Neural activity in the medial temporal lobe reveals the fidelity of mental time travel

PEPPR: A post-encoding pre-production reinstatement model of dual-list free recall

Recent events are easy to recall, but they also interfere with the recall of more distant, non-recent events. In many computational models, non-recent memories are recalled by using the context associated with those events as a cue. Some models, however, do little to explain how people initially activate non-recent contexts in the service of accurate recall. We addressed this limitation by evaluating two candidate mechanisms within the Context-Maintenance and Retrieval model. The first is a Backward-Walk mechanism that iteratively applies a generate/recognize process to covertly retrieve progressively less recent items. The second is a Post-Encoding Pre-Production Reinstatement (PEPPR) mechanism that formally implements a metacognitive control process that reinstates non-recent contexts prior to retrieval. Models including these mechanisms make divergent predictions about the dynamics of response production and monitoring when recalling non-recent items. Before producing non-recent items, Backward-Walk cues covert retrievals of several recent items, whereas PEPPR cues few, if any, covert retrievals of that sort. We tested these predictions using archival data from a dual-list externalized free recall paradigm that required subjects to report all items that came to mind while recalling from the non-recent list. Simulations showed that only the model including PEPPR accurately predicted covert recall patterns. That same model fit the behavioral data well. These findings suggest that self-initiated context reinstatement plays an important role in recall of non-recent memories and provides a formal model that uses a parsimonious non-hierarchical context representation of how such reinstatement might occur.

Improving Memory Search Through Model-Based Cue Selection

We often use cues from our environment when we get stuck searching our memories, but prior research has failed to show benefits of cuing with other, randomly selected list items during memory search. What accounts for this discrepancy? We proposed that cues' content critically determines their effectiveness and sought to select the right cues by building a computational model of how cues affect memory search. Participants (N = 195 young adults from the United States) recalled significantly more items when receiving our model's best (vs. worst) cue. Our model provides an account of why some cues better aid recall: Effective cues activate contexts most similar to the remaining items' contexts, facilitating recall in an unsearched area of memory. We discuss our contributions in relation to prominent theories about the effect of external cues.

The organizational principles of impression formation

Trait impressions about others are a fundamental tool to navigate the rich social environment and yet a unitary model of its organizational principles is still lacking. The statistical properties of impression formation observed in previous studies are akin to processes that govern information encoding and storage in memory, suggesting similar cognitive and computational mechanisms. Here, in 2,780 participants, impression formation has been formalized with a computational model representing three organizational principles of memory (temporal, semantic and valence-related). The model specifically captured two main patterns of impression formation: (1) a negative valence effect that makes negative impressions loom longer than positive ones; (2) an interaction effect between the temporal and valence content that endorses more negative impressions when negative information is met first. This work shows that mechanisms of information encoding, storage and retrieval interact in ways that explain biased impression formation about social partners, thereby providing quantitative evidence for those mechanisms in individuals' impressions of others' social qualities. We discuss the implications of these results for social impressions in different, real-world contexts, and suggest how the proposed model might be extended to capture other kinds of effects, from negativity bias and pessimism to social discrimination.

Neural unscrambling of temporal information during a nonlinear narrative

Although we must experience our lives chronologically, storytellers often manipulate the order in which they relay events. How the brain processes temporal information while encoding a nonlinear narrative remains unclear. Here, we use functional magnetic resonance imaging during movie watching to investigate which brain regions are sensitive to information about time in a narrative and test whether the representation of temporal context across a narrative is more influenced by the order in which events are presented or their underlying chronological sequence. Results indicate that medial parietal regions are sensitive to cued jumps through time over and above other changes in context (i.e., location). Moreover, when processing non-chronological narrative information, the precuneus and posterior cingulate engage in on-the-fly temporal unscrambling to represent information chronologically. Specifically, days that are closer together in chronological time are represented more similarly regardless of when they are presented in the movie, and this representation is consistent across participants. Additional analyses reveal a strong spatial signature associated with higher magnitude jumps through time. These findings are consistent with prior theorizing on medial parietal regions as central to maintaining and updating narrative situation models, and suggest the priority of chronological information when encoding narrative events.

