Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex.

Subdural electrocorticography (ECoG) is a valuable technique for neuroscientific research and for emerging neurotechnological clinical applications. As ECoG grids accommodate increasing numbers of electrodes and higher densities with new manufacturing methods, the question arises at what point the benefit of higher density ECoG is outweighed by spatial oversampling. To clarify the optimal spacing between ECoG electrodes, in the current study we evaluate how ECoG grid density relates to the amount of non-shared neurophysiological information between electrode pairs, focusing on the sensorimotor cortex. We simultaneously recorded high-density (HD, 3 mm pitch) and ultra-high-density (UHD, 0.9 mm pitch) ECoG, obtained intraoperatively from six participants. We developed a new metric, the normalized differential root mean square (ndRMS), to quantify the information that is not shared between electrode pairs. The ndRMS increases with inter-electrode center-to-center distance up to 15 mm, after which it plateaus. We observed differences in ndRMS between frequency bands, which we interpret in terms of oscillations in frequencies below 32 Hz with phase differences between pairs, versus (un)correlated signal fluctuations in the frequency range above 64 Hz. The finding that UHD recordings yield significantly higher ndRMS than HD recordings is attributed to the amount of tissue sampled by each electrode. These results suggest that ECoG densities with submillimeter electrode distances are likely justified.

Normative atlases of high-frequency oscillation and spike rates under Sevoflurane anesthesia.

OBJECTIVE: We analyzed the dose-dependent effects of Sevoflurane anesthesia on high-frequency oscillations (HFOs) and spike discharges at non-epileptic sites and evaluated their effectiveness in identifying the epileptogenic zone. METHODS: We studied 21 children with drug-resistant focal epilepsy who achieved seizure control after focal resective surgery. Open-source detectors quantified HFO and spike rates during extraoperative and intraoperative intracranial EEG recordings performed before resection. We determined under which anesthetic conditions HFO and spike rates differentiated the seizure onset zone (SOZ) within the resected area from non-epileptic sites. RESULTS: We analyzed 925 artifact-free electrodes, including 867 at non-epileptic sites and 58 at SOZ sites. Higher Sevoflurane doses significantly increased HFO and spike rates at non-epileptic sites, exhibiting spatial variability among different detectors. These biomarkers were elevated in the SOZ more than in non-epileptic sites under 2-4 vol% Sevoflurane anesthesia, with Cohen's d effect sizes above 3.0 and Mann-Whitney U-Test r effect sizes above 0.5. CONCLUSIONS: We provided normative atlases of HFO and spike rates under different Sevoflurane anesthesia conditions. Sevoflurane elevates HFO and spike rates preferentially in the epileptogenic zone. SIGNIFICANCE: Assessing the relative severity of biomarker levels across sites may be relevant for localizing the epileptogenic zone under Sevoflurane anesthesia.

Mapping cognitive activity from electrocorticography field potentials in humans performing NBack task.

Objective. Advancements in data science and assistive technologies have made invasive brain-computer interfaces (iBCIs) increasingly viable for enhancing the quality of life in physically disabled individuals. Intracortical microelectrode implants are a common choice for such a communication system due to their fine temporal and spatial resolution. The small size of these implants makes the implantation plan critical for the successful exfiltration of information, particularly when targeting representations of task goals that lack robust anatomical correlates.Approach. Working memory processes including encoding, retrieval, and maintenance are observed in many areas of the brain. Using human electrocorticography (ECoG) recordings during a working memory experiment, we provide proof that it is possible to localize cognitive activity associated with the task and to identify key locations involved with executive memory functions.Results.From the analysis, we could propose an optimal iBCI implant location with the desired features. The general approach is not limited to working memory but could also be used to map other goal-encoding factors such as movement intentions, decision-making, and visual-spatial attention.Significance. Deciphering the intended action of a BCI user is a complex challenge that involves the extraction and integration of cognitive factors such as movement planning, working memory, visual-spatial attention, and the decision state. Examining field potentials from ECoG electrodes while participants engaged in tailored cognitive tasks can pinpoint location with valuable information related to anticipated actions. This manuscript demonstrates the feasibility of identifying electrodes involved in cognitive activity related to working memory during user engagement in the NBack task. Devoting time in meticulous preparation to identify the optimal brain regions for BCI implant locations will increase the likelihood of rich signal outcomes, thereby improving the overall BCI user experience.

