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A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory.

Abstract Evidence suggests that hippocampal adult neurogenesis is critical for discriminating considerably interfering memories. During adult neurogenesis, synaptic competition modifies the weights of synaptic connections nonlocally across neurons, thus providing a different form of unsupervised learning from Hebb’s local plasticity rule. However, how synaptic competition achieves separating similar memories largely remains unknown. Here, we aim to link synaptic competition with such pattern separation. In synaptic competition, adult-born neurons are integrated into the existing neuronal pool by competing with mature neurons for synaptic connections from the entorhinal cortex. We show that synaptic competition and neuronal maturation play distinct roles in separating interfering memory patterns. Furthermore, we demonstrate that a feedforward neural network trained by a competition-based learning rule can outperform a multilayer perceptron trained by the backpropagation algorithm when only a small number of samples are available. Our results unveil the functional implications and potential applications of synaptic competition in neural computation.

Physical exercise has beneficial effects on neurocognitive function, including hippocampus-dependent episodic memory. Exercise intensity level can be assessed according to whether it induces a stress response; the most effective exercise for improving hippocampal function remains unclear. Our prior work using a special treadmill running model in animals has shown that stress-free mild exercise increases hippocampal neuronal activity and promotes adult neurogenesis in the dentate gyrus (DG) of the hippocampus, improving spatial memory performance. However, the rapid modification, from mild exercise, on hippocampal memory function and the exact mechanisms for these changes, in particular the impact on pattern separation acting in the DG and CA3 regions, are yet to be elucidated. To this end, we adopted an acute-exercise design in humans, coupled with high-resolution functional MRI techniques, capable of resolving hippocampal subfields. A single 10-min bout of very light-intensity exercise ( 30 % V ˙ O 2 peak ) results in rapid enhancement in pattern separation and an increase in functional connectivity between hippocampal DG/CA3 and cortical regions (i.e., parahippocampal, angular, and fusiform gyri). Importantly, the magnitude of the enhanced functional connectivity predicted the extent of memory improvement at an individual subject level. These results suggest that brief, very light exercise rapidly enhances hippocampal memory function, possibly by increasing DG/CA3–neocortical functional connectivity.

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost‐effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech‐adoption increases, and external events (i.e., COVID‐19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in‐clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study‐provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

Adult hippocampal neurogenesis is the process by which new functional neurons are added to the adult dentate gyrus of the hippocampus. Animal studies have shown that the degree of adult hippocampal neurogenesis is regulated by local environmental cues as well as neural network activities. Furthermore, accumulating evidence has suggested that adult hippocampal neurogenesis plays prominent roles in hippocampus-dependent brain functions. In this review, we summarize the mechanisms underlying the regulation of adult hippocampal neurogenesis at various developmental stages and propose how adult-born neurons contribute to structural and functional hippocampal plasticity.

Pattern separation, or the process by which highly similar stimuli or experiences in memory are represented by non-overlapping neural ensembles, has typically been ascribed to processes supported by the hippocampus. Converging evidence from a wide range of studies, however, suggests that pattern separation is a multistage process supported by a network of brain regions. Based on this evidence, considered together with related findings from the interference resolution literature, we propose the ‘cortico-hippocampal pattern separation’ (CHiPS) framework, which asserts that brain regions involved in cognitive control play a significant role in pattern separation. Particularly, these regions may contribute to pattern separation by (1) resolving interference in sensory regions that project to the hippocampus, thus regulating its cortical input, or (2) directly modulating hippocampal processes in accordance with task demands. Considering recent interest in how hippocampal operations are modulated by goal states likely represented and regulated by extra-hippocampal regions, we argue that pattern separation is similarly supported by neocortical–hippocampal interactions.