Reassessing hierarchical correspondences between brain and deep networks through direct interface

Functional correspondences between deep convolutional neural networks (DCNNs) and the mammalian visual system support a hierarchical account in which successive stages of processing contain ever higher-level information. However, these correspondences between brain and model activity involve shared, not task-relevant, variance. We propose a stricter account of correspondence: If a DCNN layer corresponds to a brain region, then replacing model activity with brain activity should successfully drive the DCNN's object recognition decision. Using this approach on three datasets, we found that all regions along the ventral visual stream best corresponded with later model layers, indicating that all stages of processing contained higher-level information about object category. Time course analyses suggest that long-range recurrent connections transmit object class information from late to early visual areas.

Identifying the neural dynamics of category decisions with computational model-based functional magnetic resonance imaging

Successful categorization requires a careful coordination of attention, representation, and decision making. Comprehensive theories that span levels of analysis are key to understanding the computational and neural dynamics of categorization. Here, we build on recent work linking neural representations of category learning to computational models to investigate how category decision making is driven by neural signals across the brain. We uniquely combine functional magnetic resonance imaging with drift diffusion and exemplar-based categorization models to show that trial-by-trial fluctuations in neural activation from regions of occipital, cingulate, and lateral prefrontal cortices are linked to category decisions. Notably, only lateral prefrontal cortex activation was associated with exemplar-based model predictions of trial-by-trial category evidence. We propose that these brain regions underlie distinct functions that contribute to successful category learning.

Medial prefrontal cortex and hippocampal activity differentially contribute to ordinal and temporal context retrieval during sequence memory

Remembering sequences of events defines episodic memory, but retrieval can be driven by both ordinality and temporal contexts. Whether these modes of retrieval operate at the same time or not remains unclear. Theoretically, medial prefrontal cortex (mPFC) confers ordinality, while the hippocampus (HC) associates events in gradually changing temporal contexts. Here, we looked for evidence of each with BOLD fMRI in a sequence task that taxes both retrieval modes. To test ordinal modes, items were transferred between sequences but retained their position (e.g., AB3). Ordinal modes activated mPFC, but not HC. To test temporal contexts, we examined items that skipped ahead across lag distances (e.g., ABD). HC, but not mPFC, tracked temporal contexts. There was a mPFC and HC by retrieval mode interaction. These current results suggest that the mPFC and HC are concurrently engaged in different retrieval modes in support of remembering when an event occurred.

Temporal context guides visual exploration during scene recognition

Memories for episodes are temporally structured. Cognitive models derived from list-learning experiments attribute this structure to the retrieval of temporal context information that indicates when a memory occurred. These models predict key features of memory recall, such as the strong tendency to retrieve studied items in the order in which they were first encountered. Can such models explain ecological memory behaviors, such as eye movements during encoding and retrieval of complex visual stimuli? We tested predictions from retrieved-context models using three data sets involving recognition memory and free viewing of complex scenes. Subjects reinstated sequences of eye movements from one scene-viewing episode to the next. Moreover, sequence reinstatement decayed over time and was associated with successful memory. We observed memory-driven reinstatement even after accounting for intrinsic scene properties that produced consistent eye movements. These findings confirm predictions of retrieved-context models, suggesting retrieval of temporal context influences complex behaviors generated during naturalistic memory experiences. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Reward prediction errors create event boundaries in memory

