A cerebral apparatus

Abstract

A cerebral apparatus 100 comprising a housing; a processor 120 positioned in the housing 118; and an electrode bundle 122 coupled to the processor and suitable for insertion into a ventricular pathway of a patient. Wherein the electrode bundle is configured to, in response to insertion into the cerebral ventricular pathway expand to at least partially contact a wall of at least one cerebral ventricle of the cerebral ventricular pathway and communicate an electrical signal between the processor and one or more cerebral structures adjacent to the cerebral ventricular pathway. The electrode bundle may comprise a resilient structure. The cerebral apparatus may comprise a chemical injector system.

Description

Field The present disclosure relates to a cerebral apparatus and in particular a cerebral apparatus for deep brain stimulation. Background Deep Brain Stimulation (DBS) relates to the stimulation of a patient's brain using an electrode that is surgically implanted within the brain. The electrodes can emit electrical impulses to regulate abnormal brain activity and potentially treat movement disorders like Parkinson's disease and essential tremor. Implantation of the electrode requires precise neurosurgery that carries associated risks. Summary According to a first aspect of the present disclosure there is provided a cerebral apparatus comprising: a housing; a processor positioned in the housing; and an electrode bundle coupled to the processor and suitable for insertion into a ventricular pathway of a patient, wherein the electrode bundle is configured to, in response to insertion into the cerebral ventricular pathway: expand to at least partially contact a wall of at least one cerebral ventricle of the cerebral ventricular pathway; and communicate an electrical signal between the processor and one or more cerebral structures adjacent to the cerebral ventricular pathway. The cerebral apparatus advantageously provides a surgically ergonomic device. That is the electrode bundle of the cerebral apparatus can be implanted into a patient's brain with much greater ease than conventional deep brain stimulation devices because the electrode bundle is configured for insertion into the ventricle channel rather than brain tissue. The cerebral apparatus may be suitable for monitoring, or the treatment of, a neurological disorder. The cerebral apparatus may be suitable for monitoring, or the treatment of, epilepsy. The cerebral apparatus may be suitable for monitoring, or the treatment of, a movement disorder. The cerebral apparatus may be suitable for monitoring, or the treatment of, Parkinson's disease. The electrode bundle may be configured to receive a stimulation signal from the processor and stimulate one or more cerebral structures adjacent to the cerebral ventricle pathway. The stimulation signal may provide deep brain stimulation. The electrode bundle may be configured to sense a neurophysiological signal in the one or more cerebral structures and transmit the neurophysiological signal to the processor. The housing may be positioned between a skull and a scalp of the patient. The electrode bundle may comprise: a compressed state for compressing the electrode bundle into a surgical catheter for insertion into the ventricular pathway; and an expanded state for contacting the wall of the at least one ventricle. The ventricular pathway may comprise one or more of: a lateral ventricle, a third ventricle and an intraventricular foramen. The electrode bundle may comprise a resilient structure. The electrode bundle may comprise a sheath. The sheath may provide the resilient structure. The electrode bundle may comprise a branching structure with a plurality of electrode strands. Each electrode strand may be configured to address a respective one of the one or more cerebral structures. The electrode bundle may comprise a plurality of electrode wires. Each electrode wire may have a different length and may terminate with an electrode contact point. The plurality of electrode wires may be held together by a sheath. The electrode contact points may be on an external surface of the sheath. The cerebral apparatus may comprise a chemical injector system. The processor may be configured to: receive a monitoring signal from the electrode bundle; determine if the monitoring signal is representative of a life-threatening seizure; and control the chemical injector system to inject neuro inhibitory chemicals into the ventricular pathway of the patient if the monitoring signal is representative of a life-threatening seizure. The processor may be configured to: receive one or more monitoring signals from the electrode bundle; compare the one or more monitoring signals to a cerebral map register comprising a plurality of cerebral maps each representative of electrical signals associated with a respective brain state of the patient; and identify a brain state of the patient by matching the one or more monitoring signals to a corresponding cerebral network map of the cerebral map register. The patient brain state may comprise one or more of: an ictal brain state; and an interictal brain state. The processor may be configured to: receive a plurality of monitoring signals; receive a plurality of patient activity data cotemporaneous with the monitoring signals; associate each monitoring signal with a patient brain state as identified by the patient activity data; and define a cerebral network map for each patient brain state. The processor may be configured to define each cerebral map by identifying one or more correlations between two or more monitoring signals associated with the respective patient brain state. The processor may be configured to identify the one or more correlations by: identifying a correlation between: a first monitoring signal from a first cerebral structure during a first time period corresponding to a first brain state; and a second monitoring signal from the first cerebral structure during a second time period corresponding to the first brain state. The processor may be configured to identify the one or more correlations by: identifying a correlation between a first monitoring signal from a first cerebral structure during a first time period corresponding to a first brain state; and a second monitoring signal from a second cerebral structure during the first time period corresponding to the first brain state. The cerebral apparatus may be configured to identify the one or more correlations by identifying one or more signature signal parameters associated with the two or more monitoring signals. The signature signal parameters may comprise one or more of: a frequency of the monitoring signal, a frequency peak of a frequency spectrum of the monitoring signal, a phase of the monitoring signal and an amplitude of the monitoring signal. The processor may be configured to provide a stimulation signal based on the patient brain state. The processor may be configured to: receive a patient brain state from a monitoring device; and provide a stimulation signal based on the patient brain state. The processor may be configured to provide a stimulation signal as one or more stimulation sub-signals to a respective one or more wires of the electrode bundle to excite a respective one or more of the cerebral structures. The cerebral apparatus may be configured to provide the stimulation signal to stimulate a remedial brain state of the patient. The remedial brain state may comprise a rapid-eye-movement sleep state. The cerebral apparatus may be configured to provide the stimulation signal to disrupt a brain state representative of a neurological disorder state. The neurological disorder state may be a seizure state. The cerebral apparatus may be configured to provide the DBS signal to provide neural entrainment at one or more of the one or more cerebral structures. The cerebral apparatus may be configured to provide the DBS signal at a resonance frequency of the one or more cerebral structures. According to a second aspect of the present disclosure there is provided a method of implanting a cerebral apparatus comprising the steps of: cannulating a lateral ventricle frontal horn; inserting an introducer catheter comprising an electrode bundle in a compressed state; and removing the introducer catheter such that the electrode bundle expands to at least partially contact a wall of at least one cerebral ventricle. According to a third aspect of the present disclosure there is provided a deep brain stimulation device comprising a plurality of electrodes for stimulating a plurality of nuclei targets in a brain of a patient. The cerebral apparatus may be configured to provide the stimulation signal to stimulate a remedial brain state of the patient. The remedial brain state may comprise a rapideye-movement sleep state. The cerebral apparatus may be configured to provide the DBS signal to provide neural entrainment at one or more more cerebral structures. The cerebral apparatus may be configured to provide the DBS signal at a resonance frequency of one or more cerebral structures. The processor may be configured to: receive a patient brain state from a monitoring device; and provide a stimulation signal based on the patient brain state. The processor may be configured to provide a stimulation signal as a plurality of stimulation sub-signals, each sub signal being provided to a respective electrode to excite a respective cerebral structure. The cerebral apparatus may be configured to provide the stimulation signal to disrupt a brain state representative of a neurological disorder state. The neurological disorder state may be a seizure state. The deep brain stimulation device may be provided for the treatment of epilepsy in the patient. According to a fourth aspect of the present disclosure, there is provided a method of providing deep brain stimulation comprising: providing a stimulation signal as a plurality of stimulation sub-signals to excite a respective plurality of cerebral structures; wherein providing the stimulation signal comprises stimulating a remedial brain state of the patient, wherein the remedial brain state comprises a rapid-eye-movement sleep state. According to a fifth aspect of the present disclosure, there is provided a method of providing deep brain stimulation comprising: providing a stimulation signal as a plurality of stimulation sub-signals to excite a respective plurality of cerebral structures; wherein