Intracranial Electrodes Research Articles

Online speech synthesis using a chronically implanted brain–computer interface in an individual with ALS

Brain–computer interfaces (BCIs) that reconstruct and synthesize speech using brain activity recorded with intracranial electrodes may pave the way toward novel communication interfaces for people who have lost their ability to speak, or who are at high risk of losing this ability, due to neurological disorders. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a man with impaired articulation due to ALS, participating in a clinical trial (ClinicalTrials.gov, NCT03567213) exploring different strategies for BCI communication. The 3-stage approach reported here relies on recurrent neural networks to identify, decode and synthesize speech from electrocorticographic (ECoG) signals acquired across motor, premotor and somatosensory cortices. We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the participant from a vocabulary of 6 keywords previously used for decoding commands to control a communication board. Evaluation of the intelligibility of the synthesized speech indicates that 80% of the words can be correctly recognized by human listeners. Our results show that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words while preserving the participant’s voice profile, and provide further evidence for the stability of ECoG for speech-based BCIs.

Ictal Direct Current Shifts Preceded Much Earlier Than High Frequency Oscillations After Status: Is It the Effect of Status or Antiseizure Medication?

While spikes and sharp waves are considered as markers of epilepsy in conventional electroencephalography, ictal direct current (DC) shifts and high-frequency oscillations (HFOs) appear to be useful biomarkers for epileptogenicity. We analyzed how ictal DC shifts and HFOs were affected by focal status epilepticus and antiseizure medications (ASMs). A 20-year-old female patient who underwent long-term intracranial electrode implantation for epilepsy surgery presented with 72 habitual seizures and a focal status epilepticus episode lasting for 4 h. Ten, 3, and 10 consecutive habitual seizures were analyzed before the status, after the status, and after ASM (valproate) loading, respectively. Before and immediately after the status, ictal DC shifts remained the same in terms of the amplitude, duration, and slope of DC shifts. High-frequency oscillations also remained the same in terms of the duration, frequency, and power except for the power of the lower frequency band. After ASM loading, the duration, amplitude, and slope of the ictal DC shift were significantly attenuated. The duration, frequency, and power of the HFOs were significantly attenuated. Furthermore, the interval between the DC onset and HFO onset was significantly longer and the interval between the HFO onset and ictal DC shift peak was significantly shorter. The attenuation of ictal DC shifts and HFOs after ASM loading implies that astrocyte and neuronal activity may be both attenuated by ASMs. This finding may help with our understanding of the pathophysiology of epilepsy and can aid with the discovery of new approaches for epilepsy management.

Subclinical epileptiform discharges in Alzheimer’s disease are associated with increased hippocampal blood flow

BackgroundIn epilepsy, the ictal phase leads to cerebral hyperperfusion while hypoperfusion is present in the interictal phases. Patients with Alzheimer’s disease (AD) have an increased prevalence of epileptiform discharges and a study using intracranial electrodes have shown that these are very frequent in the hippocampus. However, it is not known whether there is an association between hippocampal hyperexcitability and regional cerebral blood flow (rCBF). The objective of the study was to investigate the association between rCBF in hippocampus and epileptiform discharges as measured with ear-EEG in patients with Alzheimer’s disease. Our hypothesis was that increased spike frequency may be associated with increased rCBF in hippocampus.MethodsA total of 24 patients with AD, and 15 HC were included in the analysis. Using linear regression, we investigated the association between rCBF as measured with arterial spin-labelling MRI (ASL-MRI) in the hippocampus and the number of spikes/sharp waves per 24 h as assessed by ear-EEG.ResultsNo significant difference in hippocampal rCBF was found between AD and HC (p-value = 0.367). A significant linear association between spike frequency and normalized rCBF in the hippocampus was found for patients with AD (estimate: 0.109, t-value = 4.03, p-value < 0.001). Changes in areas that typically show group differences (temporal-parietal cortex) were found in patients with AD, compared to HC.ConclusionsIncreased spike frequency was accompanied by a hemodynamic response of increased blood flow in the hippocampus in patients with AD. This phenomenon has also been shown in patients with epilepsy and supports the hypothesis of hyperexcitability in patients with AD. The lack of a significant difference in hippocampal rCBF may be due to an increased frequency of epileptiform discharges in patients with AD.Trial registrationThe study is registered at clinicaltrials.gov (NCT04436341).

