Decision-making is an essential cognitive function. It can be impaired due to a number of neurological and psychiatric disorders as well as external factors such as time pressure or stress. To assist users during decision-making, we propose a decision-making brain computer interface (BCI) that can alert to uninformed decision-making, prompt additional information seeking and therefore improve decision-making quality. To this aim, we establish the feasibility of decoding uninformed decision-making from local field potentials recorded with implanted stereo-electroencephalography (sEEG) electrodes in 6 participants. We show that decoding of available information above chance level is possible for all participants, both after stimulus presentation, as well as before task response. Starting from stimulus onset, the temporal processing hierarchy of informed vs. uninformed decision-making spans from visual processing through hippocampal memory processes to frontal control network shifting. The anterior insula, known to be a decision-making hub, codes available information during the decision phase prior to button press. These results further elucidate the neural basis of coded information availability and confirm the feasibility of a decision-making BCI. ### Competing Interest Statement The authors have declared no competing interest. P.W., P.L.K., M.V. and C.H. acknowledge funding by the project INTENSE, 17619 C.H. acknowledges funding by the Kavli Foundation

Objective Stereoelectroencephalography (sEEG) is commonly employed in the workup for epilepsy surgery in patients with focal drug-resistant epilepsy (DRE). Intracranial hemorrhage is a known complication, with reported incidence rates ranging from .9% to 19.1%. Rarely, pseudoaneurysms have been reported in literature as a potential cause. This retrospective cohort study aims to describe the occurrence, clinical characteristics, and management of iatrogenic pseudoaneurysms following sEEG and the clinical outcome of the described cases.Methods A cohort of 395 patients (4067 depth electrodes) with DRE who underwent sEEG was retrospectively analyzed. The identified patients with pseudoaneurysms were analyzed in detail, focusing on timing of detection and location of the aneurysms, clinical characteristics, management strategies, and clinical outcome.Results A symptomatic iatrogenic pseudoaneurysm was identified in six of 395 cases (1.5%), with a per-electrode risk of .15% (6/4067); all occurred at the M2/M3 branches of the middle cerebral artery. All six cases presented with intracerebral or subarachnoid hemorrhage. Aneurysms were detected with combined cerebral computed tomographic angiography (CTA) and digital subtraction angiography (DSA) and treated without complications by surgical clipping or endovascular embolization. The depth electrode implantation and planned sEEG recording had to be either prematurely discontinued or canceled in four of six cases. No patients died; five experienced neurological symptoms and required prolonged hospitalization, with four needing additional rehabilitation.Significance Pseudoaneurysms following sEEG represent a serious complication with significant clinical consequences and warrant early detection and intervention. Occurrence is underreported in literature. It is recommended to use CTA and DSA when a pseudoaneurysm is suspected, particularly in cases of intraparenchymal or subarachnoid hemorrhage, and especially when depth electrodes are in close proximity to a blood vessel.

OBJECTIVE:To investigate whether local lesions created by stereo-electroencephalography (SEEG)-guided radiofrequency thermocoagulation (RFTC) affect distant brain connectivity and excitability in patients with focal, drug-resistant epilepsy (DRE). METHODS:Ten patients with focal DRE underwent SEEG implantation and subsequently 1 Hz bipolar repetitive electrical stimulation (RES) for 30 s before and after RFTC. Root mean square (RMS) of cortico-cortical evoked potentials (CCEPs) was calculated for 15 ms to 300 ms post-stimulation with baseline correction. Contact pairs were categorized as both coagulated, hybrid, or both non-coagulated. The data were divided into nine categories based on the stimulating and recording contact pair combinations. RMS of CCEPs was compared before and after (<12 h) RFTC using a two-sample t test (Hochberg corrected, p < 0.05) for each patient. Boost score, indicating power increase during seizures before RFTC relative to baseline, was analyzed in 4 s windows with 1 s overlap during seizure duration. RESULTS:RFTC altered connectivity across all categories. Of interest, decreases and increases in RMS were observed in connections between non-coagulated contacts distant from coagulation site (range: 1.09-85 mm, median = 17.7 mm, interquartile range [IQR] 10.1-32.3). Contact pairs involved in significantly altered non-coagulated connections showed a higher boost score correlation in the theta, beta, and gamma bands, as well as a stronger maximum correlation with coagulated sites in the delta band than contacts for which connectivity did not change after RFTC. SIGNIFICANCE:This study highlights how local lesions alter distant brain connectivity, providing insights for future research on epilepsy network changes and seizure outcomes following RFTC.

