Human intracranial high-frequency activity maps episodic memory formation in space and time

Human Genomic Signatures of Brain Oscillations During Memory Encoding

Memory encoding is an essential step for all learning. However, the genetic and molecular mechanisms underlying human memory encoding remain poorly understood, and how this molecular framework permits the emergence of specific patterns of brain oscillations observed during mnemonic processing is unknown. Here, we directly compare intracranial electroencephalography recordings from the neocortex in individuals performing an episodic memory task with human gene expression from the same areas. We identify genes correlated with oscillatory memory effects across 6 frequency bands. These genes are enriched for autism-related genes and have preferential expression in neurons, in particular genes encoding synaptic proteins and ion channels, supporting the idea that the genes regulating voltage gradients are involved in the modulation of oscillatory patterns during successful memory encoding across brain areas. Memory-related genes are distinct from those correlated with other forms of cognitive processing and resting state fMRI. These data are the first to identify correlations between gene expression and active human brain states as well as provide a molecular window into memory encoding oscillations in the human brain.

Multivariate stochastic volatility modeling of neural data

Because multivariate autoregressive models have failed to adequately account for the complexity of neural signals, researchers have predominantly relied on non-parametric methods when studying the relations between brain and behavior. Using medial temporal lobe (MTL) recordings from 96 neurosurgical patients, we show that time series models with volatility described by a multivariate stochastic latent-variable process and lagged interactions between signals in different brain regions provide new insights into the dynamics of brain function. The implied volatility inferred from our process positively correlates with high-frequency spectral activity, a signal that correlates with neuronal activity. We show that volatility features derived from our model can reliably decode memory states, and that this classifier performs as well as those using spectral features. Using the directional connections between brain regions during complex cognitive process provided by the model, we uncovered perirhinal-hippocampal desynchronization in the MTL regions that is associated with successful memory encoding.

Cortical gray-white matter blurring and declarative memory impairment in MRI-negative temporal lobe epilepsy

Magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE) may be a distinct syndrome from TLE with mesial temporal sclerosis (TLE-MTS). Imaging and neuropsychological features of TLE-MTS are well-known; yet, these features are only beginning to be described in MRI-negative TLE. This study examined whether a quantitative measure of cortical gray and white matter blurring (GWB) was elevated in the temporal lobes ipsilateral to the seizure onset zone of individuals with MRI-negative TLE relative to TLE-MTS and healthy controls (HCs) and whether GWB elevations were associated with neuropsychological comorbidity. Gray-white matter blurring from 34 cortical regions and hippocampal volumes were quantified and compared across 28 people with MRI-negative TLE, 15 people with TLE-MTS, and 51 HCs. Declarative memory was assessed with standard neuropsychological tests and the intracarotid amobarbital procedure (IAP). In the group with MRI-negative TLE (left and right onsets combined), hippocampal volumes were within normal range but GWB was elevated, relative to HCs, across several mesial and lateral temporal lobe regions ipsilateral to the seizure onset zone. Gray-white matter blurring did not differ between the groups with TLE-MTS and HC or between the groups with TLE-MTS and MRI-negative TLE. The group with MRI-negative TLE could not be distinguished from the group with TLE-MTS on any of the standard neuropsychological tests; however, ipsilateral hippocampal volumes and IAP memory scores were lower in the group with TLE-MTS than in the group with MRI-negative TLE. The group with left MRI-negative TLE had lower general cognitive abilities and verbal fluency relative to the HC group, which adds to the characterization of neuropsychological comorbidities in left MRI-negative TLE. In addition, ipsilateral IAP memory performance was reduced relative to contralateral memory performance in MRI-negative TLE, indicating some degree of ipsilateral memory dysfunction. There was no relationship between hippocampal volume and IAP memory scores in MRI-negative TLE; however, decreased ipsilateral IAP memory scores were correlated with elevated GWB in the ipsilateral superior temporal sulcus of people with left MRI-negative TLE. In sum, GWB elevations in the ipsilateral temporal lobe of people with MRI-negative TLE suggest that GWB may serve as a marker for reduced structural integrity in regions in or near the seizure onset zone. Although mesial temporal abnormalities might be the major driver of memory dysfunction in TLE-MTS, a loss of structural integrity in lateral temporal lobe regions may contribute to IAP memory dysfunction in MRI-negative TLE.

Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation

Decreases in low-frequency power (2–30 Hz) alongside high-frequency power increases (>40 Hz) have been demonstrated to predict successful memory formation. Parsimoniously, this change in the frequency spectrum can be explained by one factor, a change in the tilt of the power spectrum (from steep to flat) indicating engaged brain regions. A competing view is that the change in the power spectrum contains several distinct brain oscillatory fingerprints, each serving different computations. Here, we contrast these two theories in a parallel magnetoencephalography (MEG)–intracranial electroencephalography (iEEG) study in which healthy participants and epilepsy patients, respectively, studied either familiar verbal material or unfamiliar faces. We investigated whether modulations in specific frequency bands can be dissociated in time and space and by experimental manipulation. Both MEG and iEEG data show that decreases in alpha/beta power specifically predicted the encoding of words but not faces, whereas increases in gamma power and decreases in theta power predicted memory formation irrespective of material. Critically, these different oscillatory signatures of memory encoding were evident in different brain regions. Moreover, high-frequency gamma power increases occurred significantly earlier compared to low-frequency theta power decreases. These results show that simple “spectral tilt” cannot explain common oscillatory changes and demonstrate that brain oscillations in different frequency bands serve different functions for memory encoding.

There are two competing explanations for electrophysiological signatures during cognitive processes. One assumes simultaneous increases in high frequencies paired with decreases in low frequencies, whereas the other suggests that different frequencies index separate oscillatory processes. This study reports data that support the latter view.

