tegmental fiber pathway in the subject, and minimize activation of the medial centromedial-parafascicular fiber pathway in the subject, as shown in Figure 5.

[0064] The present technology identifies the geometric requirements for selective activation of CL / DTTm to facilitate cognitively mediated behaviors, including but not limited to executive function, wakefulness, sustained attention, working memory, decision making, and motor executive function (e.g., controlled movements of the hand and arm). The primary effect of selective CL / DTTm stimulation is to activate neuronal populations across frontal cortical structures and the striatum while minimizing off-target effects. Based on known anatomical and physiological demonstrations, other cortical structures, such as the posterior parietal cortex and primary sensory cortices, are also direct targets of CL / DTTm activation. In one embodiment, 75%-100% of the dorsal medial tegmental tract fibers within the central thalamus of the subject are stimulated, and less than 25% of the fibers of the medial central nucleus-parafascicularis nucleus within the central thalamus of the subject are stimulated. In another embodiment, 90%-100% of the dorsal medial tegmental tract fibers in the central thalamus of a subject are stimulated, and less than 10% of the fibers of the medial central nucleus-parafascicularis nucleus in the central thalamus of a subject are stimulated.

[0065] In one embodiment, the deep brain stimulation device 18 further includes a sensor 40 configured to provide feedback to determine a state of neuronal activity during application of electrical stimulation as described above. One or more of the electrical stimulation conditions may be adjusted based on the state of neuronal activity to provide enhanced selective activation of the central thalamus of the subject based on feedback from the sensor 40.

[0066] Another aspect of the technology relates to a method for treating a pathological condition characterized by arousal dysregulation in a human subject. The method involves selecting a human subject having arousal dysregulation. One or more electrodes, each with a plurality of contacts, are provided. A three-dimensional orientation of a major axis of a CL / DTTm fiber bundle of the human subject is determined. The plurality of contacts of the one or more electrodes are then positioned in the central thalamic fibers of the human subject in substantial alignment with the three-dimensional orientation of the major axis of the determined CL / DTTm fiber bundle. Electrical stimulation is then applied to the plurality of contacts of the one or more electrodes positioned to selectively activate central thalamic fibers in substantial alignment with the three-dimensional orientation of the major axis of the determined CL / DTTm fiber bundle. Electrical stimulation is then applied to the plurality of contacts of the one or more electrodes positioned to selectively activate central thalamic fibers of the human subject. Positioning and application are performed to maximize activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject, and to minimize activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject.

[0067] Arousal dysregulation is a key component underlying a wide range of acquired, congenital, and idiopathic neuropsychiatric diseases. Most notably, traumatic brain injury results in arousal dysregulation. Additional forms of structural brain trauma that disrupt arousal regulation include anoxia, hypoxia, hypoxic-ischemic injury, stroke, encephalitis from infectious or autoimmune causes, and a wide range of primary degenerative diseases, such as Parkinson's disease. Importantly, support for arousal regulation is currently in clinical trials for the restoration of cognitive function during seizures or post-seizure states of cortical hypofunction. Arousal dysregulation is a major untreated feature of neuropsychiatric disorders, such as schizophrenia or autism. Thus, the techniques described and illustrated herein may be used to treat brain trauma, neurological degenerative diseases, epilepsy, movement disorders, cognitive impairment after encephalitis, developmental disorders, cognitive impairment after hypoxic-ischemic injury, neuropsychiatric disorders, cognitive impairment of mixed disorders after intensive care unit (ICU), and / or post-ICU adult respiratory distress syndrome. These applications are described as relevant examples, but are not exhaustive of the applications of the specific use of the system to enable selective CL / DTTm activation in an individual to improve wakefulness regulation.

[0068] In one embodiment, the subject with a pathological condition characterized by arousal dysregulation can be selected for treatment with the above-mentioned method.The subject can have a pathological condition selected from the group consisting of brain trauma, neurological degenerative disease, epilepsy, movement disorder, cognitive impairment after encephalitis, developmental disorder, cognitive impairment after hypoxic-ischemic injury, and neuropsychiatric disorder.

[0069] The technology allows for the specific positioning of the system in the central thalamus to optimize the behavioral enhancements that can be achieved through improved arousal regulation. The technology guides the conceptualization and placement of the system and allows the user to explore the space of stimulation configurations and activation patterns to map the broad behavioral outcomes of the system, as described in more detail below. These maps are inherently multidimensional: they include effects on the CL / DTTm and Cm-Pf->TRN pathways, the multiple behavioral enhancement effects that may occur, and, just as importantly, off-target side effects.

[0070] Selective activation of the DTTm fiber pathway projecting through the CL nucleus and not activating the projection of the Cm-Pf complex fiber promotes performance. Such selective activation can be used as a therapeutic option for treating subjects suffering from wakefulness dysregulation and persistent cognitive dysfunction. As disclosed in Baker, et al., "Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates." J. Neurophysiol. 116:2383-2404 (2016), the entire disclosure of which is incorporated herein by reference, shaping the DBS field within the "wings" of the CL resulted in robust behavioral facilitation and enhanced activity of frontal and striatal populations. These findings are consistent with the behavioral and physiological effects of conventional CT-DBS in case studies of very severe traumatic brain injury (TBI) subjects, as disclosed in Schiff, et al., "Behavioural Improvements with Thalamic Stimulation After Severe Traumatic Brain Injury." Nature. 448, 600-3 (2007), the entire disclosure of which is incorporated herein by reference.

[0071] The present technique separates components of the CL thalamus by isolating contributions due to CL and DTTm from those of the Cm-Pf complex. These behavioral results support 1) an intrathalamic inhibitory network similar to that defined in rodents, as disclosed in Crabtree, et al., “New Intrathalamic Pathways Allowing Modality-Related and Cross Modality Switching in the Dorsal Thalamus.” J. Neurosci. 22, 8754-8761 (2002) and Crabtree, “Functional Diversity of Thalamic Reticular Subnetworks.” Front. Syst. Neurosci. s12 (2018), the disclosures of which are incorporated herein by reference in their entireties; and 2) a novel inhibitory network similar to that defined in rodents, as disclosed in ND Schiff, “Recovery of Consciousness After Brain Injury: A Mesocircuit Hypothesis.” Trends Neurosci. 33, 1-9 (2010), the disclosures of which are incorporated herein by reference in their entireties. This could be explained by two mechanisms: the role that the two pathways play in controlling the anterior forebrain mesocircuit, a system involving the thalamus, frontal cortex, and basal ganglia that regulates the overall level of activity in the anterior forebrain, as disclosed in

[0072] In one embodiment, the position of segmented single-lead and multi-lead systems may be optimized to selectively target the cell bodies of CL and DTTm pathways and to avoid fiber projections from Cm-Pf. Isolated activation of the DTTm pathway projecting from CL to fronto-striatal targets promotes behavioral performance. In contrast, mixed activation of DTTm and fibers projecting from the Cm-Pf complex through TRN either prevents or weakens these facilitatory effects.

[0073] Although both CL and Cm-Pf have strong striatal projections, their innervation patterns in the striatum are significantly different, both regionally and with respect to the cellular elements and cell types innervated. Of note in single fiber studies is that CL afferents also synapse within the TRN before fanning out widely over the rostral striatum, as disclosed in Deschenes, et al., "Striatal and Cortical Projections of Single Neurons From the Central Lateral Thalamic Nucleus in the Rat," Neuroscience. 72, 679-687 (1996), the entire disclosure of which is incorporated herein by reference. In contrast, Parent, et al., "Axonal Collateralization in Primate Basal Ganglia and Related Thalamic Nuclei." Thalamus Relat. Syst. 2, 71 (2002), Smith, et al., "The Thalamostriatal Systems: Anatomical and Functional Organization in Normal and Parkinsonian States." Brain Res. Bull. 78, 60-68 (2009), Storch, et al., "Reliability and Validity of the Yale Global Tic Severity Scale." Psychol. Assess. 17, 486-491 (2005), and Smith, et al., "The Thalamostriatal System in Normal and Diseased States." Front. Syst. Neurosci. 8 (2014), the disclosures of which are incorporated herein by reference in their entireties. As disclosed in, Cm-Pf fibers abundantly project within regionally precise zones of the striatum, forming bush-like local arborizations.CL and Pf afferents are known to project into medium spiny neurons, the main neuronal population in the striatum, as disclosed in Bolam, et al., "Synaptic Organisation of the Basal Ganglia." J. Anat. 196, 527-542 (2000) and Ellender, et al., "Heterogeneous Properties of Central Lateral and Parafascicular Thalamic Synapses in the Striatum." J. Physiol. 591, 257-72 (2013), the disclosures of which are incorporated herein by reference in their entireties, while Cm neurons project into local cholinergic inhibitory neurons, as disclosed in Smith, et al., "The Thalamostriatal Systems: Anatomical and Functional Organization in Normal and Parkinsonian States." Brain Res. Bull. 78, 60-68 (2009), the disclosures of which are incorporated herein by reference in their entireties.Most importantly, see Li et al., “Uncovering the Modulatory Interactions of Brain Networks in Cognition with Central Thalamic Deep Brain Stimulation Using Functional Magnetic Resonance Imaging.” Neuroscience. 440, 65-84 (2020); Liu, et al., “Frequency-Selective Control of Cortical and Subcortical Networks by Central Thalamus.” Elife. 4, 1-27 (2015); and Baker, et al., “Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates.” J. Neurophysiol. 116:2383-2404 (2016), the disclosures of which are incorporated herein by reference in their entireties. As disclosed in, CL fibers have strong and widespread fronto-striatal projections that potently activate the entire frontal / prefrontal cortex and the rostral striatum with high frequency stimulation.