Reaching out your hand is an effortless yet complex behavior that is indispensable in daily life. Neural correlates of reaching behavior have been observed and decoded beyond the motor cortex, but the degree and granularity of movement representation are not fully understood. Here, we decode 12 kinematics of goal-directed reaching behavior from 18 participants implanted with stereotactic-electroencephalography electrodes performing a 3D reaching task. The decoder is able to decode continuous movement kinematics using low-, mid-, and high-frequency information in all participants using preferential subspace identification. Neural correlates of movements are observed throughout the brain, including deeper structures. Switching to a goal-centric reference frame enables the decoder to decode hand position, indicating that low-frequency activity is involved in higher-order processing of movements. Our results strengthen the evidence that brain-wide motor-related dynamics can be decoded and may provide opportunities for brain-computer interfaces for individuals with a compromised motor cortex.

Speech brain-computer interfaces (BCIs) offer a solution for those affected by speech impairments by decoding brain activity into speech. Current neuroprosthetics focus on the motor cortex, which might not be suitable for all patient populations. We investigate potential alternative targets for a speech BCI across a brain-wide distribution. Thirty participants are recorded with intracranial electroencephalography during speech production. We continuously predict speech from a brain-wide global to a single-channel local scale, across anatomical features. We find significant speech detection accuracy in both gray and white matter, no significant difference between gyri and sulci, and limited contribution from subcortical areas. Potential targets are located within the depths of and surrounding the lateral fissure bilaterally, such as the (sub)central sulcus, the transverse temporal gyrus, the supramarginal cortex, and parts of the insula. The results highlight the potential benefit of extending beyond the motor cortical surface and reaching the sulcal depth for speech neuroprostheses.

Introduction: Periventricular nodular heterotopias (PVNH) are developmental abnormalities with neurons abnormally clustered around the cerebral ventricles. Patients frequently present with focal drug-resistant epilepsy (DRE). However, the relationship between PVNH and the seizure onset zone (SOZ) is complex. Stereo-electroencephalography (SEEG) is an invasive diagnostic procedure for patients with DRE. In selected patients, the SEEG may be converted into a therapeutic procedure, lesioning the probable (SOZ) with pulsed radiofrequency thermocoagulation (RFTC). The aim of our study was to evaluate the efficacy and safety of SEEGRFTC in a series of DRE patients with PVNH. Methods: Twenty-four patients with focal DRE related to PVNH and treated with SEEG-guided-RFTC restricted to nodules were prospectively collected between 2016 and 2023 and retrospectively analyzed after a follow-up of at least 12 months. Results: Seventeen patients (71 %) responded (ILAE class 1-4) after SEEG-guided RFTC of whom eleven (46 %) became seizure-free (class 1) at last follow up, nine (45 %) despite residual PVNH tissue on MRI. SEEG seizure onset was restricted to PVNH in eleven patients (class 1 in 45 %) and simultaneously in PVNH and other cortical areas in thirteen patients (class 1 in 46 %). Out of 31 SEEG-RFTC procedures in twenty-four patients, adverse events, related to RFTC, were recorded in eight (26 %), of which two patients (8 %) had predicted permanent visual complaints whilst the other five had transient complaints. Significance: This study demonstrates that a considerable percentage of patients, even with bilateral, multiple PVNH and involvement of adjacent cortical regions can be rendered seizure-free with SEEG-guided-RFTC restricted to the nodules. Furthermore, this study delivers evidence that the complete destruction of the entire nodule is not necessary to render a patient seizure free. This justifies the use of SEEG in patients with single, multiple or bilateral PVNHs to provide insight into the epileptogenic organization in and around these lesions.