Decoding the tradeoff between encoding and retrieval to predict memory for overlapping events

When new events overlap with past events, there is a natural tradeoff between encoding the new event and retrieving the past event. Given the ubiquity of overlap among memories, this tradeoff between memory encoding and retrieval is of central importance to computational models of episodic memory (O'Reilly & McClelland 1994; Hasselmo 2005). However, prior studies have not directly linked neural markers of encoding/retrieval tradeoffs to behavioral measures of how overlapping events are remembered. Here, by decoding patterns of scalp electroencephalography (EEG) from male and female human subjects, we show that tradeoffs between encoding and retrieval states are reflected in distributed patterns of neural activity and, critically, these neural tradeoffs predict how overlapping events will later be remembered. Namely, new events that overlapped with past events were more likely to be subsequently remembered if neural patterns were biased toward a memory encoding state-or, conversely, away from a retrieval state. Additionally, we show that neural markers of encoding vs. retrieval states are surprisingly independent from previously-described EEG predictors of subsequent memory. Instead, we demonstrate that previously-described EEG predictors of subsequent memory are better explained by task engagement than by memory encoding, per se. Collectively, our findings provide important insight into how the memory system balances memory encoding and retrieval states and, more generally, into the neural mechanisms that support successful memory formation.

Memory and the developing brain: From description to explanation with innovation in methods

Recent advances in human cognitive neuroscience show great promise in extending our understanding of the neural basis of memory development. We briefly review the current state of knowledge, highlighting that most work has focused on describing the neural correlates of memory in cross-sectional studies. We then delineate three examples of the application of innovative methods in addressing questions that go beyond description, towards a mechanistic understanding of memory development. First, structural brain imaging and the harmonization of measurements across laboratories may uncover ways in which the maturation of the brain constrains the development of specific aspects of memory. Second, longitudinal designs and sophisticated modeling of the data may identify age-driven changes and the factors that determine individual developmental trajectories. Third, recording memory-related activity directly from the developing brain presents an unprecedented opportunity to examine how distinct brain structures support memory in real time. Finally, the growing prevalence of data sharing offers additional means to tackle questions that demand large-scale datasets, ambitious designs, and access to rare samples. We propose that the use of such innovative methods will move our understanding of memory development from a focus on describing trends to explaining the causal factors that shape behavior.

Dynamic Theta Networks in the Human Medial Temporal Lobe Support Episodic Memory

The medial temporal lobe (MTL) is a locus of episodic memory in the human brain. It is comprised of cytologically distinct subregions that, in concert, give rise to successful encoding and retrieval of context-dependent memories. However, the functional connections between these subregions are poorly understood. To determine functional connectivity among MTL subregions, we had 131 subjects fitted with indwelling electrodes perform a verbal memory task and asked how encoding or retrieval correlated with inter-regional synchronization. Using phase-based measures of connectivity, we found that synchronous theta (4-8 Hz) activity underlies successful episodic memory. During encoding, we observed a dynamic pattern of connections converging on the left entorhinal cortex, beginning with the perirhinal cortex and shifting through hippocampal subfields. Retrieval-associated networks demonstrated enhanced involvement of the subiculum and CA1, reflecting a substantial reorganization of the encoding network. We posit that coherent theta activity within the MTL marks periods of successful memory, but distinct patterns of connectivity dissociate key stages of memory processing.

Medial Orbitofrontal Cortex, Dorsolateral Prefrontal Cortex, and Hippocampus Differentially Represent the Event Saliency

Two primary functions attributed to the hippocampus and prefrontal cortex (PFC) network are retaining the temporal and spatial associations of events and detecting deviant events. It is unclear, however, how these two functions converge into one mechanism. Here, we tested whether increased activity with perceiving salient events is a deviant detection signal or contains information about the event associations by reflecting the magnitude of deviance (i.e., event saliency). We also tested how the deviant detection signal is affected by the degree of anticipation. We studied regional neural activity when people watched a movie that had varying saliency of a novel or an anticipated flow of salient events. Using intracranial electroencephalography from 10 patients, we observed that high-frequency activity (50-150 Hz) in the hippocampus, dorsolateral PFC, and medial OFC tracked event saliency. We also observed that medial OFC activity was stronger when the salient events were anticipated than when they were novel. These results suggest that dorsolateral PFC and medial OFC, as well as the hippocampus, signify the saliency magnitude of events, reflecting the hierarchical structure of event associations.

Human Verbal Memory Encoding Is Hierarchically Distributed in a Continuous Processing Stream

Processing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here, we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High γ frequency activity (65–115 Hz) showed consistent power responses during encoding of subsequently recalled and forgotten words on a subset of electrodes localized in 16 distinct cortical areas activated in the tasks. More of the high γ power during word encoding, and less power before and after the word presentation, was characteristic of successful recall and observed across multiple brain regions. Latencies of the induced power changes and this subsequent memory effect (SME) between the recalled and forgotten words followed an anatomical sequence from visual to prefrontal cortical areas. Finally, the magnitude of the memory effect was unexpectedly found to be the largest in selected brain regions both at the top and at the bottom of the processing stream. These included the language processing areas of the prefrontal cortex and the early visual areas at the junction of the occipital and temporal lobes. Our results provide evidence for distributed encoding of verbal memory organized along a hierarchical posterior-to-anterior processing stream.