IntroductionTendency to experience inaccurate beliefs alongside perceptual anomalies constitutes positive schizotypal traits in the general population and shows continuity with the positive symptoms of schizophrenia. It has been hypothesized that the positive symptomatology of schizophrenia, and by extension, positive schizotypy, are associated with specific alterations in memory functions. Imbalance between memory generalization and episodic memory specificity has been proposed on several counts; however, the direction of the imbalance is currently unclear.ObjectivesWe aimed to contrast two competing hypotheses regarding the association between positive schizotypy, and memory alterations in a general population sample (N=71) enriched for positive schizotypy from a larger pool of individuals (N=614).MethodsPositive schizotypy was measured with the short-version of the O-LIFE questionnaire, and memory specificity and generalization was captured by the well-established Mnemonic Similarity Task.ResultsDistortions in the behavioural memory performance indices were found to correlate with positive schizotypy: individuals prone to unusual experiences demonstrated increased discrimination and reduced generalization (explaining 10% and 17% of variance, respectively). Associations were robust when controlled for the disorganized, negative and impulsive-asocial dimensions of schizotypy and associated psychopathology.ConclusionsOur findings show that people who are prone to irrational beliefs and unusual experiences also show measurable alterations in memory and likely have difficulty grasping the global picture and rather be overpowered by fragments of information.DisclosureNo significant relationships.

Adult hippocampal neurogenesis is a unique and exceptional process in the mammalian brain that in a lifelong and activity-dependent way generates new excitatory principal neurons. A comprehensive view on their function in greater contexts has now emerged, revealing to which extent the hippocampus (and hence brain and mind) depend on these neurons. Due to a postmitotic period of heightened synaptic plasticity they bias incoming excitation to the dentate gyrus to non-overlapping subnetworks, resulting in pattern separation and the avoidance of catastrophic interference. Temporally, this promotes the flexible integration of novel information into familiar contexts and contributes to episodic memory, which in humans would be critical for autobiographic memory. Together these local effects represent a unique strategy to solve the plasticity-stability dilemma that all learning neuronal networks are facing. Neurogenesis-dependent plasticity also improves memory consolidation. This relates to the surprising involvement of adult neurogenesis in forgetting, which is also hypothesized to be critically relevant for negative plasticity, for example in post-traumatic stress disorder. In addition, adult-born neurons also directly mediate stress-resilience and take part in affective behaviors. Finally, the activity- and experience-dependent plasticity that is contributed by adult neurogenesis is associated with an individualization of the hippocampal circuitry. While a solid and largely consensual understanding of how new neurons contribute to hippocampal function has been reached, an overarching unifying theory that embeds neurogenesis-dependent functionality and effects on connectomics is still missing. More sophisticated multi-electrode electrophysiology, advanced ethologically relevant behavioral tests, and next-generation computational modeling will let us take the next steps.

Adaptive learning systems need to meet two complementary and partially conflicting goals: detecting regularities in the world versus remembering specific events. The hippocampus (HC) keeps a fine balance between computations that extract commonalities of incoming information (i.e., pattern completion) and computations that enable encoding of highly similar events into unique representations (i.e., pattern separation). Histological evidence from young rhesus monkeys suggests that HC development is characterized by the differential development of intrahippocampal subfields and associated networks. However, due to challenges in the in vivo investigation of such developmental organization, the ontogenetic timing of HC subfield maturation remains controversial. Delineating its course is important, as it directly influences the fine balance between pattern separation and pattern completion operations and, thus, developmental changes in learning and memory. Here, we relate in vivo, high-resolution structural magnetic resonance imaging data of HC subfields to behavioral memory performance in children aged 6–14 y and in young adults. We identify a multivariate profile of age-related differences in intrahippocampal structures and show that HC maturity as captured by this pattern is associated with age differences in the differential encoding of unique memory representations.

The dentate gyrus (DG) is crucial for distinguishing similar events through pattern separation. It has been proposed that sparse firing granule cells (GCs) perform these computational functions in the DG. GCs are the principal neurons of the DG, and it has been reported that they form a heterogeneous population, including semilunar granule cells (SGCs) and adult-born granule cells (adult-born GCs), both of which have different physiological properties from the GCs. Given their undeniable interactions with GCs, it is important to investigate how the different subpopulations of GCs contribute to pattern separation. By constructing a biologically relevant computational model of the DG, we found that SGCs and adult-born GCs can dynamically regulate pattern separation. Specifically, SGCs and 4–8-week-old adult-born GCs contribute to pattern separation. However, 0–4-week-old adult-born GCs initially increase pattern separation efficiency, then decrease it. Furthermore, SGCs and 4–8-week-old adult-born GCs enhance the sparse firing of GCs, thereby improving pattern separation efficiency. Regarding 0–4-week-old adult-born GCs, the net effect of mossy cells (MCs) on GCs shifts from inhibition to excitation as adult-born GCs mature, resulting in a decrease in pattern separation efficiency.