providing the stimulation signal comprises providing the stimulation signal to provide neural entrainment at one or more more cerebral structures. According to a sixth aspect of the present disclosure, there is provided a method of providing deep brain stimulation comprising: providing a stimulation signal as a plurality of stimulation sub-signals to excite a respective plurality of cerebral structures; wherein providing the stimulation signal comprises providing the stimulation signal at a resonance frequency of one or more cerebral structures. There may be provided a computer program, which when run on a computer, causes the computer to configure any apparatus, including a circuit, controller, converter, or device disclosed herein or perform any method disclosed herein. The computer program may be a software implementation, and the computer may be considered as any appropriate hardware, including a digital signal processor, a microcontroller, and an implementation in read only memory (ROM), erasable programmable read only memory (EPROM) or electronically erasable programmable read only memory (EEPROM), as non-limiting examples. The software may be an assembly program. The computer program may be provided on a computer readable medium, which may be a physical computer readable medium such as a disc or a memory device, or may be embodied as a transient signal. Such a transient signal may be a network download, including an internet download. There may be provided one or more non-transitory computer-readable storage media storing computer-executable instructions that, when executed by a computing system, causes the computing system to perform any method disclosed herein. Brief Description of the Drawings One or more embodiments will now be described by way of example only with reference to the accompanying drawings in which: Figure 1A illustrates a cerebral apparatus according to a first aspect of the present disclosure; Figure IB illustrates an example electrode bundle of the cerebral apparatus of Figure 1A; Figure 2 shows an example processor for a cerebral apparatus according to an embodiment of the present disclosure; Figure 3 illustrates a method of surgically inserting a cerebral apparatus according to an embodiment of the present disclosure; Figure 4 illustrates a method of registering, calibrating and operating the cerebral apparatus in a monitoring mode of the cerebral apparatus according to an embodiment of the present disclosure; Figure 5 illustrates a method of recording and characterising cerebral network signals received by the cerebral apparatus for generating a personalised cerebral network map according to an embodiment of the present disclosure; Figure 6 illustrates a method of monitoring a patient using the cerebral apparatus according to an embodiment of the present disclosure; and Figure 7 illustrates a method of providing deep brain stimulation using the cerebral apparatus according to an embodiment of the present disclosure. Detailed Description The present disclosure provides a surgically ergonomic cerebral apparatus which can be implanted in a patient with relative ease and safety relative to a conventional deep brain stimulation device. The cerebral apparatus may be used for neural network monitoring I mapping and / or deep brain stimulation. The present disclosure also provides deep brain stimulation signalling that can provide improved outcomes in patient treatment, in particular for the treatment of epilepsy. Epidemiology of Epilepsy Epilepsy is a family of neurological disorders characterised by the development of recurrent unprovoked seizures. It is one of the most common neurological diseases in childhood and is associated with an increased risk of premature death when compared to the general population due to both direct effects of seizure events and indirect factors including SUDEP (sudden, unexplained {unexpected}, death in epilepsy). Congenital diseases and genetic abnormalities are more prevalent among the aetiology of paediatric epilepsy compared to adult-onset epilepsy. Pathophysiology In each patient seizures are thought to be generated by differing mechanisms and parameters. However, there is thought to exist a limited number of common pathways that ultimately lead to ictogenesis (seizure onset). Various theories have been proposed to explain the generation and termination of seizures. Selective silencing of inhibitory neurones is thought to play a role in the initiation of the ictal state, while the nature and extent of seizure propagation is thought to be caused by hypersynchronous recruitment of excitatory (pyramidal) neurones. Generalised seizures demonstrate global neural synchronicity. A peculiar aspect of seizure electrophysiology is that while seizure onset is thought to develop at the neuronal level, seizure termination is believed to be due to regional or global effect. Anticonvulsant therapy is the first line treatment in most paediatric epilepsy patients, however a third of patients become drug resistant, experience persisting seizures despite trial of dual anticonvulsant. Risk of drug resistant epilepsy is higher in children with earlier onset, those with learning difficulties, and those who have failed to achieve seizure control using one anticonvulsant. The likelihood of long-term seizure freedom in this group is low. Epilepsy surgery is potentially curative and is recommended at an earlier stage in children with epilepsy because early intervention might improve neurodevelopmental outcomes. However, surgical outcome is strongly correlated with MRI findings; best outcomes are seen in patients with structural abnormality on MRI scan that are concordant with multiple data points including clinical history, EEG abnormalities and video telemetry. The challenge here is that approximately 70% of patients will have a normal MRI scan. Epilepsy engenders risk of premature death, cognitive impairment, neurodevelopmental disorder, and reduced overall quality of life. These clinical and functional consequences disproportionately affect those with drug resistant epilepsy, generalised epilepsy syndromes, and those prone to status epilepticus. Complex systems approach to epilepsy In drug resistant paediatric epilepsy patients without a structural lesion visible on cranial imaging, further investigations have been performed to elicit the location of the epileptogenic zone (EZ) within the brain. Electroencephalogram (EEG) and functional imaging studies are performed as part of this investigative process. Studies of ictal EEG data have revealed complex relationship-dynamics between anatomically separate couplings of brain grey-matter zones that are co-activated simultaneously during the time course of a seizure. Study of the relationship dynamics yielded new investigation methods which have expedited detection of anatomically occult epileptogenic zones, propagation zones, and have increased our understanding of ictogenesis. This connectivity analysis has also shifted understanding of epilepsy away from a historical premise of focal structural abnormalities to a disease model which frames epilepsy as a complex network that is optimally defined through mapping in the space domain: with either functional or structural connectivity analysis; and mapping in the time domain with dynamic systems modelling. Together connectome which has predefined nodes in space, whose connectivity varies in time with stereotyped biomarkers during the ictal state and the interictal period offers a refined personalised description of epilepsy for each patient. Through whole brain functional connectivity studies, significant leaps in understanding of several epilepsy syndromes have been obtained, including: • Temporal lobe epilepsy network (characterised by a patient feeling full, chewing lips, and / or random hand movements) o The connectivity network includes many nodal points along the Papez circuit of the limbic system, including the amygdala, hippocampus, and thalamus though nodal points can vary between individuals. o In temporal lobe epilepsy there appears to be general reduced nodal network connectivity. • Temporal lobe epilepsy network with secondary generalisation (entire brain seizure, potentially fatal if occurrence is overnight, can result in full body seizure) o There is evidence of altered thalamocortical communication. o There is evidence of altered interactions between the thalamus and the basal ganglia, ■ The basal ganglia are thought to play a role in gate-keeping thalamocortical communication. • Generalised onset epilepsy networks o represented by a cortico-subcortical network involving nodal connections between the frontal lobe, thalamus, cerebellum and basal ganglia, with focal cortical discharges precipitating generalised spike waves. o Interestingly it appears that the sensorimotor cortex region of the network has an atypical resting synchronous state which is suspected to predispose to ictogenesis with minimal / no external stimulation or trigger. Adaptive neuromodulation Deep Brain Stimulation (DBS) is the implantation of electrodes into deep brain structures for the purpose of restorative neuromodulation in those affected by degenerative neurological disorders. DBS is mainly used in the treatment of movement disorders, such as Parkinson's Disease and Essential Tremor, though its utility has been investigated in other neurological conditions, including epilepsy. Table 1 illustrates from Yan et al. (2023) for refractory epilepsy single centre study. Epilepsy subtype DBS Target Target rationale Number of participants > 50% seizure frequency reduction Temporal lobe epilepsy Anterior Nucleus of Thalamus / ANT Functional connection to limbic system 45 64% Occipital lobe epilepsy Pulvinar / PN Multiple cortical connections 1 100% (1 / ) including occipital lobe Lennox-Gastaut Syndrome / Generalised onset epilepsy Centromedian Nucleus of thalamus / CMNT Diffuse connections with frontal lobe, basal ganglia and brainstem 3 100% (3 / 3) Motor cortex epileptogenic zone Substantia Nigra / STN STN modulates the pyramidal tract 16 81% Table 1: refractory epilepsy single centre study While the mechanism of action of DBS is not completely understood, it is thought to facilitate restorative neuromodulation via a combination of local electrical effects, wider electrical-network effectivity, and latent neural plasticity effects. There are limited data with respect to the efficacy of DBS treatment of epilepsy. However, there