We remember when things change. Particularly salient are experiences where there is a change in rewards, eliciting reward prediction errors (RPEs). How do RPEs influence our memory of those experiences? One idea is that this signal directly enhances the encoding of memory. Another, not mutually exclusive, idea is that the RPE signals a deeper change in the environment, leading to the mnemonic separation of subsequent experiences from what came before, thereby creating a new latent context and a more separate memory trace. We tested this in four experiments where participants learned to predict rewards associated with a series of trial-unique images. High-magnitude RPEs indicated a change in the underlying distribution of rewards. To test whether these large RPEs created a new latent context, we first assessed recognition priming for sequential pairs that included a high-RPE event or not (Exp. 1: n = 27 & Exp. 2: n = 83). We found evidence of recognition priming for the high-RPE event, indicating that the high-RPE event is bound to its predecessor in memory. Given that high-RPE events are themselves preferentially remembered (Rouhani, Norman, & Niv, 2018), we next tested whether there was an event boundary across a high-RPE event (i.e., excluding the high-RPE event itself; Exp. 3: n = 85). Here, sequential pairs across a high RPE no longer showed recognition priming whereas pairs within the same latent reward state did, providing initial evidence for an RPE-modulated event boundary. We then investigated whether RPE event boundaries disrupt temporal memory by asking participants to order and estimate the distance between two events that had either included a high-RPE event between them or not (Exp. 4). We found (n = 49) and replicated (n = 77) worse sequence memory for events across a high RPE. In line with our recognition priming results, we did not find sequence memory to be impaired between the high-RPE event and its predecessor, but instead found worse sequence memory for pairs across a high-RPE event. Moreover, greater distance between events at encoding led to better sequence memory for events across a low-RPE event, but not a high-RPE event, suggesting separate mechanisms for the temporal ordering of events within versus across a latent reward context. Altogether, these findings demonstrate that high-RPE events are both more strongly encoded, show intact links with their predecessor, and act as event boundaries that interrupt the sequential integration of events. We captured these effects in a variant of the Context Maintenance and Retrieval model (CMR; Polyn, Norman, & Kahana, 2009), modified to incorporate RPEs into the encoding process.

A Joint Modelling Approach to Analyze Risky Decisions by Means of Diffusion Tensor Imaging and Behavioural Data

Understanding dependencies between brain functioning and cognition is a challenging task which might require more than applying standard statistical models to neural and behavioural measures to be accomplished. Recent developments in computational modelling have demonstrated the advantage to formally account for reciprocal relations between mathematical models of cognition and brain functional, or structural, characteristics to relate neural and cognitive parameters on a model-based perspective. This would allow to account for both neural and behavioural data simultaneously by providing a joint probabilistic model for the two sources of information. In the present work we proposed an architecture for jointly modelling the reciprocal relation between behavioural and neural information in the context of risky decision-making. More precisely, we offered a way to relate Diffusion Tensor Imaging data to cognitive parameters of a computational model accounting for behavioural outcomes in the popular Balloon Analogue Risk Task (BART). Results show that the proposed architecture has the potential to account for individual differences in task performances and brain structural features by letting individual-level parameters to be modelled by a joint distribution connecting both sources of information. Such a joint modelling framework can offer interesting insights in the development of computational models able to investigate correspondence between decision-making and brain structural connectivity.

Prefrontal Pathways Provide Top-Down Control of Memory for Sequences of Events

We remember our lives as sequences of events, but it is unclear how these memories are controlled during retrieval. In rats, the medial prefrontal cortex (mPFC) is positioned to influence sequence memory through extensive top-down inputs to regions heavily interconnected with the hippocampus, notably the nucleus reuniens of the thalamus (RE) and perirhinal cortex (PER). Here, we used an hM4Di synaptic-silencing approach to test our hypothesis that specific mPFC→RE and mPFC→PER projections regulate sequence memory retrieval. First, we found non-overlapping populations of mPFC cells project to RE and PER. Second, suppressing mPFC activity impaired sequence memory. Third, inhibiting mPFC→RE and mPFC→PER pathways effectively abolished sequence memory. Finally, a sequential lag analysis showed that the mPFC→RE pathway contributes to a working memory retrieval strategy, whereas the mPFC→PER pathway supports a temporal context memory retrieval strategy. These findings demonstrate that mPFC→RE and mPFC→PER pathways serve as top-down mechanisms that control distinct sequence memory retrieval strategies.

The nucleus reuniens of the thalamus sits at the nexus of a hippocampus and medial prefrontal cortex circuit enabling memory and behavior

The nucleus reuniens of the thalamus (RE) is a key component of an extensive network of hippocampal and cortical structures and is a fundamental substrate for cognition. A common misconception is that RE is a simple relay structure. Instead, a better conceptualization is that RE is a critical component of a canonical higher-order cortico-thalamo-cortical circuit that supports communication between the medial prefrontal cortex (mPFC) and the hippocampus (HC). RE dysfunction is implicated in several clinical disorders including, but not limited to Alzheimer's disease, schizophrenia, and epilepsy. Here, we review key anatomical and physiological features of the RE based primarily on studies in rodents. We present a conceptual model of RE circuitry within the mPFC-RE-HC system and speculate on the computations RE enables. We review the rapidly growing literature demonstrating that RE is critical to, and its neurons represent, aspects of behavioral tasks that place demands on memory focusing on its role in navigation, spatial working memory, the temporal organization of memory, and executive functions.

