Power shifts track serial position and modulate encoding in human episodic memory

Episodic boundaries affect neural features of representational drift in humans

A core feature of episodic memory is representational drift, the gradual change in aggregate oscillatory features that supports temporal association of memory items. However, models of drift overlook the role of episodic boundaries, which indicate a shift from prior to current context states. Our study focuses on the impact of task boundaries on representational drift in the parietal and temporal lobes in 99 subjects during a free recall task. Using intracranial EEG recordings, we show boundary representations reset gamma band drift in the medial parietal lobe, selectively enhancing the recall of early list (primacy) items. Conversely, the lateral temporal cortex shows increased drift for recalled items but lacked sensitivity to task boundaries. Our results suggest regional sensitivity to varied contextual features: the lateral temporal cortex uses drift to differentiate items, while the medial parietal lobe uses drift-resets to associate items with the current context. We propose drift represents relational information tailored to a region's sensitivity to unique contextual elements. Our findings offer a mechanism to integrate models of temporal association by drift with event segmentation by episodic boundaries.

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.

Semantic associations restore neural encoding mechanisms

Lapses in attention can negatively impact later memory of an experience. Attention and encoding resources are thought to decline as more experiences are encountered in succession, accounting for the primacy effect in which memory is better for items encountered early compared to late in a study list. However, accessing prior knowledge during study can facilitate subsequent memory, suggesting a potential avenue to counteract this decline. Here, we investigated the extent to which semantic associations-shared meaning between experiences-can counteract declines in encoding resources. Our hypothesis is that semantic associations restore neural encoding mechanisms, which in turn improves memory. We recorded scalp electroencephalography (EEG) while male and female human participants performed a delayed free recall task. Half of the items from late in each study list were semantically associated with an item presented earlier in the list. We find that semantic associations improve memory specifically for late list items and selectively modulate the neural signals engaged during the study of late list items. Relative to other recalled items, late list items that are subsequently semantically clustered-recalled consecutively with their semantic associate-elicit increased high-frequency activity and decreased low-frequency activity, a hallmark of successful encoding. Our findings demonstrate that semantic associations restore neural encoding mechanisms and improve later memory. More broadly, these findings suggest that prior knowledge modulates the orientation of attention to influence encoding mechanisms.

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.

To remember or not to remember: Neural oscillations and ERPs as predictors of intentional associative fear learning

It is widely accepted that impaired safety learning to a safe stimulus is a pathological feature of anxiety disorders. Safety learning refers to learning that a stimulus is associated with the absence of threat. Cognitive mechanisms that underlie successful threat and safety learning are, however, poorly understood. This study aimed to identify various physiological markers, including neural oscillations and event-related potentials (ERPs) that predict successful threat and safety learning. Therefore, to detect potential differences in these markers, we measured EEG in a fear learning framework combined with a subsequent memory paradigm. Thirty-seven participants were asked to memorize a series of associations between faces and an aversive unconditioned stimulus (US) or its omission. We found a decrease of power in the alpha band in occipital brain regions during learning for both threatening (conditioned stimuli, CS+) and safe faces (control stimuli, CS-) that were subsequently remembered to be associated with a US or not. No effects in theta band were found. In regard to ERPs, a late positive potential (LPP) and a P300 component were larger for remembered than for forgotten CS-US associations. The P300 was also enhanced to remembered US and US omissions, thus replicating previous findings. These results point to the importance of cognitive resource allocation as an underlying mechanism of fear learning and electrophysiological measurements as potential biomarkers for successful threat and safety learning.

