EP4669416A1

EP4669416A1 - Intracranial Neural Electrical Stimulation System Based on Interictal Epileptic Activity for the Treatment of Epileptic Seizures

Info

Publication number: EP4669416A1
Application number: EP23797659.2A
Authority: EP
Inventors: Vasileios KOKKINOS; Athanasios KAKAROUNTAS
Original assignee: Individual
Current assignee: Individual
Priority date: 2023-02-20
Filing date: 2023-09-07
Publication date: 2025-12-31
Also published as: WO2024175218A1; AU2023432245A1; CN120957782A; GR1010550B

Abstract

An intracranial neuronal electrical stimulation system for the treatment of epilepsy and other brain disorders involving seizures is provided, that applies intracranial neuronal electrical stimulation to interictal epileptic activity in an individualized manner, immediately upon detection of each interictal epileptic pattern, and in which stimulation is activated via intracranial electroencephalographic (EEG) detection. Said intracranial stimulation of interictal epileptic activity acts over time, disrupting the process of epileptic network establishment, reducing the potential of neuronal hypersynchronization, bringing about improvements in seizure control. The present invention further includes the utilization of neuromodulation biomarkers, the use of which dynamically optimizes detection capabilities and provides a more accurate overview of the patient's therapeutic course. Finally, the present implementation exploits the detection of ictal intracranial EEG patterns, as well as patterns of high-risk conditions (such as status epilepticus, and sudden unexpected death in epilepsy), in order to provide immediate notification to the patient/caregivers so that timely measures can be taken for the patient's safety.

Description

INTRACRANIAL NEURONAL ELECTRICAL STIMULATION SYSTEM BASED ON INTERICTAL EPILEPTIC ACTIVITY FOR THE TREATMENT OF EPILEPTIC SEIZURES

TECHNICAL FIELD

The present invention is directed to an intracranial neuronal electrical stimulation system for the treatment of epilepsy and other brain disorders involving seizures.

PRIOR ART

Epilepsy is a devastating brain disorder that affects nearly 50 million people worldwide. Epilepsy is the 4th most common neurological disorder and is manifested by epileptic seizures. Epilepsy is defined as a "sudden, excessive, and rapid discharge" of neuronal populations in the brain that can be detected by the electroencephalogram (EEG). Seizures have significant and often devastating consequences for the patients' quality of life, excluding them from common activities (such as driving, swimming, etc.), affecting their personal life and family planning, as well as stigmatizing them socially and professionally. In addition, poorly controlled seizures can cause harmful conditions of varying severity, ranging from prolonged seizures leading to the condition known as status epilepticus to seizures followed by severe cardiorespiratory arrest, either during or after their end, which are responsible for "sudden, unexpected death in epilepsy - SUDEP".

Today, two main therapeutic pathways are widely available: antiepileptic drugs and epilepsy surgery. The treatment of epilepsy with antiepileptic drugs achieves seizurefreedom in 70% of patients. Nevertheless, the side effects of antiepileptic drugs can have significant consequences on the patients' quality of life, resulting in failure of the therapeutic goals in 40% of patients. Epilepsy surgery is an established treatment option for drug-resistant patients. The main goal of epilepsy surgery is to completely resect (or completely disconnect) areas of the brain responsible for the primary organization of epileptic activity that gives rise to seizures. Nevertheless, it is estimated that only 50% of patients with drug-resistant epilepsy become candidates for epilepsy surgery. For those patients who are "refractory" to both antiepileptic therapy and epilepsy surgery, intracranial neuronal electrical stimulation (or neurostimulation) is offered as a palliative treatment to improve seizure control. Over the past few decades, the US Food and Drug Administration (FDA) has approved neurostimulation devices to address the treatment failures of antiepileptic drugs, as well as failures to enroll patients in a surgical plan. Open-loop neuronal electrical stimulation systems (i.e., systems that do not have feedback capability), such as the vagus nerve stimulator (VNS) and deep brain stimulation (DBS) were designed to deliver periodic and diffuse electrical stimulation to the epileptic brain in order to inhibit the generation of unknown origin epileptic activity. Clinical studies of these devices have shown highly variable efficacy, with 25% to 75% of patients reporting a 50% reduction in seizures postoperatively, with only 5% achieving seizure-freedom. However, data emerged that seizure control could be improved by up to 50% when patients' guardians/caregivers externally used a supplied neurostimulator magnetic activation system when they perceived that the patient was about to have a seizure or when the seizure had already started, in order to activate the open-loop implantable neurostimulator. These data suggest that a closed- loop neurostimulation system may have higher efficacy.

The only FDA-approved closed-loop intracranial neurostimulation system for the brain is the Response Neurostimulator (RNS), and it consists of a four-channel programmable processing unit that can both record and electrically stimulate the human brain. This device is surgically placed in the skull by means of craniotomy and the electrodes are implanted inside the brain, in the epileptogenic areas, as the latter have been determined in the context of the pre-operative evaluation process to which each patient undergoes in specialized epilepsy centers. The efficacy of RNS in reducing seizures has been demonstrated in multicenter clinical studies, where an average of 70% of patients with focal seizures experienced a significant reduction in seizure frequency. Up to 30% of patients had a 6- month seizure-free period postoperatively, and nearly 15% remained seizure-free for more than a year.

The current methodology for treating epileptic seizures with closed-loop intracranial neuronal electrical stimulation is based on the detection of the neurophysiological markers that indicate the onset of an epileptic seizure and the immediate application of the programmed electrical stimulation in such a way as to immediately and instantaneously terminate the ongoing seizure event, such as this is recorded in the intracranial EEG (US Pat No. 6,016,449; WO 2004/043536 Al). The main hypothesis regarding the mechanism of action of RNS is the immediate and instantaneous termination of ongoing seizure activity using intracranial neuronal electrical stimulation. Although examples of this mechanism of action have occasionally been sporadically presented in the published literature, no systematic studies of the chronic effect of closed-loop intracranial neuronal electrical stimulation on the brain have been performed. Conversely, there is evidence that when changes in the neurophysiological properties of intracranially recorded seizures are detected, patients report improvements in seizure control, such as reduced seizure frequency, as well as reduced seizure intensity and/or duration. These neurophysiological changes are summed up in the rough term "neuromodulation". As the main claim and proposed mechanism of action of the RNS neurostimulation system is the immediate and instantaneous termination of seizure activity, the occurrence of such neurophysiological phenomena appears to be a side-effect of its action. There is thus a need to provoke the emergence of neuromodulation with sufficient specificity, using closed-loop intracranial neuronal electrical stimulation techniques. To this end it is advantageous to design a closed-loop intracranial neuronal electrical stimulation system that acts over time, progressively altering and weakening the underlying epileptic network, rendering it incapable of producing hypersynchronized activity and generating paroxysmal discharges. Also, it is desirable to reliably and quantifiably detect the occurrence of neuromodulation generated by intracranial neuronal electrical stimulation.

SUMMARY OF THE INVENTION

According to the present invention, a system of intracranial neuronal electrical stimulation targeting the interictal epileptic activity according to claim 1 is provided.

According to the present invention, a system of intracranial neuronal electrical stimulation of interictal epileptic activity for the treatment of brain disorders involving seizures is provided, said system comprising an implantable device (35) which comprises a central intracranial stimulation unit (22) connected via a physical intracranial interface unit (27) to at least two intracranially implantable electrodes of at least two contacts (25) each. The electrodes are surgically implantable within the brain parenchyma (24) of the patient (23). The central intracranial stimulation unit (22) is designed to record the intracranial electroencephalogram (EEG), detect patterns of interictal epileptic activity (4), and provide immediate (such as in less than 1 second) and individualized intracranial neuronal electrical stimulation (5) upon detection of said interictal patterns.

The present invention provides an intracranial neuromodulation system for the treatment of epilepsy and other brain disorders involving seizures, such as developmental brain malformations, brain tumors, brain arteriovenous malformations, strokes, brain injuries, and others. The proposed system uses the intracranial EEG signal to apply intracranial neuronal electrical stimulation to the interictal, rather than the ictal, seizure activity. The said activation of electrical stimulation through the continuous recording of the intracranial EEG and the continuous detection of interictal epileptic discharges, constitutes the first and therapeutic closed-loop of the present invention. Although the disclosed embodiment lends itself primarily to the treatment of seizures, it is nevertheless also possible to respond to other types of neurological disorders, such as movement disorders (e.g., Parkinson's disease) and chronic pain, as well as neuropsychiatric disorders such as bipolar disorder, depression, eating disorders, and obsessive compulsive disorder.

