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

Time-Resolved Aperiodic and Oscillatory Dynamics during Human Visual Memory Encoding

Biological neural networks translate sensory information into neural code that is held in memory over long timescales. Theories for how this occurs often posit a functional role of neural oscillations. However, recent advances show that neural oscillations are often confounded with non-oscillatory, aperiodic neural activity. Here we analyze a dataset of intracranial human EEG recordings (N = 13; 10 female) to test the hypothesis that aperiodic activity plays a role in visual memory, independent and distinct from oscillations. By leveraging a new approach to time-resolved parameterization of neural spectral activity, we find event-related changes in both oscillations and aperiodic activity during memory encoding. During memory encoding, aperiodic-adjusted alpha oscillatory power significantly decreases while, simultaneously, aperiodic neural activity "flattens out". These results provide novel evidence for task-related dynamics of both aperiodic and oscillatory activity in human memory, paving the way for future investigations into the unique functional roles of these two neural processes in human cognition.

DLPFC Stimulation Suppresses High-Frequency Neural Activity in the Human sgACC

Transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (DLPFC) is hypothesized to relieve symptoms of depression by inhibiting activity in the subgenual anterior cingulate cortex (sgACC). However, we have a limited understanding of how TMS influences neural activity in the sgACC, owing to its deep location within the brain. To better understand the mechanism of antidepressant response to TMS, we recruited two neurosurgical patients with indwelling electrodes and delivered TMS pulses to the DLPFC while simultaneously recording local field potentials from the sgACC. Spectral analysis revealed a decrease in high-frequency activity (HFA; 70-180 Hz) after each stimulation pulse, which was especially pronounced in the sgACC relative to other regions. TMS-evoked HFA power was generally anticorrelated between the DLPFC and sgACC, even while low-frequency phase locking between the two regions was enhanced. Together, these findings support the notion that TMS to the DLPFC can suppress neural firing in the sgACC, suggesting a possible mechanism by which this treatment regulates mood.

Reinstatement and transformation of memory traces for recognition

Episodic memory relies on the formation and retrieval of content-specific memory traces. In addition to their veridical reactivation, previous studies have indicated that traces may undergo substantial transformations. However, the exact time course and regional distribution of reinstatement and transformation during recognition memory have remained unclear. We applied representational similarity analysis to human intracranial electroencephalography to track the spatiotemporal dynamics underlying the reinstatement and transformation of memory traces. Specifically, we examined how reinstatement and transformation of item-specific representations across occipital, ventral visual, and lateral parietal cortices contribute to successful memory formation and recognition. Our findings suggest that reinstatement in temporal cortex and transformation in parietal cortex coexist and provide complementary strategies for recognition. Further, we find that generalization and differentiation of neural representations contribute to memory and probe memory-specific correspondence with deep neural network (DNN) model features. Our results suggest that memory formation is particularly supported by generalized and mnemonic representational formats beyond the visual features of a DNN.

Antagonistic behavior of brain networks mediated by low-frequency oscillations: electrophysiological dynamics during internal-external attention switching

Antagonistic activity of brain networks likely plays a fundamental role in how the brain optimizes its performance by efficient allocation of computational resources. A prominent example involves externally/internally oriented attention tasks, implicating two anticorrelated, intrinsic brain networks: the default mode network (DMN) and the dorsal attention network (DAN). To elucidate electrophysiological underpinnings and causal interplay during attention switching, we recorded intracranial EEG (iEEG) from 25 epilepsy patients with electrode contacts localized in the DMN and DAN. We show antagonistic network dynamics of activation-related changes in high-frequency (> 50 Hz) and low-frequency (< 30 Hz) power. The temporal profile of information flow between the networks estimated by functional connectivity suggests that the activated network inhibits the other one, gating its activity by increasing the amplitude of the low-frequency oscillations. Insights about inter-network communication may have profound implications for various brain disorders in which these dynamics are compromised.

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.

Dichotomous frequency-dependent phase synchrony in the sensorimotor network characterizes simplistic movement

It is hypothesized that disparate brain regions interact via synchronous activity to control behavior. The nature of these interconnected ensembles remains an area of active investigation, and particularly the role of high frequency synchronous activity in simplistic behavior is not well known. Using intracranial electroencephalography, we explored the spectral dynamics and network connectivity of sensorimotor cortical activity during a simple motor task in seven epilepsy patients. Confirming prior work, we see a "spectral tilt" (increased high-frequency (HF, 70-100 Hz) and decreased low-frequency (LF, 3-33 Hz) broadband oscillatory activity) in motor regions during movement compared to rest, as well as an increase in LF synchrony between these regions using time-resolved phase-locking. We then explored this phenomenon in high frequency and found a robust but opposite effect, where time-resolved HF broadband phase-locking significantly decreased during movement. This "connectivity tilt" (increased LF synchrony and decreased HF synchrony) displayed a graded anatomical dependency, with the most robust pattern occurring in primary sensorimotor cortical interactions and less robust pattern occurring in associative cortical interactions. Connectivity in theta (3-7 Hz) and high beta (23-27 Hz) range had the most prominent low frequency contribution during movement, with theta synchrony building gradually while high beta having the most prominent effect immediately following the cue. There was a relatively sharp, opposite transition point in both the spectral and connectivity tilt at approximately 35 Hz. These findings support the hypothesis that task-relevant high-frequency spectral activity is stochastic and that the decrease in high-frequency synchrony may facilitate enhanced low frequency phase coupling and interregional communication. Thus, the "connectivity tilt" may characterize behaviorally meaningful cortical interactions.

EEG decoders track memory dynamics

Encoding- and retrieval-related neural activity jointly determine mnemonic success. We ask whether electroencephalographic activity can reliably predict encoding and retrieval success on individual trials. Each of 98 participants performed a delayed recall task on 576 lists across 24 experimental sessions. Logistic regression classifiers trained on spectral features measured immediately preceding spoken recall of individual words successfully predict whether or not those words belonged to the target list. Classifiers trained on features measured during word encoding also reliably predict whether those words will be subsequently recalled and further predict the temporal and semantic organization of the recalled items. These findings link neural variability predictive of successful memory with item-to-context binding, a key cognitive process thought to underlie episodic memory function.