Emerging Opportunities for Advancing Cognitive Neuroscience

Cognitive neuroscience can be substantially advanced if structured mechanisms are created to increase its social impact and to develop synergies with some currently more distant disciplines that are developing relevant knowledge. We present such opportunities and argue that pursuing these can benefit from establishing a centralized coordinating organizational approach.

Overlap between hippocampal pre-encoding and encoding patterns supports episodic memory

It is well-established that whether the information will be remembered or not depends on the extent to which the learning context is reinstated during post-encoding rest and/or at retrieval. It has yet to be determined, however, if the fundamental importance of contextual reinstatement to memory extends to periods of spontaneous neurocognitive activity prior to learning. We thus asked whether memory performance can be predicted by the extent to which spontaneous pre-encoding neural patterns resemble patterns elicited during encoding. Individuals studied and retrieved lists of words while undergoing fMRI-scanning. Multivoxel hippocampal patterns during resting periods prior to encoding resembled hippocampal patterns at encoding most strongly for items that were subsequently remembered. Furthermore, across subjects, the magnitude of similarity correlated with a behavioral measure of episodic recall. The results indicate that the neural context before learning is an important determinant of memory.

Identifying task-general effects of stimulus familiarity in the parietal memory network

Studies of human memory have implicated a "parietal memory network" in the recognition of familiar stimuli. However, the automatic vs. top-down nature of information processing within this network is not yet understood. If the network processes stimuli automatically, one can expect repetition-related changes both when familiarity is central to an ongoing task and when it is task-irrelevant. Here, we tested this prediction in a group of 40 human subjects using fMRI. Subjects initially named 100 objects aloud in the scanner. They then repeated the same task with novel and previously-named objects intermixed (where familiarity was not task-relevant) and separately were asked to make old/new recognition decisions in response to pictures of novel and previously-named objects (where familiarity was central to task completion). Accuracy was matched across conditions, and voice reaction times reflected typical behavioral priming effects. Repetition enhancement effects were restricted primarily to parietal cortex-and in particular, the parietal memory network-and were task-general in nature, whereas repetition suppression effects were task-dependent and occurred primarily in frontal and ventral temporal cortex. Task context effects were also present in the parietal memory network and impacted responses to both novel and familiar items. We conclude by discussing implications of these findings with respect to current hypotheses regarding parietal contributions to memory retrieval.

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.

Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension

Recent decades have ushered in tremendous progress in understanding the neural basis of language. Most of our current knowledge on language and the brain, however, is derived from lab-based experiments that are far removed from everyday language use, and that are inspired by questions originating in linguistic and psycholinguistic contexts. In this paper we argue that in order to make progress, the field needs to shift its focus to understanding the neurobiology of naturalistic language comprehension. We present here a new conceptual framework for understanding the neurobiological organization of language comprehension. This framework is non-language-centered in the computational/neurobiological constructs it identifies, and focuses strongly on context. Our core arguments address three general issues: (i) the difficulty in extending language-centric explanations to discourse; (ii) the necessity of taking context as a serious topic of study, modeling it formally and acknowledging the limitations on external validity when studying language comprehension outside context; and (iii) the tenuous status of the language network as an explanatory construct. We argue that adopting this framework means that neurobiological studies of language will be less focused on identifying correlations between brain activity patterns and mechanisms postulated by psycholinguistic theories. Instead, they will be less self-referential and increasingly more inclined towards integration of language with other cognitive systems, ultimately doing more justice to the neurobiological organization of language and how it supports language as it is used in everyday life.

Time Regained: How the Human Brain Constructs Memory for Time

Life's episodes unfold against a context that changes with time. Recent neuroimaging studies have revealed significant findings about how specific areas of the human brain may support the representation of temporal information in memory. A consistent theme in these studies is that the hippocampus appears to play a central role in representing temporal context, as operationalized in neuroimaging studies of arbitrary lists of items, sequences of items, or meaningful, lifelike events. Additionally, activity in a posterior medial cortical network may reflect the representation of generalized temporal information for meaningful events. The hippocampus, posterior medial network, and other regions-particularly in prefrontal cortex-appear to play complementary roles in memory for temporal context.