In a preferred embodiment, the system disclosed herein further includes a diagnostic/prognostic loop via novel neuromodulation biomarkers, which on the one hand adapts computational intelligence (CI) detection algorithms to the dynamic data of epileptic intracranial EEG seizures, and on the other hand provides the supervising neurologist a reliable and quantified measure to assess the patient's condition in the context of the neurostimulation treatment. Specifically, the present invention utilizes a set of four neurophysiological biomarkers that can reliably and quantifiably detect both the existence and quality of neuromodulation in the underlying epileptiform networks of the human brain as a result of chronic intracranial neuronal electrical stimulation, as well as contribute to the adaptation of the intracranial neuronal electrical stimulation parameters to the neuromodulation data. The advantage of this integration is that, through the primary diagnostic/prognostic loop, a series of neuromodulation biomarkers are utilized, which inform the intracranial ictal EEG pattern detection methodology for the existence and quality of neuromodulation in the underlying epileptic networks. Thus, the presence, combination, or absence of these biomarkers is an alternative method of assessing the efficacy of intracranial neuronal electrical stimulation, for which the only current "biomarker" of efficacy based on the RNS system claims is the immediate and instantaneous termination of epileptic events. This provides a truly personalized treatment for each patient, as each CI algorithm integrated into the implantable device is trained exclusively on the data of each patient.

In another preferred embodiment, the system disclosed herein includes an additional safety loop by utilizing the detection of intracranial ictal EEG patterns, and also the detection of high-risk patterns for status epilepticus and SUDEP, which aims to protect the bodily integrity of the patient and minimize the risks faced by the patient during the manifestation of an epileptic seizure. The advantage of this integration is that, with the additional novel safety loop, the detection of intracranial ictal EEG patterns is utilized to provide immediate notification to the patient and/or authorized guardians/caregivers to take timely measures for their safety and bodily integrity.

Finally, the present invention regards a method of intracranial neuronal electrical stimulation which, based on the above original ideas, disrupts the process of establishment of epileptic networks, reduces the possibility of neuronal hypersynchronization and brings about positive/beneficial neuromodulation in the intracranial EEG of epileptic seizures. This novel technique applies intracranial neuronal electrical stimulation to interictal, rather than ictal, epileptic activity. This technique does not produce effects of an acute nature, as proposed by the RNS technique of immediate and instantaneous termination of epileptic seizures, but acts over time, progressively altering and weakening the underlying epileptic network, rendering it incapable of producing hypersynchronized activity and creating paroxysmal discharges.

Further features and advantages of the present invention, as well as the structure and operation of various embodiments of the present invention, are described in detail below with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will now be described with reference to certain embodiments thereof illustrated in the accompanying drawings. It should be noted that the attached drawings illustrate preferred embodiments of the invention, therefore they should not be considered as limiting the scope of the invention. It is also understood that the illustrations may include optional features which are not necessary in any embodiment.

Figure 1 schematically illustrates an installed epileptogenic network.

Figure 2 shows the expected application of intracranial neuronal electrical stimulation on the ability of the network to generate seizure activity.

Figure 3 schematically illustrates the expected effect of the present intracranial neuronal electrical stimulation technique on epileptic interictal and ictal discharges. (A) The intracranial EEG pattern of an epileptic seizure before the application of the proposed intracranial neuronal electrical stimulation technique. (B) The application of the proposed intracranial neuronal electrical stimulation (shown as striped boxes) targeting individual interictal spikes at the moment of their emergence. (C) The expected intracranial EEG pattern of an epileptic seizure after the application of the proposed intracranial neuronal electrical stimulation technique.

Figure 4 schematically illustrates an embodiment of the implantable device.

Figure 5 schematically shows the two preferred ways of implanting the device. (A) Placement on the cranial bone using standard cranioscrews, without craniotomy. (B) Subcutaneous, subclavian placement in the upper sternum.

Figure 6 schematically shows the electrical stimulation subunit (30) and the digital intracranial interface unit (28).

Figure 7 illustrates the computational intelligence unit (32).

Figure 8 summarizes an embodiment of the intracranial neuronal electrical stimulation system of interictal epileptic activity, which is activated each time interictal activity is detected on intracranial EEG.

Figure 9 is a schematic illustration of the external EEG neuromodulation assessment computational system (108) and its interactions with the external CI learning and parameterization computing system (109) and the external monitoring device (62).

Figure 10 schematically shows the charging process of the external monitoring device (62) and the implantable device (35) placed on the cranial bone (A) and subcutaneously on the sternum (B).

Figure 11 is a schematic illustration of the external contactless battery charging device (91).

Figure 12 shows the battery contactless charging subunit (33) connected to the battery (61) of the implantable device (35).

Figure 13 is a schematic representation of the contactless battery charging unit (64) connected to the battery (83) of the external monitoring device (62). Figure 14 illustrates the external immediate notification device (104) which is wirelessly connected to the external monitoring device (62).

Figure 15 schematically shows the external monitoring device (62).

Figure 16 is a schematic representation of the physical intracranial interface unit (27) and the biosignal recording subunit (29).

Figure 17 illustrates the bi-directional wireless intercom subunit (31).

Figure 18 is a schematic representation of the bi-directional wireless intercom subunit (63).

Figure 19 shows the external interface subunit (66).

Figure 20 schematically illustrates the biometric identification subunit (67).

Figure 21 presents novel neurophysiological biomarkers for detecting neuromodulation in epileptic networks as a result of chronic intracranial neuronal electrical stimulation. (A) Neuronal Oscillation Frequency Shift (NOFS) index in the ictal intracranial EEG. (B) Neuronal Oscillation Amplitude Shift (NOAS) index. (C) Neural Oscillation Density Shift (NODS) index. (D) Neuronal Oscillation Temporal Sustainability Shift (NOTSS) Index.

DETAILED DESCRIPTION OF THE INVENTION

The invention is described below, with reference to detailed illustrative embodiments. It will be apparent that a system according to the invention can be embodied in a wide variety of forms. Accordingly, the specific structural and functional details disclosed herein are representative and do not limit the scope of the invention.

Terms not specifically defined herein should be given the meaning that would be given to them by one skilled in the art in light of the present disclosure and the general context.

As used herein, the term “neuromodulation” refers to the change of neurophysiological characteristics of ictal EEG discharges as a result of electrical stimulation.

The term "interictal activity" refers to abnormal electrical brain activity that occurs during the intervals between seizures. As used herein, the terms “interictal patterns” or “patterns of interictal epileptic activity” are used interchangeably to refer to the variability in morphology and spatial distribution of the interictal epileptic activity, as it presents on continuous intracranial EEG.

The term "post-ictal activity" refers to abnormal electrical brain activity that occurs in the immediate interval after the end of an epileptic seizure.

The term “computational Intelligence” refers to the analysis and design of models for learning and/or generalization based on numerical data and includes, but is not limited to, machine learning, decision support, data mining, neural networks, fuzzy systems, intelligent systems, expert systems and evolutionary computation or a combination thereof.

As used herein, the terms "therapeutic" and "treatment" refer to the elimination, reduction, suppression, inhibition of the progression, severity and/or extent of a disease, lesion, clinical sign or symptom in a subject. Said terms also refer to the alleviation, in whole or in part, of the clinical signs and symptoms associated with a disorder or disease such as, for example, epilepsy.

The present invention takes into account the already well established fact that epilepsy is a disorder of brain networks. It is also well established that distinct brain regions are anatomically and functionally interconnected in order to exchange information synaptically and enhance neuronal performance. It is also well established that epileptogenic areas interfere electrochemically and use normal neuronal pathways through the brain in order to propagate the abnormal epileptiform activity they produce. Over time, a primary epileptogenic region creates epileptogenic networks by recruiting regions that are anatomically and functionally interconnected with it. These areas then become secondarily epileptogenic and over time, combined with poor seizure control, can in turn become primarily epileptogenic.