Human Hippocampal Ripples Signal Encoding of Episodic Memories

Direct human brain recordings have confirmed the presence of high-frequency oscillatory events, termed ripples, during awake behavior. While many prior studies have focused on medial temporal lobe (MTL) ripples during memory retrieval, here we investigate ripples during memory encoding. Specifically, we ask whether ripples during encoding predict whether and how memories are subsequently recalled. Detecting ripples from MTL electrodes implanted in 116 neurosurgical participants (n = 61 male) performing a verbal episodic memory task, we find that encoding ripples do not distinguish recalled from not recalled items in any MTL region, even as high-frequency activity during encoding predicts recall in these same regions. Instead, hippocampal ripples increase during encoding of items that subsequently lead to recall of temporally and semantically associated items during retrieval, a phenomenon known as clustering. This subsequent clustering effect arises specifically when hippocampal ripples co-occur during encoding and retrieval, suggesting that ripples mediate both encoding and reinstatement of episodic memories.

Gamma Oscillations as a Biomarker of Neural Circuit Function in Psychosis: Where Are We, and Where Do We Go from Here?

This chapter is a selective and critical review of the literature on gamma oscillations in schizophrenia and related studies in other relevant fields that pertain to the hypothesis that abnormal gamma oscillations underlie symptoms of psychosis in individuals with schizophrenia. These gamma abnormalities result from deficient recurrent inhibition, in which parvalbumin-expressing, fast-spiking inhibitory interneurons do not receive sufficient excitation from N-methyl-D-aspartate receptors, resulting in a loss of phasic control over pyramidal cell spiking and impairment of gamma generation. The evidence for this hypothesis is critically reviewed, focusing on studies in the areas of visual feature binding, auditory steady-state response, and spontaneous gamma activity. The current state of the field is discussed, and recommendations for future directions are presented.

Neurophysiological mechanisms of cognition in the developing brain: Insights from intracranial EEG studies

The quest to understand how the development of the brain supports the development of complex cognitive functions is fueled by advances in cognitive neuroscience methods. Intracranial EEG (iEEG) recorded directly from the developing human brain provides unprecedented spatial and temporal resolution for mapping the neurophysiological mechanisms supporting cognitive development. In this paper, we focus on episodic memory, the ability to remember detailed information about past experiences, which improves from childhood into adulthood. We review memory effects based on broadband spectral power and emphasize the importance of isolating narrowband oscillations from broadband activity to determine mechanisms of neural coordination within and between brain regions. We then review evidence of developmental variability in neural oscillations and present emerging evidence linking the development of neural oscillations to the development of memory. We conclude by proposing that the development of oscillations increases the precision of neural coordination and may be an essential factor underlying memory development. More broadly, we demonstrate how recording neural activity directly from the developing brain holds immense potential to advance our understanding of cognitive development.

Hippocampal activity predicts contextual misattribution of false memories

Failure of contextual retrieval can lead to false recall, wherein people retrieve an item or experience that occurred in a different context or did not occur at all. Whereas the hippocampus is thought to play a crucial role in memory retrieval, we lack understanding of how the hippocampus supports retrieval of items related to a target context while disregarding related but irrelevant information. Using direct electrical recordings from the human hippocampus, we investigate the neural process underlying contextual misattribution of false memories. In two large datasets, we characterize key physiological differences between correct and false recalls that emerge immediately prior to vocalization. By differentiating between false recalls that share high or low contextual similarity with the target context, we show that low-frequency activity (6 to 18 Hz) in the hippocampus tracks similarity between the current and retrieved context. Applying multivariate decoding methods, we were able to reliably predict the contextual source of the to-be-recalled item. Our findings elucidate one of the hallmark features of episodic memory: our ability to distinguish between memories that were formed on different occasions.

Gamma oscillations and episodic memory

Enhanced gamma oscillatory activity (30-80 Hz) accompanies the successful formation and retrieval of episodic memories. While this co-occurrence is well documented, the mechanistic contributions of gamma oscillatory activity to episodic memory remain unclear. Here, we review how gamma oscillatory activity may facilitate spike timing-dependent plasticity, neural communication, and sequence encoding/retrieval, thereby ensuring the successful formation and/or retrieval of an episodic memory. Based on the evidence reviewed, we propose that multiple, distinct forms of gamma oscillation can be found within the canonical gamma band, each of which has a complementary role in the neural processes listed above. Further exploration of these theories using causal manipulations may be key to elucidating the relevance of gamma oscillatory activity to episodic memory.

Oscillatory and non-oscillatory brain activity reflects fear expression in an immediate and delayed fear extinction task

Fear extinction is pivotal for inhibiting fear responding to former threat-predictive stimuli. In rodents, short intervals between fear acquisition and extinction impair extinction recall compared to long intervals. This is called Immediate Extinction Deficit (IED). Importantly, human studies of the IED are sparse and its neurophysiological correlates have not been examined in humans. We, therefore, investigated the IED by recording electroencephalography (EEG), skin conductance responses (SCRs), an electrocardiogram (ECG), and subjective ratings of valence and arousal. Forty male participants were randomly assigned to extinction learning either 10 min after fear acquisition (immediate extinction) or 24 h afterward (delayed extinction). Fear and extinction recall were assessed 24 h after extinction learning. We observed evidence for an IED in SCR responses, but not in the ECG, subjective ratings, or in any assessed neurophysiological marker of fear expression. Irrespective of extinction timing (immediate vs. delayed), fear conditioning caused a tilt of the non-oscillatory background spectrum with decreased low-frequency power (<30 Hz) for threat-predictive stimuli. When controlling for this tilt, we observed a suppression of theta and alpha oscillations to threat-predictive stimuli, especially pronounced during fear acquisition. In sum, our data show that delayed extinction might be partially advantageous over immediate extinction in reducing sympathetic arousal (as assessed via SCR) to former threat-predictive stimuli. However, this effect was limited to SCR responses since all other fear measures were not affected by extinction timing. Additionally, we demonstrate that oscillatory and non-oscillatory activity is sensitive to fear conditioning, which has important implications for fear conditioning studies examining neural oscillations.

