High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?

Despite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected in the human mesial temporal lobe and neocortical intracranial recordings spanning gamma/epsilon (60-150 Hz), ripple (80-250 Hz) and higher frequency ranges. Separate from other non-oscillatory activities, these brief electrophysiological oscillations of distinct duration, frequency and amplitude are thought to be generated by coordinated spiking of neuronal ensembles within volumes as small as a single cortical column. Although the exact origins, mechanisms, and physiological roles in health and disease remain elusive, they have been associated with human memory consolidation and cognitive processing. Recent studies suggest their involvement in encoding and recall of episodic memory with a possible role in the formation and reactivation of memory traces. High frequency oscillations are detected during encoding, throughout maintenance, and right before recall of remembered items, meeting a basic definition for an engram activity. The temporal coordination of high frequency oscillations reactivated across cortical and subcortical neural networks is ideally suited for integrating multimodal memory representations, which can be replayed and consolidated during states of wakefulness and sleep. High frequency oscillations have been shown to reflect coordinated bursts of neuronal assembly firing and offer a promising substrate for tracking and modulation of the hypothetical electrophysiological engram.

Direct electrical brain stimulation of human memory: lessons learnt and future perspectives.

Modulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental level, it remains elusive as to how delivering electrical current in a given brain area leads to enhanced memory processing. Starting from the local and distal physiological effects on neural populations, the mechanisms of enhanced memory encoding, maintenance, consolidation or recall in response to direct electrical stimulation are only now being unravelled. With the advent of innovative neurotechnologies for concurrent recording and stimulation intracranially in the human brain, it becomes possible to study both acute and chronic effects of stimulation on memory performance and the underlying neural activities. In this review, we summarize the effects of various invasive stimulation approaches for modulating memory functions. We first outline the challenges that were faced in the initial studies of memory enhancement and the lessons learnt. Electrophysiological biomarkers are then reviewed as more objective measures of the stimulation effects than behavioural outcomes. Finally, we classify the various stimulation approaches into continuous and phasic modulation with an open or closed loop for responsive stimulation based on analysis of the recorded neural activities. Although the potential advantage of closed-loop responsive stimulation over the classic open-loop approaches is inconclusive, we foresee the emerging results from ongoing longitudinal studies and clinical trials will shed light on both the mechanisms and optimal strategies for improving declarative memory. Adaptive stimulation based on the biomarker analysis over extended periods of time is proposed as a future direction for obtaining lasting effects on memory functions. Chronic tracking and modulation of neural activities intracranially through adaptive stimulation opens tantalizing new avenues to continually monitor and treat memory and cognitive deficits in a range of brain disorders. Brain co-processors created with machine-learning tools and wireless bi-directional connectivity to seamlessly integrate implanted devices with smartphones and cloud computing are poised to enable real-time automated analysis of large data volumes and adaptively tune electrical stimulation based on electrophysiological biomarkers of behavioural states. Next-generation implantable devices for high-density recording and stimulation of electrophysiological activities, and technologies for distributed brain-computer interfaces are presented as selected future perspectives for modulating human memory and associated mental processes.

Independent dynamics of low, intermediate, and high frequency spectral intracranial EEG activities during human memory formation.

A wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various frequency ranges are coordinated across the space of the human cortex and time of memory processing is inconclusive. They can either be coordinated together across the frequency spectrum at the same cortical site and time or induced independently in particular bands. We used a large dataset of human intracranial electroencephalography (iEEG) to parse the spatiotemporal dynamics of spectral activities induced during formation of verbal memories. Encoding of words for subsequent free recall activated low frequency theta, intermediate frequency alpha and beta, and high frequency gamma power in a mosaic pattern of discrete cortical sites. A majority of the cortical sites recorded activity in only one of these frequencies, except for the visual cortex where spectral power was induced across multiple bands. Each frequency band showed characteristic dynamics of the induced power specific to cortical area and hemisphere. The power of the low, intermediate, and high frequency activities propagated in independent sequences across the visual, temporal and prefrontal cortical areas throughout subsequent phases of memory encoding. Our results provide a holistic, simplified model of the spectral activities engaged in the formation of human memory, suggesting an anatomically and temporally distributed mosaic of coordinated brain rhythms.

CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain.

The emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor, assess, and control these higher brain functions without acquiring signals from the brain. Features of gaze position and pupil dilation can be effectively used to track our attention in healthy mental processes, to enable interaction in disorders of consciousness, or to even predict memory performance in various brain diseases. In this perspective article, we propose the term 'CyberEye' to encompass emerging cognitive applications of eye-tracking interfaces for neuroscience research, clinical practice, and the biomedical industry. As CyberEye technologies continue to develop, we expect BCIs to become less dependent on brain activities, to be less invasive, and to thus be more applicable.

Evidence for verbal memory enhancement with electrical brain stimulation in the lateral temporal cortex.

Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement in the human brain have been focused on the hippocampus and other mesial temporal lobe structures, with a few reports of memory improvement in small studies of individual brain regions. Here, we investigated the effect of stimulation in four brain regions known to support declarative memory: hippocampus, parahippocampal neocortex, prefrontal cortex and temporal cortex. Intracranial electrode recordings with stimulation were used to assess verbal memory performance in a group of 22 patients (nine males). We show enhanced performance with electrical stimulation in the lateral temporal cortex (paired t-test, P = 0.0067), but not in the other brain regions tested. This selective enhancement was observed both on the group level, and for two of the four individual subjects stimulated in the temporal cortex. This study shows that electrical stimulation in specific brain areas can enhance verbal memory performance in humans.awx373media15704855796001.

Dissecting gamma frequency activity during human memory processing.

Gamma frequency activity (30-150 Hz) is induced in cognitive tasks and is thought to reflect underlying neural processes. Gamma frequency activity can be recorded directly from the human brain using intracranial electrodes implanted in patients undergoing treatment for drug-resistant epilepsy. Previous studies have independently explored narrowband oscillations in the local field potential and broadband power increases. It is not clear, however, which processes contribute to human brain gamma frequency activity, or their dynamics and roles during memory processing. Here a large dataset of intracranial recordings obtained during encoding of words from 101 patients was used to detect, characterize and compare induced gamma frequency activity events. Individual bursts of gamma frequency activity were isolated in the time-frequency domain to determine their spectral features, including peak frequency, amplitude, frequency span, and duration. We found two distinct types of gamma frequency activity events that showed either narrowband or broadband frequency spans revealing characteristic spectral properties. Narrowband events, the predominant type, were induced by word presentations following an initial induction of broadband events, which were temporally separated and selectively correlated with evoked response potentials, suggesting that they reflect different neural activities and play different roles during memory encoding. The two gamma frequency activity types were differentially modulated during encoding of subsequently recalled and forgotten words. In conclusion, we found evidence for two distinct activity types induced in the gamma frequency range during cognitive processing. Separating these two gamma frequency activity components contributes to the current understanding of electrophysiological biomarkers, and may prove useful for emerging neurotechnologies targeting, mapping and modulating distinct neurophysiological processes in normal and epileptogenic brain.

Reactivation of seizure-related changes to interictal spike shape and synchrony during postseizure sleep in patients.