The present invention also takes into account the already well-documented fact that the potential for neuronal hypersynchronization is the main property of epileptiform networks to which they owe their epileptic dynamics. Neuronal synchrony is a physiological property of neuronal populations in the brain, and represents their ability to exchange information and organize themselves efficiently in order to carry out the brain functions they perform. However, when neuronal synchrony exceeds normal levels for a prolonged period of time (neuronal hypersynchrony), the electrochemical activity produced has the potential to generate a seizure. In turn, electrochemically mediated synaptic recruitment of secondary epileptogenic regions from the primary epileptogenic region is the key process of generating neuronal hypersynchrony which in turn causes seizures. This neuronal hypersynchronization is recorded by the intracranial EEG as a sequence of high-intensity discharges, usually of a sharp morphology, that repeat rhythmically or semi-rhythmically throughout the seizure.

The present invention is based on the original idea that the aforementioned recruitment of the secondary epileptogenic areas from the primary epileptogenic area takes place over time by means of brief paroxysmal discharges which are exchanged between said areas. These brief paroxysmal discharges are recorded on the EEG as interictal seizure activity. Although this is an extremely well-known form of epileptic activity, its role in epileptogenesis is unclear and controversial in the published literature. Examples of interictal epileptic activity include sharp waves, sharp-wave complexes, spikes, spike-wave complexes, polyspikes, polyspike-wave complexes, and fast paroxysmal activity. The idea that interictal activity is a neuronal recruitment vehicle for the establishment and expansion of epileptic networks, and consequently established neuronal hypersynchronization, is novel.

The present invention is based on the also novel idea that by targeting interictal epileptic activity with intracranial neuronal electrical stimulation in an individualized manner, immediately upon their manifestation (such as in less than 1 second), the neuronal recruitment process is disrupted and over time fails to establish an epileptogenic network. In the context used herein, “individualized” is the manner whereby the stimulation is adjusted according to the unique morphology and spatial distribution of each patient’s interictal activity. Figure 1 shows an established epileptogenic network, with a primary epileptogenic node (1) that is anatomically and functionally connected via bidirectional synapses (3) to distinct neuronal populations that have become secondarily epileptogenic (2) over time through exchange of interictal epileptic activity (4), here depicted as a spikewave complex, over bidirectional synaptic pathways (3). Each node of the epileptogenic network, primary (1) and secondary (2), is colored in one of four shades of gray, which represent the degree of established epileptogenesis, i.e. its ability to produce independent epileptogenic activity: A. The black color suggests that the neuronal population in question has the potential to generate abundant epileptogenic activity - this is the main property of the primary epileptogenic region (1). B. Dark gray color indicates that the neuronal population in question has the potential to produce frequent epileptic activity. C. Medium gray color indicates that the neuronal population in question has the potential to produce occasional epileptic activity. D. Light gray color indicates that the neuronal population in question has the potential to produce rare epileptic activity. Recruitment of the secondary epileptogenic nodes (2) by the primary epileptogenic node (1) is achieved through chronic bidirectional interictal interaction (4), making the former (2) producers of frequent epileptic activity. As proposed in the context of the present invention, neuronal electrical stimulation of interictal epileptic activity causes isolation of the primary epileptogenic node from the rest of the network, disrupts the connectivity of the existing network, and significantly reduces the network’s potential to generate neuronal hypersynchrony that would lead to the manifestation of paroxysmal epileptic discharges.

Figure 2 shows the expected effect of applying intracranial neuronal electrical stimulation (5) of interictal epileptic activity (4) in an individualized manner, immediately upon its manifestation, in terms of the ability of the network to generate seizure activity. Chronic intracranial neuronal electrical stimulation (5) targeting the interictal EEG activity in an individualized fashion (4) over time significantly reduces the influence of the primary epileptogenic node (1) on the secondary epileptogenic nodes (2). Consequently, the potential for epileptogenesis in the secondary nodes is reduced, from the level of generating frequent epileptic activity to the levels of occasional or rare manifestation. Thus, the overall epileptogenic potential of the described network is reduced, rendering any paroxysmal discharges eventually being generated either less frequent (reduced frequency paroxysmal discharges), less intense (reduced intensity paroxysmal discharges), or shorter in duration (reduced duration paroxysmal discharges). Furthermore, by depriving secondary epileptogenic areas of chronic primary epileptogenic influence, the likelihood of them generating independent activity in the future may be greatly reduced. The effects of these changes in the neurophysiological properties of the epileptic network, as a result of chronic intracranial neuronal electrical stimulation of interictal epileptic activity in an immediate and individualized manner, are identified on the intracranial EEG as a positive/beneficial neuromodulation phenomenon. The idea that intracranial neuronal electrical stimulation of interictal epileptic activity in an immediate and individualized manner causes the connectivity of epileptic networks in the brain to be degraded and is detected as positive/beneficial neuromodulation in intracranial EEG is novel.

Figure 3 shows the expected effect of the present intracranial neural electrical stimulation technique on paroxysmal discharges in three temporally distinct phases (phase 1: before application, phase 2: during application, phase 3: after application). In Figure 3 A, a sample intracranial EEG of a focal ictal epileptic discharge (6) is shown, as it evolves in time from left to right. During this first phase, in which the proposed technique of intracranial neuronal electrical stimulation has not yet been applied, the ictal epileptic discharge (6) is the result of the full manifestation of the underlying epileptogenic network. At the onset of seizure activity (left), the low-intensity normal EEG becomes more synchronized, generating progressively higher intensity synchronized spiking activity (middle). This activity develops into the main ictal activity where high-intensity and highly synchronized rhythmic spike discharges are generated (right). This ictal epileptic activity (6) is the target of the current technique of intracranial neuronal electrical stimulation in the existing closed-loop RNS neurostimulation system, which aims to acutely and instantaneously interrupt the activity during its development and terminate it immediately. In Figure 3B, a sample intracranial EEG (7) of interictal spiking epileptic activity (4) (marked with an asterisk * on top) is shown. The system disclosed herein is designed to apply the proposed intracranial neuronal electrical stimulation (shown as striped boxes in Figure 3B) to target individual interictal epileptic spikes (5) immediately after their detection (4), instead of targeting the fully developed epileptic ictal discharge (6). The expected effect of chronic intracranial neuronal electrical stimulation of interictal epileptic activity in an immediate and individualized manner upon detection of said interictal epileptic activity is shown in Figure 3C (8), where the epileptic discharge of Figure 3A (6) has undergone significant neurophysiological changes suggestive of neuromodulation. Specifically, the neuromodulated epileptic seizure (8) appears with reduced synchronized activity, with lower intensity waveforms and without high synchronization of rhythmic spike discharges. This epileptic ictal discharge, which was produced by an underlying epileptic network that has undergone neuromodulation due to chronic intracranial neuronal electrical stimulation of interictal activity, is of such a form as to suggest deconstruction of the epileptic network. This phenomenon is the main goal of the novel technique of intracranial neuronal electrical stimulation proposed here.

Thus, in a first overview of the present invention, an intracranial neuronal electrical stimulation system is provided which is based on the methodology of intracranial neuronal electrical stimulation of interictal epileptic activity in an immediate and individualized manner upon detection of said interictal epileptic activity. Figure 4 shows an embodiment of the intracranial neuronal electrical stimulation system of interictal epileptic activity, which is activated via continuous intracranial EEG detection. Said system includes an implantable device (35), which can be placed inside the patient's body (23) by a surgical procedure. Based on current neurosurgical techniques, implantation can be performed in two ways: a. Placement on the cranial bone (Figure 5A) using standard cranial screws, without craniotomy, b. Placement subcutaneously, subclavian to the upper part of the sternum (Figure 5B). With the surgical procedure of placing the implantable device inside the patient's body (either on the cranial bone or in the chest) the craniotomy procedure is bypassed, thus significantly reducing the degree of invasiveness in the patient's body during the implantation process.

During the same surgical procedure described above, intracranial electrodes can be placed within the brain parenchyma (24) in such a way as to cover areas of the epileptic network. The implantable device (35) is the main neuromodulator, and is responsible for the continuous recording of intracranial EEG, the detection of interictal and ictal intracranial EEG patterns, and the application of the technique of intracranial neuronal electrical stimulation of interictal epileptic activity in an individualized and immediate manner upon detection of said interictal epileptic activity.