AB073. Electrocorticography high-gamma dynamics during intraoperative hand movement mapping.

BACKGROUND: Intraoperative functional mapping for glioma resection often necessitates awake craniotomies, requiring active patient participation. This procedure presents challenges for both the surgical team and the patient. Thus, minimizing mapping time becomes crucial. Passive mapping utilizing electrocorticography (ECoG) presents a promising approach to reduce intraoperative mapping efforts via direct electrical stimulation. This study aims to identify an efficient mapping protocol for hand movement by optimizing mapping duration and localization accuracy. METHODS: Three glioma patients (two males, one female) underwent awake craniotomy for tumor resection at Asahikawa Medical University Hospital and Kindai University in Osaka. Patients were maintained at a bispectral index (BIS) level above 90 to ensure wakefulness during mapping. Data were collected using a DC-coupled g.HIamp biosignal amplifier, digitized with 24-bit resolution at a minimum sampling rate of 1,200 Hz. Each session comprised ten runs, each lasting 250 seconds, consisting of a 12-second rest phase (baseline) followed by a 12-second grasping period containing ten grasping movements. High-gamma activity (HGA, 60-170 Hz) was recorded from ECoG locations on the pre- and postcentral gyrus. Locations exhibiting significant grasping-related HGA, with stronger responses during early trials within a run, were classified as "attenuated". RESULTS: Among 37 electrodes on the sensorimotor cortex, 16 exhibited significant HGA during grasping. Three locations demonstrated significant attenuation after three runs, with one location showing attenuation after the first three trials within a run. CONCLUSIONS: The observed attenuation effect of short-term repeated movements during intraoperative monitoring is relatively modest initially. However, as the number of repeated grasping blocks increases, the number of attenuated locations also rises. Consequently, minimizing overall mapping time, rather than reducing the number of tasks per block, is paramount. For statistical analysis, a minimum of 20 grasping trials (two runs of ten movements) or 48 seconds of motor mapping is recommended. Alternatively, a mapping protocol involving a third run or 30 grasping trials (72 seconds) may enhance data robustness. These preliminary findings, though based on a limited patient cohort, warrant confirmation and further investigation, particularly in epilepsy patients.

Novel technique of switching TIVA and sevoflurane during epilepsy surgery for combined intraoperative motor evoked potentials monitoring and electrocorticography: an illustrative case report.

BACKGROUND: During epilepsy surgery, it is equally important to record electrocorticography (ECoG) for detecting epileptogenic activity and guiding brain resection, and to evaluate neuromonitoring data, particularly motor evoked potentials (MEP), for avoidance of postoperative neurological complications. However, sevoflurane, which is commonly used during recording of ECoG, may attenuate the MEP response. It enforces anesthesiologists and neurosurgeons to select one anesthetic agent over another, facilitating either ECoG or MEP monitoring. CASE PRESENTATION: In the presented case of a 20-year-old man, who underwent surgery for temporal lobe epilepsy, a novel technique of neuroanesthesia was introduced, integrating initial induction of the total intravenous anesthesia (TIVA) with propofol (effect-site concentration, 2.3-3.0 µg/ml), its subsequent switching to sevoflurane (end-tidal concentration, 2.5%) for ECoG recording, and further change back to TIVA for MEP monitoring during brain resection. CONCLUSIONS: Intraoperative switch of anesthetic agents according to specific intraoperative requirements may be useful for cases of brain surgery requiring both ECoG recordings and MEP monitoring.

The effect of common parameters of bipolar stimulation on brain evoked potentials.