some important technology limitations that have been reported by clinicians, and patients, including: • Technical difficulty of implantation • Risk of stroke, disability, mortality • Electrode tip proximity to critical neural and vascular structures • Stereotactic surgery system limitations • Battery consumption • Battery replacement and infection risk • Devices designed with poor surgical ergonomics. • Adverse neurological side effects of DBS • Lack of understanding with respect to mechanism of action of DBS. These factors also apply to other neuromodulation technologies such as vagal nerve stimulators. These limitations affect clinical outcomes, surgical complication rates, and predispose to adverse treatment side effects and serious complications such as status epilepticus. The James Lind Alliance set understanding the mechanisms that cause epilepsy in children and using medical devices and advanced data analytics to improve prediction and management of epilepsy as a Top 10 Epilepsy Research Priorities. Cerebral Apparatus Figure 1A illustrates a cerebral apparatus 100 according to an embodiment of the present disclosure. In this example, the apparatus 100 has been implanted in the brain of a patient. The brain includes a cerebral ventricular system comprising a network of interconnected cavities known as cerebral ventricles. A portion of the cerebral ventricular system of the brain is illustrated which includes: the left lateral ventricle 102 located in the left cerebral hemisphere; the right lateral ventricle 104 located in the right cerebral hemisphere; the third ventricle 106; and the intraventricular foramen 108 (also known as the foramen of Monro) connecting the lateral ventricles 102, 104 to the third ventricle 106. The ventricular system of the brain also includes a fourth ventricle (not illustrated). Tissue structures of the brain adjacent to one or more ventricles are also illustrated including: i. the corpus callosum 110, part of which forms the roof of the lateral ventricles 102, 104. The corpus callosum is a potential nodal point in generalised onset epilepsy connectivity networks. ii. the caudate nucleus 112 (part of the basal ganglia) located lateral to the lateral ventricle 104 (one in each hemisphere). The caudate nucleus is part of the basal ganglia and may play a role in gate keeping secondary generalisation of temporal lobe seizures. iii. the fornix 114 adjacent to the intraventricular foramen 108; iv. the thalamus 116 - located immediately lateral to the third ventricle 106 and deep to the lateral ventricles 102, 104. Multiple nuclei of the thalamus have been investigated as targets in temporal lobe and generalised onset epilepsy connectivity networks. The adjacent subthalamic nuclei has been associated with motor cortex epilepsy. The cerebral apparatus 100 comprises a housing 118 and a processor 120 positioned in the housing. The housing 118 can be positioned between the skull and the scalp of the patient. The cerebral apparatus 100 further comprises an electrode bundle 122 for insertion into a cerebral ventricular pathway of the patient. As described herein, the cerebral ventricular pathway includes a path through one or more ventricles of the cerebral ventricular system. In this example, the cerebral ventricular pathway includes the left lateral ventricle 102, the third ventricle 106; and the intraventricular foramen 108. The electrode bundle 122 has been surgically inserted into the cerebral ventricular pathway. As discussed further below, upon insertion into the cerebral ventricular pathway, the electrode bundle 122 expands to at least partially contact a wall of at least one ventricle of the cerebral ventricular pathway. The wall may also be referred to as an ependymal surface of the ventricle. Following insertion, the electrode bundle 122 can communicate electrical signals between the processor 120 and brain tissue structures (also referred to herein as cerebral structures) adjacent to I external to the cerebral ventricular pathway. The electrical signals may comprise monitoring signals (also referred to herein as neurophysiological signals) communicated from the brain tissue structures to the processor 120 or may comprise stimulation signals communicated from the processor 120 to the brain tissue structures for deep brain stimulation. Example signals are discussed below. Figure IB illustrates an example electrode bundle 122. In this example, the electrode bundle 122 comprises a branching structure. The electrode bundle 122 includes a main stem 124 comprising a bundle of electrode strands 126-1, 126-2, 126-3, 126-4, 126-5 (collectively referred to as electrode strands 126). Each strand 126 may include a plurality of electrode wires. The electrode strands 126 in the main stem 124 may be held together, for example by a surrounding sheath and / or by an adhesive. Each electrode strand 126 may be held together with the other electrode strands 126 for a respective different portion of a length of the main stem 124. In this way, each electrode strand 126 can separate from the main stem 124 at different points along the length of the main stem 124 for positioning at a respective position in the cerebral ventricular pathway. Each strand 126 may be configured to expand and be positioned to communicate with a respective deep brain nuclei target adjacent to a wall of a portion of the cerebral ventricular pathway. The nuclei target may comprise one of: a. the corpus callosum 110 at a superior surface of the lateral ventricle 102, 104; b. the caudate nucleus 112 at a lateral surface of the lateral ventricle 102, 104 c. the fornix 114 at the intraventricular foramen 108; d. one of multiple Thalamic nuclei targets at the inferomedial surface of the lateral ventricle 102, 104 and lateral walls of third ventricle 106; and e. subthalamic nuclei groups via posterior of third ventricle 106. In the illustrated example, a first electrode strand 126-1 separates from the main stem 124 after a first length for (expansion and) positioning within the lateral ventricle to communicate with the caudate nucleus 112. A second electrode strand 126-2 separates from the main stem 124 after a second length for (expansion and) positioning within the lateral ventricle to communicate with the corpus callosum 110. A third electrode strand 126-3 separates from the main stem 124 after a third length for (expansion and) positioning within the lateral ventricle to communicate with the fornix 114. A fourth electrode strand 126-4 separates from the main stem 124 after a fourth length for (expansion and) positioning within the third ventricle to communicate with an ipsilateral side of the thalamus 116. A fifth electrode strand 126-5 separates from the main stem 124 after a fifth length for (expansion and) positioning within the third ventricle to communicate with a contralateral side of the thalamus 116. In this way, each strand comprises a stem portion and a branching portion for expansion and positioning within a ventricle. Each electrode strand 126 may comprise a bundle of electrode wires. Each electrode wire may be held together with the other electrode wires, for example by adhesive and / or by a surrounding insulating sheath. In this example, the electrode wires are surrounded by a silicone sheath. The same insulating sheath or a different insulating sheath may surround the main stem 124 and the other electrode strands 126. Each electrode wire may terminate at a respective electrical contact point 128. In this example, the contact points 128 are on an external surface of the insulating sheath and coupled to the respective electrode wire through an opening in the insulating sheath. In other examples, the contact points 128 may be positioned within corresponding openings in the insulating sheath. Each electrode wire within an electrode strand 126 may have a different length. In this way, each electrode strand 126 has a plurality of electrode contact points 128 distributed along the length of the electrode strand 126. Each electrode contact point 128 is individually addressable because it has its own corresponding electrode wire. The electrode bundle 122 may comprise a resilient structure. The resilient structure of the electrode bundle 122 may be compressed prior to implantation. For example, the electrode bundle 122 may be compressed into a surgical (introducer) catheter for endoscopic insertion. In response to implantation I insertion, the electrode bundle 122 may expand / resile towards its uncompressed state to partially contact the wall of at least one cerebral ventricle. For example, in response to removal of the introducer catheter, the resilient structure may resile to a less compressed state and expand within the cerebral ventricular pathway to at least partially contact the ependymal surface adjacent to a target nuclei. In this example, the strands 126 each comprise a helical structure when in a relaxed state (which may also be referred to as an expanded state). In particular, the branch portion of the strands 126 may comprise the helical structure. The helical structure may arise from a helical structure of the insulating sheath. Prior to implantation, the strands 126 may be compressed into a compressed state and positioned in the introducer catheter, e.g. by compression along the axis of the helix or by pulling the helix into a linear shape. Following implantation and removal of the introducer catheter, the strands may resile or recoil into their natural helical shape and expand within a ventricle to at least partially contact a wall of the ventricle, as illustrated in Figure 1A. The helical structure can provide intraventricular stability of the electrode strand 126. The helical structure can provide electrical contact stability (i.e. a stable contact between a portion of the electrical contact points and the ventricle wall (see below)). As the electrode contact points 128 are distributed along the length of the electrode strand 126, expansion of the electrode strand 126 to contact the wall of the ventricle will result in contact between a subset of the electrode contact points 128 and the wall I ependymal surface. In some examples, the electrode strand 126 may be configured to push against and / or stick to the wall to ensure good contact between the electrode contact points 128 and the wall. For example, the natural expanded state of the electrode strand 126 may extend to a larger volume than the volume of the target ventricle