The implantable device in Figure 4 comprises two main parts:

Al. A physical intracranial interface unit (27) which includes adapters for connecting at least two intracranial electrodes. Said electrodes are those that are surgically implantable within the patient's brain parenchyma to cover anatomically the epileptic network. The implantable device (35) may be interconnected with two, three, four, five, six, seven or eight intracranial electrodes via the corresponding physical intracranial interface unit (27). An advantage of the system of the above integration is that it provides for inputs of more than two intracranial electrodes, thus enabling a greater coverage of the epileptic networks compared to that provided by the existing closed-loop RNS system, thus increasing both the flexibility of the surgical plan and the effectiveness of electrical stimulation. Each intracranially implantable electrode (25) can include at least two recording contacts. Preferably, each intracranially implantable electrode has five recording contacts (25). In this latter case, the fifth intracranial electrode contact is used as a reference input to the differential amplifier to generate four (4) bipolar intracranial EEG channels per electrode: Channel 1 = Contact 1 - Contact 5, Channel 2 = Contact 2 - Contact 5 , Channel 3 = Contact 3 - Contact 5, and Channel 4 = Contact 4 - Contact 5. By creating four bipolar channels, individual continuous recording of intracranial EEG signals from each contact is achieved. More preferably, the implantable device (35) is interconnected with eight intracranial electrodes where each intracranially implantable electrode (25) includes five recording contacts. This configuration allows the optimal relationship between the amount of recorded data versus the physical volume of the implantable device (35).

In one embodiment, the physical intracranial interface unit (27) is also interconnected with one or more auxiliary biosensors (26), preferably with two to four auxiliary biosensors (26) which capture accompanying biomarkers essential for the evaluation of high-risk patterns such as status epilepticus and SUDEP. Suitable biosensors include, but are not limited to, heart rate, temperature and oxygen saturation biosensors.

A2. Central intracranial stimulation unit (22), which is mainly responsible for the implementation of the intracranial neuronal electrical stimulation of interictal epileptic activity in an immediate and individualized manner, activated by intracranial EEG detection. This unit records the intracranial EEG from the implantable electrodes and activates the process of intracranial neuronal electrical stimulation at the time when interictal activity is detected in the intracranial EEG. At the same time, it sends the recorded data to the external monitoring device (62), and controls the energy reserves and the charging process of its battery (61).

The central intracranial stimulation unit (22) is connected to the intracranially implantable electrodes (25), and is responsible for recording the intracranial electroencephalogram (EEG), for providing targeted and individualized intracranial neuronal electrical stimulation by detecting patterns of interictal epileptic activity, for applying a variety of electrical stimulation patterns (including a set of stimulation pulse patterns), for optionally also detecting patterns of ictal epileptic activity, and for monitoring the battery (61) of the implantable device (35). In a preferred embodiment, the central intracranial stimulation unit (22) is also interconnected with one or more auxiliary biosensors (26), which record accompanying biosignals necessary for the evaluation of high-risk patterns of epileptic activity, such as status epilepticus and SUDEP. Suitable biosensors include, but are not limited to, heart rate, temperature and oxygen saturation biosensors.

In another embodiment, the central intracranial stimulation unit (22) includes an electrical stimulation subunit (30) which is designed to generate and deliver electrical pulses according to pre-set programming parameters (Figure 6). The electrical stimulation subunit (30) can be configured to generate electrical pulses in a synchronous manner by activating all contacts simultaneously, or in an asynchronous manner by selectively activating specific contacts. As interictal activity appears asynchronously in the EEG signal, the preferred mode of generating electrical pulses from the electrical stimulation subunit (30) is asynchronous. Preferably, the electrical stimulation subunit (30) comprises a biphasic electrical pulse generator (41), which can selectively produce either square, symmetrical trapezoidal, or symmetrical triangular electrical pulses. The generator can provide an asynchronous mode of application of electrical pulses, which is performed immediately upon detection of interictal epileptic intracranial EEG patterns. More preferably, the shape, intensity, frequency and/or duration parameters of single pulses and pulse sequences are programmed by the external monitoring device (62). In this case, the electrical stimulation is selectively performed on specific contacts of the implantable intracranial electrodes by means of a line selector (42) and according to the programming received from the external monitoring device (62). Preferably, the biphasic electrical pulse generator has parameterized options for intensity, frequency and duration of single pulses and pulse sequences.

In another embodiment of the system of the present invention, the central intracranial stimulation unit (22) further comprises an embedded computational intelligence (CI) subunit (32), which detects patterns of ictal, interictal, and optionally also post-ictal, epileptic activity, and/or patterns of high risk, in the intracranial EEG (Figure 7), and provides the system with the relevant detection information of the corresponding intracranial EEG patterns, preferably to the electrical stimulation subunit (30). Based on the above, and the current technical knowledge, the person skilled in the relevant art can design the CI subunit so as to compute output data in response to the input data, given that in closed-loop systems, such as the one hereby proposed, all the required information resides by definition in the recorded EEG; consequently no limitation applies as to the kind and complexity of the widely available algorithms that can be used. Preferably, the embedded CI subunit (32) is an embedded machine learning subunit. The embedded CI subunit may comprise one or more of the following distinct pattern detectors: 1. Interictal epileptic activity pattern detector (43). 2. Ictal activity pattern detector (44). 3. High-risk post-ictal epileptic activity pattern detector (45). 4. Auxiliary detector (46) for the detection of novel intracranial patterns and accompanying bio-signals. In a preferred embodiment, the embedded CI subunit (32) comprises a discrete detector of interictal epileptic activity patterns (43), which are individualized for each patient (23), detecting each recording channel of the intracranially implantable electrodes (25), and processing all recorded intracranial EEG signals. In another preferred embodiment, the integrated YN subunit (32) includes a discrete ictal activity pattern detector (44), which is personalized for each patient (23) that is detecting each recording channel from the intracranially implantable electrodes (25) and is processing all the recorded intracranial EEG signals. In another preferred embodiment, the embedded CI subunit (32) includes a discrete detector of high-risk postictal epileptic activity patterns (45), which are individualized for each patient (23), that is detecting each recording channel from the intracranially implantable electrodes (25), and is processing all the recorded intracranial EEG signals in conjunction with the accompanying bio-signals recorded by the auxiliary biosensors (26) in the embodiments where such biosensors are available. According to a preferred embodiment, the detectors operate with parameters which are individualized for each patient, and applied to all available recording channels of the implantable electrodes. The detection information may be recorded in the biosignal recording subunit (29), based on their respective time-stamps, in order to correlate the recording signals with the time of recognition of specific patterns. In the embodiment of Figure 7, the parameters of all detectors (47) of the embedded CI subunit (32), including their architecture elements, are setup and updated via wireless transmission by the external monitoring device (62).

In the embodiment of the central intracranial stimulation unit (22) of Figure 4, the embedded CI subunit (32) is designed to communicate with the electrical stimulation subunit (30) such that, when interictal epileptic intracranial EEG patterns (4) are detected by the embedded CI subunit (32), the electrical stimulation pulses generated by the electrical stimulation subunit (30) to be provided asynchronously to specific contacts of the implantable intracranial electrodes via a line selector (42) and according to the pre-installed programming.

The activation of electrical stimulation through the recording of continuous intracranial EEG by the detection of individual interictal epileptic discharges and the immediate application of intracranial neuronal electrical stimulation (Figure 8: 35 -> 5 -> 24 -> 4 -> 35), constitutes the first therapeutic closed loop of present invention.

It therefore follows that the system disclosed herein is completely opposed to the current technology of closed-loop intracranial neuronal electrical stimulation systems implemented by the existing RNS system which aims to electrically stimulate the unfolding ictal epileptic phenomena during their development in order to intercept them and terminate them directly and instantaneously. Accordingly, an advantage of the present invention over the current state of the art is that it implements a novel therapeutic approach, the technique of intracranial neuronal electrical stimulation of interictal epileptic activity in an immediate and individualized manner, which aims to progressively weaken epileptic networks in their ability to produce seizures.

As one skilled in the relevant art would find apparent from the above description, the arrangement illustrated in Figure 4 is only one example of the present invention. Many other configurations or modifications are possible, as discussed in the present disclosure and as could be made by one skilled in the art without departing from the scope of the invention as defined by the claims.

