Discovering Neurophysiological Characteristics of Pathological High-Frequency Oscillations in Epilepsy with an Explainable Deep Generative Model.

Interictal high-frequency oscillation (HFO) is a promising biomarker of the epileptogenic zone (EZ). However, objective definitions to distinguish between pathological and physiological HFOs have remained elusive, impeding HFOs' clinical applications. We employed self-supervised deep generative variational autoencoders to learn such discriminative HFO features directly from their morphologies in a data-driven manner. We studied a large retrospective cohort of 185 patients who underwent intracranial monitoring and analyzed 686,410 candidate HFO events collected from 18,265 brain contacts across diverse brain regions. The model automatically clustered HFOs into distinct morphological groups in the latent space. One cluster consisted of putative morphologically defined pathological HFOs (mpHFOs): HFOs in that cluster were observed to be associated with spikes and exhibited high signal intensity both in the HFO band (>80 Hz) at detection and in the sub-HFO band (10-80 Hz) surrounding the detection and were primarily localized in the seizure onset zone (SOZ). Moreover, resection of brain regions based on a higher prevalence of interictal mpHFOs better predicted postoperative seizure outcomes than current clinical standards based on SOZ removal. Our self-supervised, explainable, deep generative model distills pathological HFOs and thus potentially helps delineate the EZ purely from interictal intracranial EEG data.

Cortical and white matter substrates supporting visuospatial working memory.

OBJECTIVE: In tasks involving new visuospatial information, we rely on working memory, supported by a distributed brain network. We investigated the dynamic interplay between brain regions, including cortical and white matter structures, to understand how neural interactions change with different memory loads and trials, and their subsequent impact on working memory performance. METHODS: Patients undertook a task of immediate spatial recall during intracranial EEG monitoring. We charted the dynamics of cortical high-gamma activity and associated functional connectivity modulations in white matter tracts. RESULTS: Elevated memory loads were linked to enhanced functional connectivity via occipital longitudinal tracts, yet decreased through arcuate, uncinate, and superior-longitudinal fasciculi. As task familiarity grew, there was increased high-gamma activity in the posterior inferior-frontal gyrus (pIFG) and diminished functional connectivity across a network encompassing frontal, parietal, and temporal lobes. Early pIFG high-gamma activity was predictive of successful recall. Including this metric in a logistic regression model yielded an accuracy of 0.76. CONCLUSIONS: Optimizing visuospatial working memory through practice is tied to early pIFG activation and decreased dependence on irrelevant neural pathways. SIGNIFICANCE: This study expands our knowledge of human adaptation for visuospatial working memory, showing the spatiotemporal dynamics of cortical network modulations through white matter tracts.

Developmental atlas of phase-amplitude coupling between physiologic high-frequency oscillations and slow waves.

We investigated the developmental changes in high-frequency oscillation (HFO) and Modulation Index (MI) - the coupling measure between HFO and slow-wave phase. We generated normative brain atlases, using subdural EEG signals from 8251 nonepileptic electrode sites in 114 patients (ages 1.0-41.5 years) who achieved seizure control following resective epilepsy surgery. We observed a higher MI in the occipital lobe across all ages, and occipital MI increased notably during early childhood. The cortical areas exhibiting MI co-growth were connected via the vertical occipital fasciculi and posterior callosal fibers. While occipital HFO rate showed no significant age-association, the temporal, frontal, and parietal lobes exhibited an age-inversed HFO rate. Assessment of 1006 seizure onset sites revealed that z-score normalized MI and HFO rate were higher at seizure onset versus nonepileptic electrode sites. We have publicly shared our intracranial EEG data to enable investigators to validate MI and HFO-centric presurgical evaluations to identify the epileptogenic zone.

Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities.

Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function. We aimed to build the first-ever brain atlases directly visualizing the network dynamics of eye movement-related alpha and high-gamma modulations, at cortical and white matter levels. We studied 28 patients (age: 5-20 years) who underwent intracranial EEG and electro-oculography recordings. We measured alpha and high-gamma modulations at 2167 electrode sites outside the seizure onset zone, interictal spike-generating areas and MRI-visible structural lesions. Dynamic tractography animated white matter streamlines modulated significantly and simultaneously beyond chance, on a millisecond scale. Before eye-closure onset, significant alpha augmentation occurred at the occipital and frontal cortices. After eye-closure onset, alpha-based functional connectivity was strengthened, while high gamma-based connectivity was weakened extensively in both intra-hemispheric and inter-hemispheric pathways involving the central visual areas. The inferior fronto-occipital fasciculus supported the strengthened alpha co-augmentation-based functional connectivity between occipital and frontal lobe regions, whereas the posterior corpus callosum supported the inter-hemispheric functional connectivity between the occipital lobes. After eye-opening offset, significant high-gamma augmentation and alpha attenuation occurred at occipital, fusiform and inferior parietal cortices. High gamma co-augmentation-based functional connectivity was strengthened, whereas alpha-based connectivity was weakened in the posterior inter-hemispheric and intra-hemispheric white matter pathways involving central and peripheral visual areas. Our results do not support the notion that eye closure-related alpha augmentation uniformly reflects feedforward or feedback rhythms propagating from lower to higher order visual cortex, or vice versa. Rather, proactive and reactive alpha waves involve extensive, distinct white matter networks that include the frontal lobe cortices, along with low- and high-order visual areas. High-gamma co-attenuation coupled to alpha co-augmentation in shared brain circuitry after eye closure supports the notion of an idling role for alpha waves during eye closure. These normative dynamic tractography atlases may improve understanding of the significance of EEG alpha waves in assessing the functional integrity of brain networks in clinical practice; they also may help elucidate the effects of eye movements on task-related brain network measures observed in cognitive neuroscience research.

Causal involvement of medial inferior frontal gyrus of non-dominant hemisphere in higher order auditory perception: A single case study.

The medial side of the operculum is invisible from the lateral surface of cerebral cortex, and its functions remain largely unexplored using direct evidence. Non-invasive and invasive studies have proved functions on peri-sylvian area including the inferior frontal gyrus (IFG) and superior temporal gyrus within the language-dominant hemisphere for semantic processing during verbal communication. However, within the non-dominant hemisphere, there was less evidence of its functions except for pitch or prosody processing. Here we add direct evidence for the functions of the non-dominant hemisphere, the causal involvement of the medial IFG for subjective auditory perception, which is affected by the context of the condition, regarded as a contribution in higher order auditory perception. The phenomenon was clearly distinguished from absolute and invariant pitch perception which is regarded as lower order auditory perception. Electrical stimulation of the medial surface of pars triangularis of IFG in non-dominant hemisphere via depth electrode in an epilepsy patient rapidly and reproducibly elicited perception of pitch changes of auditory input. Pitches were perceived as either higher or lower than those given without stimulation and there was no selectivity for sound type. The patient perceived sounds as higher when she had greater control over the situation when her eyes were open and there were self-cues, and as lower when her eyes were closed and there were investigator-cues. Time-frequency analysis of electrocorticography signals during auditory naming demonstrated medial IFG activation, characterized by low-gamma band augmentation during her own vocal response. The overall evidence provides a neural substrate for altered perception of other vocal tones according to the condition context.

Sevoflurane-induced high-frequency oscillations, effective connectivity and intraoperative classification of epileptic brain areas.

OBJECTIVE: To determine how sevoflurane anesthesia modulates intraoperative epilepsy biomarkers on electrocorticography, including high-frequency oscillation (HFO) effective connectivity (EC), and to investigate their relation to epileptogenicity and anatomical white matter. METHODS: We studied eight pediatric drug-resistant focal epilepsy patients who achieved seizure control after invasive monitoring and resective surgery. We visualized spatial distributions of the electrocorticography biomarkers at an oxygen baseline, three time-points while sevoflurane was increasing, and at a plateau of 2 minimum alveolar concentration (MAC) sevoflurane. HFO EC was combined with diffusion-weighted imaging, in dynamic tractography. RESULTS: Intraoperative HFO EC diffusely increased as a function of sevoflurane concentration, although most in epileptogenic sites (defined as those included in the resection); their ability to classify epileptogenicity was optimized at sevoflurane 2 MAC. HFO EC could be visualized on major white matter tracts, as a function of sevoflurane level. CONCLUSIONS: The results strengthened the hypothesis that sevoflurane-activated HFO biomarkers may help intraoperatively localize the epileptogenic zone. SIGNIFICANCE: Our results help characterize how HFOs at non-epileptogenic and epileptogenic networks respond to sevoflurane. It may be warranted to establish a normative HFO atlas incorporating the modifying effects of sevoflurane and major white matter pathways, as critical reference in epilepsy presurgical evaluation.