Passive functional mapping of receptive language cortex during general anesthesia using electrocorticography

OBJECTIVE

To investigate the feasibility of passive functional mapping in the receptive language cortex during general anesthesia using electrocorticographic (ECoG) signals.

METHODS

We used subdurally placed ECoG grids to record cortical responses to speech stimuli during awake and anesthesia conditions. We identified the cortical areas with significant responses to the stimuli using the spectro-temporal consistency of the brain signal in the broadband gamma (BBG) frequency band (70-170 Hz).

RESULTS

We found that ECoG BBG responses during general anesthesia effectively identify cortical regions associated with receptive language function. Our analyses demonstrated that the ability to identify receptive language cortex varies across different states and depths of anesthesia. We confirmed these results by comparing them to receptive language areas identified during the awake condition. Quantification of these results demonstrated an average sensitivity and specificity of passive language mapping during general anesthesia to be 49±7.7% and 100%, respectively.

CONCLUSION

Our results demonstrate that mapping receptive language cortex in patients during general anesthesia is feasible.

SIGNIFICANCE

Our proposed protocol could greatly expand the population of patients that can benefit from passive language mapping techniques, and could eliminate the risks associated with electrocortical stimulation during an awake craniotomy.

Hippocampal Theta and Episodic Memory

Computational models of rodent physiology implicate hippocampal theta as a key modulator of learning and memory (Buzsáki and Moser, 2013; Lisman and Jensen, 2013), yet human hippocampal recordings have shown divergent theta correlates of memory formation. Herweg et al. (2020) suggest that decreases in memory-related broadband power mask narrowband theta increases. Their survey also notes that the theta oscillations appear most prominently in contrasts that isolate memory retrieval processes and when aggregating signals across large brain regions. We evaluate these hypotheses by analyzing human hippocampal recordings captured as 162 neurosurgical patients (n = 86 female) performed a free recall task. Using the Irregular-Resampling Auto-Spectral Analysis (IRASA) to separate broad and narrowband components of the field potential, we show that (1) broadband and narrowband components of theta exhibit opposite effects, with broadband signals decreasing and narrowband theta increasing during successful encoding; (2) whereas low-frequency theta oscillations increase before successful recall, higher-frequency theta and alpha oscillations decrease, masking the positive effect of theta when aggregating across the full band; and (3) the effects of theta on memory encoding and retrieval do not differ between reference schemes that accentuate local signals (bipolar) and those that aggregate signals globally (whole-brain average). In line with computational models that ascribe a fundamental role for hippocampal theta in memory, our large-scale study of human hippocampal recordings shows that 3-4 Hz theta oscillations reliably increase during successful memory encoding and before spontaneous recall of previously studied items.SIGNIFICANCE STATEMENT Analyzing recordings from 162 participants, we resolve a long-standing question regarding the role of hippocampal theta oscillations in the formation and retrieval of episodic memories. We show that broadband spectral changes confound estimates of narrowband theta activity, thereby accounting for inconsistent results in the literature. After accounting for broadband effects, we find that increased theta activity marks successful encoding and retrieval of episodic memories, supporting rodent models that ascribe a key role for hippocampal theta in memory function.

The contribution of gamma bursting to spontaneous gamma activity in schizophrenia

Increased spontaneous gamma (30-100 Hz) activity (SGA) has been reported in the auditory cortex in schizophrenia. This phenomenon has been correlated with psychotic symptoms such as auditory hallucinations and could reflect the dysfunction of NMDA receptors on parvalbumin-expressing inhibitory interneurons. Previous findings are from time-averaged spectra, so it is unknown whether increased spontaneous gamma occurs at a constant level, or rather in bursts. To better understand the dynamical nature of spontaneous gamma activity in schizophrenia, here we examined the contribution of gamma bursting and the slope of the EEG spectrum to this phenomenon. The main results from this data set were previously reported. Participants were 24 healthy control participants (HC) and 24 matched participants with schizophrenia (SZ). The data were from EEG recordings during auditory steady-state stimulation, which were localized to bilateral pairs of dipoles in auditory cortex. Time-frequency analysis was performed using Morlet wavelets. Oscillation bursts in the gamma range were defined as periods during which power exceeded 2 standard deviations above the trial-wide average value for at least one cycle. We extracted the burst parameters power, count, and area, as well as non-burst trial power and spectral slope. Gamma burst power and non-burst trial power were greater in SZ than HC, but burst count and area did not differ. Spectral slope was less negative in SZ than HC. Regression modeling found that gamma burst power alone best predicted SGA for both HC and SZ (> = 90% of variance), while spectral slope made a small contribution and non-burst trial power did not influence SGA. Increased SGA in the auditory cortex in schizophrenia is accounted for by increased power within gamma bursts, rather than a tonic increase in gamma-range activity, or a shift in spectral slope. Further research will be necessary to determine if these measures reflect different network mechanisms. We propose that increased gamma burst power is the main component of increased SGA in SZ and could reflect abnormally increased plasticity in cortical circuits due to enhanced plasticity of synapses on parvalbumin-expressing inhibitory interneurons. Thus, increased gamma burst power may be involved in producing psychotic symptoms and cognitive dysfunction.

Fronto-parietal single-trial brain connectivity benefits successful memory recognition

Successful recognition has been known to produce distinct patterns of neural activity. Many studies have used spectral power or event-related potentials of single recognition-specific regions as classification features. However, this does not accurately reflect the mechanisms behind recognition, in that recognition requires multiple brain regions to work together. Hence, classification accuracy of subsequent memory performance could be improved by using functional connectivity within memory-related brain networks instead of using local brain activity as classifiers. In this study, we examined electroencephalography (EEG) signals while performing a word recognition memory task. Recorded EEG signals were collected using a 32-channel cap. Connectivity measures related to the left hemispheric fronto-parietal connectivity (P3 and F3) were found to contribute to the accurate recognition of previously studied memory items. Classification of subsequent memory outcome using connectivity features revealed that the classifier with support vector machine achieved the highest classification accuracy of 86.79 ± 5.93% (mean ± standard deviation) by using theta (3-8 Hz) connectivity during successful recognition trials. The results strongly suggest that highly accurate classification of subsequent memory outcome can be achieved by using single-trial functional connectivity.