Neural activity reveals interactions between episodic and semantic memory systems during retrieval

Whereas numerous findings support a distinction between episodic and semantic memory, it is now widely acknowledged that these two forms of memory interact during both encoding and retrieval. The precise nature of this interaction, however, remains poorly understood. To examine the role of semantic organization during episodic encoding and retrieval, we recorded intracranial encephalographic signals as 69 neurosurgical patients studied and subsequently recalled categorized and unrelated word lists. Applying multivariate classifiers to neural recordings, we were able to reliably predict encoding success, retrieval success, and temporal and categorical clustering during recall. By assessing how these classifiers generalized across list types, we identified specific retrieval processes that predicted recall of categorized lists and distinguished between recall transitions within and between category clusters. These results particularly implicate retrieval (rather than encoding) processes in the categorical organization of episodic memories. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Prefrontal high gamma during a magnetoencephalographic working memory task

In human electrophysiology research, the high gamma part of the power spectrum (~>60 Hz) is a relatively new area of investigation. Despite a low signal-to-noise ratio, evidence exists that it contains significant information about activity in local cortical networks. Here, using magnetoencephalography (MEG), we found high gamma activity when comparing data from an n-back working memory task to resting data in a large sample of normal volunteers. Initial analysis of power spectra from 0-back, 2-back, and rest trials showed three frequency bands exhibiting task-related differences: alpha, beta, and high gamma. Unlike alpha and beta, the high gamma spectrum was broad, without a peak at a single frequency. In addition, power in high gamma was highest for the 2-back and lowest during rest, while the opposite pattern occurred in the other bands. Beamformer source localization of each of the three frequency bands revealed a distinct set of sources for high gamma. These included several regions of prefrontal cortex that exhibited greater power when both n-back conditions were compared to rest. A subset of these regions had more power when the 2-back was compared to 0-back, which indicates a role in working memory performance. Our results show that high gamma will be important for understanding cortical processing during cognitive and other tasks. Furthermore, data from human intracortical recordings suggest that high gamma is the aggregate of spiking in local cortical networks, which implies that MEG could serve to bridge experimental modalities by noninvasively observing task-related modulation of spiking rates.

Gamma oscillations during episodic memory processing provide evidence for functional specialization in the longitudinal axis of the human hippocampus

The question of whether the anterior and posterior hippocampus serve different or complementary functional roles during episodic memory processing has been motivated by noteworthy findings in rodent experiments and from noninvasive studies in humans. Researchers have synthesized these data to postulate several models of functional specialization, However, the issue has not been explored in detail using direct brain recordings. We recently published evidence that theta power increases during episodic memory encoding occur in the posterior hippocampus in humans. In our current investigation we analyzed an expanded data set of 32 epilepsy patients undergoing stereo EEG seizure mapping surgery with electrodes precisely targeted to the anterior and posterior hippocampus simultaneously who performed an episodic memory task. Using a repeated measures design, we looked for an interaction between encoding versus retrieval differences in gamma oscillatory power and anterior versus posterior hippocampal location. Our findings are consistent with a recently articulated model (the HERNET model) favoring posterior hippocampal activation during retrieval related processing. We also tested for encoding versus retrieval differences in the preferred gamma frequency band (high versus low gamma oscillations) motivated by published rodent data.

Direct Cortical Recordings Suggest Temporal Order of Task-Evoked Responses in Human Dorsal Attention and Default Networks

The past decade has seen a large number of neuroimaging studies focused on the anticorrelated functional relationship between the default mode network (DMN) and the dorsal attention network (DAN). Due principally to the low temporal resolution of functional neuroimaging modalities, the fast-neuronal dynamics across these networks remain poorly understood. Here we report novel human intracranial electrophysiology data from six neurosurgical patients (four males) with simultaneous coverage of well characterized nodes of the DMN and DAN. Subjects performed an arithmetic processing task, shown previously to evoke reliable deactivations (below baseline) in the DMN, and activations in the DAN. In this cohort, we show that DMN deactivations lag DAN activations by approximately 200 ms. Our findings suggest a clear temporal order of processing across the two networks during the current task and place the DMN further than the DAN in a plausible information-processing hierarchy.SIGNIFICANCE STATEMENT The human brain contains an intrinsic and strictly organized network architecture. Our understanding of the interplay across association networks has relied primarily on the slow fluctuations of the hemodynamic response, and as such it has lacked essential evidence regarding the temporal dynamics of activity across these networks. The current study presents evidence from high spatiotemporal methods showing that well studied areas of the default mode network display delayed task-induced activity relative to divergent responses in dorsal attention network nodes. This finding provides direct and critical evidence regarding the temporal chronology of neuronal events across opposing brain networks.

Hippocampal CA1 gamma power predicts the precision of spatial memory judgments

The hippocampus plays a critical role in spatial memory. However, the exact neural mechanisms underlying high-fidelity spatial memory representations are unknown. We report findings from presurgical epilepsy patients with bilateral hippocampal depth electrodes performing an object-location memory task that provided a broad range of spatial memory precision. During encoding, patients were shown a series of objects along the circumference of an invisible circle. At test, the same objects were shown at the top of the circle (0°), and patients used a dial to move the object to its location shown during encoding. Angular error between the correct location and the indicated location was recorded as a continuous measure of performance. By registering pre- and postimplantation MRI scans, we were able to localize the electrodes to specific hippocampal subfields. We found a correlation between increased gamma power, thought to reflect local excitatory activity, and the precision of spatial memory retrieval in hippocampal CA1 electrodes. Additionally, we found a similar relationship between gamma power and memory precision in the dorsolateral prefrontal cortex and a directional relationship between activity in this region and in the CA1, suggesting that the dorsolateral prefrontal cortex is involved in postretrieval processing. These results indicate that local processing in hippocampal CA1 and dorsolateral prefrontal cortex supports high-fidelity spatial memory representations.

Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings

OBJECTIVE

We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordings obtained from human stereo EEG subjects. We also sought to test the impact of applying t-distributed stochastic neighbor embedding (tSNE) for unsupervised dimensionality reduction, as well as testing the effect of reducing input features to a core set of memory relevant brain areas. This work builds upon published efforts to develop a closed-loop stimulation device to improve memory performance.