Paving the Way for Memory Enhancement: Development and Examination of a Neurofeedback System Targeting the Medial Temporal Lobe

Neurofeedback (NF) shows promise in enhancing memory, but its application to the medial temporal lobe (MTL) still needs to be studied. Therefore, we aimed to develop an NF system for the memory function of the MTL and examine neural activity changes and memory task score changes through NF training. We created a memory NF system using intracranial electrodes to acquire and visualise the neural activity of the MTL during memory encoding. Twenty trials of a tug-of-war game per session were employed for NF and designed to control neural activity bidirectionally (Up/Down condition). NF training was conducted with three patients with drug-resistant epilepsy, and we observed an increasing difference in NF signal between conditions (Up-Down) as NF training progressed. Similarities and negative correlation tendencies between the transition of neural activity and the transition of memory function were also observed. Our findings demonstrate NF's potential to modulate MTL activity and memory encoding. Future research needs further improvements to the NF system to validate its effects on memory functions. Nonetheless, this study represents a crucial step in understanding NF's application to memory and provides valuable insights into developing more efficient memory enhancement strategies.

Characterization of High-Gamma Activity in Electrocorticographic Signals

Introduction

Electrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information.

Methods

To address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA.

Results

The high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks.

Discussion

This study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies.

Neural temporal context reinstatement of event structure during memory recall

The transformation of experiences into meaningful events and memories is intertwined with the notion of time. Temporal perception can influence, and be influenced by, segmenting continuous experience into meaningful events. Episodic memories formed from these events become associated with temporal information as well. However, it is less clear how temporal perception contributes to structuring events and organizing memory: whether it plays a more active or passive role, and whether this temporal information is encoded initially during perception or influenced by retrieval processes. To address these questions, we examined how event segmentation influences temporal representations during initial perception and memory retrieval, without testing temporal information explicitly. Using a neural measure of temporal context extracted from scalp electroencephalography in human participants (N = 170), we found reduced temporal context similarity between studied items separated by an event boundary when compared to items from the same event. Furthermore, while participants freely recalled list items, neural activity reflected reinstatement of temporal context representations from the study phase, including temporal disruption. A computational model of episodic memory, the context maintenance and retrieval (CMR) model, predicted these results, and made novel predictions regarding the influence of temporal disruption on recall order. These findings implicate the impact of event structure on memory organization via temporal representations, underscoring the role of temporal information in event segmentation and episodic memory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Direct brain recordings suggest a causal subsequent-memory effect

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analysing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output-a biomarker of successful encoding-tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas, in the prefrontal cortex, HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brain's ability to learn new information.

Hippocampal non-theta state: The "Janus face" of information processing

The vast majority of studies on hippocampal rhythms have been conducted on animals or humans in situations where their attention was focused on external stimuli or solving cognitive tasks. These studies formed the basis for the idea that rhythmical activity coordinates the work of neurons during information processing. However, at rest, when attention is not directed to external stimuli, brain rhythms do not disappear, although the parameters of oscillatory activity change. What is the functional load of rhythmical activity at rest? Hippocampal oscillatory activity during rest is called the non-theta state, as opposed to the theta state, a characteristic activity during active behavior. We dedicate our review to discussing the present state of the art in the research of the non-theta state. The key provisions of the review are as follows: (1) the non-theta state has its own characteristics of oscillatory and neuronal activity; (2) hippocampal non-theta state is possibly caused and maintained by change of rhythmicity of medial septal input under the influence of raphe nuclei; (3) there is no consensus in the literature about cognitive functions of the non-theta-non-ripple state; and (4) the antagonistic relationship between theta and delta rhythms observed in rodents is not always observed in humans. Most attention is paid to the non-theta-non-ripple state, since this aspect of hippocampal activity has not been investigated properly and discussed in reviews.

Long-lasting, dissociable improvements in working memory and long-term memory in older adults with repetitive neuromodulation

The development of technologies to protect or enhance memory in older people is an enduring goal of translational medicine. Here we describe repetitive (4-day) transcranial alternating current stimulation (tACS) protocols for the selective, sustainable enhancement of auditory-verbal working memory and long-term memory in 65-88-year-old people. Modulation of synchronous low-frequency, but not high-frequency, activity in parietal cortex preferentially improved working memory on day 3 and day 4 and 1 month after intervention, whereas modulation of synchronous high-frequency, but not low-frequency, activity in prefrontal cortex preferentially improved long-term memory on days 2-4 and 1 month after intervention. The rate of memory improvements over 4 days predicted the size of memory benefits 1 month later. Individuals with lower baseline cognitive function experienced larger, more enduring memory improvements. Our findings demonstrate that the plasticity of the aging brain can be selectively and sustainably exploited using repetitive and highly focalized neuromodulation grounded in spatiospectral parameters of memory-specific cortical circuitry.