ObjectiveIctal Single Photon Emission Computed Tomography (SPECT) and stereo-electroencephalography (SEEG) are diagnostic techniques used for the management of patients with drug-resistant focal epilepsies. While hyperperfusion patterns in ictal SPECT studies reveal seizure onset and propagation pathways, the role of ictal hypoperfusion remains poorly understood. The goal of this study was to systematically characterize the spatio-temporal information flow dynamics between differently perfused brain regions using stereo-EEG recordings.MethodsWe identified seizure-free patients after resective epilepsy surgery who had prior ictal SPECT and SEEG investigations. We estimated directional connectivity between the epileptogenic-zone (EZ), non-resected areas of hyperperfusion, hypoperfusion, and baseline perfusion during the interictal, preictal, ictal, and postictal periods.ResultsCompared to the background, we noted significant information flow (1) during the preictal period from the EZ to the baseline and hyperperfused regions, (2) during the ictal onset from the EZ to all three regions, and (3) during the period of seizure evolution from the area of hypoperfusion to all three regions.ConclusionsHypoperfused brain regions were found to indirectly interact with the EZ during the ictal period.SignificanceOur unique study, combining intracranial electrophysiology and perfusion imaging, presents compelling evidence of dynamic changes in directional connectivity between brain regions during the transition from interictal to ictal states.

Using brain activity directly as input for assistive tool control can circumventmuscular dysfunction and increase functional independence for physically impaired people. The motor cortex is commonly targeted for recordings, while growing evidence shows that there exists decodable movement-related neural activity outside of the motor cortex. Several decoding studies demonstrated significant decoding from distributed areas separately. Here, we combine information from all recorded non-motor brain areas and decode executed and imagined movements using a Riemannian decoder. We recorded neural activity from 8 epilepsy patients implanted with stereotactic-electroencephalographic electrodes (sEEG), while they performed an executed and imagined grasping tasks. Before decoding, we excluded all contacts in or adjacent to the central sulcus. The decoder extracts a low-dimensional representation of varying number of components, and classified move/no-move using a minimum-distance-to-geometric-mean Riemannian classifier. We show that executed and imagined movements can be decoded from distributed non-motor brain areas using a Riemannian decoder, reaching an area under the receiver operator characteristic of 0.83 ± 0.11. Furthermore, we highlight the distributedness of the movement-related neural activity, as no single brain area is the main driver of performance. Our decoding results demonstrate a first application of a Riemannian decoder on sEEG data and show that it is able to decode from distributed brain-wide recordings outside of the motor cortex. This brief report highlights the perspective to explore motor-related neural activity beyond the motor cortex, as many areas contain decodable information.

Insulaire epilepsie wordt vaak gezien als imitator van andere focale vormen van epilepsie zoals temporaalkwab-, pariëtaalkwab- of frontaalkwabepilepsie. Indien er een goede klinische hypothese bestaat, kan er gericht prechirurgische diagnostiek plaatsvinden, inclusief intracranieel onderzoek middels stereo-EEG. In deze bijdrage wordt een voorstel gedaan voor een beslisboom, als ondersteuning bij de keuze voor de meest aangewezen minimaal invasieve behandeling van een individuele patiënt met insulaire epilepsie.

In een eerdere bijdrage die verscheen in het maartnummer van ‘Epilepsie’ werd uitgaande van een tweetal casussen, de klinische semiologie passend bij insulaire epilepsie beschreven, in relatie met de anatomische gebieden van de insula. In deze bijdrage wordt ingegaan op de meest aangewezen diagnostiek en de invasieve behandeling van deze patiënten.