APPROACH

We used a unique data set consisting of 30 stereo EEG patients with electrodes implanted into a core set of five common brain regions (along with other areas) who performed the free recall episodic memory task as brain activity was recorded. Using three different machine learning strategies, we trained classifiers to predict successful versus unsuccessful memory encoding and compared the difference in classifier performance (as measured by the AUC) at the subject level and in aggregate across modalities. We report the impact of feature reduction on the classifiers, including reducing the number of input brain regions, frequency bands, and the impact of tSNE.

RESULTS

Deep learning classifiers outperformed both support vector machines (SVM) and logistic regression (LR). A priori selection of core brain regions also improved classifier performance for LR and SVM models, especially when combined with tSNE.

SIGNIFICANCE

We report for the first time a direct comparison among traditional and deep learning methods of binary classification to the problem of predicting successful memory encoding using human brain electrophysiological data. Our findings will inform the design of brain machine interface devices to affect memory processing.

Pupil size reflects successful encoding and recall of memory in humans

Pupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most constricted in the initial fixation phase and was gradually more dilated through the subsequent encoding, distractor and recall phases of the task, as the word items were maintained in memory. Within the final recall phase, retrieving memory for individual words was associated with pupil dilation in absence of visual stimulation. Words that were successfully recalled showed significant differences in pupil response during their encoding compared to those that were forgotten – the pupil was more constricted before and more dilated after the onset of word presentation. Our results suggest pupil size as a potential biomarker for probing and modulation of memory processing.

Prediction of memory formation based on absolute electroencephalographic phases in rhinal cortex and hippocampus outperforms prediction based on stimulus-related phase shifts

Absolute (i.e. measured) rhinal and hippocampal phase values are predictive for memory formation. It has been an open question, whether the capability of mediotemporal structures to react to stimulus presentation with phase shifts may be similarly indicative of successful memory formation. We analysed data from 27 epilepsy patients implanted with depth electrodes in the hippocampus and entorhinal cortex, who performed a continuous word recognition task. Electroencephalographic phase information related to the first presentation of repeatedly presented words was used for prediction of subsequent remembering vs. forgetting applying a support vector machine. The capability to predict successful memory formation based on stimulus-related phase shifts was compared to that based on absolute phase values. Average hippocampal phase shifts were larger and rhinal phase shifts were more accumulated for later remembered compared to forgotten trials. Nevertheless, prediction based on absolute phase values clearly outperformed phase shifts and there was no significant increase in prediction accuracies when combining both measures. Our findings indicate that absolute rhinal and hippocampal phases and not stimulus-related phase shifts are most relevant for successful memory formation. Absolute phases possibly affect memory formation via influencing neural membrane potentials and thereby controlling the timing of neural firing.

Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction.

Signal Complexity of Human Intracranial EEG Tracks Successful Associative-Memory Formation across Individuals

Memory performance is highly variable among individuals. Most studies examining human memory, however, have largely focused on the neural correlates of successful memory formation within individuals, rather than the differences among them. As such, what gives rise to this variability is poorly understood. Here, we examined intracranial EEG (iEEG) recordings captured from 43 participants (23 male) implanted with subdural electrodes for seizure monitoring as they performed a paired-associates verbal memory task. We identified three separate but related signatures of neural activity that tracked differences in successful memory formation across individuals. High-performing individuals consistently exhibited less broadband power, flatter power spectral density slopes, and greater complexity in their iEEG signals. Furthermore, within individuals across three separate time scales ranging from seconds to days, successful recall was positively associated with these same metrics. Our data therefore suggest that memory ability across individuals can be indexed by increased neural signal complexity.SIGNIFICANCE STATEMENT We show that participants whose intracranial EEG exhibits less low-frequency power, flatter power spectrums, and greater sample entropy overall are better able to memorize associations, and that the same metrics track fluctuations in memory performance across time within individuals. These metrics together signify greater neural signal complexity, which may index the brain's ability to flexibly engage with information and generate separable memory representations. Critically, the current set of results provides a unique window into the neural markers of individual differences in memory performance, which have hitherto been underexplored.

Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition

The idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral neural activity, based on data from 294 neurosurgical patients fitted with indwelling electrodes. Here we report that gamma networks desynchronize and theta networks synchronize during encoding and retrieval. Furthermore, for nearly all brain regions we studied, gamma power rises as that region desynchronizes with gamma activity elsewhere in the brain, establishing gamma as a largely asynchronous phenomenon. The abundant phenomenon of theta synchrony is positively correlated with a brain region's gamma power, suggesting a predominant low-frequency mechanism for inter-regional communication.

Presurgical language mapping using event-related high-gamma activity: The Detroit procedure

A number of investigators have reported that event-related augmentation of high-gamma activity at 70-110 Hz on electrocorticography (ECoG) can localize functionally-important brain regions in children and adults who undergo epilepsy surgery. The advantages of ECoG-based language mapping over the gold-standard stimulation include: (i) lack of stimulation-induced seizures, (ii) better sensitivity of localization of language areas in young children, and (iii) shorter patient participant time. Despite its potential utility, ECoG-based language mapping is far less commonly practiced than stimulation mapping. Here, we have provided video presentations to explain, point-by-point, our own hardware setting and time-frequency analysis procedures. We also have provided standardized auditory stimuli, in multiple languages, ready to be used for ECoG-based language mapping. Finally, we discussed the technical aspects of ECoG-based mapping, including its pitfalls, to facilitate appropriate interpretation of the data.

