Differential Consolidation and Pattern Reverberations within Episodic Cell Assemblies in the Mouse Hippocampus

One hallmark feature of consolidation of episodic memory is that only a fraction of original information, which is usually in a more abstract form, is selected for long-term memory storage. How does the brain perform these differential memory consolidations? To investigate the neural network mechanism that governs this selective consolidation process, we use a set of distinct fearful events to study if and how hippocampal CA1 cells engage in selective memory encoding and consolidation. We show that these distinct episodes activate a unique assembly of CA1 episodic cells, or neural cliques, whose response-selectivity ranges from general-to-specific features. A series of parametric analyses further reveal that post-learning CA1 episodic pattern replays or reverberations are mostly mediated by cells exhibiting event intensity-invariant responses, not by the intensity-sensitive cells. More importantly, reactivation cross-correlations displayed by intensity-invariant cells encoding general episodic features during immediate post-learning period tend to be stronger than those displayed by invariant cells encoding specific features. These differential reactivations within the CA1 episodic cell populations can thus provide the hippocampus with a selection mechanism to consolidate preferentially more generalized knowledge for long-term memory storage

Spatially-Aware Transformer for Embodied Agents

Episodic memory plays a crucial role in various cognitive processes, such as the ability to mentally recall past events. While cognitive science emphasizes the significance of spatial context in the formation and retrieval of episodic memory, the current primary approach to implementing episodic memory in AI systems is through transformers that store temporally ordered experiences, which overlooks the spatial dimension. As a result, it is unclear how the underlying structure could be extended to incorporate the spatial axis beyond temporal order alone and thereby what benefits can be obtained. To address this, this paper explores the use of Spatially-Aware Transformer models that incorporate spatial information. These models enable the creation of place-centric episodic memory that considers both temporal and spatial dimensions. Adopting this approach, we demonstrate that memory utilization efficiency can be improved, leading to enhanced accuracy in various place-centric downstream tasks. Additionally, we propose the Adaptive Memory Allocator, a memory management method based on reinforcement learning that aims to optimize efficiency of memory utilization. Our experiments demonstrate the advantages of our proposed model in various environments and across multiple downstream tasks, including prediction, generation, reasoning, and reinforcement learning. The source code for our models and experiments will be available at https://github.com/junmokane/spatially-aware-transformer.Comment: ICLR 2024 Spotlight. First two authors contributed equall

Better Memory and Neural Efficiency in Young Apolipoprotein E ε4 Carriers

The apolipoprotein E (APOE) ε4 allele is the major genetic risk factor for Alzheimer's disease, but an APOE effect on memory performance and memory-related neurophysiology in young, healthy subjects is unknown. We found an association of APOE ε4 with better episodic memory compared with APOE ε2 and ε3 in 340 young, healthy persons. Neuroimaging was performed in a subset of 34 memory-matched individuals to study genetic effects on memory-related brain activity independently of differential performance. E4 carriers decreased brain activity over 3 learning runs, whereas ε2 and ε3 carriers increased activity. This smaller neural investment of ε4 carriers into learning reappeared during retrieval: ε4 carriers exhibited reduced retrieval-related activity with equal retrieval performance. APOE isoforms had no differential effects on cognitive measures other than memory, brain volumes, and brain activity related to working memory. We suggest that APOE ε4 is associated with good episodic memory and an economic use of memory-related neural resources in young, healthy human

The effect of an aerobic exercise intervention on episodic memory in individuals with and without subjective cognitive decline

The benefit exercise has on cognition in older adults has been evidenced in many studies, however the impact exercise has on specific cognitive domains, and in individuals at greatest risk of cognitive decline, requires clarification. Individuals with early cognitive decline, identified as having subjective cognitive decline (SCD), may be most receptive to cognitive benefits provided by exercise interventions. Therefore, this study aimed to investigate whether a six month aerobic exercise intervention could improve episodic memory in healthy individuals with and without subjective cognitive decline (SCD). Ninety community-dwelling healthy older adults, aged 69.19 ± 5.21 years (53% female), were randomised into either high intensity exercise, moderate intensity exercise, or a control group. Intervention groups cycled twice a week for 50 minutes, and outcome measures included the California Verbal Learning Test (CVLT-II), the Brief Visuospatial Learning Task (BVMT) and the Groton maze recall to measure episodic memory; as well as right and left hippocampal volume. Individuals in the intervention groups did not significantly differ in their performance from pre- to post-intervention on any episodic memory measure or hippocampal volume, compared to the control. There were no significant differences from pre- to post-intervention between those with and without SCD on any episodic memory measure, or for hippocampal volume. However, SCD moderated the relationship between cardiorespiratory fitness and BVMT performance, indicating that at low levels of SCD, as cardiorespiratory fitness increases, so does episodic memory. This provides partial support for the use of exercise as a prevention tool for cognitive decline; however further research is required to clarify the mechanisms of these benefits and determine the crucial window of opportunity to implement exercise interventions

A second look at memory: Different Approaches to Understanding Diversity in Memory and Cognition

Memory lies at the heart of human cognitive abilities. Therefore, understanding it from neural, psychological and computational viewpoints is of key importance for computational neuroscience, psychology and beyond. In this thesis, I explore two prominent, but different, memory systems: episodic memory and working memory. First, I propose a modification to a recent reinforcement learning algorithm for decision making in which single memories of events, i.e., episodic memories, are integrated to compute the long run value of actions. I argue that these memories are recalled and that their contributions are weighted based on context. Further, I propose that predictions made by this algorithm are combined with those that come from a standard, model-free, reinforcement learning algorithm. I suggest that humans can flexibly choose between these two sources of information to make decisions and guide actions. I show that the resulting combined model best fits data on human choices, outperforming previously proposed models. To complement these algorithmic and psychological suggestions, I present a generative model of the world according to which this sort of episodic recall is an appropriate method for making inferences and predictions of future rewards. Contrary to other suggestions for reward-based learning, this generative model can model events that not only drift continuously in time, but can also suddenly change to new or repeated events. Turning to working memory, I use information theoretic analyses to show that dynamic synapses, whose strengths adjust with usage, can increase its capacity. I argue that these components should be included in the study of working memory. The thesis ends with an explanation of the connections between these memory systems

The hippocampus, prefrontal cortex, and perirhinal cortex are critical to incidental order memory.