[0074] Despite these differences, increased alertness and behavioral facilitation have been reported for both CL and Cm-Pf electrical stimulation. In rodent studies, electrical stimulation of the CL has been shown to improve object recognition memory (Shirvalkar, et al., “Cognitive Enhancement with Central Thalamic Electrical Stimulation.” Proc. Natl. Acad. Sci. USA 103, 17007-17012 (2006), the entire disclosure of which is incorporated herein by reference), working memory (Chang, et al., “Modulation of Theta-Band Local Field Potential Oscillations Across Brain Networks With Central Thalamic Deep Brain Stimulation to Enhance Spatial Working Memory.” Front. Neurosci. 13 (2019), the entire disclosure of which is incorporated herein by reference), and decision-making (Mair, et al., “Memory Enhancement with Event-Related Stimulation of the Rostral Intralaminar Thalamic Nuclei.” J. Neurosci. 28, 17012 (2019), the entire disclosure of which is incorporated herein by reference). 14293-14300 (2008) and Mair, et al., “Cognitive Activation by Central Thalamic Stimulation: The Yerkes-Dodson Law Revisited.” Dose-Response. 9, 313-331 (2011)).In healthy NHPs, CL-based stimulation, including DTTm as shown herein, promotes sustained attention, working memory, and pattern recognition behaviors, as disclosed in Baker, et al., "Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates." J. Neurophysiol. 116:2383-2404 (2016), the entire disclosure of which is incorporated herein by reference. In humans, CL stimulation has been shown to promote a wide range of cognitive behaviors, including motor executive function and speech, as disclosed in Schiff, et al., "Behavioural Improvements with Thalamic Stimulation After Severe Traumatic Brain Injury." Nature. 448, 600-3 (2007), the entire disclosure of which is incorporated herein by reference. However, human studies have also reported facilitation of speech with Cm-Pf stimulation (Bhatnagar, et al., "Effects of Intralaminar Thalamic Stimulation on Language Functions." Brain Lang. 92, 1-11 (2005), the entire disclosure of which is incorporated herein by reference) and restoration of wakefulness in severe brain trauma.

[0075] In rodents, Crabtree, et al., "New Intrathalamic Pathways Allowing Modality-Related and Cross Modality Switching in the Dorsal Thalamus." J. Neurosci. 22, 8754-8761 (2002), the entire disclosure of which is incorporated herein by reference, provided a structural basis for a rich system of inhibitory interactions within the thalamus and characterized two key findings relevant to the current results: 1) there are rich networks of local inhibition within distinct sensory or motor nuclei; these inhibitory networks appear to be local to either sensory or motor nuclei; and 2) cross-thalamic pathways from sensory to motor via inhibition of the anterior intralaminar nuclei by the caudal intralaminar nuclei. Activation of the caudal intralaminar nuclei resulted in strong inhibition and suppression of neuronal firing in the anterior nuclei via disynaptic connections with the TRN. These findings suggest an important motif for intrathalamic inhibition of the two intralaminar nuclei groups in the thalamus. However, a key difference in rodents compared to cat or primate thalamus is that CL is included as part of the caudal intralaminar nuclei group by Crabtree and Issac, which is due in large part to the absence of Cm-Pf nuclei in rodents, as disclosed in Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, 2007, the entire disclosure of which is incorporated herein by reference.

[0076] In comparison, the Cm-Pf in primates is greatly expanded (Jones, et al., "Differential Calcium Binding Protein Immunoreactivity Distinguishes Classes of Relay Neurons in Monkey Thalamic Nuclei." Eur. J. Neurosci. 1, 222-246 (1989) and Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, 2007, the entire disclosures of which are incorporated herein by reference), and the CL is classified as a component of the rostral intralaminar nucleus group. Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, 2007, the entire disclosure of which is incorporated herein by reference, inter alia, notes that the dense cell component of the paralamellar MD can be considered as the posterior cells of the CL nucleus; these neurons project strongly to the frontal and prefrontal cortices and are in close proximity to the medial aspect of the Cm-Pf and the anterior aspect of the Pf. As disclosed in Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, 2007, the entire disclosure of which is incorporated herein by reference, several anatomists have argued that these regions should be included in the human CL nucleus. Detailed studies of the interactions of Cm-Pf and CL through the TRN are not available in non-human primates, and current modeling is only guided by observations in rodents. A direct inhibitory effect on the CL and surrounding associated nuclei through TRN projections activated by the Cm-Pf-TRN fiber bundle could explain the apparent interference when activation in DTTm and Cm-Pf-TRN fibers was balanced, and the attenuation of this interference as the “push-pull” effect became more biased towards behavioral release as DTTm involvement became relatively stronger.

[0077] DTTm activation promotes selective activation of frontostriatal neurons during wakefulness. Previous studies have shown that promoting cognitively mediated behaviors in healthy NHPs requires sufficiently strong activation of frontal and striatal neurons to alter local field potentials and individual neuronal firing dynamics, as disclosed in Baker, et al., “Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates,” J. Neurophysiol. 116:2383-2404 (2016), the entire disclosure of which is incorporated herein by reference. In the waking state, as disclosed in Steriade, et al., "Natural Waking and Sleep States: A View From Inside Neocortical Neurons." J. Neurophysiol. 85, 1969-1985 (2001) and Grillner, et al., "Microcircuits in Action - From CPGs to Neocortex." Trends Neurosci. 28, 525-533 (2005), the entire disclosures of which are incorporated herein by reference, both neurons in the frontal neocortex and medium spiny neurons in the striatum are depolarized and receive high rates of synaptic input. Therefore, to produce a sufficient impact in behavioral facilitation to be measurable, the effect of DBS must be spatially broad and potently effective across the frontal-striatal population.

[0078] As disclosed in Smith, et al., "The Thalamostriatal Systems: Anatomical and Functional Organization in Normal and Parkinsonian States." Brain Res. Bull. 78, 60-68 (2009), the entire disclosure of which is incorporated herein by reference, stimulation of the CL by microelectrode techniques in awake NHPs demonstrated modest behavioral enhancing effects. In contrast, the significant increase in behavioral facilitation achieved by the effective geometry created by "field-shaping" (fsCT-DBS) in the central thalamus in direct comparison with conventional CT-DBS can first be understood in the context of bulk activation across the frontostriatal network, as disclosed in Baker, et al., "Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates." J. Neurophysiol. 116:2383-2404 (2016), the entire disclosure of which is incorporated herein by reference. In human subjects, bulk activation of frontostriatal neuronal populations has been shown to be a common mechanism underlying a variety of effective pharmacological and electrophysiological stimulation treatment methods aimed at improving arousal regulation in the injured brain.