Intra- and inter-hemispheric network dynamics supporting object recognition and speech production.

We built normative brain atlases that animate millisecond-scale intra- and inter-hemispheric white matter-level connectivity dynamics supporting object recognition and speech production. We quantified electrocorticographic modulations during three naming tasks using event-related high-gamma activity from 1,114 nonepileptogenic intracranial electrodes (i.e., non-lesional areas unaffected by epileptiform discharges). Using this electrocorticography data, we visualized functional connectivity modulations defined as significant naming-related high-gamma modulations occurring simultaneously at two sites connected by direct white matter streamlines on diffusion-weighted imaging tractography. Immediately after stimulus onset, intra- and inter-hemispheric functional connectivity enhancements were confined mainly across modality-specific perceptual regions. During response preparation, left intra-hemispheric connectivity enhancements propagated in a posterior-to-anterior direction, involving the left precentral and prefrontal areas. After overt response onset, inter- and intra-hemispheric connectivity enhancements mainly encompassed precentral, postcentral, and superior-temporal (STG) gyri. We found task-specific connectivity enhancements during response preparation as follows. Picture naming enhanced activity along the left arcuate fasciculus between the inferior-temporal and precentral/posterior inferior-frontal (pIFG) gyri. Nonspeech environmental sound naming augmented functional connectivity via the left inferior longitudinal and fronto-occipital fasciculi between the medial-occipital and STG/pIFG. Auditory descriptive naming task enhanced usage of the left frontal U-fibers, involving the middle-frontal gyrus. Taken together, the commonly observed network enhancements include inter-hemispheric connectivity optimizing perceptual processing exerted in each hemisphere, left intra-hemispheric connectivity supporting semantic and lexical processing, and inter-hemispheric connectivity for symmetric oral movements during overt speech. Our atlases improve the currently available models of object recognition and speech production by adding neural dynamics via direct intra- and inter-hemispheric white matter tracts.

Characterizing physiological high-frequency oscillations using deep learning.

Objective.Intracranially-recorded interictal high-frequency oscillations (HFOs) have been proposed as a promising spatial biomarker of the epileptogenic zone. However, HFOs can also be recorded in the healthy brain regions, which complicates the interpretation of HFOs. The present study aimed to characterize salient features of physiological HFOs using deep learning (DL).Approach.We studied children with neocortical epilepsy who underwent intracranial strip/grid evaluation. Time-series EEG data were transformed into DL training inputs. The eloquent cortex (EC) was defined by functional cortical mapping and used as a DL label. Morphological characteristics of HFOs obtained from EC (ecHFOs) were distilled and interpreted through a novel weakly supervised DL model.Main results.A total of 63 379 interictal intracranially-recorded HFOs from 18 children were analyzed. The ecHFOs had lower amplitude throughout the 80-500 Hz frequency band around the HFO onset and also had a lower signal amplitude in the low frequency band throughout a one-second time window than non-ecHFOs, resembling a bell-shaped template in the time-frequency map. A minority of ecHFOs were HFOs with spikes (22.9%). Such morphological characteristics were confirmed to influence DL model prediction via perturbation analyses. Using the resection ratio (removed HFOs/detected HFOs) of non-ecHFOs, the prediction of postoperative seizure outcomes improved compared to using uncorrected HFOs (area under the ROC curve of 0.82, increased from 0.76).Significance.We characterized salient features of physiological HFOs using a DL algorithm. Our results suggested that this DL-based HFO classification, once trained, might help separate physiological from pathological HFOs, and efficiently guide surgical resection using HFOs.

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy.