The system of the present disclosure may also include an external monitoring device (62), which may be worn by the patient either attached to them by means of a strap (e.g., on the arm) (Figure 5) or on a means of carrying objects (e.g., e.g. in a backpack) or to be placed in his immediate environment (e.g. on his work desk). It provides the patient and/or authorized users (guardians/caretakers, clinical supervisors) with a graphic interactive environment through which they can perform procedures exclusively related to the patient's neurostimulation treatment. The external monitoring device (62) is designed to perform one or more of the following functions: to communicate with the central intracranial stimulation unit (22) and to receive, store and transmit the intracranial EEG data; to be informed by the embedded CI subunit (32) when ictal intracranial EEG patterns (6), as well as high-risk post-ictal patterns are detected; set and refresh intracranial neural electrical stimulation parameters, exchange system information with the implantable device, monitor the battery (83) of the external monitoring device (62), receive seizure warning information from the patient, and provide instant alerts upon detection of epileptic ictal patterns on the intracranial EEG.

In another embodiment, the system disclosed herein further includes an external EEG neuromodulation assessment computational system (108) which processes intracranial EEG data for the purpose of personalized assessment of neuromodulation levels (Figure 9). Preferably, said system processes intracranial EEG data with classical neurophysiological computational methods in order to detect neuromodulation phenomena based on intracranial critical EEG biomarkers, in an individualized manner for each patient. More preferably, the individualized assessment of neuromodulation levels is based on one or more biomarkers of intracranial seizure EEG selected from the group consisting of neuronal oscillation frequency shift, intracranial EEG ictal spike amplitude shift, intracranial EEG ictal spike density and the temporal prolongation of the intracranial EEG ictal neuronal oscillations. Said original biomarkers are presented in detail in Examples 1 to 4. The presence, combination or absence of these biomarkers is an alternative method of evaluating the effectiveness of intracranial neuronal electrical stimulation and provides a more accurate overview of the patient's therapeutic course. Said data may also optionally be co-evaluated with seizure diary data reported by the patient and/or guardians/caregivers provided through the external monitoring device (62).

In a preferred embodiment, the system further includes an external CI learning and parameterization computing system (109) responsible for developing the software residing and running on the embedded CI subunit (32) that detects the user's personalized ictal and interictal activity. Preferably, in embodiments in which the implantable device (35) is also interfaced with auxiliary biosensors, the external CI learning and parameterization computing system (109) develops software for the embedded CI subunit (32) to also detect high-risk patterns based on combination of post-ictal intracranial EEG data with the accompanying biosignals from the auxiliary biosensors (Figure 9). Seizure diary data reported by the patient and/or guardians/caregivers through the external monitoring device (62) may, if desired, be co-evaluated with intracranially recorded data. According to the embodiment of Figure 9, the external CI learning and parameterization computing system (109) may receive all of the patient's intracranial data for processing via the external monitoring device (62) preferably through the secure server (107). In addition, it can receive data regarding the type and quality of neuromodulation from the external EEG neuromodulation assessment computational system (108), on the basis of which it configures the corresponding algorithms for identifying ictal intracranial EEG patterns individually for each patient. According to the above preferred embodiment, the adaptation of the criteria for the detection of ictal intracranial EEG patterns through the neuromodulation biomarkers (Figure 8: 35 -> 62 -> 107 -> 108 -> 109 -> 62 -> 35) constitutes the second and diagnostic /prognostic closed loop of the present invention, thanks to which the system dynamically optimizes detection capabilities and at the same time provides a more accurate overview of the patient's therapeutic course.

According to the embodiment of Figure 4, said intracranial neural electrical stimulation system may include an external contactless battery charging device (91), wirelessly coupled to the central intracranial stimulation unit (22) and the external monitoring device (62), in order to charge their respective batteries non-invasively via electromagnetic induction (Figure 10A, 10B). An advantage of said embodiment is that the non-contact battery charging capability minimizes the need for sequential battery change surgeries of the implantable device by enabling regular non-contact charging, thereby significantly reducing the amount of invasiveness the patient may experience. According to the preferred embodiment of Figure 11, the external contactless battery charging device (91) may include an inductor system (93) and a charge management module (94) in order to perform controlled (95) wireless charging from its own chargeable-by-wire battery (92) to the battery (83) of the external monitoring device (62) and/or the battery (61) of the implantable device (35). According to a still more preferred embodiment, the external contactless battery charging device (91) includes an identification structure for coupling with the implantable device (35) and the external monitoring device (62), transmitting device identification data through an identification data coding system (96), a parallel-to- serial data converter (97), a wireless data repeater (98) and an antenna (102) in order to ensure the exclusivity of coupling with the central intracranial stimulation unit (22) and the external monitoring device (62). Alternatively or simultaneously, the identification structure coupling to the implantable device (35) and the external monitoring device (62) receives device identification data via an antenna system (102), a wireless data receiver (99), a serial-to-parallel data converter (100) and an identification data decoder (101) (Figure 11).

According to the embodiment of Figure 12, the central intracranial stimulation unit (22) may include a contactless battery charging subunit (33), which is responsible for monitoring the available energy levels of the battery (61) of the implantable device (35). This charging process is carried out by interfacing with the external contactless battery charging device (91) preferably through an induction coil system (58) and a charge management subunit (59), in order to perform controlled (60) wireless charging for the battery (61) of the implantable device (35).

According to the embodiment of Figure 13, the external monitoring device (62) may include a contactless battery charging unit (64), which is designed to interface with the external contactless battery charging device (91) via an induction coil system (80), and a charging management subunit (81), in order to perform controlled (82) wireless charging for the battery (83) of the external monitoring device (62).

In a further embodiment, the invention utilizes the detection of ictal intracranial EEG patterns to provide immediate notification to the patient and/or authorized guardians/caregivers so that timely measures can be taken for their safety and bodily integrity. According to the said embodiment, the system of the present invention may include one or more external immediate notification devices (104), wirelessly coupled to the external monitoring device (62) for the purpose of notifying the patient's guardians/caregivers who are in the immediate vicinity environment of the detection of ictal and high-risk post-ictal activity patterns (Figure 14). Preferably, one or more external immediate notification devices perform exclusive and secure coupling with the external monitoring device (62) through the external interface subunit (66) of the external monitoring device (62) (Figure 15), as will be outlined below.

Preferably, to implement the coupling with the external monitoring device (62), the one or more external instant notification devices include a Bluetooth Low Energy (BLE) or similar low-power protocol interface module (105) according to Figure 14. It may also include a notification visualization interface module (106) (via display or other visual notification means) in order to display the relevant information to authorized users (guardians/caregivers) carrying it.

This provision of alerts regarding the patient's condition to him and/or guardians/caregivers (Figure 8: 35 -> 62 -> 104 -> 23), as assessed by the intracranial EEG data and accompanying biosignals, is a third safety loop (which, although open to the system, is closed to the patient), in order to support the effort to minimize the risks to the patient during a seizure.

According to one embodiment, the central intracranial stimulation unit comprises a digital intracranial interface subunit (28) (Figure 4), which is adapted to digitize the analog data recorded by the intracranially implantable electrodes (25) (and the auxiliary biosensors (26) in the embodiments where these are included in the system) through the physical intracranial interface unit (27) (Figure 16). According to a preferred embodiment, the digital intracranial interface subunit (28) includes a differential amplifier of analog intracranial EEG signals (37) per pair of intracranial electrodes, preferably via an input isolator (36). The differential amplifier of analog intracranial EEG signals (37) is adapted to serve a dual purpose: first, to create bipolar recording channels, and second, to bring said signals to the appropriate potential levels for digitization. As already mentioned above, when the intracranially implantable electrode (25) includes five recording contacts, the fifth is used as a reference input to the differential amplifier to generate four (4) bipolar intracranial EEG channels per electrode. The input isolator (36) serves to protect the next amplifier stage from the electric current that flows during the phases of intracranial neuronal electrical stimulation. In an even more preferred embodiment, the digital intracranial interface subunit (28) comprises an analog-to-digital converter (38) per intracranial EEG signal obtained from the previous amplification stage (37), for the purpose of digitizing the analog signal.

According to the embodiment of Figure 16, the digital intracranial interface subunit (28) may be coupled to a biosignal recording subunit (29) in order to perform the continuous recording of the intracranial EEG (and accompanying biosignals in the embodiments where auxiliary biosensors (26) are included in the system). More preferably, intracranial EEG data and auxiliary biosensor data are recorded in the biosignal recording subunit (29) via the digital intracranial interface subunit (28) simultaneously from at least two, preferably eight, intracranially implantable electrodes (25) and from two to four auxiliary biosensors (26). The biosignal recording subunit (29) may include a data memory architecture (39) for storing the intracranial EEG data from the set of implantable intracranial electrodes and auxiliary biosensors as received by the digital intracranial interface subunit (28), implementing a “First-In-First-Out” (FIFO) mode of operation. Alternatively or simultaneously, the data memory architecture (39) may receive additional detection data from the embedded CI subunit (32), which provides detection information of intracranial EEG ictal and interictal patterns, as well as electrical stimulation application information.