OBJECTIVE: To identify optimal bipolar stimulation parameters for robust generation of brain evoked potentials (BEPs), namely the interelectrode distance (IED) and the intensity of stimulation (IS), in cortical and axonal stimulation. METHODS: In 15 patients who underwent awake surgery for brain tumor removal, BEPs were elicited at different values of IED and IS, respectively: 5 mm-5 mA, 5 mm-10 mA, and 10 mm-10 mA. The number of BEPs elicited by stimulation, as well as the delays and amplitudes of the N1 waves were compared between the different groups of stimulation parameters and according to the stimulated brain structure (cortical vs. axonal). RESULTS: The amplitudes of N1 increased with the intensity of bipolar stimulation, either in cortical or axonal stimulation, while N1 peak delays were not affected by the stimulation parameters. Furthermore, axonal stimulation produced more N1s than cortical stimulation, with lower latencies. CONCLUSIONS: Understanding the relationship between stimulation parameters and BEP is of utmost importance to determine whether the generated N1 waves accurately reflect the underlying structural anatomy. Other factors, such as stimulation frequency or pulse width and shape, may also play a role and warrant further investigation. SIGNIFICANCE: This study represents the first step in describing the influence of common bipolar stimulation parameters on robustness of BEPs by examining the impact of IED and IS on the N1 wave.

Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction. NEW METHOD: This study introduces a 3D convolutional neural network (3D-CNN) model to decode finger movements using ECoG data. The model employs adaptive, explainable AI (xAI) techniques to interpret the physiological relevance of brain signals. ECoG signals from epilepsy patients during awake craniotomy were processed to extract power spectral density across multiple frequency bands. These data formed a 3D matrix used to train the 3D-CNN to predict finger trajectories. RESULTS: The 3D-CNN model showed significant accuracy in predicting finger movements, with root-mean-square error (RMSE) values of 0.26-0.38 for single finger movements and 0.20-0.24 for combined movements. Explainable AI techniques, Grad-CAM and SHAP, identified the high gamma (HG) band as crucial for movement prediction, showing specific cortical regions involved in different finger movements. These findings highlighted the physiological significance of the HG band in motor control. COMPARISON WITH EXISTING METHODS: The 3D-CNN model outperformed traditional machine learning approaches by effectively capturing spatial and temporal patterns in ECoG data. The use of xAI techniques provided clearer insights into the model's decision-making process, unlike the "black box" nature of standard deep learning models. CONCLUSIONS: The proposed 3D-CNN model, combined with xAI methods, enhances the decoding accuracy of finger movements from ECoG data. This approach offers a more efficient and interpretable solution for brain-computer interface (BCI) applications, emphasizing the HG band's role in motor control.

Low-Frequency Oscillations in Mid-rostral Dorsolateral Prefrontal Cortex Support Response Inhibition.

Executive control of movement enables inhibiting impulsive responses critical for successful navigation of the environment. Circuits mediating stop commands involve prefrontal and basal ganglia structures with fMRI evidence demonstrating increased activity during response inhibition in the dorsolateral prefrontal cortex (dlPFC)-often ascribed to maintaining task attentional demands. Using direct intraoperative cortical recordings in male and female human subjects, we investigated oscillatory dynamics along the rostral-caudal axis of dlPFC during a modified Go/No-go task, probing components of both proactive and reactive motor control. We assessed whether cognitive control is topographically organized along this axis and observed that low-frequency power increased prominently in mid-rostral dlPFC when inhibiting and delaying responses. These findings provide evidence for a key role for mid-rostral dlPFC low-frequency oscillations in sculpting motor control.

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations.

Effective communication hinges on a mutual understanding of word meaning in different contexts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We developed a model-based coupling framework that aligns brain activity in both speaker and listener to a shared embedding space from a large language model (LLM). The context-sensitive LLM embeddings allow us to track the exchange of linguistic information, word by word, from one brain to another in natural conversations. Linguistic content emerges in the speaker's brain before word articulation and rapidly re-emerges in the listener's brain after word articulation. The contextual embeddings better capture word-by-word neural alignment between speaker and listener than syntactic and articulatory models. Our findings indicate that the contextual embeddings learned by LLMs can serve as an explicit numerical model of the shared, context-rich meaning space humans use to communicate their thoughts to one another.

International Delirium Pathophysiology & Electrophysiology Network for Data sharing (iDEPEND).

In an era of 'big data', we propose that a collaborative network approach will drive a better understanding of the mechanisms of delirium, and more rapid development of therapies. We have formed the International Delirium Pathophysiology & Electrophysiology Network for Data sharing (iDEPEND) group with a key aim to 'facilitate the study of delirium pathogenesis with electrophysiology, imaging, and biomarkers including data acquisition, analysis, and interpretation'. Our initial focus is on studies of electrophysiology as we anticipate this methodology has great potential to enhance our understanding of delirium. Our article describes this principle and is used to highlight the endeavour to the wider community as we establish key stakeholders and partnerships.