such that the electrode strand 126 remains partially compressed following expansion within the cerebral ventricle and pushes against the ventricle wall. In this example, the electrode bundle 122 is connected to an extracranial connector 130. The extracranial connector 130 can couple to the housing 118 to provide electrical communication between the processor 120 and the electrode bundle 122. The insulating sheath may extend into the connector 130 to ensure the electrode bundle is insulated along its entire length (other than at the electrode contact points 128). Although, a resilient branch structure has been described here, it will be appreciated that the electrode bundle may comprise alternative expansive structures. For example, the electrode bundle 122 may comprise a stent like structure that can expand within the volume of the ventricular pathway and at least partially contact the wall of at least one ventricle. The electrode bundle 122 should be sufficiently small to: (i) easily pass into multiple ventricle sizes (i.e. allow for variation in population); (ii) not obstruct circulation of cerebral spinal fluid; and (iii) be compressible into an introducer catheter for insertion into the ventricular system. Returning to Figure 1A, in this example, the cerebral apparatus 100 further comprises a chemical injector system. The cerebral apparatus 100 may include the chemical injector system when the cerebral apparatus is for use in disorders characterised by seizures such as epilepsy. The chemical injector system may include a chemical reservoir 132 in the housing to store neuro inhibitory chemicals. The chemical injector system may further include an intraventricular catheter 134 for insertion into the ventricular pathway. The chemical injector system may further include a fluid valve for controlling injection of the neuro inhibitory chemicals from the chemical reservoir into the cerebral ventricular system via the intraventricular catheter 134. The processor 120 may be coupled to the fluid valve and configured to selectively control the fluid valve to inject the neuro inhibitory chemicals into the cerebral ventricular system in response to detection of a life-threatening seizure. The processor 120 may detect a life-threatening seizure based on the electrical signals received from the one or more cerebral structures via the electrode bundle 122. The processor 120 may detect a life-threatening seizure if the electrical signals are representative of a seizure connectivity network and satisfy a life-threatening threshold (e.g. one or more amplitudes exceed a threshold, a number of sub-threshold conditions (phase locking, individual signal amplitudes) across the network are satisfied) etc. The cerebral apparatus 100 may comprises a power source such as a battery. The power source may provide power to the processor and may provide power for providing any stimulation signals. The power source may be housed in the housing. In some examples, the power source may be external to the housing and located at an external site on or within the body of the patient such as the chest or abdominal wall of the patient. Surgical implantation of a remote power source under the skin may involve a wound incision wide enough to accommodate the battery, development of a subcutaneous tissue pocket to house the power source, and creation of a subcutaneous tunnel that allows passage of wires / power cables from the power source to the cerebral apparatus. This may be performed during surgical implantation of the cerebral apparatus during a single operating theatre session, a "single-stage" implantation process; or, after the primary operation to implant the cerebral apparatus, a second operating theatre session devoted solely to implanting the power source and connecting it to the cerebral apparatus - a "two-stage" implantation process. Figure 2 shows an example processor 220 for a cerebral apparatus according to an embodiment of the present disclosure. Features of Figures 1A and IB that are also present in Figure 2 have been given corresponding reference numbers in the 200 series and are not necessarily described again here. Although the example processor 200 of Figure 2 is illustrated as a single block, it will be appreciated that the functionality of the processor 200 may be distributed over a number of processors. Furthermore, although the processor 200 is illustrated as coupled to the electrode bundle 222, the power source 236, a user interface 240 and the fluid valve 234, it will be appreciated that one or more interface circuits may be included between the processor and any of these features. In this example, the processor 200 receives power from the power source 236. In this example, the processor includes an electrode array interface 238 for coupling to the electrode bundle 222. The electrode array interface 238 includes a plurality of I / O couplings, each I / O coupling configured to couple to a respective electrode wire of the electrode bundle 222. In this way, each electrode wire, corresponding to each electrode contact point is individually addressable and identifiable by the processor 220. The electrode array interface 238 can receive monitoring signals, representative of electrical activity in the target nuclei, from the electrode bundle 222 and output the monitoring signals to a signal amplifier 242. The signal amplifier 242 can amplify the monitoring signals and pass them to an analog-to-digital converter (ADC) 244. The ADC 244 can convert the analog monitoring signals to digital monitoring signals. The ADC may pass the digital monitoring signals to a signal processor 245. The signal processor 245 can process the digital monitoring signals to determine a state of the patient's brain activity. For example, the signal processor 245 may perform frequency spectrum analysis, cerebral network signal mapping (also referred to as connectivity analysis), brain state identification, tremor detection, seizure detection and other signal processing tasks based on the digital monitoring signals. The signal processor 245 may perform connectivity analysis by determining correlations between the digital monitoring signals to identify connectivity between different cerebral structures I target nuclei (connectivity networks). Signal processing of the monitoring signals is discussed in further detail below. In this example, the signal processor 245 may output a seizure alert signal to a chemical control circuit 248. The signal processor 245 may output the seizure alert signal if the digital monitoring signals are representative of a life-threatening seizure event. In response to a seizure alert signal, the chemical control circuit can control the chemical injector system to inject the neuro inhibitory chemicals into the ventricular system of the patient in an attempt to reduce or terminate the seizure. The signal processor 245 may store the digital monitoring signals, outputs from signal analyses and / or seizure alert events in data storage 246. The data storage 246 may include a data storage array with a plurality of data storage units, each data storage unit corresponding to a unit of the electrode interface array 238. The processor 220 can output the digital monitoring signals, signal analyses and / or seizure alert events to the user interface 240. The user interface 240 may include a computing device, such as a computer or a mobile computing device (tablet, smartphone etc). The processor 220 may communicate with the user interface using a wireless communication such as WiFi ® or Bluetooth®. In some examples, the user interface may include a tactile device like a patient alarm device for a patient or clinician to activate to indicate that the patient is experiencing a seizure or severe tremor etc. A patient and or clinician may interact with the user interface to control the cerebral device and / or receive data from the cerebral device. The processor or housing 220 may include an antenna and associated communication circuitry for communicating signals between the processor 220 and the user interface 240. The signal processor 245, ADC 244 and signal amplifier 242 may be considered as forming a receive train of the processor 220. In some examples, the ADC 244 and / or signal amplifier may be incorporated in the signal processor 245. The receive train may include other signal processing functionality such as filtering, re-timing and other known signal processing functionality. In this example, the processor 220 includes a transmit train for providing stimulation signals to the electrode bundle 222 for stimulating one or more cerebral structures / target nuclei. The transmit train includes the signal processor 245, a signal generator 250, a digital-to-analog converter 252 and the electrode array interface 238. It will be appreciated that in other examples the signal processor 245 may include functionality of the signal generator 250 and / or DAC 252. Furthermore, in some examples, additional signal processing functionality may be included in the transmit train. The signal processor 245 may receive a stimulation signal instruction. The stimulation instruction may originate from the user interface 240 and / or from data storage 246. Alternatively, or in addition, the signal processor 245 may generate the stimulation signal instruction in response to the digital monitoring signals. In some examples, the data storage 246 may include a registry (not shown) for storing one or more stimulation signal instructions for responding to a particular cerebral state as indicated by the monitoring signals. The stored stimulation signal instructions may include a default stimulation signal instruction for generating a nominal stimulation signal in the absence of any specific cerebral events. As discussed below, the stimulation signal instructions may be personalised and / or may be generated as part of a mapping and calibration routine. The signal processor 245 can output the stimulation signal instruction to the signal generator 250. The signal generator 250 may generate a digital stimulation signal in response to the stimulation signal instruction and output the digital stimulation signal to the DAC 252. The DAC 252 may receive the digital stimulation signal and output a corresponding analog stimulation signal to the electrode array interface 238. The analog stimulation signal may include a plurality of stimulation signals for stimulating a corresponding plurality of the electrode