Three- and four-dimensional mapping of speech and language in patients with epilepsy

We have provided 3-D and 4D mapping of speech and language function based upon the results of direct cortical stimulation and event-related modulation of electrocorticography signals. Patients estimated to have right-hemispheric language dominance were excluded. Thus, 100 patients who underwent two-stage epilepsy surgery with chronic electrocorticography recording were studied. An older group consisted of 84 patients at least 10 years of age (7367 artefact-free non-epileptic electrodes), whereas a younger group included 16 children younger than age 10 (1438 electrodes). The probability of symptoms transiently induced by electrical stimulation was delineated on a 3D average surface image. The electrocorticography amplitude changes of high-gamma (70-110 Hz) and beta (15-30 Hz) activities during an auditory-naming task were animated on the average surface image in a 4D manner. Thereby, high-gamma augmentation and beta attenuation were treated as summary measures of cortical activation. Stimulation data indicated the causal relationship between (i) superior-temporal gyrus of either hemisphere and auditory hallucination; (ii) left superior-/middle-temporal gyri and receptive aphasia; (iii) widespread temporal/frontal lobe regions of the left hemisphere and expressive aphasia; and (iv) bilateral precentral/left posterior superior-frontal regions and speech arrest. On electrocorticography analysis, high-gamma augmentation involved the bilateral superior-temporal and precentral gyri immediately following question onset; at the same time, high-gamma activity was attenuated in the left orbitofrontal gyrus. High-gamma activity was augmented in the left temporal/frontal lobe regions, as well as left inferior-parietal and cingulate regions, maximally around question offset, with high-gamma augmentation in the left pars orbitalis inferior-frontal, middle-frontal, and inferior-parietal regions preceded by high-gamma attenuation in the contralateral homotopic regions. Immediately before verbal response, high-gamma augmentation involved the posterior superior-frontal and pre/postcentral regions, bilaterally. Beta-attenuation was spatially and temporally correlated with high-gamma augmentation in general but with exceptions. The younger and older groups shared similar spatial-temporal profiles of high-gamma and beta modulation; except, the younger group failed to show left-dominant activation in the rostral middle-frontal and pars orbitalis inferior-frontal regions around stimulus offset. The human brain may rapidly and alternately activate and deactivate cortical areas advantageous or obtrusive to function directed toward speech and language at a given moment. Increased left-dominant activation in the anterior frontal structures in the older age group may reflect developmental consolidation of the language system. The results of our functional mapping may be useful in predicting, across not only space but also time and patient age, sites specific to language function for presurgical evaluation of focal epilepsy.

Similar patterns of neural activity predict memory function during encoding and retrieval

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval.

Stable functional networks exhibit consistent timing in the human brain

Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate that cortical regions exhibit functional relationships with well-defined and consistent timing, and the stability of these relationships over multiple time scales suggests that these stable pathways may be reliably and repeatedly used for large-scale cortical communication.

Lower Parietal Encoding Activation Is Associated with Sharper Information and Better Memory

Mean fMRI activation in ventral posterior parietal cortex (vPPC) during memory encoding often negatively predicts successful remembering. A popular interpretation of this phenomenon is that vPPC reflects "off-task" processing. However, recent fMRI studies considering distributed patterns of activity suggest that vPPC actively represents encoded material. Here, we assessed the relationships between pattern-based content representations in vPPC, mean activation in vPPC, and subsequent remembering. We analyzed data from two fMRI experiments where subjects studied then recalled word-face or word-scene associations. For each encoding trial, we measured 1) mean univariate activation within vPPC and 2) the strength of face/scene information as indexed by pattern analysis. Mean activation in vPPC negatively predicted subsequent remembering, but the strength of pattern-based information in the same vPPC voxels positively predicted later memory. Indeed, univariate amplitude averaged across vPPC voxels negatively correlated with pattern-based information strength. This dissociation reflected a tendency for univariate reductions to maximally occur in voxels that were not strongly tuned for the category of encoded stimuli. These results indicate that vPPC activity patterns reflect the content and quality of memory encoding and constitute a striking example of lower univariate activity corresponding to stronger pattern-based information.

Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans

People often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting, then decoded neural activity in later sessions in which we applied stimulation during learning. Stimulation increased encoding-state estimates and recall if delivered when the classifier indicated low encoding efficiency but had the reverse effect if stimulation was delivered when the classifier indicated high encoding efficiency. Higher encoding-state estimates from stimulation were associated with greater evidence of neural activity linked to contextual memory encoding. In identifying the conditions under which stimulation modulates memory, the data suggest strategies for therapeutically treating memory dysfunction.

Contextually Mediated Spontaneous Retrieval Is Specific to the Hippocampus

Although it is now well established that the hippocampus supports memory encoding [1, 2], little is known about hippocampal activity during spontaneous memory retrieval. Recent intracranial electroencephalographic (iEEG) work has shown that hippocampal activity during encoding predicts subsequent temporal organization of memories [3], supporting a role in contextual binding. It is an open question, however, whether the hippocampus similarly supports contextually mediated processes during retrieval. Here, we analyzed iEEG recordings obtained from 215 epilepsy patients as they performed a free recall task. To identify neural activity specifically associated with contextual retrieval, we compared correct recalls, intrusions (incorrect recall of either items from prior lists or items not previously studied), and deliberations (matched periods during recall when no items came to mind). Neural signals that differentiate correct recalls from both other retrieval classes reflect contextual retrieval, as correct recalls alone arise from the correct context. We found that in the hippocampus, high-frequency activity (HFA, 44-100 Hz), a proxy for neural activation [4], was greater prior to correct recalls relative to the other retrieval classes, with no differentiation between intrusions and deliberations. This pattern was not observed in other memory-related cortical regions, including DLPFC, thus supporting a specific hippocampal contribution to contextually mediated memory retrieval.