The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortical parcellation was applied to localize the SOZ in cortical nodes of the epileptogenic hemisphere. At each node, the laminar surface analysis was followed to sample 1) the relative intensity of gray matter and white matter in multi-modal MRI and 2) the neighboring white matter connectivity using diffusion tractography edge strengths. A cross-validation was employed to train and test all layers of a multi-scale residual neural network (msResNet) that can classify SOZ node in an end-to-end fashion. A prediction probability of a given node belonging to the SOZ class was proposed as a non-invasive MRI marker of seizure onset likelihood. In an independent validation cohort, the proposed MRI marker provided a very large effect size of Cohen's d = 1.21 between SOZ and non-SOZ, and classified SOZ with a balanced accuracy of 0.75 in lesional and 0.67 in non-lesional MRI groups. The subsequent multi-variate logistic regression found the incorporation of the proposed MRI marker into interictal intracranial EEG (iEEG) markers further improves the differentiation between the epileptogenic focus (defined as SOZ resected during surgery) and non-epileptogenic sites (i.e., non-SOZ sites preserved during surgery) up to 15 % in non-lesional MRI group, suggesting that the proposed MRI marker could improve the localization of epileptogenic foci for successful pediatric epilepsy surgery.

Developmental organization of neural dynamics supporting auditory perception.

PURPOSE: A prominent view of language acquisition involves learning to ignore irrelevant auditory signals through functional reorganization, enabling more efficient processing of relevant information. Yet, few studies have characterized the neural spatiotemporal dynamics supporting rapid detection and subsequent disregard of irrelevant auditory information, in the developing brain. To address this unknown, the present study modeled the developmental acquisition of cost-efficient neural dynamics for auditory processing, using intracranial electrocorticographic responses measured in individuals receiving standard-of-care treatment for drug-resistant, focal epilepsy. We also provided evidence demonstrating the maturation of an anterior-to-posterior functional division within the superior-temporal gyrus (STG), which is known to exist in the adult STG. METHODS: We studied 32 patients undergoing extraoperative electrocorticography (age range: eight months to 28 years) and analyzed 2,039 intracranial electrode sites outside the seizure onset zone, interictal spike-generating areas, and MRI lesions. Patients were given forward (normal) speech sounds, backward-played speech sounds, and signal-correlated noises during a task-free condition. We then quantified sound processing-related neural costs at given time windows using high-gamma amplitude at 70-110 Hz and animated the group-level high-gamma dynamics on a spatially normalized three-dimensional brain surface. Finally, we determined if age independently contributed to high-gamma dynamics across brain regions and time windows. RESULTS: Group-level analysis of noise-related neural costs in the STG revealed developmental enhancement of early high-gamma augmentation and diminution of delayed augmentation. Analysis of speech-related high-gamma activity demonstrated an anterior-to-posterior functional parcellation in the STG. The left anterior STG showed sustained augmentation throughout stimulus presentation, whereas the left posterior STG showed transient augmentation after stimulus onset. We found a double dissociation between the locations and developmental changes in speech sound-related high-gamma dynamics. Early left anterior STG high-gamma augmentation (i.e., within 200 ms post-stimulus onset) showed developmental enhancement, whereas delayed left posterior STG high-gamma augmentation declined with development. CONCLUSIONS: Our observations support the model that, with age, the human STG refines neural dynamics to rapidly detect and subsequently disregard uninformative acoustic noises. Our study also supports the notion that the anterior-to-posterior functional division within the left STG is gradually strengthened for efficient speech-sound perception after birth.

Diffusion tractography predicts propagated high-frequency activity during epileptic spasms.