[0079] As disclosed in Liu, et al., “Frequency-Selective Control of Cortical and Subcortical Networks by Central Thalamus. Elife. 4, 1-27 (2015), the entire disclosure of which is incorporated herein by reference, optogenetic stimulation of local neuronal populations in the central thalamus in rodents shows that CL stimulation uniquely activates the entire frontostriatal system, as measured at the whole-brain level using functional magnetic resonance. The selective effect of stimulating DTTm fibers shown here is consistent with CL stimulation providing broad excitatory input across regions of the frontal cortex and striatum. Even limited coactivation of Cm-Pf->TRN fibers had an inhibitory effect on behavior, calling attention to further differences between CL neurons and neurons in the parafascicular (Pf) and centromedian (Cm) nuclei.

[0080] The differences between CL and Cm-Pf neurons also extend to their postsynaptic effects on inhibitory medium spiny neurons (MSNs), neurons that emerge from the striatum and project to the globus pallidus (internal compartment). Whole-cell patch clamp studies of MSNs optogenetically activated by either CL or Pf afferents have shown that CL afferents act through AMPA receptors and are more effective at driving MSN action potentials. In addition, Pf afferents acting through NMDA receptors generate long-term depression through mechanisms of synaptic plasticity, as disclosed in Ellender, et al., “Heterogeneous Properties of Central Lateral and Parafascicular Thalamic Synapses in the Striatum.” J. Physiol. 591, 257-72 (2013), the disclosure of which is incorporated herein by reference in its entirety. These physiological differences likely provide an additional contribution to the attenuation of behavioral facilitation achieved through DTTm activation when Cm-Pf fibers are coactivated; these projections continue to MSNs in the striatum. Excitation of MSNs by CL leads to disynaptic disinhibition of the thalamus through the anterior forebrain mesocircuit, as disclosed in Fridman, et al., “Neuromodulation of the Conscious State Following Severe Brain Injuries” Curr. Opin. Neurobiol. 29, 172-177 (2014) and Schiff, “Recovery of Consciousness After Brain Injury: A Mesocircuit Hypothesis” Trends Neurosci. 33, 1-9 (2010), the disclosures of which are incorporated herein by reference in their entirety, and coactivation of Pf fibers may oppose this thalamic disinhibition through inhibition of MSNs.Thus, the balance between CL / DTTm and CM-Pf afferents to MSNs provides a means by which the overall activity level of the thalamus can be regulated.

[0081] Important differences at the cortical level are also expected to affect the effects of CL versus Cm-Pf activation; CL innervates the cortex broadly, whereas Cm-Pf projections are relatively sparse, as disclosed in Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, 2007, the entire disclosure of which is incorporated herein by reference. In the neocortex, broad innervation of supragranular and infragranular layers by CL afferents is associated with supralinear summation of effects across cortical columns, as disclosed in Llinas, et al., “Temporal Binding Via Cortical Coincidence Detection of Specific and Nonspecific Thalamocortical Inputs: A Voltage-Dependent Dye-Imaging Study in Mouse Brain Slices.” Proc. Natl. Acad. Sci. US 816 A. 99, 449-454 (2002), the entire disclosure of which is incorporated herein by reference.Collectively, as disclosed in (Smith, et al., "The Thalamostriatal Systems: Anatomical and Functional Organization in Normal and Parkinsonian States." Brain Res. Bull. 78, 60-68 (2009) and Ellender, et al., "Heterogeneous Properties of Central Lateral and Parafascicular Thalamic Synapses in the Striatum." J. Physiol. 591, 257-72 (2013), the disclosures of which are incorporated herein by reference in their entireties), it is likely that the impairment of activation to the Cm-Pf reduces bulk activation of frontal and striatal regions through local synaptic effects within the striatum; here, short-term depression may affect patchy areas of the striatum innervated by Cm-Pf projections to interfere with behavioral facilitation.In addition, as discussed above, strong inhibition of cell bodies in the intrapartite and paralaminar thalamic regions of the CL (containing neurons with identical properties (Jones, The Thalamus Springer US, Boston, MA, ed. 2nd, 2007 and Munkle, et al., "The Distribution of Calbindin, Calretinin and Parvalbumin Immunoreactivity in the Human Thalamus." J. Chem. Neuroanat. 19, 155-173 (2000)), the disclosures of which are incorporated herein by reference in their entireties) via feedback inhibition from the TRN (Crabtree, et al., "New Intrathalamic Pathways Allowing Modality-Related and Cross Modality Switching in the Dorsal Thalamus." J. Neurosci. 22, 8754-8761 (2002), the disclosures of which are incorporated herein by reference in their entireties) may suppress thalamic outputs that are not captured by direct electrical stimulation.

[0082] Compared to the broad bulk activation required to produce behavioral facilitation by CT-DBS in the DTTm, recent studies in anesthetized NHPs have shown that very localized stimulation in the CL nucleus using multiple 25 μm contacts spaced 200 μm apart can produce emergence from propofol and isoflurane anesthesia, as disclosed in Redinbaugh, et al., “Thalamus Modulates Consciousness via Layer-Specific Control of Cortex.” Neuron, 1-10 (2020), the disclosure of which is incorporated herein by reference in its entirety. The effective electrical length of these microprobe contacts, which determines the locally achieved current, is very short compared to the broad area activated by the fsCT-DBS configuration studied here, as disclosed in Ranck, “Which Elements are Excited in Electrical Stimulation of Mammalian Central Nervous System: A Review.” Brain Res. 98, 417-440 (1975), the disclosure of which is incorporated herein by reference in its entirety. Of note, stimulation at 50 Hz, but not 200 Hz, was effective in producing wakefulness during anesthesia.In comparison, in the awake monkeys studied, stimulation at 150 Hz to 225 Hz demonstrated strong behavioral facilitation and robust activation in frontal and striatal regions, reflected in significant increases in the beta and gamma frequency ranges and reductions in lower frequency bands measured directly at these locations, as disclosed in Baker, et al., “Robust Modulation of Arousal Regulation, Performance and Frontostriatal Activity Through Central Thalamic Deep Brain Stimulation in Healthy Non-Human Primates.” J. Neurophysiol. 116:2383-2404 (2016), the entire disclosure of which is incorporated herein by reference.These differences are discussed in Larkum,, et al., "Calcium Electrogenesis in Distal Apical Dendrites of Layer 5 Pyramidal Cells at a Critical Frequency of Back-Propagating Action Potentials." Proc. Natl. Acad. Sci. USA 96, 14600-14604 (1999), Larkum, et al., "Dendritic Spikes in Apical Dendrites of Neocortical Layer 2 / 3 Pyramidal Neurons. J. Neurosci. 27, 8999-9008 (2007), and Larkum, et al., "Synaptic Integration in Tuft Dendrites of Layer 5 Pyramidal Neurons: A New Unifying Principle." Science 325, 756-760 (2009), the disclosures of which are incorporated herein by reference in their entireties. This likely reflects the need to increase the level of background synaptic activity received by neocortical and striatal neurons above a certain threshold in addition to achieving broad activation in the awake state, as disclosed in Bernander, , et al., “Synaptic Background Activity Influences Spatiotemporal Integration in Single Pyramidal Cells,” Proc. Natl. Acad. Sci. USA 88, 11569-11573 (1991), the entire disclosure of which is incorporated herein by reference, and the intrinsic integrative properties of individual neocortical neurons change with increasing levels of background synaptic input.Larkum, et al., "Calcium Electrogenesis in Distal Apical Dendrites of Layer 5 Pyramidal Cells at a Critical Frequency of Back-Propagating Action Potentials." Proc. Natl. Acad. Sci. USA 96, 14600-14604 (1999), Larkum, et al., "Dendritic Spikes in Apical Dendrites of Neocortical Layer 2 / 3 Pyramidal Neurons. J. Neurosci. 27, 8999-9008 (2007), and Larkum, et al., "Synaptic Integration in Tuft Dendrites of Layer 5 Pyramidal Neurons: A New Unifying Principle." Science 325, 756-760 (2009), the entire disclosures of which are incorporated herein by reference. As disclosed in Grillner, et al., "Mechanisms for Selection of Basic Motor Programs - Roles for the Striatum and Pallidum," Trends Neurosci. 28, 364-370 (2005), the entire disclosure of which is incorporated herein by reference, the primary output of the medium spiny neurons in the striatum requires a very high rate of background synaptic input to maintain sufficient membrane depolarization to generate action potentials, as disclosed in Grillner, et al., "Mechanisms for Selection of Basic Motor Programs - Roles for the Striatum and Pallidum," Trends Neurosci. 28, 364-370 (2005), the entire disclosure of which is incorporated herein by reference.Either mechanism likely plays a role in the need for high frequency stimulation during wakefulness, as disclosed in Schiff, “Central Lateral Thalamic Nucleus Stimulation Awakens Cortex via Modulation of Cross-Regional, Laminar-Specific Activity during General Anesthesia.” Neuron. 106, 1-3 (2020), the entire disclosure of which is incorporated by reference herein.