Considerable research in rodents and humans indicates the hippocampus and prefrontal cortex are essential for remembering temporal relationships among stimuli, and accumulating evidence suggests the perirhinal cortex may also be involved. However, experimental parameters differ substantially across studies, which limits our ability to fully understand the fundamental contributions of these structures. In fact, previous studies vary in the type of temporal memory they emphasize (e.g., order, sequence, or separation in time), the stimuli and responses they use (e.g., trial-unique or repeated sequences, and incidental or rewarded behavior), and the degree to which they control for potential confounding factors (e.g., primary and recency effects, or order memory deficits secondary to item memory impairments). To help integrate these findings, we developed a new paradigm testing incidental memory for trial-unique series of events, and concurrently assessed order and item memory in animals with damage to the hippocampus, prefrontal cortex, or perirhinal cortex. We found that this new approach led to robust order and item memory, and that hippocampal, prefrontal and perirhinal damage selectively impaired order memory. These findings suggest the hippocampus, prefrontal cortex and perirhinal cortex are part of a broad network of structures essential for incidentally learning the order of events in episodic memory

Audiovisual Learning in Dyslexic and Typical Adults: Modulating Influences of Location and Context Consistency

Learning to read involves efficient binding of visual to auditory information. Aberrant cross-modal binding skill has been observed in both children and adults with developmental dyslexia. Here, we examine the contribution of episodic memory to acquisition of novel cross-modal bindings in typical and dyslexic adult readers. Participants gradually learned arbitrary associations between unfamiliar Mandarin Chinese characters and English-like pseudowords over multiple exposures, simulating the early stages of letter-to-letter sound mapping. The novel cross-modal bindings were presented in consistent or varied locations (i.e., screen positions), and within consistent or varied contexts (i.e., co-occurring distractor items). Our goal was to examine the contribution, if any, of these episodic memory cues (i.e., the contextual and spatial properties of the stimuli) to binding acquisition, and investigate the extent to which readers with and without dyslexia would differ in their reliance on episodic memory during the learning process. Participants were tested on their ability to recognize and recall the bindings both during training and then in post-training tasks. We tracked participants’ eye movements remotely with their personal webcams to assess whether they would re-fixate relevant empty screen locations upon hearing an auditory cue—indicative of episodic memory retrieval—and the extent to which the so-called “looking-at-nothing behavior” would modulate recognition of the novel bindings. Readers with dyslexia both recognized and recalled significantly fewer bindings than typical readers, providing further evidence of their persistent difficulties with cross-modal binding. Looking-at-nothing behavior was generally associated with higher recognition error rates for both groups, a pattern that was particularly more evident in later blocks for bindings encoded in the inconsistent location condition. Our findings also show that whilst readers with and without dyslexia are capable of using stimulus consistencies in the input—both location and context—to assist in audiovisual learning, readers with dyslexia appear particularly reliant on consistent contextual information. Taken together, our results suggest that whilst readers with dyslexia fail to efficiently learn audiovisual binding as a function of stimulus frequency, they are able to use stimulus consistency—aided by episodic recall—to assist in the learning process

ART 2-A: An Adaptive Resonance Algorithm for Rapid Category Learning and Recognition

This article introduces ART 2-A, an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders of magnitude faster. Analysis and simulations show how the ART 2-A systems correspond to ART 2 dynamics at both the fast-learn limit and at intermediate learning rates. Intermediate learning rates permit fast commitment of category nodes but slow recoding, analogous to properties of word frequency effects, encoding specificity effects, and episodic memory. Better noise tolerance is hereby achieved without a loss of learning stability. The ART 2 and ART 2-A systems are contrasted with the leader algorithm. The speed of ART 2-A makes practical the use of ART 2 modules in large-scale neural computation.BP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530); Air Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088

Loss of memory for auditory-spatial associations following unilateral medial temporal-lobe damage

The goal of the present experiment was to determine the role of medial temporal-lobe structures in episodic memory of auditory-spatial associations. By using a two-alternative forced choice paradigm in which an association between eight different sounds and their spatial location must be recognized, learning abilities over 10 learning sessions were tested in 19 patients who had undergone a right or a left medial temporal-lobe resection for the relief of intractable seizures as well as in nine normal control participants. The data demonstrated that significant learning took place over the successive sessions for all the participants. In addition, the results showed that patients with left but not right medial temporal-lobe lesion were impaired in this learning task as compared to normal participants, suggesting the predominant implication of left medial temporal-lobe structures in auditory-spatial associative learning. The predominant role of left hemisphere structures in this memory task could be explained by a spatial categorical coding, which was enhanced by the use of eight loud-speakers. This result also suggests that the ability to store an episodic event associated with a rich spatial (or temporal) context depends on the left medial temporal-lobe structures. Thus, this finding provides an interesting parallel with data obtained in the visual modality by documenting for the first time the role of the left medial temporal-lobe in episodic learning of auditory-spatial associations