Inkjet-Printed, Flexible Organic Electrochemical Transistors for High-Performance Electrocorticography Recordings.

Organic electrochemical transistors (OECTs) have emerged as powerful tools for biosignal amplification, including electrocorticography (ECoG). However, their widespread application has been limited by the complexities associated with existing fabrication techniques, restricting accessibility and scalability. Here, we introduce a novel all-planar, all-printed high-performance OECT device that significantly enhances the accuracy and sensitivity of ECoG recordings. Achieved through an innovative three-step drop-on-demand inkjet printing process on flexible substrates, our device offers a rapid response time of 0.5 ms, a compact channel area of 1950 µm2, and is characterized by a transconductance of 11 mS. This process not only simplifies integration but also reduces costs. Our optimized in-plane gate voltage control facilitates operation at peak transconductance, which elevates the signal-to-noise ratio (SNR) by up to 133%. In vivo evaluations in a rat model of seizure demonstrate the device's performance in recording distinct electrographic phases, surpassing the capabilities of PEDOT:PSS-coated gold-based ultralow impedance passive electrodes, achieving a high SNR of 48 db. Our results underscore the potential of Inkjet-printed OECTs in advancing the accessibility and accuracy of diagnostic tools that could enhance patient care by facilitating timely detection of neurological conditions.

Iterative alignment discovery of speech-associated neural activity.

Objective. Brain-computer interfaces (BCIs) have the potential to preserve or restore speech in patients with neurological disorders that weaken the muscles involved in speech production. However, successful training of low-latency speech synthesis and recognition models requires alignment of neural activity with intended phonetic or acoustic output with high temporal precision. This is particularly challenging in patients who cannot produce audible speech, as ground truth with which to pinpoint neural activity synchronized with speech is not available.Approach. In this study, we present a new iterative algorithm for neural voice activity detection (nVAD) called iterative alignment discovery dynamic time warping (IAD-DTW) that integrates DTW into the loss function of a deep neural network (DNN). The algorithm is designed to discover the alignment between a patient's electrocorticographic (ECoG) neural responses and their attempts to speak during collection of data for training BCI decoders for speech synthesis and recognition.Main results. To demonstrate the effectiveness of the algorithm, we tested its accuracy in predicting the onset and duration of acoustic signals produced by able-bodied patients with intact speech undergoing short-term diagnostic ECoG recordings for epilepsy surgery. We simulated a lack of ground truth by randomly perturbing the temporal correspondence between neural activity and an initial single estimate for all speech onsets and durations. We examined the model's ability to overcome these perturbations to estimate ground truth. IAD-DTW showed no notable degradation (<1% absolute decrease in accuracy) in performance in these simulations, even in the case of maximal misalignments between speech and silence.Significance. IAD-DTW is computationally inexpensive and can be easily integrated into existing DNN-based nVAD approaches, as it pertains only to the final loss computation. This approach makes it possible to train speech BCI algorithms using ECoG data from patients who are unable to produce audible speech, including those with Locked-In Syndrome.

Prospects of Electrocorticography in Neuropharmacological Studies in Small Laboratory Animals.

Electrophysiological methods of research are widely used in neurobiology. To assess the bioelectrical activity of the brain in small laboratory animals, electrocorticography (ECoG) is most often used, which allows the recording of signals directly from the cerebral cortex. To date, a number of methodological approaches to the manufacture and implantation of ECoG electrodes have been proposed, the complexity of which is determined by experimental tasks and logistical capabilities. Existing methods for analyzing bioelectrical signals are used to assess the functional state of the nervous system in test animals, as well as to identify correlates of pathological changes or pharmacological effects. The review presents current areas of applications of ECoG in neuropharmacological studies in small laboratory animals. Traditionally, this method is actively used to study the antiepileptic activity of new molecules. However, the possibility of using ECoG to assess the neuroprotective activity of drugs in models of traumatic, vascular, metabolic, or neurodegenerative CNS damage remains clearly underestimated. Despite the fact that ECoG has a number of disadvantages and methodological difficulties, the recorded data can be a useful addition to traditional molecular and behavioral research methods. An analysis of the works in recent years indicates a growing interest in the method as a tool for assessing the pharmacological activity of psychoactive drugs, especially in combination with classification and prediction algorithms.