149 Dynamical Network State Sequences for Human Language Production

INTRODUCTION: Speech requires the selection of a conceptual representation, the construction of a word form, and the execution of a complex articulatory plan. Investigating this global system requires high-resolution recordings with an analytic approach to resolve discrete cognitive states. We integrated autoregressive hidden Markov models to resolve trial-by-trial state transition sequences in distributed networks derived from a large-scale electrocorticographic dataset with complete coverage of language-dominant cortex. METHODS: Intracranial electrodes (n = 25810, 134 patients), including both surface grids and stereotactic depths, were implanted for the evaluation of epilepsy. Patients performed picture naming of common objects and underwent systematic cortical stimulation mapping of language function. We used cross-validated autoregressive hidden Markov models – combining the interpretability of multivariate autoregressive analysis with the nonlinear embedding of the switching Markov characteristic – to distinguish cognitive states defined by causal interactional motifs of distributed cortical substrates and to simulate in silico lesions of dynamical network structures. RESULTS: We created a detailed spatiotemporal atlas of word production spanning the entire language-dominant cortex. From this map, we resolved network dynamics comprising sequences of state space transitions for each word articulated. This identified five essential states for speech production, each defined by a unique pattern of directed interactions within the language network. We then derived a computational lesion model for state dynamics and compared its predictions with causal perturbation by direct cortical stimulation. We assembled a global dynamical state model for language production and resolved the fine-scale interregional dynamics of conceptualization and lexical access. CONCLUSIONS: The distributed network dynamics detailed within this comprehensive interactional map of speech production advance our understanding of how both local and disconnection injuries yield complex neurological deficits, facilitating the development of novel therapeutic approaches for aphasia.

487 Cholinergic Blockade Alters Hippocampal-posterior Cingulate Cortex Synchrony During Episodic Memory Encoding

INTRODUCTION: The posterior cingulate cortex (PC) is an important region for episodic memory. Its synchrony with the hippocampus in the theta frequency, in particular, has been shown to underlie successful memory encoding. Cholinergic signaling is another important component of episodic memory, and manipulation of cholinergic signaling is often employed to better understand memory. However, the specific relationship between cholinergic signaling and hippocampal-PC synchrony has not been explored. METHODS: Eight patients with intracranial electrodes underwent two sessions of a free recall task, one in which they were given scopolamine and the other, saline. EEG recordings from these sessions during early and late encoding were then analyzed. The phases of high (5-9 Hz) and low (2-5 Hz) theta frequencies were calculated with hilbert transform, and synchrony was measured with phase-locking value (PLV), calculated for each electrode pair. Permutation tests were used to compare PLV between saline and scopolamine conditions for each electrode pair, producing a distribution of z-scores for each region-region connection. Electrodes were grouped into the regions anterior hippocampus (AH), posterior hippocampus(PH), and PC. The z-score distributions were compared against a distribution centered at zero with a t-test. RESULTS: The z-score distributions from permutation were significantly different from a null distribution for AH-PC connections in the left and right hemispheres during late encoding in high theta frequencies; AH-PH and PH-PC connections in the right hemisphere during early encoding in low theta frequencies; and PH-PC connections in the right hemisphere during late encoding in low theta frequencies. CONCLUSIONS: Changes in synchrony between PC, AH, and PH due to cholinergic blockade differ between low and high theta as well as early and late encoding.

