Contextually Mediated Spontaneous Retrieval Is Specific to the Hippocampus

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.

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.

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).

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement

Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode implantation locations. Using a data-driven approach, we employ support vector machine (SVM) classifiers to identify high-yield brain targets on a large data set of 75 human intracranial electroencephalogram subjects performing the free recall (FR) task. Further, we address whether the conserved brain regions provide effective classification in an alternate (associative) memory paradigm along with FR, as well as testing unsupervised classification methods that may be a useful adjunct to clinical device implementation. Finally, we use random forest models to classify functional brain states, differentiating encoding versus retrieval versus non-memory behavior such as rest and mathematical processing. We then test how regions that exhibit good classification for the likelihood of recall success in the SVM models overlap with regions that differentiate functional brain states in the random forest models. Finally, we lay out how these data may be used in the design of neuromodulation devices.

Neuronal activity in the human amygdala and hippocampus enhances emotional memory encoding

Emotional events comprise our strongest and most valuable memories. Here we examined how the brain prioritizes emotional information for storage using direct brain recording and deep brain stimulation. First, 148 participants undergoing intracranial electroencephalographic (iEEG) recording performed an episodic memory task. Participants were most successful at remembering emotionally arousing stimuli. High-frequency activity (HFA), a correlate of neuronal spiking activity, increased in both the hippocampus and the amygdala when participants successfully encoded emotional stimuli. Next, in a subset of participants (N = 19), we show that applying high-frequency electrical stimulation to the hippocampus selectively diminished memory for emotional stimuli and specifically decreased HFA. Finally, we show that individuals with depression (N = 19) also exhibit diminished emotion-mediated memory and HFA. By demonstrating how direct stimulation and symptoms of depression unlink HFA, emotion and memory, we show the causal and translational potential of neural activity in the amygdalohippocampal circuit for prioritizing emotionally arousing memories.

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.

Hippocampal ripples signal contextually mediated episodic recall

High-frequency oscillatory events, termed ripples, represent synchrony of neural activity in the brain. Recent evidence suggests that medial temporal lobe (MTL) ripples support memory retrieval. However, it is unclear if ripples signal the reinstatement of episodic memories. Analyzing electrophysiological MTL recordings from 245 neurosurgical participants performing episodic recall tasks, we find that the rate of hippocampal ripples rises just prior to the free recall of recently formed memories. This prerecall ripple effect (PRE) is stronger in the CA1 and CA3/dentate gyrus (CA3/DG) subfields of the hippocampus than the neighboring MTL regions entorhinal and parahippocampal cortex. PRE is also stronger prior to the retrieval of temporally and semantically clustered, as compared with unclustered, recalls, indicating the involvement of ripples in contextual reinstatement, which is a hallmark of episodic memory.

Temporal Context Modulates Encoding and Retrieval of Overlapping Events

Overlap between events can lead to interference because of a trade-off between encoding the present event and retrieving the past event. Temporal context information, "when" something occurred, a defining feature of episodic memory, can cue retrieval of a past event. However, the influence of temporal overlap, or proximity in time, on the mechanisms of interference is unclear. Here, by identifying brain states using scalp EEG from male and female human subjects, we show the extent to which temporal overlap promotes interference and induces retrieval. In this experiment, subjects were explicitly directed to either encode the present event or retrieve a past, overlapping event while perceptual input was held constant. We find that the degree of temporal overlap between events leads to selective interference. Specifically, greater temporal overlap between two events leads to impaired memory for the past event selectively when the top-down goal is to encode the present event. Using pattern classification analyses to measure neural evidence for a retrieval state, we find that greater temporal overlap leads to automatic retrieval of a past event, independent of top-down goals. Critically, the retrieval evidence we observe likely reflects a general retrieval mode, rather than retrieval success or effort. Collectively, our findings provide insight into the role of temporal overlap on interference and memory formation.SIGNIFICANCE STATEMENT When a present event overlaps with an event from the past, this leads to a trade-off between the tendency to encode the present event versus retrieve the past event. Here we show that, when two events are experienced nearby in time, the memory system is biased toward a retrieval state and that subsequent memory for the past event is impaired. These findings suggest an influence of bottom-up temporal factors on both interference and the trade-off between memory states.

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.

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.

Direct brain recordings identify hippocampal and cortical networks that distinguish successful versus failed episodic memory retrieval

Human data collected using noninvasive imaging techniques have established the importance of parietal regions towards episodic memory retrieval, including the angular gyrus and posterior cingulate cortex. Such regions comprise part of a putative core episodic retrieval network. In free recall, comparisons between contextually appropriate and inappropriate recall events (i.e. prior list intrusions) provide the opportunity to study memory retrieval networks supporting veridical recall, and existing findings predict that differences in electrical activity in these brain regions should be identified according to the accuracy of recall. However, prior iEEG studies, utilizing principally subdural grid electrodes, have not fully characterized brain activity in parietal regions during memory retrieval and have not examined connectivity between core recollection areas and the hippocampus or prefrontal cortex. Here, we employed a data set obtained from 100 human patients implanted with stereo EEG electrodes for seizure mapping purposes as they performed a free recall task. This data set allowed us to separately analyze activity in midline versus lateral parietal brain regions, and in anterior versus posterior hippocampus, to identify areas in which retrieval-related activity predicted the recollection of a correct versus an incorrect memory. With the wide coverage afforded by the stereo EEG approach, we were also able to examine interregional connectivity. Our key findings were that differences in gamma band activity in the angular gyrus, precuneus, posterior temporal cortex, and posterior (more than anterior) hippocampus discriminated accurate versus inaccurate recall as well as active retrieval versus memory search. The left angular gyrus exhibited a significant power decrease preceding list intrusions as well as unique phase-amplitude coupling properties, whereas the prefrontal cortex was unique in exhibiting a power increase during list intrusions. Analysis of connectivity revealed significant hemispheric asymmetry, with relatively sparse left-sided functional connections compared to the right hemisphere. One exception to this finding was elevated connectivity between the prefrontal cortex and left angular gyrus. This finding is interpreted as evidence for the engagement of prefrontal cortex in memory monitoring and mnemonic decision-making.