wires of the electrode bundle 222 via the electrode array interface 238. In this way, selective ones of the electrode contact points may receive a stimulation signal and selectively excite corresponding target nuclei. In some examples, some functionality of the signal processor 245 may be performed remotely from the cerebral apparatus 200. For example, the data storage 246 may output the digital monitoring signals to a remote signal processing unit 245a (optionally via the user interface 240). A remote signal processing unit 245a may perform analysis and mapping on the digital monitoring signals. Remote signal processing can provide for more computational power, additional reference population data and computationally intensive techniques, such as machine learning, higher resolution Fourier transforms and optimisation algorithms, to provide for more effective mapping, signal personalisation and / or signal analysis. In this example, the processor 220 also includes an integrity monitor 254 for receiving an integrity signal from the electrode bundle 222. The integrity monitor 254 can monitor the integrity of the electrode bundle 222 to ensure that it has not become displaced, fractured etc. in situ. In some examples, the integrity monitor 254 may be incorporated into the electrode array interface 238 or the signal processor 245. The processor 220 may include a timer 256 for enabling accurate timing and / or synchronisation of stimulation signals and / or received monitoring signals. Figure 3 illustrates a method of surgically inserting a cerebral apparatus according to an embodiment of the present disclosure. A first step 358 comprises the cranial approach incision. The wound incision may comprise curvilinear scalp wound incision at Kocher's point that mitigates wound tension. The cranial approach may include generation of a burr hole or "minicraniotomy", and incision of the dura mater fibrous membrane that overlies the brain. A second step 360 comprises endoscopic cannulation of a lateral ventricle frontal horn. The step may include visual confirmation of entry into the ventricle system via an endoscopic camera. A third step 362 comprises endoscopic insertion of an introducer catheter comprising the electrode bundle in a compressed state. The endoscopic insertion may be performed under direct endoscopic camera vision. A fourth step 364 comprises removal of the introducer catheter and resulting expansion of the electrode bundle within the cerebral ventricular pathway. A fifth step 366 comprises coupling the extracranial connector of the electrode bundle to the housing. A sixth step 368 comprises securing the housing to the skull. The housing may be secured with screws. To prevent leakage of cerebrospinal fluid around the electrode bundle, which carries a widely known risk of meningitis secondary to endoscopic ventricular cannulation, via gaps between the cerebral apparatus and the opened dura mater, closure of the dura mater tightly around electrode bundle can be aided with liquid or solid synthetic dura mater substitute. A seventh step 370 comprises providing watertight galeal closure, + / - antibiotic powder impregnation inside the scalp wound prior to closure. An eighth step 372 comprises installing a battery at a remote battery site such as the chest or abdominal wall, as mentioned previously. Signal Processing Cerebral Monitoring In some examples, the disclosed cerebral apparatus may be used to monitor electrical signals produced by a patient's brain. In this way, the cerebral apparatus can act as an alternative or adjunct to an EEG device. Conventional invasive (surgically implanted electrodes) EEG monitoring is commonly used in epilepsy surgery mapping. Scalp EEG may also be used but can be less sensitive to signals from target nuclei deep within the brain. The disclosed cerebral apparatus can provide a monitoring device with improved ergonomics and safety relative to conventional invasive EEG, and a higher sensitivity than conventional scalp EEG because the electrode bundle is adjacent to target nuclei. As discussed below, the cerebral apparatus can also, or alternatively, be used as a deep brain stimulation device. In some examples, the cerebral apparatus may operate as both a monitoring device and a deep brain stimulation device to provide closed loop deep brain stimulation. In other words, the cerebral apparatus can provide deep brain stimulation signals in response to the monitored electrical signals of the brain. Figure 4 illustrates a method of registering, calibrating and operating the cerebral apparatus in a monitoring mode of the cerebral apparatus according to an embodiment of the present disclosure. A first step 474 comprises receiving a cranial image of the patient's head following implantation of the cerebral apparatus. The cranial image following implantation may comprise a computed tomography (CT) scan, for example a 1 mm CT head scan, which provides superior spatial accuracy to MRI. Further, in some examples, the implant might not be fully MRI compatible. In some examples, the first step 474 may also comprise receiving a cranial image of the patient's head prior to implantation. The cranial image received prior to implantation may comprise a high-resolution Magnetic Resonance Imaging (MRI) scan, which is able to provide superior anatomical detail of the ventricle system and target nuclei. The two images may be fused to provide a composite image with excellent anatomical detail and spatial resolution. A second step 476 comprises spatially registering the electrode contact points that are in contact with the wall of the ventricular pathway and adjacent to a target nuclei, using the cranial image of the first step 474. In the relevant examples, a fused composite CT / MRI scan can demonstrate detailed delineate of the target nuclei (MRI), and spatially accurate positions of the electrode contacts (CT). In some examples, each electrode contact point may comprise a unique identifying marker (such as an etched or embossed number, QR code or similar) that can be identified from the cranial image, particularly CT scan. A third step 478 comprises receiving electrical signals (monitoring signals / neurophysiological signals) from the electrode bundle. The electrode signals may comprise a subset of the electrical signals that correspond to the electrode contact points that are in contact with the wall of the ventricular pathway (as identified in the second step 476). A fourth step 480 comprises processing the electrical signals and calibrating the cerebral apparatus. In some examples, the fourth step may comprise receiving an EEG taken from the patient contemporaneously with the received electrical signals from the cerebral apparatus. Calibrating the electrical signals may comprise adjusting a magnitude and / or timing of each electrical signal based on corresponding readings from the EEG. Alternatively, or in addition, calibrating the electrical signals may comprise transforming the electrical signals in the time domain to the frequency domain to provide a frequency spectrum and calibrating the electrical signals based on a frequency spectrum of the corresponding readings from the EEG. A fifth step 482 comprises recording the calibrated electrical signals as personalised cerebral network signals for the patient. As discussed below, personalised signature electrical signals from one or more cerebral structures may be recorded for different brain states (e.g. ictal / interictal). In some examples, the personalised cerebral network signals can identify connectivity networks between anatomically separated cerebral structures of the patient's brain for the different brain states. Figure 5 illustrates a method of recording and characterising cerebral network signals received by the cerebral apparatus for generating a personalised cerebral network map according to an embodiment of the present disclosure. The method corresponds to the fifth step of Figure 4. The method may be considered as identifying signature monitoring signals for different states of an individual patient's brain. A first step 584 comprises receiving the calibrated monitoring signals. A second step 586 comprises receiving patient activity data. The patient activity data may indicate whether or not the patient is experiencing a seizure (ictal data or interictal data). The patient activity data may indicate patient activities that have different cerebral network signals such as sleeping and seizure. In some examples, the patient activity data may be received via the user interface of the cerebral apparatus. For example, the patient or a clinician may interact with the user interface to indicate a patient activity, for example going to bed / sleep, exercising, working / studying. The patient or a clinician may also interact with the user interface to indicate that the patient is experiencing symptoms representative of a seizure, for example chewing lips, random hand movements etc, indicative of a temporal lobe epilepsy seizure event. In some examples, the cerebral apparatus may receive the patient activity data from a patient sensor. The patient sensor may communicate wirelessly with the cerebral apparatus or via an intervening computing device such as a smartphone or PC. The patient sensor may comprise an accelerometer and / or may comprise a smart device such as a smart watch. The patient sensor may monitor the patient activity and provide associated patient activity data indicating exercise, sleep, dream state, seizure etc. In some examples, receiving the patient activity data may comprise receiving EEG data and inferring the patient activity data based on the EEG data. A third step 588 comprises associating the received monitoring signals with the received patient activity data. In this way, the monitoring signals can be categorised (or labelled) according to patient activity. In some examples, the monitoring signals can be characterised as normal (interictal) signals and seizure (ictal) signals based on whether the patient activity data indicates an ictal or interictal state. The seizure signals may be further characterised as pre-ictal, ictal and post-ictal using the patient activity data. The monitoring signals (both ictal and interictal) may be further categorised as sleep signals and awake signals using the patient activity data. The sleep signals may be further characterised depending on dream state e.g. REM, non-REM using the patient activity data. The