Ideally, decisions are made based on prior knowledge, which allows for informed choices. Real life, however, often requires us to make decisions arbitrarily, without sufficient information. Decoding decision making processes from neural activity could allow for cognitive neuroprostheses and Brain-Computer Interfaces (BCIs) to support decision processes in rapid human-machine interactions, weigh decision-making confidence, and further enable neuromodulation protocols for the treatment of reward-related dysfunctions. To understand the differences between the decision-making processes in arbitrary and informed decisions, we recorded intracranial electroencephalography in a large number of cortical and subcortical areas from 5 patients during a categorization task. We demonstrate that individual decisions can be decoded from Local Field Potentials (LFPs) before motor response, in both arbitrary and informed conditions. Our analysis revealed dissimilar spatio-temporal patterns between arbitrary and informed decision-making, with arbitrary decisions being decodable in fewer brain regions and earlier in time compared to informed decisions.

Brain surgery is the only curative treatment for people with focal epilepsy, but it is unclear whether this induces active disease in multiple sclerosis (MS). This creates a barrier to evaluate MS patients for epilepsy surgery. We present two cases of successful epilepsy surgery in patients with pharmacoresistant epilepsy and stable MS and give an overview of the existing literature. (1) a 28-year-old woman with seizures arising from a right basal temporo-occipital ganglioglioma was seizure-free after surgery, without MS relapse but with one new MS lesion postsurgically. (2) a 46-year-old woman with seizures arising from a natalizumab-associated progressive multifocal leukoencephalopathy (PML) lesion in the right frontal lobe was seizure-free after surgery preceded by extraoperative subdural electrocorticography, with new subclinical MS lesions. We are the first to report brain surgery in a PML survivor. Both patients stabilized radiologically after initiating second-line therapies. Successful epilepsy surgery can substantially increase the quality of life in patients with pharmacoresistant epilepsy and MS. With increasing survival rates of brain tumors and PML, the risk-benefit ratio of epilepsy surgery compared to a potential MS relapse after surgery becomes critically important. Shared decision-making is valuable for balancing the risks related to both diseases.

Using brain activity directly as input for assistive tool control can circumvent muscular dysfunction and increase functional independence for physically impaired people. Most invasive motor decoding studies focus on decoding neural signals from the primary motor cortex, which provides a rich but superficial and spatially local signal. Initial non-primary motor cortex decoding endeavors have used distributed recordings to demonstrate decoding of motor activity by grouping electrodes in mesoscale brain regions. While these studies show that there is relevant and decodable movement related information outside the primary motor cortex, these methods are still exclusionary to other mesoscale areas, and do not capture the full informational content of the motor system. In this work, we recorded intracranial EEG of 8 epilepsy patients, including all electrode contacts except those contacts in or adjacent to the central sulcus. We show that executed and imagined movements can be decoded from non-motor areas; combining all non-motor contacts into a lower dimensional representation provides enough information for a Riemannian decoder to reach an area under the curve of 0.83 ± 0.11. Additionally, by training our decoder on executed and testing on imagined movements, we demonstrate that between these two conditions there exists shared distributed information in the beta frequency range. By combining relevant information from all areas into a lower dimensional representation, the decoder was able to achieve high decoding results without information from the primary motor cortex. This representation makes the decoder more robust to perturbations, signal non-stationarities and neural tissue degradation. Our results indicate to look beyond the motor cortex and open up the way towards more robust and more versatile brain-computer interfaces.