Emotional Context Shapes the Serial Position Curve

Emotional contexts affect memory processes. However, the impact of contextual priming as a function of the emotional valence on the recall of neutral information is not fully understood. The aim of the present study was to evaluate how a conditioning of emotional context during encoding may influence the subsequent memory of otherwise neutral materials in a well-established phenomenon as the serial position effect. Participants performed a free recall task for neutral words in three conditions: (i) word list alone; (ii) word list coupled with positive or neutral images; and (iii) word list coupled with negative or neutral images. Images were presented before each word stimulus. In three different experiments, the emotional context during the word list presentation was manipulated separately for primacy and recency clusters, and for the middle words ('middlecy'). Emotional context affects free recall of neutral stimuli, changing the serial position curve effect across conditions. Namely, emotional images presented in the primacy and recency clusters worsen accuracy, whereas their occurrence in the 'middlecy' cluster reduces the oblivion. The present findings show that the typical pattern related to the serial position curve for neutral information can be shaped by the conditioning of emotional context. Findings have implications in medical-legal contexts in the case of the recollection of events with high emotional content.

Dissociable oscillatory theta signatures of memory formation in the developing brain

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

How do recall requirements affect decision-making in free recall initiation? A linear ballistic accumulator approach

Models of free recall describe free recall initiation as a decision-making process in which items compete to be retrieved. Recently, Osth and Farrell (Psychological Review, 126, 578–609, 2019) applied evidence accumulation models to complete RT distributions and serial positions of participants’ first recalls in free recall, which resulted in some novel conclusions about primacy and recency effects. Specifically, the results of the modeling favored an account in which primacy was due to reinstatement of the start-of-the-list, and recency was found to be exponential in shape. In this work, we examine what happens when participants are given alternative recall instructions. Prior work has demonstrated weaker primacy and greater recency when fewer items are required to report (Ward & Tan, Memory & Cognition, 2019), and a key question is whether this change in instructions qualitatively changes the nature of the recall process, or merely changes the parameters of the recall competition. We conducted an experiment where participants studied six- or 12-item lists and were post-cued as to whether to retrieve a single item, or as many items as possible. Subsequently, we applied LBA models with various assumptions about primacy and recency, implemented using hierarchical Bayesian techniques. While greater recency was observed when only one item was required for output, the model selection did not suggest that there were qualitative differences between the two conditions. Specifically, start-of-list reinstatement and exponential recency functions were favored in both conditions.

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.

Time cells in the human hippocampus and entorhinal cortex support episodic memory

The organization of temporal information is critical for the encoding and retrieval of episodic memories. In the rodent hippocampus and entorhinal cortex, evidence accumulated over the last decade suggests that populations of "time cells" in the hippocampus encode temporal information. We identify time cells in humans using intracranial microelectrode recordings obtained from 27 human epilepsy patients who performed an episodic memory task. We show that time cell activity predicts the temporal organization of retrieved memory items. We also uncover evidence of ramping cell activity in humans, which represents a complementary type of temporal information. These findings establish a cellular mechanism for the representation of temporal information in the human brain needed to form episodic memories.