characterised monitoring signals may be stored in the data storage of the cerebral device or exported to an external computing device for analysis. A fourth step 590 comprises mapping cerebral network signals for different brain states. In some examples, the method may comprise mapping cerebral network signals for ictal monitoring signals indicative of an ictal brain state and mapping cerebral network signals for interictal monitoring signals indicative of an interictal (normal) brain state. In other examples, the method may comprise mapping cerebral network signals for other brain states such as REM sleep, nREM sleep etc. Mapping cerebral network signals may comprise identifying correlations between two or more received monitoring signals from the cerebral apparatus. In a first set of examples, identifying correlations between the two or more monitoring signals may comprise identifying a correlation between: a first signal from a first cerebral structure (electrode wire / electrode contact point) during a first time period corresponding to a first brain state; and a second signal from the first cerebral structure during a second time period corresponding to the first brain state. In other words, correlations are identified between signals corresponding to the same brain state recorded at different times at the same cerebral structure I nuclei target. The correlation may correspond to a signature frequency (e.g. a peak frequency of the frequency spectrum) and / or a signature amplitude (e.g. an amplitude greater than or less than an amplitude threshold). Similar correlations may be identified for a plurality of monitoring signals from the same cerebral structure at a plurality of time periods corresponding to the same brain state. Similar correlations may be identified for a plurality of different cerebral structures and for a plurality of different brain states. Table 2 illustrates example correlations for different brain states and different cerebral structures. In this example, for an REM brain state, the method has identified three different signature frequencies f2, f2, f3 at the respective structures: corpus callosum, caudate nucleus and thalamus. The amplitude value of 1 indicates that the amplitude of the respective signal or frequency peak is above an amplitude threshold. For a seizure brain state, the method has identified that the corpus callosum and thalamus have the same signature frequency, f4, and that there is reduced activity at the caudate nucleaus as indicated by the amplitude value of 0 indicating the amplitude of the respective signal or frequency peak is less than an amplitude threshold. The caudate nucleus is part of the basal ganglia which are thought to play a role in gatekeeping thalamocortical communication and reduced or altered activity may be associated with temporal lobe epilepsy. Brain State Monitored Cerebral Structure Signature Frequency (GHz) Amplitude (a.u.) REM sleep Corpus callosum fl 1 Caudate nucleus f2 1 Thalamus f3 1 Seizure (Ictal) Corpus callosum f4 1 Caudate nucleus - 0 Thalamus f4 1 In a second set of examples, identifying correlations between the two or more monitoring signals may comprise identifying a correlation between: a first signal from a first cerebral structure (electrode wire / electrode contact point) during a first time period corresponding to a first brain state; and a second signal from a second cerebral structure during the first time period corresponding to the first brain state. In other words, correlations are identified between signals corresponding to the same brain state recorded at the same time at different cerebral structure / nuclei target. In the example of table 2, a correlation has been identified between monitoring signals from the corpus callosum and thalamus having the same signature peak frequency. For such cotemporaneous signals, other correlations may be identified such as a fixed phase relationship or any other indication of correlation or synchronisation between the signals. For example, the two or more monitoring signals may comprise oscillatory signals with a frequency and / or phase relationship. For example, the two or more monitoring signals may have the same frequency and a fixed phase relationship. For the second set of examples, mapping the cerebral network signals may provide a connectivity map comprising a plurality (connectivity network) of cerebral structures / nuclei targets from which correlated signals are received. For the second set of examples, similar correlations may be identified for a plurality of monitoring signals from the connected cerebral structures at a plurality of time periods corresponding to the same brain state. Similar correlations may be identified for a plurality of different cerebral structures and for a plurality of different brain states. The second set of examples may be referred to as brain connectivity analysis which can represent epilepsy as a complex electrical network with a definable seizure connectivity network map (or activity map) linking distant hot spots within the brain's cortex and deeper structures in space, frequency and time. Different brain states may comprise correlations of both the first set of examples and the second set of examples. For example, a particular brain state may comprise: a temporal correlation wherein a particular cerebral structure has a signature frequency associated with that brain state at different times; and a spatial correlation wherein a plurality of cerebral structures have a frequency and / or phase relationship associated with that brain state. The fourth step 590 of mapping cerebral network signals for different brain states may comprise generating a cerebral network map for each brain state. The cerebral network map may comprise one or more of: a connectivity map representing a plurality (connectivity network) of cerebral structures that have correlated signals during the brain state; one or more cerebral structures having one or more signature signal parameters associated with the brain state; and the one or more signature signal parameters. Table 2 is an example of a cerebral network map. The resulting plurality of cerebral network maps, may be stored in data storage as a cerebral map register. In some examples, the fourth step may be performed by the processor of the cerebral apparatus. In some examples, at least a portion of the fourth step such as identifying the correlations, may be performed by a remote signal processor with the resulting cerebral network maps transferred back to the cerebral apparatus for storage as the cerebral map register. Figure 5 is described in relation to characterising seizure and non-seizure brain states suitable for epilepsy characterisation. For other non-epilepsy application examples, the method may be performed with an appropriate substitute brain state. For example, for Parkinsons characterisation, the ictal, interictal states may be replaced with tremor and non-tremor states or different levels or locations of tremor severity. Figure 6 illustrates a method of monitoring a patient using the cerebral apparatus according to an embodiment of the present disclosure. A first step 684 comprises receiving monitoring signals from the electrode bundle. A second step 692 comprises comparing the received monitoring signals against the cerebral map register. A third step 694 comprises identifying a brain state of the patient by matching the received monitoring signal to a corresponding cerebral network map of the cerebral map register. Matching the monitoring signal may comprise matching one or more signatures of the received signal with one or more corresponding signatures of the cerebral network map. Following the third step 694, the method may comprise outputting the brain state of the patient. Outputting the brain state of the patient may comprise outputting a seizure alert signal of the patient if the brain state is representative of a seizure. Outputting the seizure alert signal may comprise one or more of: outputting the seizure alert signal to the user interface; outputting the seizure alert signal to the chemical control circuit; and outputting the seizure alert signal to the signal generator to generate a remedial DBS signal. Deep Brain Stimulation In some examples, the disclosed cerebral apparatus may be used to provide DBS to a patient's brain. The apparatus may provide DBS to treat or control a movement related disorder including, Parkinson's Disease, Essential Tremor or Epilepsy. The processor may transmit a stimulation signal (a DBS signal) to the electrode bundle to stimulate one or more of the cerebral structures adjacent to the cerebral ventricular pathway. In some examples, the cerebral apparatus may be configured to provide DBS on a continuous basis. In other words, the cerebral apparatus may provide a baseline DBS signal. In addition, or alternatively, the cerebral apparatus may provide a responsive DBS signal in response to receiving an indication of a patient's brain state. For example, if the patient brain state is representative of seizure onset, the cerebral apparatus may provide the responsive DBS signal. In some examples, providing the responsive DBS signal may comprise altering or enhancing the baseline DBS signal, for example, by increasing the amplitude of the baseline signal and / or increasing the number of excited cerebral structures. Figure 7 illustrates a method of providing deep brain stimulation using the cerebral apparatus according to an embodiment of the present disclosure. A first optional step 796 comprises receiving a representation of the brain state of the patient. In some examples, the cerebral apparatus may obtain the patient brain state by performing the method of Figure 6. In other examples, the cerebral apparatus may receive the patient brain state based on user input at the user interface. For example, the patient or a clinician may interact with the user interface to indicate that the patient is experiencing a seizure or severe tremor. In other examples, the cerebral apparatus may receive the patient brain state from a separate brain monitoring apparatus such as an EEG system. A second step 798 comprises outputting a DBS signal. In some examples, the second step 798 may comprise outputting a baseline DBS signal on a continuous basis. The DBS signal may comprise any of the forms described below. The DBS signal may be selected, programmed, uploaded etc by a clinician using the user