Local field potentials: Therapeutic implications for DBS in dystonia including adaptive DBS for dystonia

Local field potentials (LFPs) are signals generated primarily by the result of the synchronous discharge of post-synaptic potentials. Detection of LFPs from intracranial electrodes sited within the basal ganglia has led to the recognition that there are specific features of the LFP that could serve as neurophysiological biomarkers of different disease states. For example, in Parkinson’s disease peaks in the beta frequency range of the power spectrum are known to correlate with the degree of bradykinesia and rigidity, whereas low frequency, alpha-theta peaks are increasingly considered a biomarker of dystonic activity. The introduction of newer deep brain stimulation (DBS) devices capable of simultaneous stimulation and LFP detection creates opportunities to investigate new strategies for treating patients with dystonia. This review aims to summarise the LFP findings seen in patients with dystonia undergoing DBS with a particular focus on the potential implications for future clinical practice and the development of adaptive DBS systems.

Safety of intracranial electrodes in an MRI environment: a technical report.

Intracranial electroencephalography (iEEG) involves placing intracranial electrodes to localise seizures in patients with medically refractory epilepsy. While magnetic resonance imaging (MRI) enables visualisation of electrodes within patient-specific anatomy, the safety of these electrodes must be confirmed prior to routine clinical utilisation. Therefore, the purpose of this study was to evaluate the safety of iEEG electrodes from a particular manufacturer in a 3.0-Tesla (3.0T) MRI environment. Measurements of magnetically induced displacement force and torque were determined for each of the 10 test articles using standardised techniques. Test articles were subsequently evaluated for radiofrequency-induced heating using a Perspex phantom in both open and 'fault' conditions. Additionally, we assessed radiofrequency (RF)-induced heating with all test articles placed into the phantom simultaneously to simulate an implantation, again in both open and 'fault' conditions. Finally, each test article was evaluated for MRI artefacts. The magnetically induced displacement force was found to be less than the force on the article due to gravity for all test articles. Similarly, the maximum magnetically induced torque was less than the worst-case torque due to gravity for all test articles apart from the 8-contact strip - for which it was 11% greater - and the depthalon cap. The maximum temperature change for any portion of any test article assessed individually was 1.7°C, or 1.2°C for any device component meant to be implanted intracranially. In the implantation configuration, the maximum recorded temperature change was 0.7°C. MRI may be safely performed for localising iEEG electrodes at 3.0T under certain conditions.

Clinical evaluation of a stereotactic system for single-stage deep brain stimulation surgery under general anesthesia: technical note.

Conventional frame-based stereotactic systems have circumferential base frames, often necessitating deep brain stimulation (DBS) surgery in two stages: intracranial electrode insertion followed by surgical re-preparation and pulse generator implantation. Some patients do not tolerate awake surgery, underscoring the need for a safe alternative for asleep DBS surgery. A frame-based stereotactic system with a skull-mounted "key" in lieu of a circumferential base frame received US FDA clearance. The authors describe the system's application for single-stage, asleep DBS surgery in 8 patients at their institution and review its workflow and technical considerations. Eight patients underwent DBS lead insertion and IPG implantation in a single surgical preparation under general anesthesia using the system. Postoperative CT imaging confirmed lead placement. Eight patients underwent implantation of 15 total leads targeting the ventral intermediate nucleus (4 patients), globus pallidus internus (GPi; 3 patients), and subthalamic nucleus (STN; 1 patient). Intraoperative microelectrode recording was conducted for GPi and STN targets. Postoperative CT imaging revealed a mean ± SD radial error of 1.24 ± 0.45 mm (n = 15 leads), without surgical complications. The stereotactic system facilitated safe and effective asleep, single-stage DBS surgery, maintaining traditional lead accuracy standards.

Effects of midazolam on high-frequency oscillations in amygdala and hippocampus of epilepsy patients.