Cued Memory Retrieval Exhibits Reinstatement of High Gamma Power on a Faster Timescale in the Left Temporal Lobe and Prefrontal Cortex

Converging evidence suggests that reinstatement of neural activity underlies our ability to successfully retrieve memories. However, the temporal dynamics of reinstatement in the human cortex remain poorly understood. One possibility is that neural activity during memory retrieval, like replay of spiking neurons in the hippocampus, occurs at a faster timescale than during encoding. We tested this hypothesis in 34 participants who performed a verbal episodic memory task while we recorded high gamma (62-100 Hz) activity from subdural electrodes implanted for seizure monitoring. We show that reinstatement of distributed patterns of high gamma activity occurs faster than during encoding. Using a time-warping algorithm, we quantify the timescale of the reinstatement and identify brain regions that show significant timescale differences between encoding and retrieval. Our data suggest that temporally compressed reinstatement of cortical activity is a feature of cued memory retrieval.SIGNIFICANCE STATEMENT We show that cued memory retrieval reinstates neural activity on a faster timescale than was present during encoding. Our data therefore provide a link between reinstatement of neural activity in the cortex and spontaneous replay of cortical and hippocampal spiking activity, which also exhibits temporal compression, and suggest that temporal compression may be a universal feature of memory retrieval.

Interictal epileptiform discharges impair word recall in multiple brain areas

OBJECTIVES

Interictal epileptiform discharges (IEDs) have been linked to memory impairment, but the spatial and temporal dynamics of this relationship remain elusive. In the present study, we aim to systematically characterize the brain areas and times at which IEDs affect memory.

METHODS

Eighty epilepsy patients participated in a delayed free recall task while undergoing intracranial electroencephalography (EEG) monitoring. We analyzed the locations and timing of IEDs relative to the behavioral data in order to measure their effects on memory.

RESULTS

Overall IED rates did not correlate with task performance across subjects (r = 0.03, p = 0.8). However, at a finer temporal scale, within-subject memory was negatively affected by IEDs during the encoding and recall periods of the task but not during the rest and distractor periods (p < 0.01, p < 0.001, p = 0.3, and p = 0.8, respectively). The effects of IEDs during encoding and recall were stronger in the left hemisphere than in the right (p < 0.05). Of six brain areas analyzed, IEDs in the inferior-temporal, medial-temporal, and parietal areas significantly affected memory (false discovery rate < 0.05).

SIGNIFICANCE

These findings reveal a network of brain areas sensitive to IEDs with key nodes in temporal as well as parietal lobes. They also demonstrate the time-dependent effects of IEDs in this network on memory.

Oscillations and Episodic Memory: Addressing the Synchronization/Desynchronization Conundrum

Brain oscillations are one of the core mechanisms underlying episodic memory. However, while some studies highlight the role of synchronized oscillatory activity, others highlight the role of desynchronized activity. We here describe a framework to resolve this conundrum and integrate these two opposing oscillatory behaviors. Specifically, we argue that the synchronization and desynchronization reflect a division of labor between a hippocampal and a neocortical system, respectively. We describe a novel oscillatory framework that integrates synchronization and desynchronization mechanisms to explain how the two systems interact in the service of episodic memory.

Data from rodent as well as human studies suggest that theta/gamma synchronization in the hippocampus (i.e., theta phase to gamma power cross-frequency coupling) mediates the binding of different elements in episodic memory.

In vivo and in vitro animal studies suggest that theta provides selective time windows for fast-acting synaptic modifications and recent computational models have implemented these mechanisms to explain human memory formation and retrieval.

Recent data from human experiments suggest that low-frequency power decreases in the neocortex, most evident in the alpha/beta frequency range, mediate encoding and reinstatement of episodic memories.

The content of reinstated memories can be decoded from cortical low-frequency patterns.

Modulation of task demands suggests that semantic processing interferes with the formation of episodic associations

Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high-frequency EEG activity (HFA, 44-100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. (PsycINFO Database Record

Expectation modulates neural representations of valence throughout the human brain

The brain's sensitivity to unexpected gains or losses plays an important role in our ability to learn new behaviors (Rescorla and Wagner, 1972; Sutton and Barto, 1990). Recent work suggests that gains and losses are ubiquitously encoded throughout the human brain (Vickery et al., 2011), however, the extent to which reward expectation modulates these valence representations is not known. To address this question, we analyzed recordings from 4306 intracranially implanted electrodes in 39 neurosurgical patients as they performed a two-alternative probability learning task. Using high-frequency activity (HFA, 70-200 Hz) as an indicator of local firing rates, we found that expectation modulated reward-related neural activity in widespread brain regions, including regions that receive sparse inputs from midbrain dopaminergic neurons. The strength of unexpected gain signals predicted subjects' abilities to encode stimulus-reward associations. Thus, neural signals that are functionally related to learning are widely distributed throughout the human brain.

Decreases in theta and increases in high frequency activity underlie associative memory encoding

Episodic memory encoding refers to the cognitive process by which items and their associated contexts are stored in memory. To investigate changes directly attributed to the formation of explicit associations, we examined oscillatory power captured through intracranial electroencephalography (iEEG) as 27 neurosurgical patients receiving subdural and depth electrodes for seizure monitoring participated in a paired associates memory task. We examined low (3-8Hz) and high (45-95Hz) frequency activity, and found that the successful formation of new associations was accompanied by broad decreases in low frequency activity and a posterior to anterior progression of increases in high frequency activity in the left hemisphere. These data suggest that the observed patterns of activity may reflect the neural mechanisms underlying the formation of novel item-item associations.

Human intracranial high-frequency activity during memory processing: neural oscillations or stochastic volatility?

Intracranial high-frequency activity (HFA), which refers to fast fluctuations in electrophysiological recordings, increases during memory processing. Two views have emerged to explain this effect: (1) HFA reflects a synchronous signal, related to underlying gamma oscillations, that plays a mechanistic role in human memory and (2) HFA reflects an asynchronous signal that is a non-specific marker of brain activation. We review recent data supporting each of these views and conclude that HFA during memory processing is more consistent with an asynchronous signal. Memory-related HFA is therefore best conceptualized as a biomarker of neural activation that can functionally map memory with high spatial and temporal precision.