[0083] Alternatively, the selective effect of 50Hz CL stimulation in anesthetized monkeys may reflect antidromic activation of brainstem cholinergic and / or noradrenergic fibers that innervate the CL. As disclosed in Garcia-Rill, et al., "Coherence and Frequency in the Reticular Activating System (RAS)." Sleep Med. Rev. 17, 227-238 (2013) and Garcia-Rill, J, et al., "The physiology of the pedunculopontine nucleus: implications for deep brain stimulation." J. Neural Transm. 122, 225-235 (2015), the entire disclosures of which are incorporated herein by reference, brainstem neurons projecting to the CL are known to have resonant properties at approximately 40-50Hz, but higher frequency stimulation rather blocks action potentials; this may explain why other researchers have not found effects during higher frequency stimulation.

[0084] A further aspect of the present technology relates to a method for surgical planning involving vector-based targeting of the human central thalamus to guide DBS, performed by one or more surgical computing devices. The method involves segmenting the central thalamus in an image of the human subject's brain to create a segmented brain model. One or more fiber pathways are modeled in the segmented brain model. Based on the modeling, a three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. An initial model position and orientation in the segmented brain model for one or more electrodes is generated based at least in part on the determined three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject. Based on the modeling and generation, a stimulation map is created. To selectively activate the central thalamus fibers of the human subject, positions and orientations of a plurality of contacts of the one or more electrodes on the central thalamus fibers of the human subject and electrical stimulation conditions for the positioned and oriented contacts of the one or more electrodes are identified. This allows maximizing the activation of the lateral centrolateral-dorsomedial tegmental pathway fiber pathway in human subjects and minimizing the activation of the median centrolateral-parafascicular nucleus fiber pathway in human subjects based on the generated simulation maps.

[0085] Yet another aspect of the present technology relates to a non-transitory computer-readable medium having stored thereon instructions for surgical planning involving vector-based targeting of the human thalamus center to guide DBS. The non-transitory computer-readable medium includes executable code that, when executed by one or more processors, causes the one or more processors to segment the thalamus center in an image of the human subject's brain to create a segmented brain model. One or more fiber pathways are modeled in the segmented brain model. Based on the modeling, a three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject is determined. Based at least in part on the determined three-dimensional orientation of the main axis of the CL / DTTm fiber bundle of the human subject, an initial model position and orientation in the segmented brain model is generated for one or more electrodes. Based on the modeling and generation, a stimulation map is created. Based on the created simulation map, positions and orientations for multiple contacts of the one or more electrodes on the central thalamic fibers of the human subject and electrical stimulation conditions for the positioned and oriented multiple contacts of the one or more electrodes are identified to selectively activate the central thalamic fibers of the human subject such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized.

[0086] Another aspect of the present technology relates to a surgical computing device. The surgical computing device includes a memory having program instructions stored therein; and one or more processors coupled to the memory and configured to execute the stored program instructions. The stored program instructions include segmenting a thalamic center in an image of a human subject's brain to create a segmented brain model. One or more fiber pathways are modeled in the segmented brain model. Based on the modeling, a three-dimensional orientation of a major axis of a CL / DTTm fiber bundle of the human subject is determined. Initial model positions and orientations are generated in the segmented brain model for one or more electrodes based at least in part on the determined three-dimensional orientation of a major axis of a CL / DTTm fiber bundle of the human subject. Based on the modeling and generation, a stimulation map is created. Based on the created simulation map, positions and orientations for multiple contacts of the one or more electrodes on the central thalamic fibers of the human subject and electrical stimulation conditions for the positioned and oriented multiple contacts of the one or more electrodes are identified to selectively activate the central thalamic fibers of the human subject such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized.

[0087] Referring now to Figure 5, a flow chart of an exemplary method for surgical planning involving vector-based targeting of the human central thalamus to guide deep brain stimulation therapy will be described. The method may be performed by one or more computing devices, such as the surgical computing device 14 as shown in Figure 1. Referring again to Figure 5, at step 500, the surgical computing device 14 segments the central thalamus within an image of the human subject's brain to create a segmented brain model.

[0088] In some embodiments, the imaging device 16 is used to obtain pre-operative magnetic resonance imaging (MRI) images of the human subject, which may optionally include specific features to aid in locating target activation and avoidance regions. In these examples, the pre-operative MRI images include image sequences that show strong contrast between white and gray matter structures in the thalamus.

[0089] Optionally, white-matter-nulled magnetization-prepared rapid acquisition (WMnMPRAGE or WMn) imaging of the human thalamus may be used, using MR acquisition parameters (e.g., inversion time TI, sequence repetition time TS, flip angle FA, receive bandwidth RBW, and / or k-space ordering strategy) to provide strong intrathalamic contrast; this allows for delineation of the inner lamina and isolation and segmentation of the central thalamic (CL) volume. In some embodiments, the image resolution (i.e., voxel size) is 1 mm or better, and / or is isotropic (e.g., equal in size for all three voxel dimensions), and / or the imaging volume covers the entire brain of the human subject.

[0090] In some embodiments of the present technology, the obtained WMn images are processed (e.g., by the surgical computing device 14) to segment (or define the spatial boundaries of) structures within the thalamus of the human subject. One exemplary approach for this segmentation is to use the THalamus Optimized Multi-Atlas Segmentation (THOMAS) algorithm, as disclosed in Su et al., “Thalamus Optimized Multi Atlas Segmentation (THOMAS): fast, fully automated segmentation of thalamic nuclei from structural MRI,” Neuroimage. 2019 Jul 1;194:272-282, the entire disclosure of which is incorporated herein by reference, although other methods for segmentation may also be used. The THOMAS algorithm segments multiple thalamic nuclei on each brain image volume.

[0091] Another exemplary approach for segmentation based on the disclosed technology is to use a single atlas method to warp a mask labeling the CL and VPM nuclei from the template brain volume to the individual image volume of interest. This second stage of thalamus segmentation may be performed in some embodiments of the present technology because the THOMAS algorithm does not identify or segment the CL and VPM nuclei. Although there are some nuclei identified by the THOMAS algorithm that may be "target avoidance regions", such as the CM nucleus, the main target activation region is the CL nucleus; the CL nucleus is identified on both sides of the brain for the individual image volume of interest using the single atlas method of this second stage of thalamus segmentation.

[0092] In step 502, the surgical computing device 14 models one or more fiber pathways in the segmented brain model generated in step 500. Identification of the locations of fiber pathway confluences can be optimally achieved, for example, by using diffusion tensor imaging (DTI) based on Edlow et al., “Neuroanatomic Connectivity of the Human Ascending Arousal System Critical to Consciousness and Its Disorders,” J. Neuropathol. Exp. Neurol. 71(6):531-46 (2012), the entire disclosure of which is incorporated herein by reference. In some embodiments, the surgical computing device 14 acquires diffusion weighted images in a manner consistent with DTI processing to cover the entire brain of the human subject with isotropic resolution of voxel dimensions of 2 mm or better. The diffusion weighted images can be acquired using imaging sequence parameters that provide high image quality and signal-to-noise ratio.

[0093] These diffusion-weighted images are then processed using DTI fiber tractography, in which specific fiber tracts are defined based on a seed region where the fiber pathway originates, a "filter region" through which the tracked fibers must pass, and, optionally, an endpoint region to which the tracked fibers will reach. The surgical computing device 14 uses fiber tractography techniques to define the CL / DTTm fiber bundles that originate in the pontine nucleus (PPN), pass through the CL nucleus of the thalamus, and terminate in the forebrain or parietal region.

[0094] In step 504, the surgical computing device 14 generates a position and orientation in the segmented brain model for at least one electrode having multiple contacts. A comparison of the spatial location of the outer wing of the CL as a target point and the orientation of the CL / DTTm defined by DTI and fiber tractography results in the main axis of the CL / DTTm fiber bundle in three dimensions and the target electrode position and orientation. More specifically, the electrode orientation is based on the orientation of the electrode contacts, which corresponds to the determined main axis of the CL / DTTm fiber bundle. The surgical computing device 14 also determines a surgical trajectory of electrode insertion to achieve the target position and orientation. Thus, the target electrode position and orientation guides the localization of the DBS lead, as described in more detail below.