High-frequency oscillations (HFOs) are associated with normal brain function, but are also increasingly recognized as potential biomarkers of epileptogenic tissue. Considering the important role of interneuron activity in physiological HFO generation, we studied their modulation by midazolam (MDZ), an agonist of γ-aminobutyric acid type A (GABAA)-benzodiazepine receptors. Here, we analyzed 80 intracranial electrode contacts in amygdala and hippocampus of 13 patients with drug-refractory focal epilepsy who had received MDZ for seizure termination during presurgical monitoring. Ripples (80-250 Hz) and fast ripples (FRs; 250-400 Hz) were compared before and after seizures with MDZ application, and according to their origin either within or outside the individual seizure onset zone (SOZ). We found that MDZ distinctly suppressed all HFOs (ripples and FRs), whereas the reduction of ripples was significantly less pronounced inside the SOZ compared to non-SOZ contacts. The rate of FRs inside the SOZ was less affected, especially in hippocampal contacts. In a few cases, even a marked increase of FRs following MDZ administration was seen. Our results demonstrate, for the first time, a significant HFO modulation in amygdala and hippocampus by MDZ, thus giving insights into the malfunction of GABA-mediated inhibition within epileptogenic areas and its role in HFO generation.

The value of additional electrodes when stereo-electroencephalography is inconclusive.

Stereo-electroencephalography (SEEG) is the preferred method for intracranial localization of the seizure-onset zone (SOZ) in drug-resistant focal epilepsy. Occasionally SEEG evaluation fails to confirm the pre-implantation hypothesis. This leads to a decision tree regarding whether the addition of SEEG electrodes (two-step SEEG - 2sSEEG) or placement of subdural electrodes (SDEs) after SEEG (SEEG2SDE) would help. There is a dearth of literature encompassing this scenario, and here we aimed to characterize outcomes following unplanned two-step intracranial EEG (iEEG). All 225 adult SEEG cases over 8 years at our institution were reviewed to extract patient data and outcomes following a two-step evaluation. Three raters independently quantified benefits of additional intracranial electrodes. The relationship between two-step iEEG benefit and clinical outcome was then analyzed. Fourteen patients underwent 2sSEEG and nine underwent SEEG2SDE. In the former cohort, the second SEEG procedure was performed for these reasons-precise localization of the SOZ (36%); defining margins of eloquent cortex (21%); and broadening coverage in the setting of non-localizable seizure onsets (43% of cases). Sixty-four percent of 2sSEEG cases were consistently deemed beneficial (Light's κ = 0.80). 2sSEEG performed for the first two indications was much more beneficial than when onsets were not localizable (100% vs 17%, p = .02). In the SEEG2SDE cohort, SDEs identified the SOZ and enabled delineation of margins relative to eloquent cortex in all cases. The two-step iEEG is useful if the initial evaluation is broadly concordant with the original electroclinical hypothesis, where it can clarify onset zones or delineate safe surgical margins; however, it provides minimal benefit when the implantation hypothesis is erroneous, and we recommend that 2sSEEG not be generally utilized in such cases. SDE implantation after SEEG minimizes the need for SDEs and is helpful in delineating surgical boundaries relative to ictal-onset zones and eloquent cortex.

Decoding Single and Paired Phonemes Using 7T Functional MRI

Several studies have shown that mouth movements related to the pronunciation of individual phonemes are represented in the sensorimotor cortex. This would theoretically allow for brain computer interfaces that are capable of decoding continuous speech by training classifiers based on the activity in the sensorimotor cortex related to the production of individual phonemes. To address this, we investigated the decodability of trials with individual and paired phonemes (pronounced consecutively with one second interval) using activity in the sensorimotor cortex. Fifteen participants pronounced 3 different phonemes and 3 combinations of two of the same phonemes in a 7T functional MRI experiment. We confirmed that support vector machine (SVM) classification of single and paired phonemes was possible. Importantly, by combining classifiers trained on single phonemes, we were able to classify paired phonemes with an accuracy of 53% (33% chance level), demonstrating that activity of isolated phonemes is present and distinguishable in combined phonemes. A SVM searchlight analysis showed that the phoneme representations are widely distributed in the ventral sensorimotor cortex. These findings provide insights about the neural representations of single and paired phonemes. Furthermore, it supports the notion that speech BCI may be feasible based on machine learning algorithms trained on individual phonemes using intracranial electrode grids.

IEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.

Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

Present and Prospective Advancements in the Field of Deep Brain Stimulation Technology

Deep brain stimulation (DBS) in the neurosurgery domain allows for precise control of particular neural circuits. DBS has shown significant therapeutic effectiveness in the management of essential tremor, dystonia, and Parkinson's disease (PD). Moreover, ongoing research is investigating the potential of DBS as a therapy modality for several additional conditions characterized by aberrant circuitry, including depression and dementia. Over the last two decades, there has been a gradual improvement in DBS (Deep Brain Stimulation) devices, which today integrate an extension wire, pulse generator, and intracranial electrode. These components have been borrowed from the field of cardiology. The present paradigm of DBS is expected to undergo significant changes due to recent breakthroughs in technology and imaging, as well as a more comprehensive understanding of brain illnesses. Anticipated advancements in the tolerability and efficacy of DBS may be attributed to progress made in several areas, including battery and electrodes designing, stimulation systems, on-demand and closed-loop stimulation, including sensor technologies. This review provides a comprehensive examination of the historical and projected trajectory of DBS technology. By retrospectively examining the progress of DBS, we may enhance our understanding and recognition of our current position, as well as proactively forecast the next obstacles and prospects.

Intracerebral electrographic activity following a single dose of diazepam nasal spray: A pilot study.

Rescue benzodiazepine medication can be used to treat seizure clusters, which are intermittent, stereotypic episodes of frequent seizure activity that are distinct from a patient's usual seizure pattern. The NeuroPace RNS® System is a device that detects abnormal electrographic activity through intracranial electrodes and administers electrical stimulation to control seizures. Reductions in electrographic activity over days to weeks have been associated with the longer-term efficacy of daily antiseizure medications (ASMs). In this pilot study, electrographic activity over hours to days was examined to assess the impact of a single dose of a proven rescue therapy (diazepam nasal spray) with a rapid onset of action. Adult volunteers (>18 years old) with clinically indicated RNS (stable settings and ASM usage) received a weight-based dose of diazepam nasal spray in the absence of a clinical seizure. Descriptive statistics for a number of detections and a sum of durations of detections at 10-min, hourly, and 24-h intervals during the 7-day (predose) baseline period were calculated. Post-dose detections at each time interval were compared with the respective baseline-detection intervals using a 1 SD threshold. The number of long episodes that occurred after dosing also were compared with the baseline. Five participants were enrolled, and four completed the study; the excluded participant had recurrent seizures during the study. There were no consistent changes (difference >1 SD) in detections between post-dose and mean baseline values. Although variability was high (1 SD was often near or exceeded the mean), three participants showed possible trends for reductions in one or more electrographic variables following treatment. RNS-assessed electrographic detections and durations were not shown to be sensitive measures of short-term effects associated with a single dose of rescue medication in this small group of participants. The variability of detections may have masked a measurable drug effect. Rescue drugs are used to treat seizure clusters. Responsive neurostimulation (RNS) devices detect and record epilepsy brain waves and then send a pulse to help stop seizures. This pilot study looked at whether one dose of a rescue treatment changes brain activity detected by RNS. There was a very wide range of detections, which made it difficult to see if or how the drug changed brain activity. New studies should look at other types of brain activity, multiple doses, and larger patient groups.