OBJECTIVE: Local field potentials (LFPs) arise from synchronous activation of millions of neurons, producing seemingly consistent waveform shapes and relative synchrony across electrodes. Interictal spikes (IISs) are LFPs associated with epilepsy that are commonly used to guide surgical resection. Recently, changes in neuronal firing patterns observed in the minutes preceding seizure onset were found to be reactivated during postseizure sleep, a process called seizure-related consolidation (SRC), due to similarities with learning-related consolidation. Because IISs arise from summed neural activity, we hypothesized that changes in IIS shape and relative synchrony would be observed in the minutes preceding seizure onset and would be reactivated preferentially during postseizure slow-wave sleep (SWS). METHODS: Scalp and intracranial recordings were obtained continuously across multiple days from clinical macroelectrodes implanted in patients undergoing treatment for intractable epilepsy. Data from scalp electrodes were used to stage sleep. Data from intracranial electrodes were used to detect IISs using a previously established algorithm. Partial correlations were computed for sleep and wake periods before and after seizures as a function of correlations observed in the minutes preceding seizures. Magnetic resonance imaging (MRI) and computed tomography (CT) scans were co-registered with electroencephalography (EEG) to determine the location of the seizure-onset zone (SOZ). RESULTS: Changes in IIS shape and relative synchrony were observed on a subset of macroelectrodes minutes before seizure onset, and these changes were reactivated preferentially during postseizure SWS. Changes in synchrony were greatest for pairs of electrodes where at least one electrode was located in the SOZ. SIGNIFICANCE: These data suggest preseizure changes in neural activity and their subsequent reactivation occur across a broad spatiotemporal scale: from single neurons to LFPs, both within and outside the SOZ. The preferential reactivation of seizure-related changes in IISs during postseizure SWS adds to a growing body of literature suggesting that pathologic neural processes may utilize physiologic mechanisms of synaptic plasticity.

Evidence for consolidation of neuronal assemblies after seizures in humans.

The establishment of memories involves reactivation of waking neuronal activity patterns and strengthening of associated neural circuits during slow-wave sleep (SWS), a process known as "cellular consolidation" (Dudai and Morris, 2013). Reactivation of neural activity patterns during waking behaviors that occurs on a timescale of seconds to minutes is thought to constitute memory recall (O'Keefe and Nadel, 1978), whereas consolidation of memory traces may be revealed and served by correlated firing (reactivation) that appears during sleep under conditions suitable for synaptic modification (Buhry et al., 2011). Although reactivation has been observed in human neuronal recordings (Gelbard-Sagiv et al., 2008; Miller et al., 2013), reactivation during sleep has not, likely because data are difficult to obtain and the effect is subtle. Seizures, however, provide intense and synchronous, yet sparse activation (Bower et al., 2012) that could produce a stronger consolidation effect if seizures activate learning-related mechanisms similar to those activated by learned tasks. Continuous wide-bandwidth recordings from patients undergoing intracranial monitoring for drug-resistant epilepsy revealed reactivation of seizure-related neuronal activity during subsequent SWS, but not wakefulness. Those neuronal assemblies that were most strongly activated during seizures showed the largest correlation changes, suggesting that consolidation selectively strengthened neuronal circuits activated by seizures. These results suggest that seizures "hijack" physiological learning mechanisms and also suggest a novel epilepsy therapy targeting neuronal dynamics during post-seizure sleep.

Interictal high-frequency oscillations in focal human epilepsy.

PURPOSE OF REVIEW: Localization of focal epileptic brain is critical for successful epilepsy surgery and focal brain stimulation. Despite significant progress, roughly half of all patients undergoing focal surgical resection, and most patients receiving focal electrical stimulation, are not seizure free. There is intense interest in high-frequency oscillations (HFOs) recorded with intracranial electroencephalography as potential biomarkers to improve epileptogenic brain localization, resective surgery, and focal electrical stimulation. The present review examines the evidence that HFOs are clinically useful biomarkers. RECENT FINDINGS: Performing the PubMed search 'High-Frequency Oscillations and Epilepsy' for 2013-2015 identifies 308 articles exploring HFO characteristics, physiological significance, and potential clinical applications. SUMMARY: There is strong evidence that HFOs are spatially associated with epileptic brain. There remain, however, significant challenges for clinical translation of HFOs as epileptogenic brain biomarkers: Differentiating true HFO from the high-frequency power changes associated with increased neuronal firing and bandpass filtering sharp transients. Distinguishing pathological HFO from normal physiological HFO. Classifying tissue under individual electrodes as normal or pathological. Sharing data and algorithms so research results can be reproduced across laboratories. Multicenter prospective trials to provide definitive evidence of clinical utility.