[0095] Optionally, electrode positions may be further generated based on the data stored on the surgical computing device 14 to identify implantation areas for providing selective activation of the subject's thalamus. In one embodiment, to identify electrode positions, the segmented brain model is registered to a brain model atlas to identify anatomical nuclei within the segmented brain model. Registration may be performed using techniques such as symmetric normalization, although other techniques may also be used.

[0096] In step 506, the surgical computing device 14 creates a stimulation map. The stimulation map is created using a segmented model of the subject's central thalamus. Electrode positions are used to apply the modeled stimulation to generate a stimulation map to identify fiber pathways that are activated as a result of applying the modeled stimulation. In some embodiments, biophysical modeling, when applied to 3D fiber trajectories developed from DTI, is used to render activated and / or avoided fiber bundles. This interaction is modeled by first calculating the electric field created in the brain as a function of electrode position and stimulation settings, and second predicting activation based on voltage values ​​along each fiber tract or in each nucleus.

[0097] Referring to Fig. 6, a method for image-guided surgical planning is illustrated to facilitate vector targeting of the human central thalamus for guiding deep brain stimulation therapy. Specifically, Fig. 6 illustrates an overview of a method for image-guided surgical planning of CT-DBS, including segmentation of the thalamus and thalamic nuclei using MRI imaging with thalamic contrast enhancement and automated segmentation. In this example, WMn imaging is used with the thalamic segmentation algorithm of THOMAS plus CL-VPM automated segmentation to define the target and avoided nuclei; DTI with tractography is used to define the target and avoided fiber tracts; and electrodes and biophysical modeling of neuronal activation are used to define electrode position and orientation, as well as surgical trajectory.

[0098] Referring to Fig. 7, a WMn image is shown showing contrast in the thalamus to allow identification of individual thalamic nuclei. In this example, the WMn image shows contrast in the thalamus to allow clear identification of individual thalamic nuclei, and includes visual evidence of the CL nucleus, as well as sufficient contrast to allow automatic segmentation of 14 thalamic nuclei using the THOMAS algorithm. Thus, the WMn image with high contrast in the thalamus of human subjects facilitates improved segmentation of thalamic nuclei using the THOMAS algorithm, which may not be possible when using other magnetic resonance sequences that do not provide or reduce contrast in the thalamus.

[0099] Referring to Fig. 8, the combination of WMn imaging and DTI imaging is illustrated, which provides both target and avoided nuclei and target and avoided fiber tracts.The target and avoided nuclei and target and avoided fiber tracts are used to define vector targeting, which takes into account both the position and trajectory (i.e. orientation) of DBS lead (e.g. electrode contact) relative to the target projection from the nucleus and the fiber bundle emanating from the nucleus.Thus, the vector targeting of the present technology combines a three-dimensional model of the thalamic nucleus with the model fibers projecting from the nucleus to target structures within the frontal cortex and striatum, for example, in a human subject.In this example, high-resolution diffusion imaging and subsequent DTI tractography are used to identify the DTTm fiber tract, which facilitates the determination of the main axis of the DTTm fiber tract and the orientation of the corresponding electrode contact and surgical trajectory.

[0100] Returning to FIG. 5 , at step 508, the surgical computing device 14 may optionally determine whether the electrode position, contact orientation, and surgical trajectory are satisfactory. The decision regarding the electrode position and contact orientation may be based in part on the stimulation map created at step 506; and whether the electrode position is ideal for selectively activating the centrothalamic fibers of the subject such that activation of the centrolateral-dorsomedial tegmental fiber pathway in the subject is maximized and activation of the centromedial-parafascicular fiber pathway in the subject is minimized. The decision regarding the surgical trajectory may be based on the particular anatomy of the human subject, such as, for example, one or more lesions that are desired to be avoided during electrode insertion. The one or more lesions are in one or more of the centrothalamus, cerebral cortex, or striatum. In some embodiments, the decision at step 508 may be automated, such as when the surgical trajectory affects a brain lesion, and in other embodiments, the decision at step 508 may be based on manual observation and input by the surgeon into the surgical computing device 14. If the surgical computing device 14 determines that one or more of the position, orientation, or surgical trajectory is not satisfactory, it takes the No branch back to step 504 .

[0101] In subsequent iterations of steps 504-506, the surgical computing device generates alternative electrode positions and / or orientations and / or alternative surgical trajectories that remain substantially aligned with the major axes of the CL / DTTm fiber bundles, but that, for example, enhance activation or avoidance and / or avoid the lesion. In some examples, navigation around the lesion in the thalamus is achieved by making adjustments for increased activation coverage of remaining fibers available in the target capture structures, and avoidance of nearby regions of fibers representing the target avoidance structures.

[0102] For illustrative purposes, modeling of fibers surrounding a local thalamic lesion that prevents some of the fibers for target capture from exiting into the volume of tissue to be stimulated can be problematic. Using the bioelectric field modeling described above with respect to step 506, single or multiple electrodes are virtually placed, and the activation of each fiber bundle from the target capture or target avoidance structure is quantitatively assessed based on the local positioning and orientation of the electrodes under various combinations of electrode contact geometry (e.g., active cathode) and the simulated activation and stimulation parameters (e.g., voltage or current amplitude, pulse width of the stimulation pulse, frequency of the stimulation pulse, phase per contact of the stimulation signal). This approach allows planning of single or multi-electrode systems for navigation of placement in the brain with large, multifocal lesions.

[0103] Returning to step 508, if the surgical computing device 14 determines that the position, orientation, and surgical trajectory are satisfactory, it proceeds to step 510 on the yes branch. In step 510, the position and orientation, surgical trajectory, and electrical stimulation conditions for the one or more electrodes in the subject's central thalamic fibers are established and, based on the simulation map created in step 506, are used to insert and selectively activate the subject's central thalamic fibers such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the subject is maximized and activation of the medial central nucleus-parafascicular nucleus fiber pathway in the subject is minimized.

[0104] Thus, electrodes are positioned within the central thalamic fibers of a subject such that the electrode contacts are substantially aligned with the orientation of the major axes of the CL / DTTm fiber bundles and in some embodiments avoid the lesion. Optionally, the voltage for evoking stimulation is shaped to achieve selective activation of targeted fiber pathways or nuclei while avoiding non-targeted pathways or nuclei. Shaping is achieved through the implantation of one or more DBS leads in each hemisphere and the selection of stimulation settings; stimulation settings include those in which both inter-lead and intra-lead stimulation is applied.

[0105] The exemplary method may be used in pre-operative, intra-operative, and post-operative settings. Pre-operative planning may be used to determine the location, orientation, and trajectory for implanting electrodes / leads in each brain hemisphere to obtain the highest likelihood of activating the target structures while avoiding other structures. During pre-operative planning, a wide range of positions, orientations, and trajectories of the DBS leads are explored. The parameter space includes six degrees of freedom in terms of spatial transformation, and seven degrees of freedom for directional DBS leads. The described method allows for determining the location and orientation for implanting an electrode, such as electrode 32, to selectively activate the central thalamic fibers of a subject such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the subject is maximized, and activation of the medial central nucleus-parafascicular nucleus fiber pathway in the subject is minimized.

[0106] The exemplary method may also be used intraoperatively to further determine whether the applied activation is on target during execution of the preoperative plan. Information gathered intraoperatively, such as feedback from the sensor 40, is used to assess the degree to which the preoperative plan is being followed. This data is recorded and stored in a subject model on the surgical computing device 14. One or more sensors 40 are temporarily implanted within the subject's body to record neural activity that may indicate whether the preoperative plan is being executed. Intraoperative imaging (MRI, CT, endoscopy) using the imaging device 16 may also be used to verify lead position.

[0107] In addition, the exemplary method may be utilized in post-operative planning. Post-operative planning may be utilized to program a stimulator, such as a stimulation signal generator 38, to provide stimulation to a subject to provide therapeutic benefit. A post-operative scan (MRI or CT) using the imaging device 16 is used to ascertain the actual location and orientation of the DBS leads, such as the electrodes 32, in each hemisphere. This scan is co-registered with the pre-operative scan of the subject model, stored on the surgical computing device 14. At this point, the lead position is fixed and cannot be changed without additional surgery. Thus, electrical stimulation conditions, such as which electrodes are activated as anodes or cathodes and which waveforms are used, as described above, may be adjusted to achieve targeted activation with negligible spillover into other structures. Simulations are used to systematically explore this parameter space and recommend stimulation settings for a stimulation signal generator 38, such as a pulse generator.