Single-photon emission computed tomography (SPECT) during seizures and magnetoencephalography (MEG) during the interictal state are noninvasive modalities employed in the localization of the epileptogenic zone in patients with drug-resistant focal epilepsy (DRFE). The present study aims to investigate whether there exists a preferentially high MEG functional connectivity (FC) among those regions of the brain that exhibit hyperperfusion or hypoperfusion during seizures. We studied MEG and SPECT data in 30 consecutive DRFE patients who had resective epilepsy surgery. We parcellated each ictal perfusion map into 200 regions of interest (ROIs) and generated ROI time series using source modeling of MEG data. FC between ROIs was quantified using coherence and phase-locking value. We defined a generalized linear model to relate the connectivity of each ROI, ictal perfusion z score, and distance between ROIs. We compared the coefficients relating perfusion z score to FC of each ROI and estimated the connectivity within and between resected and unresected ROIs. We found that perfusion z scores were strongly correlated with the FC of hyper-, and separately, hypoperfused ROIs across patients. High interictal connectivity was observed between hyperperfused brain regions inside and outside the resected area. High connectivity was also observed between regions of ictal hypoperfusion. Importantly, the ictally hypoperfused regions had a low interictal connectivity to regions that became hyperperfused during seizures. We conclude that brain regions exhibiting hyperperfusion during seizures highlight a preferentially connected interictal network, whereas regions of ictal hypoperfusion highlight a separate, discrete and interconnected, interictal network.

Speech production is an intricate process involving a large number of muscles and cognitive processes. The neural processes underlying speech production are not completely understood. As speech is a uniquely human ability, it can not be investigated in animal models. High-fidelity human data can only be obtained in clinical settings and is therefore not easily available to all researchers. Here, we provide a dataset of 10 participants reading out individual words while we measured intracranial EEG from a total of 1103 electrodes. The data, with its high temporal resolution and coverage of a large variety of cortical and sub-cortical brain regions, can help in understanding the speech production process better. Simultaneously, the data can be used to test speech decoding and synthesis approaches from neural data to develop speech Brain-Computer Interfaces and speech neuroprostheses.

ABSTRACTSpeech production is an intricate process involving a large number of muscles and cognitive processes. The neural processes underlying speech production are not completely understood. As speech is a uniquely human ability, it can not be investigated in animal models. High-fidelity human data can only be obtained in clinical settings and is therefore not easily available to all researchers. Here, we provide a dataset of 10 participants reading out individual words while we measured intracranial EEG from a total of 1103 electrodes. The data, with its high temporal resolution and coverage of a large variety of cortical and sub-cortical brain regions, can help in understanding the speech production process better. Simultaneously, the data can be used to test speech decoding and synthesis approaches from neural data to develop speech Brain-Computer Interfaces and speech neuroprostheses.

Hoewel ictale single-photon emission computed tomography van de hersenen reeds vele jaren gebruikt wordt als vooronderzoek voor epilepsiechirurgie, komen in deze bijdrage enkele nieuwe inzichten ter sprake die cruciaal zijn voor de klinische interpretatie van dit onderzoek.

In deze bijdrage een weergave van de ervaringen met thermocoagulatie van epileptogene zones in het Academisch Centrum voor Epileptologie, Kempenhaeghe/MUMC+. Besproken worden de uitkomst na behandeling (wel/niet aanvalsvrij) in relatie met verschillen in lokalisatie, type onderliggend lijden en uitgebreidheid van de epileptogene zone, evenals mogelijke complicaties na behandeling. De afgelopen jaren is het indicatiegebied iets uitgebreid maar het grootste deel bestaat uit patiënten met periventriculaire heterotopieën.

Speech Neuroprostheses have the potential to enable communication for people with dysarthria or anarthria. Recent advances have demonstrated high-quality text decoding and speech synthesis from electrocorticographic grids placed on the cortical surface. Here, we investigate a less invasive measurement modality in three participants, namely stereotactic EEG (sEEG) that provides sparse sampling from multiple brain regions, including subcortical regions. To evaluate whether sEEG can also be used to synthesize high-quality audio from neural recordings, we employ a recurrent encoder-decoder model based on modern deep learning methods. We find that speech can indeed be reconstructed with correlations up to 0.8 from these minimally invasive recordings, despite limited amounts of training data.