Interictal Gamma Event Connectivity Differentiates the Seizure Network and Outcome in Patients after Temporal Lobe Epilepsy Surgery

Studies of interictal EEG functional connectivity in the epileptic brain seek to identify abnormal interactions between brain regions involved in generating seizures, which clinically often is defined by the seizure onset zone (SOZ). However, there is evidence for abnormal connectivity outside the SOZ (NSOZ), and removal of the SOZ does not always result in seizure control, suggesting, in some cases, that the extent of abnormal connectivity indicates a larger seizure network than the SOZ. To better understand the potential differences in interictal functional connectivity in relation to the seizure network and outcome, we computed event connectivity in the theta (4-8 Hz, ThEC), low-gamma (30-55 Hz, LGEC), and high-gamma (65-95 Hz, HGEC) bands from interictal depth EEG recorded in surgical patients with medication-resistant seizures suspected to begin in the temporal lobe. Analysis finds stronger LGEC and HGEC in SOZ than NSOZ of seizure-free (SF) patients (p = 1.10e-9, 0.0217), but no difference in not seizure-free (NSF) patients. There were stronger LGEC and HGEC between mesial and lateral temporal SOZ of SF than NSF patients (p = 0.00114, 0.00205), and stronger LGEC and ThEC in NSOZ of NSF than SF patients (p = 0.0089, 0.0111). These results show that event connectivity is sensitive to differences in the interactions between regions in SOZ and NSOZ and SF and NSF patients. Patients with differential strengths in event connectivity could represent a well-localized seizure network, whereas an absence of differences could indicate a larger seizure network than the one localized by the SOZ and higher likelihood for seizure recurrence.

EEG biomarkers of free recall

Brain activity in the moments leading up to spontaneous verbal recall provide a window into the cognitive processes underlying memory retrieval. But these same recordings also subsume neural signals unrelated to mnemonic retrieval, such as response-related motor activity. Here we examined spectral EEG biomarkers of memory retrieval under an extreme manipulation of mnemonic demands: subjects either recalled items after a few seconds or after several days. This manipulation helped to isolate EEG components specifically related to long-term memory retrieval. In the moments immediately preceding recall we observed increased theta (4-8 Hz) power (+T), decreased alpha (8-20 Hz) power (-A), and increased gamma (40-128 Hz) power (+G), with this spectral pattern (+T-A + G) distinguishing the long-delay and immediate recall conditions. As subjects vocalized the same set of studied words in both conditions, we interpret the spectral +T-A + G as a biomarker of episodic memory retrieval.

Oscillations support short latency co-firing of neurons during human episodic memory formation

Theta and gamma oscillations in the medial temporal lobe are suggested to play a critical role for human memory formation via establishing synchrony in neural assemblies. Arguably, such synchrony facilitates efficient information transfer between neurons and enhances synaptic plasticity, both of which benefit episodic memory formation. However, to date little evidence exists from humans that would provide direct evidence for such a specific role of theta and gamma oscillations for episodic memory formation. Here, we investigate how oscillations shape the temporal structure of neural firing during memory formation in the medial temporal lobe. We measured neural firing and local field potentials in human epilepsy patients via micro-wire electrode recordings to analyze whether brain oscillations are related to co-incidences of firing between neurons during successful and unsuccessful encoding of episodic memories. The results show that phase-coupling of neurons to faster theta and gamma oscillations correlates with co-firing at short latencies (~20-30 ms) and occurs during successful memory formation. Phase-coupling at slower oscillations in these same frequency bands, in contrast, correlates with longer co-firing latencies and occurs during memory failure. Thus, our findings suggest that neural oscillations play a role for the synchronization of neural firing in the medial temporal lobe during the encoding of episodic memories.

The hippocampus as the switchboard between perception and memory

Adaptive memory recall requires a rapid and flexible switch from external perceptual reminders to internal mnemonic representations. However, owing to the limited temporal or spatial resolution of brain imaging modalities used in isolation, the hippocampal-cortical dynamics supporting this process remain unknown. We thus employed an object-scene cued recall paradigm across two studies, including intracranial electroencephalography (iEEG) and high-density scalp EEG. First, a sustained increase in hippocampal high gamma power (55 to 110 Hz) emerged 500 ms after cue onset and distinguished successful vs. unsuccessful recall. This increase in gamma power for successful recall was followed by a decrease in hippocampal alpha power (8 to 12 Hz). Intriguingly, the hippocampal gamma power increase marked the moment at which extrahippocampal activation patterns shifted from perceptual cue toward mnemonic target representations. In parallel, source-localized EEG alpha power revealed that the recall signal progresses from hippocampus to posterior parietal cortex and then to medial prefrontal cortex. Together, these results identify the hippocampus as the switchboard between perception and memory and elucidate the ensuing hippocampal-cortical dynamics supporting the recall process.

Ripples reflect a spectrum of synchronous spiking activity in human anterior temporal lobe

Direct brain recordings have provided important insights into how high-frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80-120 Hz ripple band contribute to broadband high-frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

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.

Stimulation of the left dorsolateral prefrontal cortex with slow rTMS enhances verbal memory formation

Encoding of episodic memories relies on stimulus-specific information processing and involves the left prefrontal cortex. We here present an incidental finding from a simultaneous EEG-TMS experiment as well as a replication of this unexpected effect. Our results reveal that stimulating the left dorsolateral prefrontal cortex (DLPFC) with slow repetitive transcranial magnetic stimulation (rTMS) leads to enhanced word memory performance. A total of 40 healthy human participants engaged in a list learning paradigm. Half of the participants (N = 20) received 1 Hz rTMS to the left DLPFC, while the other half (N = 20) received 1 Hz rTMS to the vertex and served as a control group. Participants receiving left DLPFC stimulation demonstrated enhanced memory performance compared to the control group. This effect was replicated in a within-subjects experiment where 24 participants received 1 Hz rTMS to the left DLPFC and vertex. In this second experiment, DLPFC stimulation also induced better memory performance compared to vertex stimulation. In addition to these behavioural effects, we found that 1 Hz rTMS to DLPFC induced stronger beta power modulation in posterior areas, a state that is known to be beneficial for memory encoding. Further analysis indicated that beta modulations did not have an oscillatory origin. Instead, the observed beta modulations were a result of a spectral tilt, suggesting inhibition of these parietal regions. These results show that applying 1 Hz rTMS to DLPFC, an area involved in episodic memory formation, improves memory performance via modulating neural activity in parietal regions.