[0108] System 12 further allows for immediate determination of post-implant location of electrodes to allow for accurate post-implant titration of behavioral effects, as well as annotation of positive and negative behavioral effects, to customize the system for programming of current to an individual subject. System 12 also allows for post-implant titration of electrically evoked activity when used in conjunction with high density EEG.

[0109] 9A and 9B, a conceptual overview is shown showing the placement of vectors in a three-dimensional collection of fibers that are adjusted for bulk activation of fibers of the CL / DTTm structure. The vectors are placed via initial lead placement in virtual space using MR imaging to select a skull entry position and a tip position that is substantially aligned with the determined major axis of the CL / DTTm fiber bundle; estimation of activation of target and avoidance structures; and iterative adjustment of the lead trajectory and tip position until at least one electrode achieves its purpose. Thus, the vectors in Figs. 9A and 9B represent the orientation of electrode contacts in three-dimensional space that are positioned and oriented to substantially correspond to the major axis of the CL / DTTm fiber bundle and to provide satisfactory target activation and target avoidance.

[0110] Referring to FIG. 10, a volume rendering of two thalamic nuclei (activation target) and the central midline nucleus (avoidance target), a target DTTm fiber bundle, and a DBS lead with an active electrode are shown. In this example, two thalamic nuclei (CL-blue (activation target)) and the central midline nucleus (pink (avoidance target)) of the target DTTm fiber bundle (purple), and a DBS lead with an active electrode (gray and white) are shown with an applied electric field (yellow) that activates certain fibers. Referring to FIG. 11, another volume rendering of the two thalamic nuclei of FIG. 10 is shown with the fibers activated by the applied electric field isolated. In this example, the isolated activated fibers are shown in yellow.

[0111] 12, multiple target activation and avoidance pathways in the human central thalamus are illustrated. In this specific example, the CL and PPN are the target fiber pathways and the MD, VPM, and CM are the avoidance fiber pathways, although in other examples other pathways may be target and / or avoidance fiber pathways.

[0112] Referring to FIG. 13, a fiber activation profile is illustrated, including a histogram of activation percentages of target activation regions and target avoidance regions for a general thalamic model system. In this example, the illustrated histograms show activation percentages of activation targets (blue) and activation percentages of avoidance targets (yellow, green) for a general thalamic model system. Referring to FIG. 14, changes in fiber activation achieved by adjusting electrode positions from those illustrated in FIG. 13 are illustrated. Electrode positions are adjusted between FIG. 13 and FIG. 14 based on the techniques of the present disclosure such that the orientation of the electrode contacts is substantially aligned with the major axis of the fiber bundle, resulting in improved target activation and reduced activation of avoidance targets / regions.

[0113] Referring to Figure 15, human thalamus imaging data from a human subject with TBI is illustrated, including activation percentages of CL and PPN targets, as well as other thalamic nuclei (VPM, CM, MD) of avoidance targets. As shown in Figure 15, activation of activation targets is increased and activation of avoidance targets is decreased through four contacts of an exemplary electrode based on the technology described and illustrated herein. EXAMPLES

[0114] This description is further illustrated by the following examples, which should not be considered limiting in any way. In one example, the lateral portion ("wing") of the lateral central nucleus of the thalamus and its associated fiber bundle, the dorsal tegmental tract medial component (DTTm), CL / DTTm-DBS, was selected as the target of activation in six human subjects (ages 23-60, 3-18 years after injury). Five of the six completed the study, as shown in Table 1 below with corresponding demographically adjusted scores.

[0115] [Table 1]

[0116] To meet the need for precise and accurate location of vectors representing CL / DTTm targets in human subjects, CL / DTTm targeting was performed based on imaging, positioning of stimulating electrodes at intended locations based on segmentation of the thalamus and predictive biophysical models estimating activation of projection fibers as described above, and adjusting electrode orientation to optimize stimulation of intended CL / DTTm fiber bundles.We selected the Trail Making Test part B (TMT-B) as the primary efficacy endpoint based on the well-established relationship between diffuse axonal injury (DAI) resulting from msTBI and persistent impairments in executive attention and information processing speed control.

[0117] Bilateral electrode implantation was performed safely in all subjects, with position and orientation guided by subject-specific imaging to target CL / DTTm. Five subjects completed the study, which included a 2-week stimulation titration phase and a 3-month open-label treatment phase. As described in more detail below, all five subjects exceeded the preselected primary outcome benchmark of a 10% improvement in time to TMT-B completion from preoperative baseline to the end of the treatment phase (improvements of 15%, 24%, 26%, 42%, and 52%).

[0118] For each subject, white matter nulled magnetization prepared rapid acquisition gradient echo (WMn-MPRAGE) and DTI MRI data were obtained for use in a dedicated processing pipeline. In addition to the conventional scanning protocol used for clinical pre-operative DBS planning, subjects were scanned with WMn-MPRAGE and DTI protocols on a 3T GE MR750 with a 32-channel head coil. WMnMPRAGE image volumes were acquired with the following parameters: 3D MPRAGE sequence, coronal orientation, TE 4.7ms, TR 11.1ms, TI 500ms, TS 5000ms, 240 views per segment, FA: 8°, RBW + / - 11.9kHz, spatial resolution 1mm isotropic, k-space ordering of 220 slices per volume; 2D radial fan beam, ARC parallel imaging acceleration ratio: 1.5x1.5. DTI image volumes were acquired using the following parameters: 2D diffusion-weighted single-shot spin-echo echo-planar imaging (EPI) sequence, axial orientation, TE 74ms, TR 8000ms, RBW + / -250kHz, diffusion direction: 60, diffusion weighting (b-value): 2500 s / mm^2, spatial resolution 2mm isotropic, number of slices per volume 70, parallel imaging acceleration rate: 2, scan time 11 minutes. WMnMPRAGE and DTI image volumes were visually inspected to ensure that the scans were of sufficient quality for analysis and were not compromised by motion artifacts.

[0119] Each subject's WMn images were then processed using the THOMAS automated thalamic segmentation algorithm; however, because the THOMAS algorithm does not include the lateral central nucleus as a default intranuclear structure, CL boundaries were identified using single-atlas segmentation using a CL atlas derived from the THOMAS template by manual segmentation by an experienced neuroradiologist; the THOMAS template is a very high-quality WMn image formed by nonlinear registration and averaging of 20 WMn volumes.

[0120] More specifically, whole-brain WMnMPRAGE volumes were processed with THOMAS thalamic segmentation without preprocessing. Volumes of 12 lateralized structures were segmented and extracted in each brain hemisphere: the whole thalamus, 10 thalamic nuclei (anterior ventral nucleus [AV], centromedian nucleus [CM], lateral geniculate nucleus [LGN], dorsomedial nucleus [MD], medial geniculate nucleus [MGN], pulvinar [Pul], anterior ventral nucleus [VA], anterior ventral nucleus [VLA], posterior ventral nucleus [VLP], and posterolateral ventral nucleus [VPL]), and one nearby suprathalamic structure, the habenula (Hb). THOMAS segments the whole thalamus separately from the thalamic nuclei; this whole thalamus encompasses all of these aforementioned structures, as well as the mammillothalamic tract, and several additional thalamic areas that were not labeled (i.e., areas between the segmented thalamic nuclei).

[0121] In addition to THOMAS segmentation, a single atlas segmentation approach was used to segment the CL and VPM nuclei in each hemisphere, utilizing CL and VPM nuclei that were manually segmented by a single experienced neuroradiologist (TT) on the THOMAS template; the THOMAS template is a very high-quality WMn volume formed by careful registration and averaging of 20 WMn volumes. The resulting single CL and VPM atlas was nonlinearly warped to each subject's WMn volume, and the CL and VPM boundaries were established by trimming any CL and VPM voxels that overlapped with the THOMAS nuclei.