Dissociated roles of the inferior frontal gyrus and superior temporal sulcus in audiovisual processing: top-down and bottom-up mismatch detection

Visual inputs can distort auditory perception, and accurate auditory processing requires the ability to detect and ignore visual input that is simultaneous and incongruent with auditory information. However, the neural basis of this auditory selection from audiovisual information is unknown, whereas integration process of audiovisual inputs is intensively researched. Here, we tested the hypothesis that the inferior frontal gyrus (IFG) and superior temporal sulcus (STS) are involved in top-down and bottom-up processing, respectively, of target auditory information from audiovisual inputs. We recorded high gamma activity (HGA), which is associated with neuronal firing in local brain regions, using electrocorticography while patients with epilepsy judged the syllable spoken by a voice while looking at a voice-congruent or -incongruent lip movement from the speaker. The STS exhibited stronger HGA if the patient was presented with information of large audiovisual incongruence than of small incongruence, especially if the auditory information was correctly identified. On the other hand, the IFG exhibited stronger HGA in trials with small audiovisual incongruence when patients correctly perceived the auditory information than when patients incorrectly perceived the auditory information due to the mismatched visual information. These results indicate that the IFG and STS have dissociated roles in selective auditory processing, and suggest that the neural basis of selective auditory processing changes dynamically in accordance with the degree of incongruity between auditory and visual information.

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.

Brain computer interface to enhance episodic memory in human participants

Recent research has revealed that neural oscillations in the theta (4-8 Hz) and alpha (9-14 Hz) bands are predictive of future success in memory encoding. Because these signals occur before the presentation of an upcoming stimulus, they are considered stimulus-independent in that they correlate with enhanced memory encoding independent of the item being encoded. Thus, such stimulus-independent activity has important implications for the neural mechanisms underlying episodic memory as well as the development of cognitive neural prosthetics. Here, we developed a brain computer interface (BCI) to test the ability of such pre-stimulus activity to modulate subsequent memory encoding. We recorded intracranial electroencephalography (iEEG) in neurosurgical patients as they performed a free recall memory task, and detected iEEG theta and alpha oscillations that correlated with optimal memory encoding. We then used these detected oscillatory changes to trigger the presentation of items in the free recall task. We found that item presentation contingent upon the presence of pre-stimulus theta and alpha oscillations modulated memory performance in more sessions than expected by chance. Our results suggest that an electrophysiological signal may be causally linked to a specific behavioral condition, and contingent stimulus presentation has the potential to modulate human memory encoding.

Event memory: A theory of memory for laboratory, autobiographical, and fictional events

An event memory is a mental construction of a scene recalled as a single occurrence. It therefore requires the hippocampus and ventral visual stream needed for all scene construction. The construction need not come with a sense of reliving or be made by a participant in the event, and it can be a summary of occurrences from more than one encoding. The mental construction, or physical rendering, of any scene must be done from a specific location and time; this introduces a "self" located in space and time, which is a necessary, but need not be a sufficient, condition for a sense of reliving. We base our theory on scene construction rather than reliving because this allows the integration of many literatures and because there is more accumulated knowledge about scene construction's phenomenology, behavior, and neural basis. Event memory differs from episodic memory in that it does not conflate the independent dimensions of whether or not a memory is relived, is about the self, is recalled voluntarily, or is based on a single encoding with whether it is recalled as a single occurrence of a scene. Thus, we argue that event memory provides a clearer contrast to semantic memory, which also can be about the self, be recalled voluntarily, and be from a unique encoding; allows for a more comprehensive dimensional account of the structure of explicit memory; and better accounts for laboratory and real-world behavioral and neural results, including those from neuropsychology and neuroimaging, than does episodic memory.

Corticothalamic phase synchrony and cross-frequency coupling predict human memory formation

The anterior thalamic nucleus (ATN) is thought to play an important role in a brain network involving the hippocampus and neocortex, which enables human memories to be formed. However, its small size and location deep within the brain have impeded direct investigation in humans with non-invasive techniques. Here we provide direct evidence for a functional role for the ATN in memory formation from rare simultaneous human intrathalamic and scalp electroencephalogram (EEG) recordings from eight volunteering patients receiving intrathalamic electrodes implanted for the treatment of epilepsy, demonstrating real-time communication between neocortex and ATN during successful memory encoding. Neocortical-ATN theta oscillatory phase synchrony of local field potentials and neocortical-theta-to-ATN-gamma cross-frequency coupling during presentation of complex photographic scenes predicted later memory for the scenes, demonstrating a key role for the ATN in human memory encoding.

Theta and high-frequency activity mark spontaneous recall of episodic memories

Humans possess the remarkable ability to search their memory, allowing specific past episodes to be re-experienced spontaneously. Here, we administered a free recall test to 114 neurosurgical patients and used intracranial theta and high-frequency activity (HFA) to identify the spatiotemporal pattern of neural activity underlying spontaneous episodic retrieval. We found that retrieval evolved in three electrophysiological stages composed of: (1) early theta oscillations in the right temporal cortex, (2) increased HFA in the left hemisphere including the medial temporal lobe (MTL), left inferior frontal gyrus, as well as the ventrolateral temporal cortex, and (3) motor/language activation during vocalization of the retrieved item. Of these responses, increased HFA in the left MTL predicted recall performance. These results suggest that spontaneous recall of verbal episodic memories involves a spatiotemporal pattern of spectral changes across the brain; however, high-frequency activity in the left MTL represents a final common pathway of episodic retrieval.

Contribution of research on 'Epilepsy & behavior' to the refinement of functional brain atlas in four dimensions

Intracranial stimulation mapping by Penfield et al. largely contributed to our current knowledge of the functional organization of motor, sensory, and language systems. The functional maps were generated and printed in two dimensions, based on the summary results of direct cortical stimulation of which locations varied across patients. Intracranial measurement of electrocorticographic changes elicited by a task can localize the regions involved in or participating to the given task. Augmentation of high-gamma activity at >80 Hz is considered to reflect in situ cortical activation at each moment. In the late 2000s, the spatial-temporal profiles of event-related high-gamma activity began to be published as a video material in journals. We have referred to our animation movie as ‘in-vivo animation of event-related high-gamma activity’, that demonstrates ‘when’ and ‘where’ cortical regions are activated in a self-explanatory fashion. Summation of event-related high-gamma measures derived from a large cohort of patients, as previously performed by Penfield et al, is expected to generate unique four-dimensional functional brain atlas covering the whole cerebral cortex.