OBJECTIVE: To determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare the observed propagation patterns across patients with successful or unsuccessful surgical outcomes. METHODS: Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion magnetic resonance imaging (MRI) tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated. Properties of this structural network were used to predict oscillation onset times and amplitudes, and this relationship was compared across patients who did and did not achieve seizure freedom following resective surgery. RESULTS: Onset propagation patterns were relatively consistent across each patient's spasm events. An electrode's average ictal oscillation onset latency was most significantly associated with the length of direct corticocortical tracts connecting to the area with the earliest average oscillation onset (p < .001, model R2  = .54). Moreover, patients demonstrating a faster propagation of ictal oscillation signals within the corticocortical network were more likely to have seizure recurrence following resective surgery (p = .039). In addition, ictal oscillation amplitude was associated with connecting tractography length and weighted fractional anisotropy (FA) measures along these pathways (p = .002/.030, model R2  = .31/.25). Characteristics of analogous corticothalamic pathways did not show significant associations with ictal oscillation onset latency or amplitude. SIGNIFICANCE: Spatiotemporal propagation patterns of high-frequency activity in epileptic spasms align with length and FA measures from onset-originating corticocortical pathways. Considering the data in this individualized framework may help inform surgical decision-making and expectations of surgical outcomes.

Temporally and functionally distinct large-scale brain network dynamics supporting task switching.

OBJECTIVE: Our daily activities require frequent switches among competing responses at the millisecond time scale. We determined the spatiotemporal characteristics and functional significance of rapid, large-scale brain network dynamics during task switching. METHODS: This cross-sectional study investigated patients with drug-resistant focal epilepsy who played a Lumosity cognitive flexibility training game during intracranial electroencephalography (iEEG) recording. According to a given task rule, unpredictably switching across trials, participants had to swipe the screen in the direction the stimulus was pointing or moving. Using this data, we described the spatiotemporal characteristics of iEEG high-gamma augmentation occurring more intensely during switch than repeat trials, unattributable to the effect of task rule (pointing or moving), within-stimulus congruence (the direction of stimulus pointing and moving was same or different in a given trial), or accuracy of an immediately preceding response. Diffusion-weighted imaging (DWI) tractography determined whether distant cortical regions showing enhanced activation during task switch trials were directly connected by white matter tracts. Trial-by-trial iEEG analysis deduced whether the intensity of task switch-related high-gamma augmentation was altered through practice and whether high-gamma amplitude predicted the accuracy of an upcoming response among switch trials. RESULTS: The average number of completed trials during five-minute gameplay was 221.4 per patient (range: 171-285). Task switch trials increased the response times, whereas later trials reduced them. Analysis of iEEG signals sampled from 860 brain sites effectively elucidated the distinct spatiotemporal characteristics of task switch, task rule, and post-error-specific high-gamma modulations. Post-cue, task switch-related high-gamma augmentation was initiated in the right calcarine cortex after 260 ms, right precuneus after 330 ms, right entorhinal after 420 ms, and bilateral anterior middle-frontal gyri after 450 ms. DWI tractography successfully showed the presence of direct white matter tracts connecting the right visual areas to the precuneus and anterior middle-frontal regions but not between the right precuneus and anterior middle-frontal regions. Task-related high-gamma amplitudes in later trials were reduced in the calcarine, entorhinal and anterior middle-frontal regions, but increased in the precuneus. Functionally, enhanced post-cue precuneus high-gamma augmentation improved the accuracy of subsequent responses among switch trials. CONCLUSIONS: Our multimodal analysis uncovered two temporally and functionally distinct network dynamics supporting task switching. High-gamma augmentation in the visual-precuneus pathway may reflect the neural process facilitating an attentional shift to a given updated task rule. High-gamma activity in the visual-dorsolateral prefrontal pathway, rapidly reduced through practice, may reflect the cost of executing appropriate stimulus-response translation.

Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery.