Temporal and spatial context in the mind and brain

Theories of episodic memory have long hypothesized that recollection of a specific instance from one's life is mediated by recovery of a neural state of spatiotemporal context. This paper reviews recent theoretical advances in formal models of spatiotemporal context and a growing body of neurophysiological evidence from human imaging studies and animal work that neural populations in the hippocampus and other brain regions support a representation of spatiotemporal context.

What's in a context? Cautions, limitations, and potential paths forward

The purpose of memory is to guide current and future behavior based on previous experiences. Part of this process involves either discriminating between or generalizing across similar experiences that contain overlapping conditions (such as space, time, or internal state), which we often conceptualize as "contexts". In this review, we highlight major challenges facing the field as we attempt a neuroscience-based approach to the study of context and its impact on learning and memory. Here, we review some of the methodologies and approaches used to investigate context in both animals and humans, including the neurobiological mechanisms involved. Finally, we propose three tenets for operationalizing context in the experimental setting: 1) contexts must be stable over time along an experiential dimension; 2) contexts must be at least moderately complex in nature and their representations must be modifiable or adaptable, and 3) contexts must have some behavioral relevance (be it overt or incidental) so that its role can be measured.

Memory Retrieval Re-Activates Erk1/2 Signaling in the Same Set of CA1 Neurons Recruited During Conditioning

The hippocampus enables a range of behaviors through its intrinsic circuits and concerted actions with other brain regions. One such important function is the retrieval of episodic memories. How hippocampal cells support retrieval of contextual fear memory remains largely unclear. Here we monitored phospho-activation of extracellular-regulated kinase (Erk1/2) across neuronal populations of the hippocampus to find that CA1 pyramidal neurons, but not cells in CA3 or dentate gyrus, specifically respond to retrieval of an aversive context. In contrast, retrieval of a neutral context that fails to elicit a threat response did not activate Erk1/2. Moreover, retrieval preferentially re-activated Erk1/2 in the same set of CA1 neurons previously activated during conditioning in a context-specific manner. By confining drug inhibition within dorsal CA1, we established the crucial role for Erk1/2 activity in retrieval of long-term memory, as well as in amygdala activation associated with fear expression. These data provide functional evidence that Erk1/2 signaling in CA1 encodes a specific neural representation of contextual memory with emotional value.

Model-based cognitive neuroscience

This special issue explores the growing intersection between mathematical psychology and cognitive neuroscience. Mathematical psychology, and cognitive modeling more generally, has a rich history of formalizing and testing hypotheses about cognitive mechanisms within a mathematical and computational language, making exquisite predictions of how people perceive, learn, remember, and decide. Cognitive neuroscience aims to identify neural mechanisms associated with key aspects of cognition using techniques like neurophysiology, electrophysiology, and structural and functional brain imaging. These two come together in a powerful new approach called model-based cognitive neuroscience, which can both inform cognitive modeling and help to interpret neural measures. Cognitive models decompose complex behavior into representations and processes and these latent model states can be used to explain the modulation of brain states under different experimental conditions. Reciprocally, neural measures provide data that help constrain cognitive models and adjudicate between competing cognitive models that make similar predictions about behavior. As examples, brain measures are related to cognitive model parameters fitted to individual participant data, measures of brain dynamics are related to measures of model dynamics, model parameters are constrained by neural measures, model parameters or model states are used in statistical analyses of neural data, or neural and behavioral data are analyzed jointly within a hierarchical modeling framework. We provide an introduction to the field of model-based cognitive neuroscience and to the articles contained within this special issue.

Integrating Theoretical Models with Functional Neuroimaging

The development of mathematical models to characterize perceptual and cognitive processes dates back almost to the inception of the field of psychology. Since the 1990s, human functional neuroimaging has provided for rapid empirical and theoretical advances across a variety of domains in cognitive neuroscience. In more recent work, formal modeling and neuroimaging approaches are being successfully combined, often producing models with a level of specificity and rigor that would not have been possible by studying behavior alone. In this review, we highlight examples of recent studies that utilize this combined approach to provide novel insights into the mechanisms underlying human cognition. The studies described here span domains of perception, attention, memory, categorization, and cognitive control, employing a variety of analytic and model-inspired approaches. Across these diverse studies, a common theme is that individually tailored, creative solutions are often needed to establish compelling links between multi-parameter models and complex sets of neural data. We conclude that future developments in model-based cognitive neuroscience will have great potential to advance our theoretical understanding and ability to model both low-level and high-level cognitive processes.