In a preferred embodiment, the types of archiving recordings that the biosignal recording subunit (29) can perform are selected from the following group, consisting of: 1. Regular archiving of continuous intracranial EEG background recordings of fixed 5 minutes duration every 30 minutes for diagnostic use by the supervising neurologist, 2. Emergency archiving of continuous intracranial EEG recordings during seizure pattern detection, which are of variable duration and include 1 minute before the first detection and 5 minutes after the last detection of seizure activity, to be used both in the diagnostic context as well as for the immediate notification of the patient and/or his guardians/caregivers, 3. Emergency archiving of continuous intracranial EEG recordings during the detection of a high-risk postictal pattern, which are of variable duration and include an extension of the recording up to 5 minutes after the latest detection of the post-ictal high-risk pattern, so that they can be used to immediately notify the patient's guardians/caregivers, and 4. a combination of any of the above. Overall, the system performs archiving of recordings in an intermittent (non- continuous) manner, both in terms of regular background EEG recordings, and in terms of emergency recordings of epileptic activities, in order for the physical storage of the data (data memory) to be limited in such a way as to fit within the narrow confines of a device implantable in the human body. Recordings (of biomarker, stimulation and detection data) may be controlled via a programmable timer (40) and synchronized using time-stamps (real- time measurement data) that accompany the sampling via a real-time clock embedded in the central intracranial stimulation unit (22). In an even more preferred embodiment, the biosignal recording subunit (29) makes regular 5 -minute continuous intracranial EEG recording archiving every 30 minutes of the hour, controlled by a programmable timer (40). Recording and archiving 5 minutes of intracranial EEG every 30 minutes in total corresponds to 4 hours of data per 24 hours, which forty-fold (x40) increases the daily sample of intracranial information compared to that provided by the current RNS system, thus greatly increasing the degree of representativeness of data on treatment status and progress. In an alternative preferred embodiment, the biosignal recording subunit (29) makes emergency archiving of continuous intracranial EEG recording during seizure pattern detection, which are of variable duration and include 1 minute before the first detection and 5 minutes after the last detection of seizure activity, controlled by a programmable timer (40). In another alternative preferred embodiment, the biosignal recording subunit (29) performs emergency archiving of continuous intracranial EEG recordings during high-risk post-ictal pattern detection, which are of variable duration and include an extension of the ictal recording up to 5 minutes after the last post-ictal high-risk pattern detection, controlled by a programmable timer (40).

The central intracranial stimulation unit (22) may be equipped with a bi-directional wireless intercom subunit (31) (Figure 17), in order to implement wireless coupling with the external monitoring device (62). Preferably, the pairing with the external monitoring device (62) is exclusive so as to ensure communication security. The said coupling may include one or more of the following categories of information exchange: 1. The transmission of intracranial EEG data and ictal intracranial EEG pattern detection information to the external monitoring device. 2. Receiving programming parameters and architecture elements for the CI subunits, as well as for the electrical stimulation, from the external monitoring device (62). 3. The exchange of system information with the external monitoring device (62). In the context of data transmission security, the bi-directional wireless intercom subunit (31) includes a data encoding module (50) which includes data encoding, and/or compression, and/or encryption capabilities, preferably through a parallel-to-serial data converter system (51), wireless data transponder (52) and antenna (57). Accordingly, for secure data reception, it may include a data decoding module (55) which includes data decoding, and/or decompression, and/or data decryption capabilities, preferably via an analog antenna system (57), a wireless data receiver (53) and a serial-to-parallel data converter (54). According to one embodiment, the bi-directional wireless intercom subunit (31) includes an asynchronous data transmission module (48) for transmitting the stored intracranial EEG data, accompanied by the corresponding stored intracranial EEG pattern recognition information, to the external monitoring device (62). Alternatively or simultaneously, the bidirectional wireless intercom subunit (31) includes a synchronous data transmission module (49) for transmitting on-demand system information and real-time intracranial ictal EEG pattern recognition information to the external monitoring device (62). The data is received steadily with synchronous transmission. The two-way wireless intercom module may also include a power monitoring module (56), which monitors the power consumption of the implantable device and regulates the asynchronous data transmission, which is the largest amount of data, so that the consumed transmission power remains below a predetermined threshold value.

To better coordinate its operation, the central intracranial stimulation unit (22) may include a central control unit (34), comprising either a special purpose integrated circuit or a general purpose processor, and is designed to perform pre-installed programming from built-in memory and based on this arbitrates one or more subunits of the central intracranial stimulation unit regarding the use of data channels and conditional states of the system. The central control unit incorporates a real-time clock, on the basis of which it synchronizes data and sequences of control procedures.

According to the embodiment of Figure 15, the external monitoring device (62) may include a bi-directional wireless intercom subunit (63), which is coupled via a wireless connection to the implantable device (35). Preferably, the said pairing is performed exclusively with the implantable device (35) in order to ensure communication security. The bi-directional wireless intercom subunit (63) may be configured to transmit to the implantable device (35) programming parameters, and/or system information, of the CI and electrical stimulation units. In a preferred embodiment, for greater security when sending data wirelessly the bidirectional wireless intercom subunit (63) includes a data encoding module (71) which includes data encoding, and/or compression, and/or encryption capabilities for the security of wireless transmission, via a parallel-to-serial converter system (72), a wireless data repeater (73) and an antenna (79). Alternatively, or in parallel, the bi-directional wireless intercom subunit (63) may be configured to receive from the implantable device (35) intracranial EEG data, accompanying biosignal data, intracranial EEG pattern recognition data and/or system information. In a preferred embodiment, for greater security during wireless data reception, the bi-directional wireless intercom subunit (63) includes a data decoding module (76) which includes data decoding, and/or decompression, and/or decryption capabilities for wireless security reception, via an antenna system (79), a wireless data receiver (74) and a serial-to-parallel data converter (75).

According to the embodiment of Figure 18, the bi-directional wireless intercom subunit (63) may include an asynchronous data acquisition module (77) for receiving the recorded data from the implantable device, accompanied by the corresponding stored information identifying intracranial EEGs and high-risk patterns. Alternatively, or in parallel, it may include a synchronous data acquisition module (78) for receiving on-demand system information and intracranial EEG critical and high-risk pattern recognition information in real time from the implantable device (35).

The external monitoring device (62) may preferably be wirelessly coupled to one or more external immediate notification devices (104) via the external interface subunit (66), in order to notify the patient's guardians/caregivers in the patient's immediate environment of the detection of ictal and high-risk post-ictal activity patterns (Figure 14). The external interface subunit (66) (Figures 15, 19) is designed to transmit the intracranial EEG data (including coded, and/or compressed, and/or encrypted data), the accompanying biosignals when they are available, as well as intracranial EEG pattern recognition information, preferably via a secure ethemet interface to a secure server (107). Optionally, the external interface subunit (66) may receive upgraded versions of the parameters of the embedded CI subunit (32) from the external CI learning and parameterization computing system (109). According to the embodiment of Figure 19, the external interface subunit (66) may include an ethemet interface module (86), which implements IEEE 802.11 protocol (without version limitation) or other high-bandwidth wireless protocol, through a synchronous transmission system (84) and data selector (85), for interfacing preferably through a secure server (107). Alternatively, or simultaneously, the external interface subunit (66) may include a Bluetooth low energy (BLE) or similar low energy protocol interface module (87), via a synchronous transmission system (84) and a data selector (85).

The external monitoring device (62) may optionally include one or more intracranial EEG data storage subunits (65), coupled to the bi-directional wireless communication subunit (63) for local storage of intracranial EEG data, accompanying biosignals, and/or intracranial EEG pattern identification information, as obtained from the implantable device (35).

For secure and exclusive access by the patient and/or authorized users (guardians/caregivers, clinical managers), the external monitoring device (62) may include a biometric identification subunit (67) (Figure 20). Preferably, the biometric identification subunit (67) provides secure access via a biometric controller system (89), a biometric data storage module (88) and an external biometric fingerprint sensor (90).