Insights into human cognition from intracranial EEG: A review of audition, memory, internal cognition, and causality

By recording neural activity directly from the human brain, researchers gain unprecedented insight into how neurocognitive processes unfold in real time. We first briefly discuss how intracranial electroencephalography (iEEG) recordings, performed for clinical practice, are used to study human cognition with the spatiotemporal and single-trial precision traditionally limited to non-human animal research. We then delineate how studies using iEEG have informed our understanding of issues fundamental to human cognition: auditory prediction, working and episodic memory, and internal cognition. We also discuss the potential of iEEG to infer causality through the manipulation or 'engineering' of neurocognitive processes via spatiotemporally precise electrical stimulation. We close by highlighting limitations of iEEG, potential of burgeoning techniques to further increase spatiotemporal precision, and implications for future research using intracranial approaches to understand, restore, and enhance human cognition.

Encoding dynamics in free recall: Examining attention allocation with pupillometry

In four experiments pupillary responses were used to examine attention allocation and encoding dynamics in free recall. In Experiment 1, pupillary responses increased (and then decreased) across serial position suggesting that attention was increasingly allocated to items during learning until working memory was overloaded. In Experiment 2, manipulating presentation duration resulted in larger and more sustained pupillary responses with increased presentation duration, suggesting that participants were likely engaging in more elaborative and attention-demanding processes. In Experiment 3a, manipulating list-length resulted in decreased pupillary responses across serial position suggesting that participants were prioritizing early list items and less attention was allocated to later items. In Experiment 3b, when list-length was known, pupillary responses in the long-list length condition tended to decrease across serial position whereas pupillary responses in the short list-length condition tended to increase and decrease across serial positon. These results suggest that participants flexibly allocate attention to items during encoding depending on the nature of the task and the types of processes that are engaged in. These results further suggest the potential of utilizing pupillary responses to track attention allocation during learning.

Neural fatigue influences memory encoding in the human hippocampus

Here we examine the variability underlying successful memory encoding. Successful encoding of successive study items may fatigue encoding resources, thus decreasing the ability to encode subsequent items (Tulving and Rosenbaum, 2006); alternatively, successful encoding may be persistent, leading to more successful encoding (Kahana, Aggarwal, and Phan, 2018). Analyzing intracranial electroencephalographic activity while subjects studied lists of words for subsequent free recall, we examined high-frequency activity (HFA) in hippocampus and dorsolateral prefrontal cortex (DLPFC), as HFA was greater for subsequently recalled than non-recalled items in these regions. We compared non-recalled items with good encoding history (i.e. one of the two preceding items was recalled) with non-recalled items with poor encoding history (i.e. neither prior item was recalled). In the hippocampus, good encoding history led to reduced HFA, whereas in the DLPFC, good encoding history led to enhanced HFA. Hippocampal findings appear consistent with the neural fatigue hypothesis, whereas the DLPFC results appear consistent with persistent encoding states.

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.

Computational Models of Memory Search

The capacity to search memory for events learned in a particular context stands as one of the most remarkable feats of the human brain. How is memory search accomplished? First, I review the central ideas investigated by theorists developing models of memory. Then, I review select benchmark findings concerning memory search and analyze two influential computational approaches to modeling memory search: dual-store theory and retrieved context theory. Finally, I discuss the key theoretical ideas that have emerged from these modeling studies and the open questions that need to be answered by future research.

Multiple-Time-Scale Analysis of Attention as Revealed by EEG, NIRS, and Pupil Diameter Signals During a Free Recall Task: A Multimodal Measurement Approach

Attention plays a fundamental role in acquiring and understanding information. Therefore, it is useful to evaluate attention objectively in such fields as education and mental health. Aimed at extracting objective indicators of attention from physiological signals, this study examined the characteristics of electroencephalography (EEG), near-infrared spectroscopy (NIRS), and pupil diameter signals during a free recall task. The objective was to clarify the temporal characteristics of these signals in relation to attention. We used a free recall task as a cognitive task with an attentional load. The participants attempted to memorize and then recall 13 serially presented words. Our hypothesis was that the significant physiological responses should differ depending on the time scale of the attention evaluation. The physiological responses were compared on the basis of differences between success and failure to recall a word on a short time scale, in terms of the attentional state among five serial position groups on a middle time scale, and on the basis of differences between trials with many and few words recalled on a long time scale. We found that the response of each physiological signal depended on the attention in the different time-scale comparisons. (1) The P300 amplitudes of the EEG signals for the words that were recalled were significantly higher than those for the words that were not recalled. (2) Pupillary dilation differed significantly depending on the serial position group. (3) Functional connectivity in the right hemisphere revealed by NIRS was significantly stronger in trials with many words recalled than in those with few words recalled. Different temporal characteristics of physiological signals with respect to attention were suggested by multimodal measurement and multiple-time-scale analysis. Consideration of these characteristics should help in the development of applications requiring objective attention evaluation.