Stimulation of the human medial temporal lobe between learning and recall selectively enhances forgetting

BACKGROUND

Direct electrical stimulation applied to the human medial temporal lobe (MTL) typically disrupts performance on memory tasks, however, the mechanism underlying this effect is not known.

OBJECTIVE

To study the effects of MTL stimulation on memory performance.

METHODS

We studied the effects of MTL stimulation on memory in five patients undergoing invasive electrocorticographic monitoring during various phases of a memory task (encoding, distractor, recall).

RESULTS

We found that MTL stimulation disrupted memory performance in a timing-dependent manner; we observed greater forgetting when applying stimulation during the delay between encoding and recall, compared to when it was applied during encoding or recall.

CONCLUSIONS

The results suggest that recall is most dependent on the MTL between learning and retrieval.

Task-specific Aspects of Goal-directed Word Generation Identified via Simultaneous EEG–fMRI

Generating words according to a given rule relies on retrieval-related search and postretrieval control processes. Using fMRI, we recently characterized neural patterns of word generation in response to episodic, semantic, and phonemic cues by comparing free recall of wordlists, category fluency, and letter fluency [Shapira-Lichter, I., Oren, N., Jacob, Y., Gruberger, M., & Hendler, T. Portraying the unique contribution of the default mode network to internally driven mnemonic processes. Proceedings of the National Academy of Sciences, U.S.A., 110, 4950–4955, 2013]. Distinct selectivity for each condition was evident, representing discrete aspects of word generation-related memory retrieval. For example, the precuneus, implicated in processing spatiotemporal information, emerged as a key contributor to the episodic condition, which uniquely requires this information. Gamma band is known to play a central role in memory, and increased gamma power has been observed before word generation. Yet, gamma modulation in response to task demands has not been investigated. To capture the task-specific modulation of gamma power, we analyzed the EEG data recorded simultaneously with the aforementioned fMRI, focusing on the activity locked to and immediately preceding word articulation. Transient increases in gamma power were identified in a parietal electrode immediately before episodic and semantic word generation, however, within a different time frame relative to articulation. Gamma increases were followed by an alpha-theta decrease in the episodic condition, a gamma decrease in the semantic condition. This pattern indicates a task-specific modulation of the gamma signal corresponding to the specific demands of each word generation task. The gamma power and fMRI signal from the precuneus were correlated during the episodic condition, implying the existence of a common cognitive construct uniquely required for this task, possibly the reactivation or processing of spatiotemporal information.

The mental time travel continuum: on the architecture, capacity, versatility and extension of the mental bridge into the past and future

Mental time travel (MTT) is the ability to remember past events and to anticipate or imagine events in the future. MTT globally serves to optimize decision-making processes, improve problem-solving capabilities and prepare for future needs. MTT is also essential in providing our concept of self, which includes knowledge of our personality, our strengths and weaknesses, as well as our preferences and aversions. We will give an overview in which ways the capacity of animals to perform MTT is different from humans. Based on the existing literature, we conclude that MTT might represent a quantitative rather than qualitative entity with a continuum of MTT capacities in both humans and nonhuman animals. Given its high complexity, MTT requires a large processing capacity in order to integrate multimodal stimuli during the reconstruction of past and/or future events. We suggest that these operations depend on a highly specialized working memory subsystem, ‘the MTT platform’, which might represent a necessary additional component in the multi-component working memory model by Alan Baddeley.

A predictive framework for evaluating models of semantic organization in free recall

Research in free recall has demonstrated that semantic associations reliably influence the organization of search through episodic memory. However, the specific structure of these associations and the mechanisms by which they influence memory search remain unclear. We introduce a likelihood-based model-comparison technique, which embeds a model of semantic structure within the context maintenance and retrieval (CMR) model of human memory search. Within this framework, model variants are evaluated in terms of their ability to predict the specific sequence in which items are recalled. We compare three models of semantic structure, latent semantic analysis (LSA), global vectors (GloVe), and word association spaces (WAS), and find that models using WAS have the greatest predictive power. Furthermore, we find evidence that semantic and temporal organization is driven by distinct item and context cues, rather than a single context cue. This finding provides important constraint for theories of memory search.