The graphic user interface to the patient and/or other authorized users for entering and reviewing information related to neurostimulation therapy may be provided by the external monitoring device (62) via a display interface subunit (69). For the same reason, the external monitoring device (62) includes and executes an operating system (68) which provides a graphic user interface to the patient (23) and/or other authorized users (103) for entering and reviewing information (Figure 15).

The external monitoring device (62) may include a central control unit (70), which comprises either a special purpose integrated circuit or a general purpose processor, and which performs the programming as indicated by the installed operating system (68). The central control unit (70) arbitrates the above subunits of the external monitoring device regarding the use of the data channels and the conditional states of the system. The external monitoring device (62) includes a central control unit (70) with a processor that performs the programming as determined by the operating system (68) and arbitrates the subunits of bidirectional wireless intercom (63), contactless battery charging (64), intracranial EEG data storage (65), external interface (66), biometric identification (67), display interface (69) and/or the operating system (68), with respect to the use of data channels and conditional states of the system.

According to the above, the external monitoring device (62) may be configured to perform one or more of the following functions: a. To be an intermediary device for forwarding data that can be recorded and generated by the implantable device (ie, intracranial EEG, accompanying biomarkers, detection data respectively to the external EEG neuromodulation assessment computational system (108)) and/or from the external CI learning and parameterization computing system (109), and/or to the external immediate notification devices (104), b. To be a programming device of the implantable device (35) in terms of electrical stimulation parameters, detection parameters and central programming, c. To provide information on the charging levels of both its own battery (83) and the battery (61) of the implantable device (35), for the optimal organization of charging procedures, and d. To provide a seizure diary application, which the patient or guardians/caregivers inform, and whose data is co-evaluated with intracranial EEG data and ictal pattern recognition data from the external CI learning and parameterization computing system (109). In another aspect of the present invention, a method of intracranial neuronal electrical stimulation is provided which, based on the original ideas explained above, disrupts the process of epileptic network establishment, reduces the possibility of neuronal hypersynchronization, and induces positive/beneficial neuromodulation in the intracranial EEG of seizures. This novel technique applies intracranial neuronal electrical stimulation to interictal, rather than ictal, epileptic activity, in an immediate and individualized manner upon detection of the interictal epileptic activity. This technique does not produce effects of an acute nature, as proposed by the RNS technique of immediate and instantaneous termination of epileptic seizures, but acts over time, progressively altering and weakening the underlying epileptic network, rendering it incapable of producing hypersynchronized activity and creating paroxysmal discharges.

According to the above aspect, a method of intracranial neuronal electrical stimulation for the treatment of epilepsy and other brain disorders involving seizures is provided, which comprises of the following steps in the following order: a) surgical implantation of a device, which includes at least two intracranially implantable electrodes of at least two recording contacts each, within the patient's brain parenchyma, b) intermittent regular and emergency archiving of the intracranial EEG recording through the electrodes, c) detection of interictal epileptic discharges in the intracranial EEG, and d) delivery of electrical impulses of stimulation to each interictal discharge, in an immediate and individualized manner (eventually an asynchronous manner).

According to a preferred embodiment, after step (d), the above method comprises the following steps: e) detection of critical discharges of the critical intracranial EEG through the electrodes, f) detection of post-ictal high-risk intracranial EEG patterns and auxiliary biosignals through the electrodes, g) formulation of algorithms for identifying ictal intracranial EEG patterns, and their changes, individually for each patient using one or more biomarkers of the ictal intracranial EEG, and h) adaptation and renewal of the programming parameters of the intracranial neuronal electrical stimulation individually for each patient.

Neurophysiological biomarkers to detect neuromodulation in epileptic networks as a result of chronic intracranial neuronal electrical stimulation.

EXAMPLE 1

Neuronal Oscillation Frequency Shift (NOFS) Index

This neurophysiological biomarker of neuromodulation regards changes in the frequency content of the neuronal oscillations of the critical intracranial EEG and is hereby called the neuronal oscillation frequency shift (NOSF) index. Figure 21A shows the occurrence of NOSF in the raw intracranial EEG as a result of chronic intracranial neuronal electrical stimulation. On the left of Figure 21 A is shown a sample of ictal intracranial EEG of neuronal oscillation frequency f (9), as manifested before application of intracranial neuronal electrical stimulation. To the right of Figure 21 A, the two manifestations of NOSF are shown, as they can manifest after the application of intracranial electrical stimulation. The upper right quadrant shows NOSF of the intracranial ictal EEG manifesting as an increase in the baseline neuronal oscillation frequency f by a factor a, where a > 1, resulting in the establishment of a new and increased neuronal oscillation frequency f mod = a*f > f (10).

In the lower right quadrant, NOSF of the intracranial ictal EEG is shown as a reduction of the baseline neuronal oscillation frequency f by a factor of b, where b < 1, resulting in the establishment of a new and reduced neuronal oscillation frequency fn>od= b*f< f (l l).

The neurophysiological biomarker NOSF is expressed as

Af = f - f mod and predicts two subclasses of neuromodulation: one manifested by an increase in neuronal oscillation frequency and one manifested by a decrease in neuronal oscillation frequency. The former is an indication of reduced neuronal hypersynchronization in the underlying epileptiform network as a result of failure to recruit sufficient secondarily epileptogenic regions and is a phenomenon of positive/beneficial neuromodulation. The latter is evidence of increased neuronal hypersynchronization in the underlying epileptiform network as a 1 result of increased recruitment of secondarily epileptogenic regions and is a phenomenon of negative/damaging neuromodulation.

EXAMPLE 2

Neuronal Oscillation Amplitude Shift (NOAS) Index

The second neurophysiological biomarker of neuromodulation regards changes in the amplitude of the sharp discharges of the ictal intracranial EEG and is hereby called the neuronal oscillation amplitude change (NOAS) index. Figure 21B shows the occurrence of NOAS in the raw intracranial EEG as a result of chronic intracranial neuronal electrical stimulation. On the left of Figure 2 IB is shown a sample of ictal intracranial EEG with sharp ictal discharges of oscillation amplitude k (12), as it manifests before the application of intracranial neuronal electrical stimulation. On the right, the two NOAS manifestations are shown, as they can manifest after the application of intracranial electrical stimulation. The upper right quadrant shows a NOAS of the intracranial ictal EEG manifested as an increase in the baseline amplitude k of spikes by a factor), where) > 1, resulting in the establishment of a new and increased amplitude of spikes k _mod=j*k > k (13).

The lower right quadrant shows a NOAS of the intracranial ictal EEG manifested as a reduction in the baseline spike amplitude k by a factor of y, where y < 1, resulting in the establishment of a new and reduced spike amplitude k _m0d= y*k < k (14).

The neurophysiological biomarker NOAS is expressed as:

Ak k - k mod and predicts two subtypes of neuromodulation: one manifested by an increase in neuronal oscillation amplitude and one manifested by a decrease in neuronal oscillation amplitude. The former is evidence of increased neuronal hypersynchronization in the underlying epileptiform network as a result of increased recruitment of secondarily epileptogenic regions and is a phenomenon of negative/damaging neuromodulation. The latter is an indication of reduced neuronal hypersynchronization in the underlying epileptiform network as a result of failure to recruit sufficient secondary epileptogenic regions and is a phenomenon of positive/beneficial neuromodulation.

EXAMPLE 3 Neuronal Oscillation Density Shift (NODS) Index

The third neurophysiological biomarker of neuromodulation regards changes in the density of spike discharges of the ictal intracranial EEG and is hereby called the neuronal oscillation density shift (NODS) index. Figure 21 C shows the appearance of NODS in the raw intracranial EEG as a result of chronic intracranial neuronal electrical stimulation. On the left of Figure 21C is shown a sample of ictal intracranial EEG with spike density i (15), as it manifests before the application of intracranial neuronal electrical stimulation. On the right, the two NODS manifestations are presented, as they can manifest after the application of intracranial electrical stimulation. In the upper right quadrant is shown a NODS of the intracranial ictal EEG manifested as an increase in the baseline spike density i by a factor c, where c > 1, resulting in the establishment of a new and increased spike density: i mod= c*i > i (16).

In the lower right quadrant is shown a NODS of the intracranial ictal EEG manifested as a decrease in spike density i by a factor d, where d < 1, resulting in the establishment of a new and reduced spike density i mod ⁼ d*i < i (17).