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.

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.

Electrical Stimulation in Hippocampus and Entorhinal Cortex Impairs Spatial and Temporal Memory

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients of both sexes who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects' abilities to remember items located far away from boundaries. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred.SIGNIFICANCE STATEMENT Numerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.

Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI

Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2-20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

Pathophysiology and Treatment of Memory Dysfunction After Traumatic Brain Injury

Memory is fundamental to everyday life, and cognitive impairments resulting from traumatic brain injury (TBI) have devastating effects on TBI survivors. A contributing component to memory impairments caused by TBI is alteration in the neural circuits associated with memory function. In this review, we aim to bring together experimental findings that characterize behavioral memory deficits and the underlying pathophysiology of memory-involved circuits after TBI. While there is little doubt that TBI causes memory and cognitive dysfunction, it is difficult to conclude which memory phase, i.e., encoding, maintenance, or retrieval, is specifically altered by TBI. This is most likely due to variation in behavioral protocols and experimental models. Additionally, we review a selection of experimental treatments that hold translational potential to mitigate memory dysfunction following injury.

A four-component model of age-related memory change

We develop a novel, computationally explicit, theory of age-related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that include aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates 4 components: (a) the ability to sustain attention across an encoding episode, (b) the ability to retrieve contextual representations for use as retrieval cues, (c) the ability to monitor retrievals and reject intrusions, and (d) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the 4-component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus, we provide a 4-component theory of a complex pattern of age differences across 2 key laboratory tasks.

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.

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.

High gamma oscillations in medial temporal lobe during overt production of speech and gestures

The study of the production of co-speech gestures (CSGs), i.e., meaningful hand movements that often accompany speech during everyday discourse, provides an important opportunity to investigate the integration of language, action, and memory because of the semantic overlap between gesture movements and speech content. Behavioral studies of CSGs and speech suggest that they have a common base in memory and predict that overt production of both speech and CSGs would be preceded by neural activity related to memory processes. However, to date the neural correlates and timing of CSG production are still largely unknown. In the current study, we addressed these questions with magnetoencephalography and a semantic association paradigm in which participants overtly produced speech or gesture responses that were either meaningfully related to a stimulus or not. Using spectral and beamforming analyses to investigate the neural activity preceding the responses, we found a desynchronization in the beta band (15-25 Hz), which originated 900 ms prior to the onset of speech and was localized to motor and somatosensory regions in the cortex and cerebellum, as well as right inferior frontal gyrus. Beta desynchronization is often seen as an indicator of motor processing and thus reflects motor activity related to the hand movements that gestures add to speech. Furthermore, our results show oscillations in the high gamma band (50-90 Hz), which originated 400 ms prior to speech onset and were localized to the left medial temporal lobe. High gamma oscillations have previously been found to be involved in memory processes and we thus interpret them to be related to contextual association of semantic information in memory. The results of our study show that high gamma oscillations in medial temporal cortex play an important role in the binding of information in human memory during speech and CSG production.