Dopamine and deep brain stimulation accelerate the neural dynamics of volitional action in Parkinson's disease.

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinson's disease is associated with impaired action initiation, also termed akinesia. Both dopamine and subthalamic deep brain stimulation (DBS) can alleviate akinesia, but the underlying mechanisms are unknown. An important question is whether dopamine and DBS facilitate de novo build-up of neural dynamics for motor execution or accelerate existing cortical movement initiation signals through shared modulatory circuit effects. Answering these questions can provide the foundation for new closed-loop neurotherapies with adaptive DBS, but the objectification of neural processing delays prior to performance of volitional action remains a significant challenge. To overcome this challenge, we studied readiness potentials and trained brain signal decoders on invasive neurophysiology signals in 25 DBS patients (12 female) with Parkinson's disease during performance of self-initiated movements. Combined sensorimotor cortex electrocorticography and subthalamic local field potential recordings were performed OFF therapy (n = 22), ON dopaminergic medication (n = 18) and on subthalamic deep brain stimulation (n = 8). This allowed us to compare their therapeutic effects on neural latencies between the earliest cortical representation of movement intention as decoded by linear discriminant analysis classifiers and onset of muscle activation recorded with electromyography. In the hypodopaminergic OFF state, we observed long latencies between motor intention and motor execution for readiness potentials and machine learning classifications. Both, dopamine and DBS significantly shortened these latencies, hinting towards a shared therapeutic mechanism for alleviation of akinesia. To investigate this further, we analysed directional cortico-subthalamic oscillatory communication with multivariate granger causality. Strikingly, we found that both therapies independently shifted cortico-subthalamic oscillatory information flow from antikinetic beta (13-35 Hz) to prokinetic theta (4-10 Hz) rhythms, which was correlated with latencies in motor execution. Our study reveals a shared brain network modulation pattern of dopamine and DBS that may underlie the acceleration of neural dynamics for augmentation of movement initiation in Parkinson's disease. Instead of producing or increasing preparatory brain signals, both therapies modulate oscillatory communication. These insights provide a link between the pathophysiology of akinesia and its' therapeutic alleviation with oscillatory network changes in other non-motor and motor domains, e.g. related to hyperkinesia or effort and reward perception. In the future, our study may inspire the development of clinical brain computer interfaces based on brain signal decoders to provide temporally precise support for action initiation in patients with brain disorders.

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation.

Objective.Micro-electrocorticographic (µECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to useµECoG arrays to decode, in rats, body position during open field navigation, through isolated single-unit activities.Approach. µECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300-3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns.Main results.Single-unit spikes could be extracted during chronic recording fromµECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively.Significance. µECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.

Recording of hippocampal activity on the effect of convulsant doses of caffeine.

Seizures occur when there is a hyper-excitation of the outer layer of the brain, with subsequent excessive synchrony in a group of neurons. According to the World Health Organization (WHO), an estimated 50 million people are affected by this disease, a third of whom are resistant to the treatments available on the market. Caffeine (1,3,7-trimethylxanthine), which belongs to the purine alkaloid family, is the most widely consumed psychoactive drug in the world. It is ingested by people through drinks containing this substance, such as coffee, and as an adjuvant in analgesic therapy with non-steroidal antiflammatory drugs. The present study evaluated the electrocorticographic changes observed in the hippocampus of Wistar rats subjected to acute doses of caffeine (150 mg/kg i.p), which represents a toxic dose of caffeine corresponding to an estimated acute intake of more than 12 cups of coffee to record its convulsant activity. Our results showed, for the first time, that the administration of high doses of caffeine (150 mg/kg i.p.) in rats caused an increase in the spectral distribution of power in all frequency bands and suggested the appearance of periods of ictal and interictal peaks in the electrocorticogram (ECog). We have also shown that the anticonvulsants phenytoin, diazepam and phenobarbital have a satisfactory response when associated with caffeine.

Evoking artificial speech perception through invasive brain stimulation for brain-computer interfaces: current challenges and future perspectives.