This prospective study determined the use of intracranially recorded spectral responses during naming tasks in predicting neuropsychological performance following epilepsy surgery. We recruited 65 patients with drug-resistant focal epilepsy who underwent preoperative neuropsychological assessment and intracranial EEG recording. The Clinical Evaluation of Language Fundamentals evaluated the baseline and postoperative language function. During extra-operative intracranial EEG recording, we assigned patients to undergo auditory and picture naming tasks. Time-frequency analysis determined the spatiotemporal characteristics of naming-related amplitude modulations, including high gamma augmentation at 70-110 Hz. We surgically removed the presumed epileptogenic zone based on the intracranial EEG and MRI abnormalities while maximally preserving the eloquent areas defined by electrical stimulation mapping. The multivariate regression model incorporating auditory naming-related high gamma augmentation predicted the postoperative changes in Core Language Score with r2 of 0.37 and in Expressive Language Index with r2 of 0.32. Independently of the effects of epilepsy and neuroimaging profiles, higher high gamma augmentation at the resected language-dominant hemispheric area predicted a more severe postoperative decline in Core Language Score and Expressive Language Index. Conversely, the model incorporating picture naming-related high gamma augmentation predicted the change in Receptive Language Index with an r2 of 0.50. Higher high gamma augmentation independently predicted a more severe postoperative decline in Receptive Language Index. Ancillary regression analysis indicated that naming-related low gamma augmentation and alpha/beta attenuation likewise independently predicted a more severe Core Language Score decline. The machine learning-based prediction model suggested that naming-related high gamma augmentation, among all spectral responses used as predictors, most strongly contributed to the improved prediction of patients showing a >5-point Core Language Score decline (reflecting the lower 25th percentile among patients). We generated the model-based atlas visualizing sites, which, if resected, would lead to such a language decline. With a 5-fold cross-validation procedure, the auditory naming-based model predicted patients who had such a postoperative language decline with an accuracy of 0.80. The model indicated that virtual resection of an electrical stimulation mapping-defined language site would have increased the relative risk of the Core Language Score decline by 5.28 (95% confidence interval: 3.47-8.02). Especially, that of an electrical stimulation mapping-defined receptive language site would have maximized it to 15.90 (95% confidence interval: 9.59-26.33). In summary, naming-related spectral responses predict neuropsychological outcomes after epilepsy surgery. We have provided our prediction model as an open-source material, which will indicate the postoperative language function of future patients and facilitate external validation at tertiary epilepsy centres.

Significance of event related causality (ERC) in eloquent neural networks.

Neural activity emerges and propagates swiftly between brain areas. Investigation of these transient large-scale flows requires sophisticated statistical models. We present a method for assessing the statistical confidence of event-related neural propagation. Furthermore, we propose a criterion for statistical model selection, based on both goodness of fit and width of confidence intervals. We show that event-related causality (ERC) with two-dimensional (2D) moving average, is an efficient estimator of task-related neural propagation and that it can be used to determine how different cognitive task demands affect the strength and directionality of neural propagation across human cortical networks. Using electrodes surgically implanted on the surface of the brain for clinical testing prior to epilepsy surgery, we recorded electrocorticographic (ECoG) signals as subjects performed three naming tasks: naming of ambiguous and unambiguous visual objects, and as a contrast, naming to auditory description. ERC revealed robust and statistically significant patterns of high gamma activity propagation, consistent with models of visually and auditorily cued word production. Interestingly, ambiguous visual stimuli elicited more robust propagation from visual to auditory cortices relative to unambiguous stimuli, whereas naming to auditory description elicited propagation in the opposite direction, consistent with recruitment of modalities other than those of the stimulus during object recognition and naming. The new method introduced here is uniquely suitable to both research and clinical applications and can be used to estimate the statistical significance of neural propagation for both cognitive neuroscientific studies and functional brain mapping prior to resective surgery for epilepsy and brain tumors.

Refining epileptogenic high-frequency oscillations using deep learning: a reverse engineering approach.