Encoding of episodic memories relies on stimulus-specific information processing and involves the left prefrontal cortex. An incidental finding from a simultaneous EEG-TMS experiment reveals that applying 1-Hz repetitive transcranial magnetic stimulation to this area of the brain improves memory performance by modulating neural activity in parietal regions.

Prediction of Successful Memory Encoding Based on Lateral Temporal Cortical Gamma Power

Prediction of successful memory encoding is important for learning. High-frequency activity (HFA), such as gamma frequency activity (30–150 Hz) of cortical oscillations, is induced during memory tasks and is thought to reflect underlying neuronal processes. Previous studies have demonstrated that medio-temporal electrophysiological characteristics are related to memory formation, but the effects of neocortical neural activity remain underexplored. The main aim of the present study was to evaluate the ability of gamma activity in human electrocorticography (ECoG) signals to differentiate memory processes into remembered and forgotten memories. A support vector machine (SVM) was employed, and ECoG recordings were collected from six subjects during verbal memory recognition task performance. Two-class classification using an SVM was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies (low gamma, 30–60 Hz; high gamma, 60–150 Hz) at time points during pre- and during stimulus intervals. The SVM classifier distinguished memory performance between remembered and forgotten trials with a mean maximum accuracy of 87.5% using temporal cortical gamma activity during the 0- to 1-s interval. Our results support the functional relevance of ECoG for memory formation and suggest that lateral temporal cortical HFA may be utilized for memory prediction.

High-gamma oscillations as neurocorrelates of ADHD: A MEG crossover placebo-controlled study

Attention Deficit Hyperactive Disorder (ADHD) is a common neurobehavioral disorder with a significant and pervasive impact on patients' lives. Identifying neurophysiological correlates of ADHD is important for understanding its underlying mechanisms, as well as for improving clinical accuracy beyond cognitive and emotional factors. The present study focuses on finding a diagnostic stable neural correlate based on evaluating MEG resting state frequency bands. Twenty-two ADHD patients and 23 controls adults were blindly randomized to two methylphenidate/placebo evaluation days. On each evaluation day state anxiety was assessed, a 2N-back executive function task was performed, and resting state MEG brain activity was recorded at three timepoints. A frequency-based cluster analysis yielded higher high-gamma power for ADHD over posterior sensors and lower high-gamma power for ADHD over frontal-central sensors. These results were shown to be stable over three measurements, unaffected by methylphenidate treatment, and linked to cognitive accuracy and state anxiety. Furthermore, the differential high-gamma activity evidenced substantial ADHD diagnostic efficacy, comparable to the cognitive and emotional factors. These results indicate that resting state high-gamma activity is a promising, stable, valid and diagnostically-relevant neurocorrelate of ADHD. Due to the evolving understanding both in the cellular and network level of high-gamma oscillations, focusing future studies on this frequency band bears the potential for a better understanding of ADHD, thus advancing the specificity of the evaluation of the disorder and developing new tools for therapy.

Computational support, not primacy, distinguishes compensatory memory reorganization in epilepsy

Temporal lobe epilepsy is associated with impairment in episodic memory. A substantial subgroup, however, is able to maintain adequate memory despite temporal lobe pathology. Missing from prior work in cognitive reorganization is a direct comparison of temporal lobe epilepsy patients with intact status with those who are memory impaired. Little is known about the regional activations, functional connectivities and/or network reconfigurations that implement changes in primary computations or support functions that drive adaptive plasticity and compensated memory. We utilized task functional MRI on 54 unilateral temporal lobe epilepsy patients and 24 matched healthy controls during the performance of a paired-associate memory task to address three questions: (i) which regions implement paired-associate memory in temporal lobe epilepsy, and do they vary as a function of good versus poor performance, (ii) is there unique functional connectivity present during memory encoding that accounts for intact status by preservation of primary memory computations or the supportive computations that allow for intact memory responses and (iii) what features during memory encoding are most distinctive: is it the magnitude and location of regional activations, or the presence of enhanced functional connections to key structures such as the hippocampus? The study revealed non-dominant hemisphere regions (right posterior temporal regions) involving both increased regional activity and increased modulatory communication with the hippocampi as most important to intact memory in left temporal lobe epilepsy compared to impaired status. The profile involved areas that are neither contralateral homologues to left hemisphere memory areas, nor regions traditionally considered computationally primary for episodic memory. None of these areas of increased activation or functional connectivity were associated with advantaged memory in healthy controls. Our emphasis on different performance levels yielded insight into two forms of cognitive reorganization: computational primacy, where left temporal lobe epilepsy showed little change relative to healthy controls, and computational support where intact left temporal lobe epilepsy patients showed adaptive abnormalities. The analyses isolated the unique regional activations and mediating functional connectivity that implements truly compensatory reorganization in left temporal lobe epilepsy. The results provided a new perspective on memory deficits by making clear that they arise not just from the knockout of a functional hub, but from the failure to instantiate a complex set of reorganization responses. Such responses provided the computational support to ensure successful memory. We demonstrated that by keeping track of performance levels, we can increase understanding of adaptive brain responses and neuroplasticity in epilepsy.

Theta Synchrony Is Increased near Neural Populations That Are Active When Initiating Instructed Movement

Theta oscillations (3–8 Hz) in the human brain have been linked to perception, cognitive control, and spatial memory, but their relation to the motor system is less clear. We tested the hypothesis that theta oscillations coordinate distributed behaviorally relevant neural representations during movement using intracranial electroencephalography (iEEG) recordings from nine patients (n = 490 electrodes) as they performed a simple instructed movement task. Using high frequency activity (HFA; 70–200 Hz) as a marker of local spiking activity, we identified electrodes that were positioned near neural populations that showed increased activity during instruction and movement. We found that theta synchrony was widespread throughout the brain but was increased near regions that showed movement-related increases in neural activity. These results support the view that theta oscillations represent a general property of brain activity that may also play a specific role in coordinating widespread neural activity when initiating voluntary movement.