The neurophysiological biomarker NODS is expressed as:

Al 1 - 1 mod and predicts two subtypes of neuromodulation: one manifested by an increase in spike density frequency and one manifested by a decrease in spike density. The former is evidence of increased neuronal hypersynchronization in the underlying epileptiform network as a result of increased recruitment of secondarily epileptogenic regions and is a phenomenon of negative/damaging neuromodulation. The latter is an indication of reduced neuronal hypersynchronization in the underlying epileptiform network as a result of failure to recruit sufficient secondary epileptogenic regions and is a phenomenon of positive/beneficial neuromodulation.

EXAMPLE 4

Neuronal Oscillation Temporal Sustainability (NOTS) Index

The fourth neurophysiological biomarker of neuromodulation regards the temporal sustainability of the neuronal oscillations of the critical intracranial EEG and is hereby called the neuronal oscillation temporal sustainability (NOTS) index. Figure 21D shows the occurrence of NOTS in the raw intracranial EEG as a result of chronic intracranial neuronal electrical stimulation. On the left of Figure 21D is shown a sample of a ictal intracranial EEG of neuronal oscillation duration t between the onset and end of the ictal neuronal oscillation (18), as it occurs before the application of intracranial neuronal electrical stimulation. On the right, the three manifestations of NOTS are shown, as they can manifest after the application of intracranial electrical stimulation. Shown in the upper right quadrant is the NOTS of intracranial ictal EEG manifested as a reduction of the baseline neuronal oscillation duration t by a factor e, where e < 1, resulting in the establishment of a new and increased neuronal oscillation duration t mod= e*t < t (19).

Shown in the middle right quadrant is the intracranial ictal EEG NOTS manifested as an increase in the baseline neuronal oscillation duration t by a factor of g, where g > 1, resulting in the establishment of a new and increased neuronal oscillation duration t mod = g*t > t (20).

In the lower right quadrant shows the NOTS of the intracranial ictal EEG manifested as a discontinuity of the crisis neuronal oscillation which occupies a percentage m of the basic duration of the neuronal oscillation t, where m < 1. In this case, although the total duration of the intracranial EEG phenomenon may be equal to the basic neuronal oscillation duration t, the overall duration of the neuronal oscillation is reduced t mod= t - m*t < t. (21).

The neurophysiological biomarker NOTS is expressed as

At t - t mod and predicts three subcategories of neuromodulation: one manifested by an increase in the duration of neuronal oscillation, one manifested by a decrease in the duration of neuronal oscillation, and one manifested by the appearance of discontinuities during the evolution of the ictal EEG phenomenon that reduce the total duration of neuronal oscillation. The first and third are evidence of reduced neuronal hypersynchronization in the underlying epileptiform network as a result of failure to recruit sufficient secondary epileptogenic regions and are phenomena of positive/beneficial neuromodulation. The second is evidence of increased neuronal hypersynchronization in the underlying epileptiform network as a result of increased recruitment of secondarily epileptogenic regions and is a phenomenon of negative/damaging neuromodulation.

Claims

1. An intracranial neuronal electrical stimulation system of interictal epileptic activity for the treatment of brain disorders involving seizures, which comprises an implantable device (35) comprising a central intracranial stimulation unit (22) connected via a physical intracranial interface unit (27) to at least two intracranially implantable electrodes of at least two recording contacts (25) each; wherein said electrodes are surgically implantable within the brain parenchyma (24) of the patient (23), and wherein the central intracranial stimulation unit (22) is designed to record the continuous intracranial electroencephalogram (EEG), detect patterns of interictal epileptic activity (4), and provide immediate and individualized intracranial neuronal electrical stimulation (5) upon detection of said interictal patterns.

2. The system according to claim 1, wherein said implantable device (35) is interconnected with auxiliary biosensors (26) via the physical intracranial interface unit (27), wherein said biosensors are designed to capture biomarkers for the evaluation of high-risk patterns of epileptic activity.

3. The system according to claim 1 or 2, wherein the central intracranial stimulation unit (22) further comprises an embedded computational intelligence (CI) subunit (32) adapted to detect patterns of interictal, ictal, and optionally post-ictal activity in the continuous intracranial EEG and provide the central intracranial stimulation unit (22) with the detection information of the corresponding intracranial EEG patterns.

4. The system according to claim 3, wherein the central intracranial stimulation unit (22) is adapted so that, upon receiving interictal intracranial EEG pattern detection information, it provides electrical stimulation pulses in an immediate and individualized manner to specific contacts of the implantable intracranial electrodes according to preinstalled programming.

5. The system according to any one of claims 1 to 4, further comprising an external monitoring device (62) designed to receive, store and transmit the intracranial EEG data, establish and update the parameters of the intracranial neuronal electrical stimulation, set and refresh implantable device operating parameters (35), receive seizure warning information from the patient, and provide immediate alerts upon detection of ictal patterns in the intracranial EEG.

6. The system according to claim 5, further comprising an external EEG neuromodulation assessment computational system (108) designed to process intracranial EEG data for the personalized assessment of neurophysiological changes of ictal EEG patterns.

7. The system according to claim 6, wherein said personalized assessment of neurophysiological changes of ictal EEG patterns includes assessing one or more biomarkers of intracranial ictal EEG neuromodulation, wherein said biomarkers are selected from a group of quantifiable phenomena consisting of neuronal oscillation frequency shift, neuronal oscillation amplitude shift, neuronal oscillation density shift and neuronal oscillation temporal sustainability of the ictal intracranial EEG.

8. The system according to claim 6 or 7, wherein said system further comprises an external computational intelligence (CI) learning and parameterization computing system (109), wherein said learning system is designed to receive a combination of data relating to neurophysiological changes in intracranial ictal EEG patterns from the external EEG neuromodulation assessment computational system (108) and from the external monitoring device (62), in order to configure, based on the above data, intracranial EEG pattern recognition algorithms personalized for each patient.

9. The system according to claim 8, wherein the external EEG neuromodulation assessment computational system (108) is adapted to detect neurophysiological changes of ictal EEG patterns in the intracranial EEG data based on said biomarkers, in a personalized manner for each patient, and to inform the external computational intelligence (CI) learning and parameterization computing system (109) for said learning computing system (109) to adjust and update the programming parameters of the intracranial neural electrical stimulation in a personalized manner for each patient.

10. The system according to any one of claims 5 to 9, further comprising one or more external immediate notification devices (104), wirelessly coupled to the external monitoring device (62) for the purpose of notifying the patient's guardians/caregivers in the patient's immediate environment when patterns of seizure activity and patterns of high- risk post-ictal activity are detected.

11. The system according to any one of claims 5 to 10, wherein the central intracranial stimulation unit (22) comprises a bi-directional wireless intercom subunit (31), wirelessly coupled to the external monitoring device (62), wherein said module (31) is designed so as to transmit intracranial EEG data and/or ictal intracranial EEG pattern detection information to the external monitoring device (62) and to receive the programming parameters of the CI and electrical stimulation subunits from the external monitoring device (62).

12. The system according to any one of claims 5 to 11, wherein the external monitoring device (62) comprises a bi-directional wireless intercom subunit (63) coupled via a wireless connection to the implantable device (35) and adapted to receive intracranial EEG data, intracranial EEG pattern recognition data and/or to transmit CI and electrical stimulation unit programming parameters to the central intracranial stimulation unit (22) of the implantable device (35).

13. The system according to any one of the above claims, wherein the central intracranial stimulation unit (22) further comprises a biosignal recording subunit (29), wherein the said biosignal recording subunit is coupled to the intracranially implantable electrodes and/or auxiliary biosensors for the recording of the intracranial EEG through the intracranially implantable electrodes (25) and/or for the recording of accompanying biosignals.

14. The system according to claim 13, wherein the biosignal recording subunit (29) is designed to intermittently perform regular and occasional archiving of continuous intracranial EEG recordings under the control of a programmable timer (40).

15. The system according to any one of the preceding claims, wherein said system further comprises an external contactless battery charging device (91) configured to be wirelessly coupled to the central intracranial stimulation unit (22) and/or the external monitoring device (62), in order to charge their respective batteries (61, 83) non- invasively through electromagnetic induction.

16. The system according to claim 15, wherein the central intracranial stimulation unit (22) and/or the external monitoring device (62) comprise a contactless battery charging module (33, 64) which interfaces with the external contactless battery charging device (91) through a system of induction coils (58, 80), and a charge management subunit (59, 81).