Intracranially recorded interictal high-frequency oscillations have been proposed as a promising spatial biomarker of the epileptogenic zone. However, its visual verification is time-consuming and exhibits poor inter-rater reliability. Furthermore, no method is currently available to distinguish high-frequency oscillations generated from the epileptogenic zone (epileptogenic high-frequency oscillations) from those generated from other areas (non-epileptogenic high-frequency oscillations). To address these issues, we constructed a deep learning-based algorithm using chronic intracranial EEG data via subdural grids from 19 children with medication-resistant neocortical epilepsy to: (i) replicate human expert annotation of artefacts and high-frequency oscillations with or without spikes, and (ii) discover epileptogenic high-frequency oscillations by designing a novel weakly supervised model. The 'purification power' of deep learning is then used to automatically relabel the high-frequency oscillations to distill epileptogenic high-frequency oscillations. Using 12 958 annotated high-frequency oscillation events from 19 patients, the model achieved 96.3% accuracy on artefact detection (F1 score = 96.8%) and 86.5% accuracy on classifying high-frequency oscillations with or without spikes (F1 score = 80.8%) using patient-wise cross-validation. Based on the algorithm trained from 84 602 high-frequency oscillation events from nine patients who achieved seizure-freedom after resection, the majority of such discovered epileptogenic high-frequency oscillations were found to be ones with spikes (78.6%, P < 0.001). While the resection ratio of detected high-frequency oscillations (number of resected events/number of detected events) did not correlate significantly with post-operative seizure freedom (the area under the curve = 0.76, P = 0.06), the resection ratio of epileptogenic high-frequency oscillations positively correlated with post-operative seizure freedom (the area under the curve = 0.87, P = 0.01). We discovered that epileptogenic high-frequency oscillations had a higher signal intensity associated with ripple (80-250 Hz) and fast ripple (250-500 Hz) bands at the high-frequency oscillation onset and with a lower frequency band throughout the event time window (the inverted T-shaped), compared to non-epileptogenic high-frequency oscillations. We then designed perturbations on the input of the trained model for non-epileptogenic high-frequency oscillations to determine the model's decision-making logic. The model confidence significantly increased towards epileptogenic high-frequency oscillations by the artificial introduction of the inverted T-shaped signal template (mean probability increase: 0.285, P < 0.001), and by the artificial insertion of spike-like signals into the time domain (mean probability increase: 0.452, P < 0.001). With this deep learning-based framework, we reliably replicated high-frequency oscillation classification tasks by human experts. Using a reverse engineering technique, we distinguished epileptogenic high-frequency oscillations from others and identified its salient features that aligned with current knowledge.

Dissociable oscillatory theta signatures of memory formation in the developing brain.

Understanding complex human brain functions is critically informed by studying such functions during development. Here, we addressed a major gap in models of human memory by leveraging rare direct electrophysiological recordings from children and adolescents. Specifically, memory relies on interactions between the medial temporal lobe (MTL) and prefrontal cortex (PFC), and the maturation of these interactions is posited to play a key role in supporting memory development. To understand the nature of MTL-PFC interactions, we examined subdural recordings from MTL and PFC in 21 neurosurgical patients aged 5.9-20.5 years as they performed an established scene memory task. We determined signatures of memory formation by comparing the study of subsequently recognized to forgotten scenes in single trials. Results establish that MTL and PFC interact via two distinct theta mechanisms, an ∼3-Hz oscillation that supports amplitude coupling and slows down with age and an ∼7-Hz oscillation that supports phase coupling and speeds up with age. Slow and fast theta interactions immediately preceding scene onset further explained age-related differences in recognition performance. Last, with additional diffusion imaging data, we linked both functional mechanisms to the structural maturation of the cingulum tract. Our findings establish system-level dynamics of memory formation and suggest that MTL and PFC interact via increasingly dissociable mechanisms as memory improves across development.

Sevoflurane-based enhancement of phase-amplitude coupling and localization of the epileptogenic zone.

OBJECTIVE: Phase-amplitude coupling between high-frequency (≥150 Hz) and delta (3-4 Hz) oscillations - modulation index (MI) - is a promising, objective biomarker of epileptogenicity. We determined whether sevoflurane anesthesia preferentially enhances this metric within the epileptogenic zone. METHODS: This is an observational study of intraoperative electrocorticography data from 621 electrodes chronically implanted into eight patients with drug-resistant, focal epilepsy. All patients were anesthetized with sevoflurane during resective surgery, which subsequently resulted in seizure control. We classified 'removed' and 'retained' brain sites as epileptogenic and non-epileptogenic, respectively. Mixed model analysis determined which anesthetic stage optimized MI-based classification of epileptogenic sites. RESULTS: MI increased as a function of anesthetic stage, ranging from baseline (i.e., oxygen alone) to 2.0 minimum alveolar concentration (MAC) of sevoflurane, preferentially at sites showing higher initial MI values. This phenomenon was accentuated just prior to sevoflurane reaching 2.0 MAC, at which time, the odds of a site being classified as epileptogenic were enhanced by 86.6 times for every increase of 1.0 MI. CONCLUSIONS: Intraoperative MI best localized the epileptogenic zone immediately before sevoflurane reaching 2.0 MAC in this small cohort of patients. SIGNIFICANCE: Prospective, large cohort studies are warranted to determine whether sevoflurane anesthesia can reduce the need for extraoperative, invasive evaluation.