Biomarkers of memory variability in traumatic brain injury

Traumatic brain injury is a leading cause of cognitive disability and is often associated with significant impairment in episodic memory. In traumatic brain injury survivors, as in healthy controls, there is marked variability between individuals in memory ability. Using recordings from indwelling electrodes, we characterized and compared the oscillatory biomarkers of mnemonic variability in two cohorts of epilepsy patients: a group with a history of moderate-to-severe traumatic brain injury (n = 37) and a group of controls without traumatic brain injury (n = 111) closely matched for demographics and electrode coverage. Analysis of these recordings demonstrated that increased high-frequency power and decreased theta power across a broad set of brain regions mark periods of successful memory formation in both groups. As features in a logistic-regression classifier, spectral power biomarkers effectively predicted recall probability, with little difference between traumatic brain injury patients and controls. The two groups also displayed similar patterns of theta-frequency connectivity during successful encoding periods. These biomarkers of successful memory, highly conserved between traumatic brain injury patients and controls, could serve as the basis for novel therapies that target disordered memory across diverse forms of neurological disease.

A circuit of mossy cells controls the efficacy of memory retrieval by Gria2I inhibition of Gria2

Mossy cells (MCs) are a unique group of excitatory neurons in the hippocampus, a brain region important for emotion, learning, and memory. Due to the lack of a reliable method to isolate MCs from other cell types, how MCs integrate neural information and convey it to their synaptic targets for engaging a specific function are still unknown. Here, we report that MCs control the efficacy of spatial memory retrieval by synapsing directly onto local somatostatin-expressing (SST) cells. MC-SST synaptic transmission undergoes long-term potentiation (LTP), requiring Gria2-lacking Ca²⁺-permeable anti-α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) receptor (Ca²⁺AR). A long noncoding RNA (Gria2I) is associated with Gria2 transcriptional repressors in SST cells. Silencing Gria2I induces Gria2 transcription, blocks LTP of MCs-SST synaptic transmission, and reduces the efficacy of memory retrieval. Thus, MCs directly and functionally innervate local SST neurons, and this innervation controls the efficacy of spatial memory retrieval by Gria2I inhibition of Gria2 transcription.

Temporo-Frontal Coherences and High-Frequency iEEG Responses during Spatial Navigation in Patients with Drug-Resistant Epilepsy

The prefrontal cortex and hippocampus function in tight coordination during multiple cognitive processes. During spatial navigation, prefrontal neurons are linked to hippocampal theta oscillations, presumably in order to enhance communication. Hippocampal ripples have been suggested to reflect spatial memory processes. Whether prefrontal-hippocampal-interaction also takes place within the ripple band is unknown. This intracranial EEG study aimed to investigate whether ripple band coherences can also be used to show this communication. Twelve patients with epilepsy and intracranial EEG evaluation completed a virtual spatial navigation task. We calculated ordinary coherence between prefrontal and temporal electrodes during retrieval, re-encoding, and pre-task rest. Coherences were compared between the conditions via permutation testing. Additionally, ripples events were automatically detected and changes in occurrence rates were investigated excluding ripples on epileptic spikes. Ripple-band coherences yielded no general effect of the task on coherences across all patients. Furthermore, we did not find significant effects of task conditions on ripple rates. Subsequent analyses pointed to rather short periods of synchrony as opposed to general task-related changes in ripple-band coherence. Specifically designed tasks and adopted measures might be necessary in order to map these interactions in future studies.

Contribution of left supramarginal and angular gyri to episodic memory encoding: An intracranial EEG study

The role of the left ventral lateral parietal cortex (VPC) in episodic memory is hypothesized to include bottom-up attentional orienting to recalled items, according to the dual-attention model (Cabeza et al., 2008). However, its role in memory encoding could be further clarified, with studies showing both positive and negative subsequent memory effects (SMEs). Furthermore, few studies have compared the relative contributions of sub-regions in this functionally heterogeneous area, specifically the anterior VPC (supramarginal gyrus/BA40) and the posterior VPC (angular gyrus/BA39), on a within-subject basis. To elucidate the role of the VPC in episodic encoding, we compared SMEs in the intracranial EEG across multiple frequency bands in the supramarginal gyrus (SmG) and angular gyrus (AnG), as twenty-four epilepsy patients with indwelling electrodes performed a free recall task. We found a significant SME of decreased theta power and increased high gamma power in the VPC overall, and specifically in the SmG. Furthermore, SmG exhibited significantly greater spectral tilt SME from 0.5 to 1.6 s post-stimulus, in which power spectra slope differences between recalled and unrecalled words were greater than in the AnG (p = 0.04). These results affirm the contribution of VPC to episodic memory encoding, and suggest an anterior-posterior dissociation within VPC with respect to its electrophysiological underpinnings.

Waveform changes with the evolution of beta bursts in the human subthalamic nucleus

OBJECTIVE

Phasic bursts of beta band synchronisation have been linked to motor impairment in Parkinson's disease (PD). However, little is known about what terminates bursts.

METHODS

We used the Hilbert-Huang transform to investigate beta bursts in the local field potential recorded from the subthalamic nucleus in nine patients with PD on and off levodopa.

RESULTS

The sharpness of the beta waveform extrema fell as burst amplitude dropped. Conversely, an index of phase slips between waveform extrema, and the power of concurrent theta activity increased as burst amplitude fell. Theta activity was also increased on levodopa when beta bursts were attenuated. These phenomena were associated with reduction in coupling between beta phase and high gamma activity amplitude. We discuss how these findings may suggest that beta burst termination is associated with relative desynchronization of the beta drive, increase in competing theta activity and increased phase slips in the beta activity.

CONCLUSIONS

We characterise the dynamical nature of beta bursts, thereby permitting inferences about underlying activities and, in particular, about why bursts terminate.

SIGNIFICANCE

Understanding the dynamical nature of beta bursts may help point to interventions that can cause their termination and potentially treat motor impairment in PD.