Retrieval practice enhances new learning: the forward effect of testing

In the last couple of years, there has been a dramatic increase in laboratory research examining the benefits of recall testing on long-term learning and retention. This work was largely on the backward effect of testing, which shows that retrieval practice on previously studied information, compared to restudy of the same material, renders the information more likely to be remembered in the future. Going beyond this prominent work, more recent laboratory research provided evidence that there is also a forward effect of testing, which shows that recall testing of previously studied information can enhance learning of subsequently presented new information. Here, we provide a review of research on this forward effect of testing. The review shows that the effect is a well replicated phenomenon in laboratory studies that has been observed for both veridical information and misinformation. In particular, the review demonstrates that the effect may be applied to educational and clinical settings, enhancing learning in students and reducing memory deficits in clinical populations. The review discusses current theoretical explanations of the forward effect of testing and provides suggestions for future research directions.

Encoding-related EEG oscillations during memory formation are modulated by mood state

Mood states have a strong impact on how we process incoming information. It has been proposed that positive mood facilitates elaborative, relational encoding, whereas negative mood promotes a more careful, stimulus-driven encoding style. Previous electrophysiological studies have linked successful information encoding to power increases in slow (<8 Hz) delta/theta and fast (>30 Hz) gamma oscillations, as well as to power decreases in midrange (8-30 Hz) alpha/beta oscillations. Whether different mood states modulate encoding-related oscillations has not been investigated yet. In order to address this question, we used an experimental mood induction procedure and recorded electroencephalograms from 20 healthy participants while they performed a free recall memory task after positive and negative mood induction. We found distinct oscillatory patterns in positive and negative mood. Successful encoding in positive mood was accompanied by widespread power increases in the delta band, whereas encoding success in negative mood was specifically accompanied by frontal power decreases in the beta band. On the behavioral level, memory performance was enhanced in positive mood. Our findings show that mood differentially modulates the neural correlates of successful information encoding and thus contribute to an understanding of how mood shapes different processing styles.

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.

Repeated stimuli elicit diminished high-gamma electrocorticographic responses

In the phenomenon of repetition suppression (RS), when a person views a stimulus, the neural activity involved in processing that item is relatively diminished if that stimulus had been previously viewed. Previous noninvasive imaging studies mapped the prevalence of RS for different stimulus types to identify brain regions involved in representing a range of cognitive information. However, these noninvasive findings are challenging to interpret because they do not provide information on how RS relates to the brain's electrophysiological activity. We examined the electrophysiological basis of RS directly using brain recordings from implanted electrocorticographic (ECoG) electrodes in neurosurgical patients. Patients performed a memory task during ECoG recording and we identified high-gamma signals (65-128 Hz) that distinguished the neuronal representation of specific memory items. We then compared the neural representation of each item between novel and repeated viewings. This revealed the presence of RS, in which the neuronal representation of a repeated item had a significantly decreased amplitude and duration compared with novel stimuli. Furthermore, the magnitude of RS was greatest for the stimuli that initially elicited the largest activation at each site. These results have implications for understanding the neural basis of RS and human memory by showing that individual cortical sites exhibit the largest RS for the stimuli that they most actively represent.

Synchronous and asynchronous theta and gamma activity during episodic memory formation

To test the hypothesis that neural oscillations synchronize to mediate memory encoding, we analyzed electrocorticographic recordings taken as 68 human neurosurgical patients studied and subsequently recalled lists of common words. To the extent that changes in spectral power reflect synchronous oscillations, we would expect those power changes to be accompanied by increases in phase synchrony between the region of interest and neighboring brain areas. Contrary to the hypothesized role of synchronous gamma oscillations in memory formation, we found that many key regions that showed power increases during successful memory encoding also exhibited decreases in global synchrony. Similarly, cortical theta activity that decreases during memory encoding exhibits both increased and decreased global synchrony depending on region and stage of encoding. We suggest that network synchrony analyses, as used here, can help to distinguish between two major types of spectral modulations: (1) those that reflect synchronous engagement of regional neurons with neighboring brain areas, and (2) those that reflect either asynchronous modulations of neural activity or local synchrony accompanied by global disengagement from neighboring regions. We show that these two kinds of spectral modulations have distinct spatiotemporal profiles during memory encoding.