interface. In some examples, the second step 798 may comprise outputting the DBS signal in response to the patient brain state received at the first step. For an epilepsy example, the cerebral apparatus may output the DBS signal in response to the patient brain state being representative of a seizure state or seizure onset (or severe tremor for the example of Parkinsons disease). The cerebral apparatus may output the DBS signal as one or more sub-signals to a respective electrode wire of the electrode bundle to stimulate a respective one or more cerebral structures. A third optional step 799 comprises receiving updated monitoring signals from one or more cerebral structures and identifying a brain state based on the updated monitoring signals. If the updated monitoring signals are indicative of a safe (non-ictal, nontremor) brain state, the cerebral apparatus may continue or stop the DBS signal. If the updated monitoring signals are still indicative of a seizure state or tremor state, the cerebral apparatus may continue or enhance the DBS signal. DBS Signal Providing the DBS signal may comprise providing the stimulation signal to one or more of the cerebral structures. In other words, the DBS signal may comprise one or more sub-signals for providing to a respective electrode wire I electrode contact point I cerebral structure. Each sub-signal may have respective sub-signal parameters. The DBS signal may comprise one or more of the following signal functions (which are not mutually exclusive): i. a signal for stimulating a remedial brain state; ii. a signal for neural entrainment; and ill. a signal for stimulating a resonance frequency of a cerebral structure or a connectivity network of cerebral structures. In some examples, the cerebral apparatus may be configured to provide a DBS signal to stimulate a remedial brain state. For example, for movement disorders, such as Parkinson's disease, the DBS signal may stimulate a brain state associated with reduced tremor. For seizure related conditions, the DBS signal may be configured to stimulate an interictal brain state. REM sleep's antiepileptic properties - Most epileptiform discharges occur in sleep. A large proportion of generalised seizures occur in sleep, further SUDEP is associated with sleep; sleep duration, sleep deprivation and the sleep-wake cycle are thought to play an important role in seizure onset. There are two main states of deep sleep. Nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. NREM sleep is a low energy, restorative where the body operates at a lower physiological baseline and global cerebral activity transition from the desynchronised fast EEG patterns of wakefulness to slower synchronous frequency delta waves. In contrast, REM sleep is the state where dreams occur, it encompasses a more active physiological state, and given disengagement of the prefrontal cortex, responsible for higher level executive organisation, REM sleep is a globally chaotic neurophysiological state characterised by desynchronized theta EEG activity. Of note, REM sleep demonstrates more desynchronisation than wakefulness, likely due to disengagement of the prefrontal cortex, which is suggested to explain why dreams are often subjectively experienced as highly abstract. There is a relationship between sleep state and ictogenesis in epilepsy. Compared to NREM sleep, REM sleep can have a strong antiepileptic effect against focal interictal discharges, focal seizures, and generalized seizures. Further, REM sleep has an additional neuroprotective effect compared to wakefulness against both simple and complex seizures. The hypothesised reason for this is REM sleeps hyperdesynchronisation EEG pattern, which is suspected to prevent focal aberrant depolarization achieving summation or propagation. Of note, this mechanism is the antithesis of the hypersynchronous neuronal activity thought to trigger ictogenesis, described above. The wider significance of this neuroprotective property of certain sleep stages, is the observation that there are many neurological diseases such as epilepsy, trigeminal neuralgia, and many movement disorders where patients largely deny experiencing symptoms during sleep. Therefore, in some examples, the cerebral apparatus may be configured to provide a DBS signal to stimulate a remedial brain state comprising REM sleep. The cerebral apparatus may generate a DBS signal for stimulating REM sleep based on a corresponding cerebral map in a cerebral register. As described here, stimulating a brain state comprising REM sleep does not necessarily mean inducing REM sleep in the patient and may simply relate to stimulating electrical signals that are representative of REM sleep. If the patient is awake, the patient may remain awake. If the patient is asleep in a nREM sleep state, the stimulation may result in the patient entering REM sleep. More generally, the cerebral apparatus may be configured to provide a DBS signal to stimulate (electrical activity associated with) any remedial brain state by generating a corresponding DBS signal based on the corresponding cerebral map in the cerebral register. For example: the DBS signal may stimulate a connectivity network of a plurality of cerebral structures indicated by the cerebral map by providing a corresponding sub-signal to each of the cerebral structures in the connectivity network; and / or the DBS signal may stimulate one or more cerebral structures with a respective sub-signal having one or more corresponding signature signal parameters (frequency, amplitude etc) indicated by the cerebral map. In some examples, the cerebral apparatus may generate the cerebral register as described above. In other examples, the cerebral apparatus may receive a cerebral register that has been generated by a separate apparatus (e.g. based on an EEG). In some examples, the cerebral apparatus may be configured to provide the DBS signal to provide neural entrainment at one or more cerebral structures. Neural entrainment is a phenomenon where neural electrical signals (brainwaves) naturally synchronize to a periodic external stimulus. For example, if the DBS signal comprises a sub-signal comprising a periodic pulse at a frequency, fl, the respective stimulated cerebral structure can synchronise to the DBS signal and produce an electrical signal at the same frequency, fl, at a harmonic frequency, nfl, or at a sub-harmonic frequency, fl / n, where n is an integer. In some examples, the cerebral apparatus may provide the DBS signal to provide neural entrainment to stimulate a remedial brain state (as described above). In some examples, the cerebral apparatus may provide the DBS signal to disrupt a disease brain state such as an ictal brain state or a tremor brain state. For example, if a seizure state comprises a high level of synchronicity with a signature frequency across a seizure connectivity network, the cerebral apparatus may provide the DBS signal to stimulate one or more cerebral structures of the seizure connectivity network at a different frequency to disrupt the seizure connectivity network. For example, the cerebral apparatus may provide the DBS signal to stimulate the caudate nucleus to alter, disrupt or repair thalamocortical communication in the seizure connectivity network. In some examples, the cerebral apparatus may be configured to provide a DBS signal to provide neural entrainment at a resonant frequency of a cerebral structure or at a resonant frequency of a connectivity network (circuit) of cerebral structures. In other words, the cerebral apparatus can apply a signal at the resonance frequency or at a harmonic or subharmonic of the target's resonant frequency, to generate a pronounced response in the target. Here the target may refer to a specific cerebral structure or a connected network of cerebral structures indicative of a particular brain state. In some examples, the cerebral apparatus may provide the DBS signal to provide neural entrainment at a resonant frequency to stimulate a remedial brain state (as described above). In some examples, the cerebral apparatus may provide the DSB signal to disrupt a disease brain state such as an ictal brain state or a tremor brain state. For example, if a seizure state comprises a high level of synchronicity with a signature frequency across a seizure connectivity network, the cerebral apparatus may provide the DBS signal to stimulate one or more cerebral structures of the seizure connectivity network at the resonance frequency to disrupt the seizure connectivity network. For example, the cerebral apparatus may provide the DBS signal to stimulate the caudate nucleus at its resonant frequency to alter, disrupt or repair thalamocortical communication in the seizure connectivity network. In some examples, the cerebral apparatus may determine the resonant frequency of the cerebral structure or connectivity network by: tuning the stimulation frequency over a frequency range, measuring the associated frequency response using one or more monitoring signals from the electrode bundle and determining the resonance frequency as the stimulation frequency which stimulated the highest magnitude peak frequency. The cerebral apparatus can provide the DBS signal as a plurality of sub-signals to a respective plurality of electrode contacts to selectively communicate with deep brain targets using by generating a signal that is a subharmonic of the target neural circuits resonant frequency, thus selectively evoking exaggerated neural activity. The disclosed cerebral apparatus can manage epilepsy network dysfunction through personalised epilepsy network alteration with resonance based neural modulation, and optionally intraventricular injection of neuro inhibitory substances to terminate life threatening generalised continuous seizures. Throughout the present specification, the descriptors relating to relative orientation and position, such as "horizontal", "vertical", "top", "bottom" and "side", are used in the sense of the orientation of the cerebral apparatus as presented in the drawings. However, such descriptors are not intended to be in any way limiting to an intended use of the described or claimed invention. 5 It will be appreciated that any reference to "close to", "before", "shortly before", "after" "shortly after", "higher than", or "lower than", etc, can refer to the parameter in question being less than or greater than a threshold value, or between two threshold values, depending upon the context.