High frequency oscillations are associated with cognitive processing in human recognition memory.

High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50-125 Hz), ripple (125-250 Hz) and fast ripple (250-500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21-63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing.

Network oscillations modulate interictal epileptiform spike rate during human memory.

Eleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in interictal epileptiform spike rate in the amygdala, hippocampus, and temporal cortex. During the earliest encoding period (0-2000 ms after image presentation) in these trials there was a widespread decrease in the power of theta, alpha and beta band local field potential oscillations that coincided with emergent focal gamma frequency activity. Interictal epileptiform spike rate correlated with spectral band power changes and broadband (4-150 Hz) desynchronization, which predicted significant reduction in interictal epileptiform spike rate. Spike-triggered averaging of the field potential power spectrum detected a burst of low frequency synchronization 200 ms before the interictal epileptiform spikes that arose during this period of encoding. We conclude that interictal epileptiform spikes are modulated by the patterns of network oscillatory activity that accompany human memory offering a new mechanistic insight into the interplay of cognitive processing, local field potential dynamics and interictal epileptiform spike generation.

Pathological and physiological high-frequency oscillations in focal human epilepsy.

High-frequency oscillations (HFO; gamma: 40-100 Hz, ripples: 100-200 Hz, and fast ripples: 250-500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency, duration, and spectral amplitude of each event in single trial time-frequency spectra and compared them to pathological HFO similarly measured. Pathological HFO had higher mean spectral amplitude, longer mean duration, and lower mean frequency than physiological-induced HFO. In individual patients, support vector machine analysis correctly classified pathological HFO with sensitivities ranging from 70-98% and specificities >90% in all but one patient. In this patient, infrequent high-amplitude HFO were observed in the motor cortex just before movement onset in the motor task. This finding raises the possibility that in epileptic brain physiological-induced gamma can assume higher spectral amplitudes similar to those seen in pathologic HFO. This method if automated and validated could provide a step towards differentiating physiological HFO from pathological HFO and improving localization of epileptogenic brain.

Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall.

Short-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC populations lead in maintaining sample information across delays of an operant non-match to sample task, despite individual neurons firing only transiently. During sample encoding, distinct mPFC subpopulations joined distributed CA1-mPFC cell assemblies hallmarked by 4-5 Hz rhythmic modulation; CA1-mPFC assemblies re-emerged during choice episodes but were not 4-5 Hz modulated. Delay-dependent errors arose when attenuated rhythmic assembly activity heralded collapse of sustained mPFC encoding. Our results map component processes of memory-guided decisions onto heterogeneous CA1-mPFC subpopulations and the dynamics of physiologically distinct, distributed cell assemblies.

Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.

Coordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During quiet wakefulness and rest, CP55940 dose-dependently reduced 0.1-30 Hz local field potential power in CA1 of the hippocampus while concurrently decreasing 30-100 Hz power in mPFC; these contrasting population-level effects were paralleled by differential effects on underlying single-unit activity in the two structures. During decision-making phases of a spatial working memory task, CP5540-induced deficits in hippocampal theta and prefrontal gamma oscillations were observed alongside disrupted theta-frequency coherence between the two structures. These changes in coordinated limbic-cortical network activities correlated with (1) reduced accuracy of task performance, (2) impaired phase-locking of prefrontal single-unit spiking to the local gamma and hippocampal theta rhythms, and (3) impaired task-dependent activity in a subset of mPFC units. In addition to highlighting the importance of CA1-mPFC network oscillations for cognition, these results implicate disrupted theta-frequency coordination of CA1-mPFC activity in the cognitive deficits caused by exogenous activation of brain cannabinoid receptors.

Cognitive neuroscience: Theta network oscillations coordinate development of episodic memory.

Our ability to remember life events matures through childhood and adolescence. A new study has revealed how theta oscillations between two anatomical brain regions supporting memory and executive functions are synchronized and develop across age through functional and structural connectivity.

Hotspot of human verbal memory encoding in the left anterior prefrontal cortex.