Mossy cell synaptic dysfunction causes memory imprecision via miR-128 inhibition of STIM2 in Alzheimer's disease mouse model

Recently, we have reported that dentate mossy cells (MCs) control memory precision via directly and functionally innervating local somatostatin (SST) inhibitory interneurons. Here, we report a discovery that dysfunction of synaptic transmission between MCs and SST cells causes memory imprecision in a mouse model of early Alzheimer's disease (AD). Single-cell RNA sequencing reveals that miR-128 that binds to a 3'UTR of STIM2 and inhibits STIM2 translation is increasingly expressed in MCs from AD mice. Silencing miR-128 or disrupting miR-128 binding to STIM2 evokes STIM2 expression, restores synaptic function, and rescues memory imprecision in AD mice. Comparable findings are achieved by directly engineering MCs with the expression of STIM2. This study unveils a key synaptic and molecular mechanism that dictates how memory maintains or losses its details and warrants a promising target for therapeutic intervention of memory decays in the early stage of AD.

iEEG: Dura-lining electrodes

Intracranial electroencephalography (iEEG) is measured from electrodes placed in or on the brain. These measurements have an excellent signal-to-noise ratio and iEEG signals have often been used to decode brain activity or drive brain-computer interfaces (BCIs). iEEG recordings are typically done for seizure monitoring in epilepsy patients who have these electrodes placed for a clinical purpose: to localize both brain regions that are essential for function and others where seizures start. Brain regions not involved in epilepsy are thought to function normally and provide a unique opportunity to learn about human neurophysiology. Intracranial electrodes measure the aggregate activity of large neuronal populations and recorded signals contain many features. Different features are extracted by analyzing these signals in the time and frequency domain. The time domain may reveal an evoked potential at a particular time after the onset of an event. Decomposition into the frequency domain may show narrowband peaks in the spectrum at specific frequencies or broadband signal changes that span a wide range of frequencies. Broadband power increases are generally observed when a brain region is active while most other features are highly specific to brain regions, inputs, and tasks. Here we describe the spatiotemporal dynamics of several iEEG signals that have often been used to decode brain activity and drive BCIs.

Theta Oscillations in Human Memory

Theta frequency (4-8 Hz) fluctuations of the local field potential have long been implicated in learning and memory. Human studies of episodic memory, however, have provided mixed evidence for theta's role in successful learning and remembering. Re-evaluating these conflicting findings leads us to conclude that: (i) successful memory is associated both with increased narrow-band theta oscillations and a broad-band tilt of the power spectrum; (ii) theta oscillations specifically support associative memory, whereas the spectral tilt reflects a general index of activation; and (iii) different cognitive contrasts (generalized versus specific to memory), recording techniques (invasive versus noninvasive), and referencing schemes (local versus global) alter the balance between the two phenomena to make one or the other more easily detectable.

Tonic Resting State Hubness Supports High Gamma Activity Defined Verbal Memory Encoding Network in Epilepsy

High gamma activity (HGA) of verbal-memory encoding using invasive-electroencephalogram has laid the foundation for numerous studies testing the integrity of memory in diseased populations. Yet, the functional connectivity characteristics of networks subserving these memory linkages remains uncertain. By integrating this electrophysiological biomarker of memory encoding from IEEG with resting-state BOLD fluctuations, we estimated the segregation and hubness of HGA-memory regions in drug-resistant epilepsy patients and matched healthy controls. HGA-memory regions express distinctly different hubness compared to neighboring regions in health and in epilepsy, and this hubness was more relevant than segregation in predicting verbal memory encoding. The HGA-memory network comprised regions from both the cognitive control and primary processing networks, validating that effective verbal-memory encoding requires integrating brain functions, and is not dominated by a central cognitive core. Our results demonstrate a tonic intrinsic set of functional connectivity, which provides the necessary conditions for effective, phasic, task-dependent memory encoding.

Directional coupling of slow and fast hippocampal gamma with neocortical alpha/beta oscillations in human episodic memory

Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these 2 processes are thought to be supported by neocortical alpha/beta desynchronization and hippocampal theta/gamma synchronization, respectively. Intuitively, these 2 processes should couple to successfully create and retrieve episodic memories, yet this hypothesis has not been tested empirically. We address this by analyzing human intracranial electroencephalogram data recorded during 2 associative memory tasks. We find that neocortical alpha/beta (8 to 20 Hz) power decreases reliably precede and predict hippocampal "fast" gamma (60 to 80 Hz) power increases during episodic memory formation; during episodic memory retrieval, however, hippocampal "slow" gamma (40 to 50 Hz) power increases reliably precede and predict later neocortical alpha/beta power decreases. We speculate that this coupling reflects the flow of information from the neocortex to the hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval.

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.

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.

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.

A causal role for the precuneus in network-wide theta and gamma oscillatory activity during complex memory retrieval

Complex memory of personal events is thought to depend on coordinated reinstatement of cortical representations by the medial temporal lobes (MTL). MTL-cortical theta and gamma coupling is believed to mediate such coordination, but which cortical structures are critical for retrieval and how they influence oscillatory coupling is unclear. We used magnetoencephalography (MEG) combined with continuous theta burst stimulation (cTBS) to (i) clarify the roles of theta and gamma oscillations in network-wide communication during naturalistic memory retrieval, and (ii) understand the causal relationship between cortical network nodes and oscillatory communication. Retrieval was associated with MTL-posterior neocortical theta phase coupling and theta-gamma phase-amplitude coupling relative to a rest period. Precuneus cTBS altered MTL-neocortical communication by modulating theta and gamma oscillatory coupling. These findings provide a mechanistic account for MTL-cortical communication and demonstrate that the precuneus is a critical cortical node of oscillatory activity, coordinating cross-regional interactions that drive remembering.

When you recall an event from your past, such as a meal you ate last week, many regions of your brain become active. The coordinated activity of these regions enables you to recall the event in detail. This coordination depends on rhythmic waves of electrical activity called neural oscillations. These arise whenever large numbers of neurons synchronize when they fire. Electrodes on the scalp can be used to measure neural oscillations. Recordings show that the number of times each wave repeats per second (also known as the frequency of the oscillation), varies from one brain region to the next.