Modeling for neurosurgical laser interstitial thermal therapy with and without intracranial recording electrodes

Laser thermal ablation has become a prominent neurosurgical treatment approach, but in epilepsy patients it cannot currently be safely implemented with intracranial recording electrodes that are used to study interictal or epileptiform activity. There is a pressing need for computational models of laser interstitial thermal therapy (LITT) with and without intracranial electrodes to enhance the efficacy and safety of optical neurotherapies. In this paper, we aimed to build a biophysical bioheat and ray optics model to study the effects of laser heating in the brain, with and without intracranial electrodes in the vicinity of the ablation zone during the LITT procedure. COMSOL Multiphysics finite element method (FEM) solver software was used to create a bioheat thermal model of brain tissue, with and without blood flow incorporation via Penne's model, to model neural tissue response to laser heating. We report that the close placement of intracranial electrodes can increase the maximum temperature of the brain tissue volume as well as impact the necrosis region volume if the electrodes are placed too closely to the laser coupled diffuse fiber tip. The model shows that an electrode displacement of 4 mm could be considered a safe distance of intracranial electrode placement away from the LITT probe treatment area. This work, for the first time, models the impact of intracranially implanted recording electrodes during LITT, which could improve the understanding of the LITT treatment procedure on the brain's neural networks a sufficient safe distance to the implanted intracranial recording electrodes. We recommend modeling safe distances for placing the electrodes with respect to the infrared laser coupled diffuse fiber tip.

Insular lobe epilepsy. Part 1: semiology

The insula is often referred to as "the fifth lobe" of the brain, and its accessibility used to be very limited due to the deep location under the opercula as well as the sylvian vasculature. It was not until the availability of modern stereo-electroencephalography (SEEG) technique that the intracranial electrodes could be safely and chronically implanted within the insula, thereby enabling anatomo-electro-clinical correlations in seizures of this deep origin. Since the first report of SEEG-recorded insular seizures in late 1990s, the knowledge of insular lobe epilepsy (ILE) has rapidly expanded. Being on the frontline for the diagnosis and management of epilepsy, neurologists should have a precise understanding of ILE to differentiate it from epilepsies of other lobes or non-epileptic conditions. Owing to the multimodal nature and rich anatomo-functional connections of the insula, ILE has a wide range of clinical presentations. The following symptoms should heighten the suspicion of ILE: somatosensory symptoms involving a large/bilateral cutaneous territory or taking on thermal/painful character, and cervico-laryngeal discomfort. The latter ranges from slight dyspnea to a strong sensation of strangulation (laryngeal constriction). Other symptoms include epigastric discomfort/nausea, hypersalivation, auditory, vestibular, gustatory, and aphasic symptoms. However, most of these insulo-opercular symptoms can easily be masked by those of extra-insular seizure propagation. Indeed, sleep-related hyperkinetic (hypermotor) epilepsy (SHE) is a common clinical presentation of ILE, which shows predominant hyperkinetic and/or tonic-dystonic features that are often indistinguishable from those of fronto-mesial seizures. Subtle objective signs, such as constrictive throat noise (i.e., laryngeal constriction) or aversive behavior (e.g., facial grimacing suggesting pain), are often the sole clue in diagnosing insular SHE. Insular-origin seizures should also be considered in temporal-like seizures without frank anatomo-electro-clinical correlations. All in all, ILE is not the epilepsy of an isolated island but rather of a crucial hub involved in the multifaceted roles of the brain.

Real-time display of intracranial subdural electrodes and the brain surface during an electrode implantation procedure using permeable film.

Subdural electrode (SDE) implantation is an important method of diagnosing epileptogenic lesions and mapping brain function, even with the current preference for stereoelectroencephalography. We developed a novel method to assess SDEs and the brain surface during the electrode implantation procedure using brain images printed onto permeable films and intraoperative fluoroscopy. This method can help verify the location of the electrode during surgery and improve the accuracy of SDE implantation. We performed preoperative imaging by magnetic resonance imaging and computed tomography. Subsequently, the images were edited and fused to visualize the gyrus and sulcus better. We printed the images on permeable films and superimposed them on the intraoperative fluoroscopy display. The intraoperative and postoperative coordinates of the electrodes were obtained after the implantation surgery, and the differences in the locations were calculated. Permeable films were created for a total of eight patients with intractable epilepsy. The median difference of the electrodes between the intraoperative and postoperative images was 4.6 mm (Interquartile range 2.9-7.1). The locations of electrodes implanted outside the operation field were not significantly different from those implanted inside. Our new method may guide the implantation of SDEs into their planned location.