Eye closure causes widespread low-frequency power increase and focal gamma attenuation in the human electrocorticogram

OBJECTIVE

We sought to characterize the effects of eye closure on EEG power using electrocorticography (ECoG). Specifically, we sought to elucidate the anatomical areas demonstrating an eye closure effect, and at which frequencies this effect occurs.

METHODS

ECoG was recorded from 32 patients undergoing invasive monitoring for seizure focus localization. Patients were instructed to close and open their eyes repeatedly. ECoG power was compared in the epochs following eye closure and opening, for various frequency bands and brain regions.

RESULTS

We found that at low frequencies, eye closure causes widespread power increases involving all lobes of the brain. This effect was significant not only in the α (8-12 Hz) band but in the δ (2-4 Hz), θ (4-8 Hz), and β (15-30 Hz) bands as well. At high frequencies, eye closure causes comparatively focal power decreases over occipital cortex and frontal Brodmann areas 8 and 9.

CONCLUSIONS

Eye closure (1) affects a broad range of frequencies outside the α band and (2) involves a distributed network of neural activity in anatomical areas outside visual cortex.

SIGNIFICANCE

This study constitutes the first large-scale, systematic application of ECoG to study eye closure, which is shown to influence a broad range of frequencies and brain regions.

Intracranial recordings and human memory

Recent work involving intracranial recording during human memory performance provides superb spatiotemporal resolution on mnemonic processes. These data demonstrate that the cortical regions identified in neuroimaging studies of memory fall into temporally distinct networks and the hippocampal theta activity reported in animal memory literature also plays a central role in human memory. Memory is linked to activity at multiple interacting frequencies, ranging from 1 to 500Hz. High-frequency responses and coupling between different frequencies suggest that frontal cortex activity is critical to human memory processes, as well as a potential key role for the thalamus in neocortical oscillations. Future research will inform unresolved questions in the neuroscience of human memory and guide creation of stimulation protocols to facilitate function in the damaged brain.

From speech to thought: the neuronal basis of cognitive units in non-experimental, real-life communication investigated using ECoG

Exchange of thoughts by means of expressive speech is fundamental to human communication. However, the neuronal basis of real-life communication in general, and of verbal exchange of ideas in particular, has rarely been studied until now. Here, our aim was to establish an approach for exploring the neuronal processes related to cognitive “idea” units (IUs) in conditions of non-experimental speech production. We investigated whether such units corresponding to single, coherent chunks of speech with syntactically-defined borders, are useful to unravel the neuronal mechanisms underlying real-world human cognition. To this aim, we employed simultaneous electrocorticography (ECoG) and video recordings obtained in pre-neurosurgical diagnostics of epilepsy patients. We transcribed non-experimental, daily hospital conversations, identified IUs in transcriptions of the patients' speech, classified the obtained IUs according to a previously-proposed taxonomy focusing on memory content, and investigated the underlying neuronal activity. In each of our three subjects, we were able to collect a large number of IUs which could be assigned to different functional IU subclasses with a high inter-rater agreement. Robust IU-onset-related changes in spectral magnitude could be observed in high gamma frequencies (70–150 Hz) on the inferior lateral convexity and in the superior temporal cortex regardless of the IU content. A comparison of the topography of these responses with mouth motor and speech areas identified by electrocortical stimulation showed that IUs might be of use for extraoperative mapping of eloquent cortex (average sensitivity: 44.4%, average specificity: 91.1%). High gamma responses specific to memory-related IU subclasses were observed in the inferior parietal and prefrontal regions. IU-based analysis of ECoG recordings during non-experimental communication thus elicits topographically- and functionally-specific effects. We conclude that segmentation of spontaneous real-world speech in linguistically-motivated units is a promising strategy for elucidating the neuronal basis of mental processing during non-experimental communication.

Subsequent memory effect in intracranial and scalp EEG

Successful memory encoding is marked by increases in 30-100Hz gamma-band activity in a broad network of brain regions. Activity in the 3-8Hz theta band has also been shown to modulate memory encoding, but this effect has been found to vary in direction across studies. Because of the diversity in memory tasks, and in recording and data-analytic methods, our knowledge of the theta frequency modulations remains limited. The difference in the directionality of these theta effects could arise from a distinction between global cortical and deeper subcortical effects. To address this issue, we examined the spectral correlates of successful memory encoding using intracranial EEG recordings in neurosurgical patients and scalp EEG recordings in healthy controls. We found significant theta (3-8Hz) power modulations (both increases and decreases) and high gamma (44-100Hz) power increases in both samples of participants. These results suggest that (1) there are two separate theta mechanisms supporting memory success, a broad theta decrease present across both the cortex and hippocampus as well as a theta power increase in the frontal cortex, (2) scalp EEG is capable of resolving high frequency gamma activity, and (3) iEEG theta effects are likely not the result of epileptic pathology.

Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval

Neural oscillations in the theta band (4-8 Hz) are prominent in the human electroencephalogram (EEG), and many recent electrophysiological studies in animals and humans have implicated scalp-recorded frontal midline theta (FMT) in working memory and episodic memory encoding and retrieval processes. However, the functional significance of theta oscillations in human memory processes remains largely unknown. Here, we review studies in human and animals examining how scalp-recorded FMT relates to memory behaviors and also their possible neural generators. We also discuss models of the functional relevance of theta oscillations to memory processes and suggest promising directions for future research.