Encoding artificial perceptions through brain stimulation, especially that of higher cognitive functions such as speech perception, is one of the most formidable challenges in brain-computer interfaces (BCI). Brain stimulation has been used for functional mapping in clinical practices for the last 70 years to treat various disorders affecting the nervous system, including epilepsy, Parkinson's disease, essential tremors, and dystonia. Recently, direct electrical stimulation has been used to evoke various forms of perception in humans, ranging from sensorimotor, auditory, and visual to speech cognition. Successfully evoking and fine-tuning artificial perceptions could revolutionize communication for individuals with speech disorders and significantly enhance the capabilities of brain-computer interface technologies. However, despite the extensive literature on encoding various perceptions and the rising popularity of speech BCIs, inducing artificial speech perception is still largely unexplored, and its potential has yet to be determined. In this paper, we examine the various stimulation techniques used to evoke complex percepts and the target brain areas for the input of speech-like information. Finally, we discuss strategies to address the challenges of speech encoding and discuss the prospects of these approaches.

Intralesional epileptiform activity in a fourth ventricular hamartoma associated with epileptic hemifacial spasm in a toddler: illustrative case.

BACKGROUND: Focal epilepsy caused by a posterior fossa lesion is a rare phenomenon. In these cases, seizure onset typically occurs during the first few months of life, with episodes of epileptic hemifacial spasms and abnormal eye movements. Patients often present with drug-resistant epilepsy and often require resection for the best chance of seizure freedom. OBSERVATIONS: The authors present the case of a 19-month-old male with intractable epileptic hemifacial spasms and a dorsally exophytic right brainstem and middle cerebellar peduncle hamartoma, following 2 prior subtotal resections. The authors recommended a third suboccipital craniotomy with intraoperative electrocorticography, which revealed interictal spiking from an intralesional depth electrode. Near-total resection led to durable seizure freedom. LESSONS: Although posterior fossa lesions are rarely associated with epileptiform activity, this case demonstrates that pediatric patients with epileptic hemifacial spasms associated with a posterior fossa lesion may respond favorably to resection. Furthermore, this case demonstrates that intralesional electrocorticography can detect epileptic activity in posterior fossa lesions, which may predict postoperative seizure outcomes. https://thejns.org/doi/10.3171/CASE2452.

Gamma amplitude-envelope correlations are strongly elevated within hyperexcitable networks in focal epilepsy.

Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40-200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that in the gamma band, AECs between nodes within SOZs are markedly elevated relative to those elsewhere. AEC-based node strength, eigencentrality, and clustering coefficient are also robustly increased within the SOZ with maxima in the low-gamma band (permutation test Z-scores > 8) and yield moderate discriminability of the SOZ using ROC analysis (maximal mean AUC ~ 0.73). By contrast to AECs, phase locking values (PLVs), a measure of narrow-band phase coupling across sites, and PLV-based graph metrics discriminate the seizure onset nodes weakly. Our results suggest that gamma band AECs may provide a clinically useful marker of cortical hyperexcitability in focal epilepsy.

Duration of spreading depression is the electrophysiological correlate of infarct growth in malignant hemispheric stroke.

Spreading depolarizations (SD) contribute to lesion progression after experimental focal cerebral ischemia while such correlation has never been shown in stroke patients. In this prospective, diagnostic study, we investigate the association of SDs and secondary infarct progression after malignant hemispheric stroke. SDs were continuously monitored for 3-9 days with electrocorticography after decompressive hemicraniectomy for malignant hemispheric stroke. To ensure valid detection and analysis of SDs, a threshold based on the electrocorticographic baseline activity was calculated to identify valid electrocorticographic recordings. Subsequently SD characteristics were analyzed in association to infarct progression based on serial MRI. Overall, 62 patients with a mean stroke volume of 289.6 ± 68 cm3 were included. Valid electrocorticographic recordings were found in 44/62 patients with a mean recording duration of 139.6 ± 26.5 hours and 52.5 ± 39.5 SDs per patient. Infarct progression of more than 5% was found in 21/44 patients. While the number of SDs was similar between patients with and without infarct progression, the SD-induced depression duration per day was significantly longer in patients with infarct progression (593.8 vs. 314.1 minutes; *p = 0.046). Therefore, infarct progression is associated with a prolonged SD-induced depression duration. Real-time analysis of electrocorticographic recordings may identify secondary stroke progression and help implementing targeted management strategies.