Claims

1. A cerebral apparatus comprising:a housing;a processor positioned in the housing; andan electrode bundle coupled to the processor and suitable for insertion into a ventricular pathway of a patient, wherein the electrode bundle is configured to, in response to insertion into the cerebral ventricular pathway:expand to at least partially contact a wall of at least one cerebral ventricle of the cerebral ventricular pathway; andcommunicate an electrical signal between the processor and one or more cerebral structures adjacent to the cerebral ventricular pathway.

2. The cerebral apparatus of claim 1, wherein the electrode bundle is configured to receive a stimulation signal from the processor and stimulate one or more cerebral structures adjacent to the cerebral ventricle pathway.

3. The cerebral apparatus of claim 1 or claim 2, wherein the electrode bundle is configured to sense a neurophysiological signal in the one or more cerebral structures and transmit the neurophysiological signal to the processor.

4. The cerebral apparatus of any preceding claim, wherein the electrode bundle comprises:a compressed state for compressing the electrode bundle into a surgical catheter for insertion into the ventricular pathway; andan expanded state for contacting the wall of the at least one ventricle.

5. The cerebral apparatus of any preceding claim, wherein the electrode bundle comprises a resilient structure.

6. The cerebral apparatus of claim 5, wherein the electrode bundle comprises a sheath and the sheath provides the resilient structure.

7. The cerebral apparatus of any preceding claim, wherein the electrode bundle comprises a branching structure with a plurality of electrode strands, wherein each electrode strand is configured to address a respective one of the one or more cerebral structures.

8. The cerebral apparatus of any preceding claim, wherein the electrode bundle comprises a plurality of electrode wires, wherein each electrode wire has a different length and terminates with an electrode contact point.

9. The cerebral apparatus of claim 8, wherein the plurality of electrode wires are held together by a sheath and the electrode contact points are on an external surface of the sheath.

10. The cerebral apparatus of any preceding claim, wherein the cerebral apparatus comprises a chemical injector system and wherein the processor is configured to: receive a monitoring signal from the electrode bundle;determine if the monitoring signal is representative of a life-threatening seizure; andcontrol the chemical injector system to inject neuro inhibitory chemicals into the ventricular pathway of the patient if the monitoring signal is representative of a life-threatening seizure.

11. The cerebral apparatus of any preceding claim, wherein the processor is configured to:receive one or more monitoring signals from the electrode bundle;compare the one or more monitoring signals to a cerebral map register comprising a plurality of cerebral maps each representative of electrical signals associated with a respective brain state of the patient; andidentify a patient brain state of the patient by matching the one or more monitoring signals to a corresponding cerebral network map of the cerebral map register.

12. The cerebral apparatus of claim 11, wherein the processor is configured to: receive a plurality of monitoring signals;receive a plurality of patient activity data cotemporaneous with the monitoring signals;associate each monitoring signal with a patient brain state as identified by the patient activity data; anddefine a cerebral network map for each patient brain state.

13. The cerebral apparatus of claim 12, wherein the processor is configured to define each cerebral map by identifying one or more correlations between two or more monitoring signals associated with the respective patient brain state.

14. The cerebral apparatus of claim 13, wherein the processor is configured to identify the one or more correlations by:identifying a correlation between:a first monitoring signal from a first cerebral structure during a first time period corresponding to a first brain state;and a second monitoring signal from the first cerebral structure during a second time period corresponding to the first brain state; and / or identifying a correlation betweena first monitoring signal from a first cerebral structure during a first time period corresponding to a first brain state; anda second monitoring signal from a second cerebral structure during the first time period corresponding to the first brain state.

15. The cerebral apparatus of claim 12 or claim 13, wherein the cerebral apparatus is configured to identify the one or more correlations by identifying one or more signature signal parameters associated with the two or more monitoring signals.

16. The cerebral apparatus of any of claims 11 to 15, wherein the processor is configured to provide a stimulation signal based on the patient brain state.

17. The cerebral apparatus of any of claims 1 to 10, wherein the processor is configured to:receive a patient brain state from a monitoring device; and provide a stimulation signal based on the patient brain state.

18. The cerebral apparatus of any preceding claim, wherein the processor is configured to provide a stimulation signal as one or more stimulation sub-signals to a respective one or more wires of the electrode bundle to excite a respective one or more of the cerebral structures.

19. The cerebral apparatus of any of claims 16 to 18, wherein the cerebral apparatus is configured to provide the stimulation signal to stimulate a remedial brain state of the patient.

20. The cerebral apparatus of claim 19, wherein the remedial brain state comprises a rapid-eye-movement sleep state.

21. The cerebral apparatus of any of claims 16 to 20, wherein the cerebral apparatus is configured to provide the stimulation signal to disrupt a brain state representative of a neurological disorder state.5 22. The cerebral apparatus of claim 21, wherein the neurological disorder state is aseizure state.

23. The cerebral apparatus of any of claims 16 to 22, wherein the cerebral apparatus is configured to provide the DBS signal to provide neural entrainment at one 10 or more of the one or more cerebral structures.

24. The cerebral apparatus of claim 23, wherein the cerebral apparatus is configured to provide the DBS signal at a resonance frequency of the one or more cerebral structures.1537

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