[0122] In other words, the THOMAS segmentation was assigned a higher priority than the segmentation of the CL and VPM; the rationale is that the THOMAS segmentation (obtained by a multi-atlas approach) is more accurate than the single-atlas segmentation of the CL and VPM. Hence, by prioritizing the THOMAS nucleus, the segmentation of the CL and VPM was prevented from overlapping with the THOMAS nucleus. However, in alternative embodiments, it may be preferable to prioritize the segmentation of the CL and / or VPM over the THOMAS segmentation. The DTI images were analyzed to obtain tractography models of the fibers emanating from the CL and other nearby thalamic nuclei generated by the THOMAS algorithm.

[0123] Next, we targeted the CL nucleus and the dorsal tegmental tract medial (DTTm), a bundle of axons emanating from this region, based on several computational differences that delineated the boundaries of the intended target region. Based on known monosynaptic connections determined in previous physiological and anatomical studies, the regions of stimulated cell bodies and axons with reciprocal connections in the "outer wing" of the CL and regions of the prefrontal / frontal cortex included the anterior cingulate cortex (area 24), premotor cortex, presupplementary motor area / supplementary motor area (area 6), and dorsal medial prefrontal cortex (areas 8 and 9), including the frontal eye field. In addition, electrode placement was designed to stimulate fibers emanating from the paralaminar region (plMD) of the dorsomedial nucleus, which has a strong projection to the dorsolateral prefrontal cortex (area 46). Collectively, the major monosynaptic projections in the expected stimulation region span the medial prefrontal / frontal cortex region, with some extension to the lateral convexity of the frontal cortex.

[0124] Finite element and biophysical modeling of fiber activation was then used to guide electrode placement to achieve this CL / DTTm targeting, taking into account local vascular geometry, with model electrodes targeted within the subject's brain space adjusted for safety and entry point angles. Lead and electrode placement and orientation were adjusted to simultaneously maximize activation of CL / DTTm fiber tracts and minimize activation of off-target fibers.

[0125] Five subjects completed the full study design, including a 2-week stimulus titration phase (TP) and a 3-month open-label (OL) treatment phase. As shown in Figure 16, all five of these subjects met the preselected primary outcome benchmark of >10% improvement in TMT-B completion time from preoperative baseline to end of TP (mean improvement 31.75; minimum 15%, maximum 52%). Improvements ranged from 15% to 52%. The greatest improvements were seen in subjects with the largest initial deficits. However, even subjects whose baseline performance was in the upper normal range showed >20% improvement in performance time.

[0126] More specifically, Figures 18 and 19 illustrate an exemplary approach for target acquisition from a representative human subject, along with activation results from both hemispheres. The top row of images in the middle of Figure 18 identifies the location of the active electrode contacts in Patient 3, displayed on a coronal WMn image, with the CL volume shown in yellow (blue outlines the two contacts L3, L4 in the left hemisphere and R3, R4 in the right hemisphere). The bright red markings in the coronal images depict the passing DTTm fibers, indicating their spatial proximity to the active contacts. The left and right sides of the top row are illustrations of the activation of CL / DTTm fiber bundles achieved in the left and right hemispheres. For this subject, activation with the combination of four active contacts achieved 81% activation of CL / DTTm fibers in the left hemisphere and 78% activation of these fibers in the right hemisphere. The histograms plotted in the lower center row show the percentage of activation for CL / DTTm, MD, VPL, and Cm fibers. For most contacts, CL / DTTm fiber activation dominated the range of current amplitudes modeled for single-contact monopolar activation. These histograms formed the basis of titration studies used to establish electrode contact geometry and stimulation parameters for treatment studies.

[0127] A similar profile of modeled CL / DTTm activation was obtained across patient subjects, with most electrode placements resulting in predominant activation of these fibers. However, in patient 3, electrode contacts within the right hemisphere failed to activate modeled CL / DTTm fibers (0.5% of predicted activation). For most subjects, active contacts resulted in modeled activation of modeled CL / DTTm fibers with limited involvement of avoidance fibers.

[0128] To compare electrode placement across five human subjects, a synthetic atlas was developed to consolidate electrode placements of all patients into a single common space. Figure 19 illustrates the placement of active contacts for each subject in the common synthetic atlas space. Figure 19 shows tight clustering of active contacts for left hemisphere electrodes around the emergence of CL / DTTm fibers emerging from the CL nucleus border (light red mark), while placement of active electrode contacts in the right hemisphere showed greater variability. This difference was likely influenced by brain volume shifts induced by loss of cerebrospinal fluid during the procedure; since the right hemisphere bulb was typically placed posterior to the left hemisphere (4 / 5 subjects). FIG. 19 also shows top and angled lateral views of the left and right electrodes, demonstrating the tight clustering of placements in the left hemisphere and the relationship of the CL / DTTm fiber bundles, along with the relative activation percentages for CL / DTTm and avoidance fibers originating from MD, VPL, and Cm.

[0129] Referring to FIG. 20, cortical evoked potentials obtained across a 128-channel EEG array are illustrated for activation across two active contacts using 2 Hz duty cycle stimulation. Each column in FIG. 20 shows a superimposed time trace of the cortical evoked potentials obtained from all 128 channels. For both hemispheres, these evoked responses typically showed an initial positive deflection that peaked approximately 200 ms after the stimulation pulse; this was followed in most subjects by a second, and sometimes a third, shallower peak activation; subsidence, where the evoked response returned to a flat baseline, typically occurred within approximately 1 second. A topography plot showing the spatial variation in the depth of the evoked response at the peak (approximately 200 ms, see red line) indicates that the strongest responses appeared within the frontal regions of the ipsilateral hemisphere between the medial and lateral regions.

[0130] As illustrated in FIG. 20, there is more reproducible localization, modulation depth, and timing of peak amplitude response across subjects in the left hemisphere. Comparing these findings to those from the synthetic atlas in FIG. 19, the tighter cluster correspondence of electrode contact positions in the left electrode lead suggests that the intrasubject consistency of activation of the same fiber system is greater in the left hemisphere. Right-side electrode placements showed greater variance in tip placements than the top contacts used for activation. In some embodiments of the present technology, intraoperative measurements of evoked potentials may be used to facilitate adjustment of electrode position, orientation, or one or more other parameters of electrode activation based on the localization, modulation depth, and / or timing of cortical evoked responses. In such embodiments, for example, a method of measuring brain electrical activity (e.g., electrodes for surface electroencephalography, subdural grid or strip electrodes, or indwelling tissue electrodes); memory storage in a computer; a method of averaging; and a method of visual display to display real-time intraoperative feedback to the neurosurgeon may be used.

[0131] Five subjects completed the full study design, including a 2-week stimulus titration phase (TP) and a 3-month open-label (OL) treatment phase. As seen in Figure 19, all five of these subjects met the preselected primary outcome benchmark of >10% improvement in TMT-B completion time from preoperative baseline to end of TP (mean improvement 31.75; minimum 15%, maximum 52%). The range of improvement ranged from 15% to 52%. The largest percentage improvements were seen in subjects with the largest initial deficits (i.e., patients 2 and 5, as shown in Table 1 above). However, even subjects whose baseline performance was in the upper normal range (e.g., patients 3 and 4) showed >20% improvement in performance time.

[0132] To further assess these results, two additional comparisons were made. The Trail Making Test is one of a set of neurotheological tests that are demographically adjusted for a range of variables as part of the Halstead-Reitan Neurotheological Test Battery. Using the demographically adjusted T-scores applied to each subject's specific characteristics, the mean TMT-B performance gain across all subjects (as shown in Table 1) was found to be 9.6 with a standard deviation of 0.98 (T-scores were normalized so that 1 standard deviation equals 10 points).

[0133] Second, to estimate the likelihood that such changes in TMT-B time would occur naturally, measurements were performed against a database of longitudinal measures of TMT performance from 118 msTBI subjects followed at 1-year and 3-5-year time points (subjects drawn from a subset of subjects included in the published study of Dikmen et al., “Outcome 3 to 5 Years After Moderate to Severe Traumatic Brain Injury,” Arch Phys Med Rehabil Vol 84, October, 2003 (“Dikmen”), the entire disclosure of which is incorporated herein by reference). For the primary outcome measure, TMT-B, improvements reflect changes in central executive components of working memory and set switching, which are grouped under the term “cognitive-flexibility”. Improvements in TMT-B performance are likely indicative of functional changes in prefrontal and parietal cortical neurons (REFS) linked to CL / DTTm electrical stimulation.