Two types of oscillations are particularly important for memory: theta waves and gamma waves. Theta waves repeat between three and seven times every second, and help coordinate activity between areas of the brain that are far apart. Gamma waves are faster, repeating 65 to 85 times per second, and help to support activity within individual regions of the brain. Importantly, theta and gamma waves also interact.

Hebscher et al. set out to understand whether interactions between theta and gamma waves help us to recall personal memories. Healthy volunteers were asked to recall memories in response to cues such as ‘my kitchen’, while sitting inside a brain scanner. As predicted, interactions between theta and gamma waves contributed to memory recall. Theta waves recorded from the medial temporal lobe, a region deep within the brain, altered gamma waves in another area called the precuneus. The latter forms part of the inner surface of the brain where the two hemispheres face one another, and is important for memory vividness and visual imagery. Hebscher et al. briefly disrupted the activity of the precuneus by applying harmless magnetic fields to the scalp above it. Doing so altered theta-gamma interactions across the brain, which was related to reduced vividness of the memories.

Remembering events from our past is fundamental to our sense of self and our interactions with others. The results presented by Hebscher et al. show that reducing the activity of a single brain region, the precuneus, impairs memory recall. It does so by disrupting interactions between oscillations throughout the brain. This raises the possibility that stimulating the brain to enhance – rather than disrupt – oscillations could have the opposite effect and improve memory. Future studies could investigate whether enhancing oscillations could help to treat memory disorders.

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.

Hippocampal contributions to serial-order memory

Our memories form a record not only of our experiences, but also of their temporal structure. Although memory for the temporal structure of experience likely relies on multiple neural systems, numerous studies have implicated the hippocampus in the encoding and retrieval of temporal information. This review evaluates the literature on hippocampal contributions to human serial-order memory from the perspective of three cognitive theories: associative chaining theory, positional-coding theory and retrieved-context theory. Evaluating neural findings through the lens of cognitive theories enables us to draw more incisive conclusions about the relations between brain and behavior.

Network Brain-Computer Interface (nBCI): An Alternative Approach for Cognitive Prosthetics

Brain computer interfaces (BCIs) have been applied to sensorimotor systems for many years. However, BCI technology has broad potential beyond sensorimotor systems. The emerging field of cognitive prosthetics, for example, promises to improve learning and memory for patients with cognitive impairment. Unfortunately, our understanding of the neural mechanisms underlying these cognitive processes remains limited in part due to the extensive individual variability in neural coding and circuit function. As a consequence, the development of methods to ascertain optimal control signals for cognitive decoding and restoration remains an active area of inquiry. To advance the field, robust tools are required to quantify time-varying and task-dependent brain states predictive of cognitive performance. Here, we suggest that network science is a natural language in which to formulate and apply such tools. In support of our argument, we offer a simple demonstration of the feasibility of a network approach to BCI control signals, which we refer to as network BCI (nBCI). Finally, in a single subject example, we show that nBCI can reliably predict online cognitive performance and is superior to certain common spectral approaches currently used in BCIs. Our review of the literature and preliminary findings support the notion that nBCI could provide a powerful approach for future applications in cognitive prosthetics.

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.

The neural dynamics of deficient memory control in heavily traumatized refugees

Victims of war, torture and natural catastrophes are prone to develop posttraumatic stress disorder (PTSD). These individuals experience the recurrent, involuntary intrusion of traumatic memories. What neurocognitive mechanisms are driving this memory disorder? Here we show that PTSD symptoms in heavily traumatized refugees are related to deficits in the effective control of memory retrieval. In a think/no-think task, PTSD patients were unable to forget memories that they had previously tried to suppress when compared to control participants with the same trauma history but without PTSD. Deficits in voluntary forgetting were clinically relevant since they correlated with memory intrusions in everyday life. Magnetoencephalography (MEG) recorded during suppression attempts revealed that PTSD patients were unable to downregulate signatures of sensory long-term memory traces in the gamma frequency band (70-120 Hz). Thus, our data suggest that the inability to suppress unwanted memories through modulation of gamma activity is related to PTSD symptom severity.

Rhythm and Synchrony in a Cortical Network Model

We studied mechanisms for cortical gamma-band activity in the cerebral cortex and identified neurobiological factors that affect such activity. This was done by analyzing the behavior of a previously developed, data-driven, large-scale network model that simulated many visual functions of monkey V1 cortex (Chariker et al., 2016). Gamma activity was an emergent property of the model. The model's gamma activity, like that of the real cortex, was (1) episodic, (2) variable in frequency and phase, and (3) graded in power with stimulus variables like orientation. The spike firing of the model's neuronal population was only partially synchronous during multiple firing events (MFEs) that occurred at gamma rates. Detailed analysis of the model's MFEs showed that gamma-band activity was multidimensional in its sources. Most spikes were evoked by excitatory inputs. A large fraction of these inputs came from recurrent excitation within the local circuit, but feedforward and feedback excitation also contributed, either through direct pulsing or by raising the overall baseline. Inhibition was responsible for ending MFEs, but disinhibition led directly to only a small minority of the synchronized spikes. As a potential explanation for the wide range of gamma characteristics observed in different parts of cortex, we found that the relative rise times of AMPA and GABA synaptic conductances have a strong effect on the degree of synchrony in gamma.SIGNIFICANCE STATEMENT Canonical computations used throughout the cerebral cortex are performed in primary visual cortex (V1). Providing theoretical mechanisms for these computations will advance understanding of computation throughout cortex. We studied one dynamical feature, gamma-band rhythms, in a large-scale, data-driven, computational model of monkey V1. Our most significant conclusion is that the sources of gamma band activity are multidimensional. A second major finding is that the relative rise times of excitatory and inhibitory synaptic potentials have strong effects on spike synchrony and peak gamma band power. Insight gained from studying our V1 model can shed light on the functions of other cortical regions.

Attention improves memory by suppressing spiking-neuron activity in the human anterior temporal lobe

We identify a memory-specific attention mechanism in the human anterior temporal lobe, an area implicated in semantic processing and episodic memory formation. Spiking neuron activity is suppressed and becomes more reliable in preparation for verbal memory formation. Intracranial electroencephalography signals implicate this region as a source of executive control for attentional selection. Consistent with this interpretation, its surgical removal causes significant memory impairment for attended words relative to unattended words.

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.