High frequency oscillation network dynamics predict outcome in non-palliative epilepsy surgery.

High frequency oscillations are a promising biomarker of outcome in intractable epilepsy. Prior high frequency oscillation work focused on counting high frequency oscillations on individual channels, and it is still unclear how to translate those results into clinical care. We show that high frequency oscillations arise as network discharges that have valuable properties as predictive biomarkers. Here, we develop a tool to predict patient outcome before surgical resection is performed, based on only prospective information. In addition to determining high frequency oscillation rate on every channel, we performed a correlational analysis to evaluate the functional connectivity of high frequency oscillations in 28 patients with intracranial electrodes. We found that high frequency oscillations were often not solitary events on a single channel, but part of a local network discharge. Eigenvector and outcloseness centrality were used to rank channel importance within the connectivity network, then used to compare patient outcome by comparison with the seizure onset zone or a proportion within the proposed resected channels (critical resection percentage). Combining the knowledge of each patient's seizure onset zone resection plan along with our computed high frequency oscillation network centralities and high frequency oscillation rate, we develop a Naïve Bayes model that predicts outcome (positive predictive value: 100%) better than predicting based upon fully resecting the seizure onset zone (positive predictive value: 71%). Surgical margins had a large effect on outcomes: non-palliative patients in whom most of the seizure onset zone was resected ('definitive surgery', ≥ 80% resected) had predictable outcomes, whereas palliative surgeries (<80% resected) were not predictable. These results suggest that the addition of network properties of high frequency oscillations is more accurate in predicting patient outcome than seizure onset zone alone in patients with most of the seizure onset zone removed and offer great promise for informing clinical decisions in surgery for refractory epilepsy.

Disentanglement of Resting State Brain Networks for Localizing Epileptogenic Zone in Focal Epilepsy.

The objective of this study is to extract pathological brain networks from interictal period of E/MEG recordings to localize epileptic foci for presurgical evaluation. We proposed here a resting state E/MEG analysis framework, to disentangle brain functional networks represented by neural oscillations. By using an Embedded Hidden Markov Model, we constructed a state space for resting state recordings consisting of brain states with different spatiotemporal patterns. Functional connectivity analysis along with graph theory was applied on the extracted brain states to quantify the network features of the extracted brain states, based on which the source location of pathological states is determined. The method is evaluated by computer simulations and our simulation results revealed the proposed framework can extract brain states with high accuracy regarding both spatial and temporal profiles. We further evaluated the framework as compared with intracranial EEG defined seizure onset zone in 10 patients with drug-resistant focal epilepsy who underwent MEG recordings and were seizure free after surgical resection. The real patient data analysis showed very good localization results using the extracted pathological brain states in 6/10 patients, with localization error of about 15mm as compared to the seizure onset zone. We show that the pathological brain networks can be disentangled from the resting-state electromagnetic recording and could be identified based on the connectivity features. The framework can serve as a useful tool in extracting brain functional networks from noninvasive resting state electromagnetic recordings, and promises to offer an alternative to aid presurgical evaluation guiding intracranial EEG electrodes implantation.

Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks

Humans’ ability to adapt and learn relies on reflecting on past performance. These experiences form latent representations called internal states that induce movement variability that improves how we interact with our environment. Our study uncovered temporal dynamics and neural substrates of two states from ten subjects implanted with intracranial depth electrodes while they performed a goal-directed motor task with physical perturbations. We identified two internal states using state-space models: one tracking past errors and the other past perturbations. These states influenced reaction times and speed errors, revealing how subjects strategize from trial history. Using local field potentials from over 100 brain regions, we found large-scale brain networks such as the dorsal attention and default mode network modulate visuospatial attention based on recent performance and environmental feedback. Notably, these networks were more prominent in higher-performing subjects, emphasizing their role in improving motor performance by regulating movement variability through internal states.