[0134] FIG. 16 shows a scatter plot of TMT-B performance at 1 year versus 3-5 years for an individual Dikmen subject (solid blue circles) and for five subjects in this example (solid orange circles). As can be seen, the five subjects are distributed along the lower edge of the cloud of the distribution of longitudinal changes in the Dikmen subjects. The five sets of longitudinal changes in TMT-B times observed in our study (15-52% faster) are substantially different from the longitudinal changes in the Dikmen data set (mean of change, 4% slower): Kolmogorov-Smirnov test, p<0.005 [.0041. Note also that the time course in our study is 3 months (compared to the 3-5 year interval in Dikmen) and the starting point is 3 years or more post-injury, making this a conservative comparison. In addition, as can be seen in Figure 16, when looking at the line (y=x) of identical test performance at each measurement, Dikmen subjects tended to perform worse over time (more data points lie above this line).

[0135] The subjects in this example also showed improved performance on the TMT-A, which primarily tests search speed and may also be linked to fronto-striatal function. In addition, the derived measure BA, which examines executive control, also showed improvements. Compared to Dikmen's test-retest data, the observed changes were significant (TMT-A: 21-47% faster in this study, mean change was 6% slower in Dikmen, Kolmogorov-Smirnov test, p<0.001 [.00057]). For TMT-A, the mean performance improvement across all subjects, adjusted for demographics, was 13.4 (as shown in Table 1 above), representing an improvement of more than one standard deviation. Collectively, the comparative results in this example indicate that the faster completion times on TMT-B, TMT-A, and BA in our CL / DTTm subjects are very likely not the result of naturally occurring test-retest variability.

[0136] In addition, the Ruff 2&7 test was used as an additional performance measure to further evaluate attentional function. One subject's baseline assessment was missed due to a test administration error. This measure also showed a wide range of improvements across the four subjects; improved speed and accuracy differences were seen in all four subjects, and controlled search speed and automatic detection speed were improved in three of the four subjects who completed the full set of tests.

[0137] The preselected secondary measure TBIQoL-Fatigue showed improvement with two participants meeting the improvement benchmark, one remaining stable, and two meeting the decline benchmark. Four of five subjects also showed greater than 10% improvement in TBIQol-Executive Function (mean improvement 32.7%; min 0, max 62%). Improvements on the TBIQoL-Attention and TBIQol-Executive scales reflect self-reported improvement. Despite the short OL phase of 3 months, two of four subjects who completed the study showed a 1-point increase on the Glasgow Outcome Scale Extended (GOS-E) from preoperative baseline to the end of TP.

[0138] While preferred embodiments have been particularly depicted and described herein, it will be apparent to those skilled in the art that various modifications, additions, substitutions, and the like may be made therein without departing from the spirit of the present application, and therefore are deemed to be within the scope of the present application as defined in the appended claims.

Claims

1. 1. A method for surgical planning involving vector-based targeting of the human central thalamus to guide deep brain stimulation therapy, the method being performed by one or more surgical computing devices and comprising the steps of: segmenting a central thalamus within an image of the human subject's brain to create a segmented brain model; modeling one or more fiber pathways in the segmented brain model; determining a three-dimensional orientation of the major axes of central lateral nucleus-medial component of dorsal tegmental tract (CL / DTTm) fiber bundles in the human subject based on the modeling; generating initial model positions and orientations in the segmented brain model for one or more electrodes based at least in part on the determined three-dimensional orientations of the major axes of the CL / DTTm fiber bundles of the human subject; creating a stimulus map based on said modeling and said generating; and Based on the created simulation map, a step of identifying positions and orientations for multiple contacts of the one or more electrodes on the central thalamic fibers of the human subject, and electrical stimulation conditions for the positioned and oriented multiple contacts of the one or more electrodes, in order to selectively activate the central thalamic fibers of the human subject so that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized.

2. generating an initial model position and orientation for the segmented brain model, registering the segmented brain model to a brain model atlas to identify anatomical nuclei in the segmented brain model. The method of claim 1 further comprising:

3. The method of claim 2 , wherein the registering is performed using symmetric normalization.

4. The method of claim 1 , wherein modeling one or more fiber pathways in the segmented brain model is based on diffusion tensor data.

5. 1. A non-transitory computer-readable medium having stored thereon instructions for surgical planning involving vector-based targeting of the human central thalamus to guide deep brain stimulation therapy, comprising: When executed by one or more processors: segmenting said thalamic center within an image of the brain of a human subject to create a segmented brain model; modeling one or more fiber pathways in the segmented brain model; determining three-dimensional orientations of major axes of central lateral nucleus-medial component of dorsal tegmental tract (CL / DTTm) fiber bundles in the human subject based on the modeled one or more fiber pathways; generating an initial model position and orientation in the segmented brain model for each of one or more electrodes based at least in part on the determined three-dimensional orientation of the major axis of the CL / DTTm fiber bundle of the human subject; creating a stimulation map based on the modeled one or more fiber pathways and the generated initial model positions and orientations in the segmented brain model for each of one or more electrodes; and Based on the created simulation map, identifying positions and orientations for a plurality of contacts of the one or more electrodes on the central thalamic fibers of the human subject and electrical stimulation conditions for the positioned and oriented plurality of contacts of the one or more electrodes, in order to selectively activate the central thalamic fibers of the human subject, such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized. Executable code for causing the one or more processors to perform 1. A non-transitory computer-readable medium comprising:

6. The executable code, when executed by one or more processors, registering the segmented brain model to a brain model atlas to identify anatomical nuclei in the segmented brain model to identify positions and orientations for each of the one or more electrodes in the segmented brain model; further causing the one or more processors to The non-transitory computer-readable medium of claim 5 .

7. The non-transitory computer-readable medium of claim 5 , wherein the registering is performed using symmetric normalization.

8. 6. The non-transitory computer-readable medium of claim 5, wherein modeling one or more fiber pathways in the segmented brain model is based on diffusion tensor data.

9. a memory having program instructions stored therein; coupled to the memory and: Segmenting the central thalamus within an image of the human subject's brain to create a segmented brain model; modeling one or more fiber pathways in the segmented brain model; determining three-dimensional orientations of major axes of central lateral nucleus-medial component of dorsal tegmental tract (CL / DTTm) fiber bundles in the human subject based on the modeled one or more fiber pathways; generating an initial model position and orientation in the segmented brain model for each of one or more electrodes based at least in part on the determined three-dimensional orientation of the major axis of the CL / DTTm fiber bundle of the human subject; creating a stimulation map based on the modeled one or more fiber pathways and the generated initial model positions and orientations in the segmented brain model for each of one or more electrodes; and Based on the created simulation map, identifying positions and orientations for a plurality of contacts of the one or more electrodes on the central thalamic fibers of the human subject and electrical stimulation conditions for the positioned and oriented plurality of contacts of the one or more electrodes, in order to selectively activate the central thalamic fibers of the human subject, such that activation of the lateral central nucleus-dorsomedial tegmental tract fiber pathway in the human subject is maximized and activation of the median central nucleus-parafascicular nucleus fiber pathway in the human subject is minimized. one or more processors configured to execute the stored program instructions to perform 1. A surgical computing device comprising:

10. the one or more processors: registering the segmented brain model to a brain model atlas to identify anatomical nuclei in the segmented brain model to identify positions and orientations for each of the one or more electrodes in the segmented brain model; and further configured to execute the stored program instructions to perform 10. The surgical computing device of claim 9.

11. The surgical computing device of claim 9 , wherein the registering is performed using symmetric normalization.

12. the one or more processors: modeling the one or more fiber pathways in a segmented brain model based on diffusion tensor data. and further configured to execute the stored program instructions to perform 10. The surgical computing device of claim 9.

13. A surgical computing device according to any one of claims 9 to 12; an imaging device operatively coupled to said surgical computing device; one or more electrodes, each having a plurality of contacts; and an electrical stimulator coupled to the surgical computing device and to the one or more electrodes to enable electrical activation of the one or more electrodes based on commands from the surgical computing device.

1. A system for vector-based targeting of the human central thalamus to guide deep brain stimulation therapy, comprising:

14. The system of claim 13 , wherein the one or more electrodes comprises a plurality of electrodes.

15. 14. The system of claim 13, wherein the electrical stimulator is capable of electrically activating the one or more electrodes to apply electrical stimulation at 0.1 to 25.0 milliamps or 0.1 to 10.5 volts, independently selected for each of the one or more electrodes.

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