Six-dimensional dynamic tractography atlas of language connectivity in the developing brain.

During a verbal conversation, our brain moves through a series of complex linguistic processing stages: sound decoding, semantic comprehension, retrieval of semantically coherent words, and overt production of speech outputs. Each process is thought to be supported by a network consisting of local and long-range connections bridging between major cortical areas. Both temporal and extratemporal lobe regions have functional compartments responsible for distinct language domains, including the perception and production of phonological and semantic components. This study provides quantitative evidence of how directly connected inter-lobar neocortical networks support distinct stages of linguistic processing across brain development. Novel six-dimensional tractography was used to intuitively visualize the strength and temporal dynamics of direct inter-lobar effective connectivity between cortical areas activated during each linguistic processing stage. We analysed 3401 non-epileptic intracranial electrode sites from 37 children with focal epilepsy (aged 5-20 years) who underwent extra-operative electrocorticography recording. Principal component analysis of auditory naming-related high-gamma modulations determined the relative involvement of each cortical area during each linguistic processing stage. To quantify direct effective connectivity, we delivered single-pulse electrical stimulation to 488 temporal and 1581 extratemporal lobe sites and measured the early cortico-cortical spectral responses at distant electrodes. Mixed model analyses determined the effects of naming-related high-gamma co-augmentation between connecting regions, age, and cerebral hemisphere on the strength of effective connectivity independent of epilepsy-related factors. Direct effective connectivity was strongest between extratemporal and temporal lobe site pairs, which were simultaneously activated between sentence offset and verbal response onset (i.e. response preparation period); this connectivity was approximately twice more robust than that with temporal lobe sites activated during stimulus listening or overt response. Conversely, extratemporal lobe sites activated during overt response were equally connected with temporal lobe language sites. Older age was associated with increased strength of inter-lobar effective connectivity especially between those activated during response preparation. The arcuate fasciculus supported approximately two-thirds of the direct effective connectivity pathways from temporal to extratemporal auditory language-related areas but only up to half of those in the opposite direction. The uncinate fasciculus consisted of <2% of those in the temporal-to-extratemporal direction and up to 6% of those in the opposite direction. We, for the first time, provided an atlas which quantifies and animates the strength, dynamics, and direction specificity of inter-lobar neural communications between language areas via the white matter pathways. Language-related effective connectivity may be strengthened in an age-dependent manner even after the age of 5.

Long-term satisfaction after extraoperative invasive EEG recording.

This retrospective cohort study investigated 53 patients with drug-resistant focal epilepsy and identified factors predictive of long-term satisfaction of patients and families following extraoperative intracranial EEG (iEEG) recording. The mixed model analysis assessed the utility of intracranial EEG (iEEG) predictor variables, including the seizure-onset zone (SOZ), modulation index (MI), and naming-related high-gamma activity. Modulation index, quantifying the coupling between high-frequency activity at >80 Hz and local slow wave at 3-4 Hz, effectively functions as a surrogate marker of the burden of interictal spike-and-slow-wave discharges. The mixed model specifically incorporated 'subtraction-MI', defined as the subtraction of mean z-score normalized MI across all preserved sites from that across all resected sites. Auditory naming-related high-gamma activity at 70-110 Hz is a biomarker to characterize the underlying language and speech function. The model incorporated 'maximum resected high-gamma', defined as the high-gamma percent change largest among sites included in the resected language-dominant hemispheric region. The model also incorporated the clinical and imaging profiles of given patients. The analysis revealed that complete removal of SOZ (p = 0.003) and younger patient age (p = 0.040) were independently associated with greater satisfaction. Neither 'subtraction-MI' nor 'maximum naming-related high-gamma' showed a significant and independent association with long-term satisfaction in our patient cohort. The observed impact of complete resection of SOZ and early surgery can be considered when counseling candidates for epilepsy surgery.