Hippocampal ensemble dynamics timestamp events in long-term memory

The capacity to remember temporal relationships between different events is essential to episodic memory, but little is currently known about its underlying mechanisms. We performed time-lapse imaging of thousands of neurons over weeks in the hippocampal CA1 of mice as they repeatedly visited two distinct environments. Longitudinal analysis exposed ongoing environment-independent evolution of episodic representations, despite stable place field locations and constant remapping between the two environments. These dynamics time-stamped experienced events via neuronal ensembles that had cellular composition and activity patterns unique to specific points in time. Temporally close episodes shared a common timestamp regardless of the spatial context in which they occurred. Temporally remote episodes had distinct timestamps, even if they occurred within the same spatial context. Our results suggest that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance.

DOI:http://dx.doi.org/10.7554/eLife.12247.001

The ability to recall the timing of events is an important feature of long-term memory. Episodic memory, the mental account of “what” happened, “where” and “when”, depends on a region of a brain called the hippocampus. Certain neurons in the hippocampus, called place-cells, are known to capture information about the locations an animal has visited so that a specific pattern of place cell activity marks each location an animal visits. However, it is not clear how the brain can mark the relationship between the timing of different events.

Some studies have documented gradual changes in the activity patterns of the place cells over time, which could help mark time. If these changes are specific to a particular environment then they would not allow animals to associate in memory events that occurred close in time (for instance, in the same day) if these events occurred in different environments. To do that, a certain component of the changes in the activity patterns would have to be independent of any specific environment or context in which events occur.

Now, Rubin, Geva et al. have captured time-lapse images of the activity of thousands of hippocampal cells in mice as they explored two different environments on repeated occasions over a two-week period. The environments had different shapes, textures, visual cues, and odors. The mice were allowed to explore each environment daily for more than a week prior to the time-lapse filming so that they would be very familiar with the two environments. During the filming portion of the experiments, the mice visited one environment in the morning, and then the other in the afternoon.

The analysis of the images revealed what appeared to be unique patterns of cell activity for specific days, which gradually changed over the course of the experiment. The patterns persisted even when the animals switched to a new environment during the same day, but were different for visits to the same environment on different days. Next, Rubin, Geva et al. used the patterns of activity collected from the mice while they were in one environment to create a timeline of events. From this timeline, it was possible to accurately deduce which day each visit to the other environment occurred based on the patterns of hippocampal cell activity alone. One challenge that stems from this work is to understand the biological mechanisms that drive the patterns in neuronal activity over timescales that are relevant for long-term memory.

DOI:http://dx.doi.org/10.7554/eLife.12247.002

Decoding Episodic Retrieval Processes: Frontoparietal and Medial Temporal Lobe Contributions to Free Recall

Neuroimaging studies of recognition memory have identified distinct patterns of cortical activity associated with two sets of cognitive processes: Recollective processes supporting retrieval of information specifying a probe item's original source are associated with the posterior hippocampus, ventral posterior parietal cortex, and medial pFC. Familiarity processes supporting the correct identification of previously studied probes (in the absence of a recollective response) are associated with activity in anterior medial temporal lobe (MTL) structures including the perirhinal cortex and anterior hippocampus, in addition to lateral prefrontal and dorsal posterior parietal cortex. Here, we address an open question in the cognitive neuroscientific literature: To what extent are these same neurocognitive processes engaged during an internally directed memory search task like free recall? We recorded fMRI activity while participants performed a series of free recall and source recognition trials, and we used a combination of univariate and multivariate analysis techniques to compare neural activation profiles across the two tasks. Univariate analyses showed that posterior MTL regions were commonly associated with recollective processes during source recognition and with free recall responses. Prefrontal and posterior parietal regions were commonly associated with familiarity processes and free recall responses, whereas anterior MTL regions were only associated with familiarity processes during recognition. In contrast with the univariate results, free recall activity patterns characterized using multivariate pattern analysis did not reliably match the neural patterns associated with recollective processes. However, these free recall patterns did reliably match patterns associated with familiarity processes, supporting theories of memory in which common cognitive mechanisms support both item recognition and free recall.