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.

Longitudinal Differences in Human Hippocampal Connectivity During Episodic Memory Processing

The question of longitudinal hippocampal functional specialization is critical to human episodic memory because an accurate understanding of this phenomenon would impact theories of mnemonic function and entail practical consequences for the clinical management of patients undergoing temporal lobe surgery. The implementation of the robotically assisted stereo electroencephalography technique for seizure mapping has provided our group with the opportunity to obtain recordings simultaneously from the anterior and posterior human hippocampus, allowing us to create an unparalleled data set of human subjects with simultaneous anterior and posterior hippocampal recordings along with several cortical regions. Using these data, we address several key questions governing functional hippocampal connectivity in human memory. First, we ask whether functional networks during episodic memory encoding and retrieval are significantly different for the anterior versus posterior hippocampus (PH). We also examine how connections differ across the 2-5 Hz versus 4-9 Hz theta frequency ranges, directly addressing the relative contribution of each of these separate bands in hippocampal-cortical interactions. While we report some overlapping connections, we observe evidence of distinct anterior versus posterior hippocampal networks during memory encoding related to frontal and parietal connectivity as well as hemispheric differences in aggregate connectivity. We frame these findings in light of the proposed AT/PM memory systems. We also observe distinct encoding versus retrieval connectivity patterns between anterior and posterior hippocampal networks, we find that overall connectivity is greater for the PH in the right hemisphere, and further that these networks significantly differ in terms of frontal and parietal connectivity. We place these findings in the context of existing theoretical treatments of human memory systems, especially the proposed AT/PM system. During memory retrieval, we observe significant differences between slow-theta (2-5 Hz) and fast-theta (4-9 Hz) connectivity between the cortex and hippocampus. Finally, we test how these distinct theta frequency oscillations propagate within the hippocampus, using phase slope index to estimate the direction slow-theta and fast-theta oscillations travel during encoding and retrieval. We uncover evidence that 2-5 Hz oscillations travel in the posterior-to-anterior direction, while 5-9 Hz oscillations travel from anterior-to-posterior. Taken together, our findings describe mnemonically relevant functional connectivity differences along the longitudinal axis of the human hippocampus that will inform interpretation of models of hippocampal function that seek to integrate rodent and human data.

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.

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.

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

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

Differentiation of Human Medial Prefrontal Cortex Activity Underlies Long-Term Resistance to Forgetting in Memory

It is well known that distributing study events over time leads to better memory over long time scales, compared with massing study events together. One explanation for such long-term resistance to forgetting is that distributed study leads to neural differentiation in memory, which supports retrieval of past experiences by disambiguating highly similar memory representations. Neuroanatomical models of episodic memory retrieval propose that the hippocampus and medial prefrontal cortex (MPFC) work together to enable retrieval of behaviorally appropriate memories. However, it is not known how representations in these regions jointly support resistance to forgetting long after initial learning. Using fMRI, we measured differentiation in retrieved memory representations following an extended delay in male and female human participants. After 1 week, word-object associations were better remembered if studied across 2 d (overnight), allowing associations to be learned in distinct temporal contexts, compared with learning within a single day (same day). MPFC retrieval patterns showed differentiation for overnight relative to same day memories, whereas hippocampal patterns reflected associative retrieval success. Overnight memory differentiation in MPFC was higher for associative than item memories and higher than differentiation assessed over a brain-wide set of retrieval-active voxels. The memory-related difference in MPFC pattern differentiation correlated with memory success for overnight learning and with hippocampal-MPFC functional connectivity. These results show that learning information across days leads to differentiated MPFC memory representations, reducing forgetting after 1 week, and suggest this arises from persistent interactions between MPFC and hippocampus.SIGNIFICANCE STATEMENT Neural activity in both the hippocampus and medial prefrontal cortex (MPFC) has been linked to memory-related representations, but prior work has not examined how these representations support episodic memory retrieval over extended time scales that are characteristic of everyday retrieval. We show that differentiation in MPFC activity 1 week after encoding is higher for retrieved information learned across 2 d compared with within a single day. In hippocampus, differentiation was greater for detailed memory retrieval but was not influenced by whether information had been learned over 1 or 2 d. Differentiation in MPFC predicted behavioral robustness to forgetting and was correlated with hippocampal-MPFC connectivity. The results suggest that context-based differentiation supports robust long-term memory via persistent MPFC-hippocampal interactions.

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.