BACKGROUND: Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation. METHODS: The areas that are critical for successful encoding of verbal memory as well as the underlying neural activities were determined directly in the human brain with intracranial electrophysiological recordings in epilepsy patients. We recorded a broad range of spectral activities across the cortex of 135 patients as they memorised word lists for subsequent free recall. FINDINGS: The greatest differences in the spectral power between encoding subsequently recalled and forgotten words were found in low theta frequency (3-5 Hz) activities of the left anterior prefrontal cortex. This subsequent memory effect was proportionally greater in the lower frequency bands and in the more anterior cortical regions. We found the peak of this memory signal in a distinct part of the prefrontal cortex at the junction between the Broca's area and the frontal pole. The memory effect in this confined area was significantly higher (Tukey-Kramer test, p<0.05) than in other anatomically distinct areas. INTERPRETATION: Our results suggest a focal hotspot of human verbal memory encoding located in the higher-order processing region of the prefrontal cortex, which presents a prospective target for modulating cognitive functions in the human patients. The memory effect provides an electrophysiological biomarker of low frequency neural activities, at distinct times of memory encoding, and in one hotspot location in the human brain. FUNDING: Open-access datasets were originally collected as part of a BRAIN Initiative project called Restoring Active Memory (RAM) funded by the Defence Advanced Research Project Agency (DARPA). CT, ML, MTK and this research were supported from the First Team grant of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund.

Contribution of Ictal Source Imaging for Localizing Seizure Onset Zone in Patients With Focal Epilepsy.

OBJECTIVE: To determine whether seizure onset zone (SOZ) can be localized accurately prior to surgical planning in patients with focal epilepsy, we performed noninvasive EEG recordings and source localization analyses on 39 patients. METHODS: In 39 patients with focal epilepsy, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We investigated a novel approach for directly imaging sources of seizures and interictal spikes from high-density EEG recordings, and rigorously validated it for noninvasive localization of SOZ determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison. RESULTS: Ictal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients. CONCLUSION: Noninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.

Human Computer Interface for Tracking Eye Movements Improves Assessment and Diagnosis of Patients With Acquired Brain Injuries.

One of the first clinical signs differentiating the minimally conscious state from the vegetative state is the presence of smooth pursuit eye movements occurring in direct response to moving salient stimuli. Glasgow Coma Scale (GCS) is one of the most commonly used diagnostic tools for acute phase assessment of the level of consciousness, together with a neurological examination. These classic measures are limited to qualitative neurological examination without more quantitative measures provided from e.g., tasks with tracking position of the gaze. Among this and other limitations, it is prone to a relatively high rate of misdiagnosis. Here, we developed an interface for gaze tracking to enhance the assessment of consciousness in 10 patients with acquired brain injuries. According to the acute phase GCS assessment, nine of them were considered unaware and below the minimally conscious state. Chronic neurological examination confirmed six of them below the minimally conscious state. Our new Human Computer Interface (HCI) revealed that six patients were conscious enough to complete at least one of the gaze tracking tasks. Among these six patients, one was originally diagnosed as remaining in a vegetative state and one in coma. The patient diagnosed as remaining in a chronic vegetative state scored six GCS points acutely. Following assessment with our HCI the patient was re-diagnosed with a possible locked-in syndrome. Our HCI method provides a new complementary tool for clinical assessment of patients suffering from disorders of consciousness.

Author Correction: Pupil size reflects successful encoding and recall of memory in humans.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance.

Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable metrics that quantify spectral characteristics of the normalized iEEG signal based on power-in-band and synchrony measures. Unsupervised clustering of the metrics identified distinct sets of active electrodes across different subjects. In the total population of 11,869 electrodes, our method achieved 97% sensitivity and 92.9% specificity with the most efficient metric. We validated our results with anatomical localization revealing significantly greater distribution of active electrodes in brain regions that support verbal memory processing. We propose our machine-learning framework for objective and efficient classification and interpretation of electrophysiological signals of brain activities supporting memory and cognition.