scholarly journals Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation

2021 ◽  
Vol 17 (12) ◽  
pp. e1009681
Author(s):  
Michiel W. H. Remme ◽  
Urs Bergmann ◽  
Denis Alevi ◽  
Susanne Schreiber ◽  
Henning Sprekeler ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
Computational Models ◽  
Hippocampal Formation ◽  
Spatial Scales ◽  
Single Cells ◽  
Brain Regions ◽  
Quantitative Agreement ◽  
Long Term Memory ◽  
Hebbian Plasticity ◽  
Mathematical Analyses

Systems memory consolidation involves the transfer of memories across brain regions and the transformation of memory content. For example, declarative memories that transiently depend on the hippocampal formation are transformed into long-term memory traces in neocortical networks, and procedural memories are transformed within cortico-striatal networks. These consolidation processes are thought to rely on replay and repetition of recently acquired memories, but the cellular and network mechanisms that mediate the changes of memories are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways—two ubiquitous features of neural circuits in the brain. We explore this hypothesis in the context of hippocampus-dependent memories. Using computational models and mathematical analyses, we illustrate how memories are transferred across circuits and discuss why their representations could change. The analyses suggest that Hebbian plasticity mediates consolidation by transferring a linear approximation of a previously acquired memory into a parallel pathway. Our modelling results are further in quantitative agreement with lesion studies in rodents. Moreover, a hierarchical iteration of the mechanism yields power-law forgetting—as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.

scholarly journals Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation

2020 ◽  
Author(s):  
Michiel Remme ◽  
Urs Bergmann ◽  
Denis Alevi ◽  
Susanne Schreiber ◽  
Henning Sprekeler ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
Hippocampal Formation ◽  
Spatial Scales ◽  
Single Cells ◽  
Quantitative Agreement ◽  
Long Term Memory ◽  
Consolidation Process ◽  
Hebbian Plasticity ◽  
Psychophysical Studies

AbstractSystems memory consolidation involves a transfer of declarative memories that initially depend on the hippocampal formation into long-term memory traces in neocortical networks. This consolidation process is thought to rely on replay of recently acquired memories, but the cellular and network mechanisms that mediate the memory transfer are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways — two ubiquitous features of neural circuits in the brain. We explore this hypothesis in a computational model to illustrate how memories are transferred across circuits and why their representations could change. These modelling results are in quantitative agreement with lesion studies in rodents. A hierarchical iteration of the mechanism yields power-law forgetting — as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.

scholarly journals An Indexing Theory for Working Memory based on Fast Hebbian Plasticity

2018 ◽  
Author(s):  
Florian Fiebig ◽  
Pawel Herman ◽  
Anders Lansner
Keyword(s):  
Working Memory ◽  
Computational Models ◽  
Human Memory ◽  
Long Term Memory ◽  
Memory Representation ◽  
Hebbian Plasticity ◽  
Short And Long Term ◽  
Spiking Neural Network Model

AbstractWorking memory (WM) is a key component of human memory and cognition. Computational models have been used to study the underlying neural mechanisms, but neglected the important role of short- and long-term memory interactions (STM, LTM) for WM. Here, we investigate these using a novel multi-area spiking neural network model of prefrontal cortex (PFC) and two parieto-temporal cortical areas based on macaque data. We propose a WM indexing theory that explains how PFC could associate, maintain and update multi-modal LTM representations. Our simulations demonstrate how simultaneous, brief multi-modal memory cues could build a temporary joint memory representation as an “index” in PFC by means of fast Hebbian synaptic plasticity. This index can then reactivate spontaneously and thereby reactivate the associated LTM representations. Cueing one LTM item rapidly pattern-completes the associated un-cued item via PFC. The PFC-STM network updates flexibly as new stimuli arrive thereby gradually over-writing older representations.

scholarly journals Memory destabilization during reconsolidation: a consequence of homeostatic plasticity?

2021 ◽  
Vol 28 (10) ◽  
pp. 371-389
Author(s):  
Felippe E. Amorim ◽  
Renata L. Chapot ◽  
Thiago C. Moulin ◽  
Jonathan L.C. Lee ◽  
Olavo B. Amaral
Keyword(s):  
Protein Synthesis ◽  
Boundary Conditions ◽  
Memory Retrieval ◽  
Computational Models ◽  
Molecular Mechanisms ◽  
Brain Regions ◽  
Homeostatic Plasticity ◽  
Protein Synthesis Inhibition ◽  
Hebbian Plasticity ◽  
Neuronal Mechanisms

Remembering is not a static process: When retrieved, a memory can be destabilized and become prone to modifications. This phenomenon has been demonstrated in a number of brain regions, but the neuronal mechanisms that rule memory destabilization and its boundary conditions remain elusive. Using two distinct computational models that combine Hebbian plasticity and synaptic downscaling, we show that homeostatic plasticity can function as a destabilization mechanism, accounting for behavioral results of protein synthesis inhibition upon reactivation with different re-exposure times. Furthermore, by performing systematic reviews, we identify a series of overlapping molecular mechanisms between memory destabilization and synaptic downscaling, although direct experimental links between both phenomena remain scarce. In light of these results, we propose a theoretical framework where memory destabilization can emerge as an epiphenomenon of homeostatic adaptations prompted by memory retrieval.

scholarly journals Offline ventral subiculum-ventral striatum serial communication is required for spatial memory consolidation

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
G. Torromino ◽  
L. Autore ◽  
V. Khalil ◽  
V. Mastrorilli ◽  
M. Griguoli ◽  
...  
Keyword(s):  
Spatial Memory ◽  
Memory Consolidation ◽  
Ventral Striatum ◽  
Spatial Information ◽  
Hippocampal Formation ◽  
Critical Role ◽  
Brain Regions ◽  
Complex Information ◽  
Line Cross ◽  
Insight Into

AbstractThe hippocampal formation is considered essential for spatial navigation. In particular, subicular projections have been suggested to carry spatial information from the hippocampus to the ventral striatum. However, possible cross-structural communication between these two brain regions in memory formation has thus far been unknown. By selectively silencing the subiculum–ventral striatum pathway we found that its activity after learning is crucial for spatial memory consolidation and learning-induced plasticity. These results provide new insight into the neural circuits underlying memory consolidation and establish a critical role for off-line cross-regional communication between hippocampus and ventral striatum to promote the storage of complex information.

scholarly journals Memory destabilization during reconsolidation – A consequence of homeostatic plasticity?

2021 ◽  
Author(s):  
F.E. Amorim ◽  
R.L. Chapot ◽  
T.C. Moulin ◽  
J.L.C. Lee ◽  
O.B. Amaral
Keyword(s):  
Protein Synthesis ◽  
Boundary Conditions ◽  
Memory Retrieval ◽  
Computational Models ◽  
Molecular Mechanisms ◽  
Brain Regions ◽  
Homeostatic Plasticity ◽  
Protein Synthesis Inhibition ◽  
Hebbian Plasticity ◽  
Neuronal Mechanisms

ABSTRACTRemembering is not a static process: when retrieved, a memory can be destabilized and become prone to modifications. This phenomenon has been demonstrated in a number of brain regions, but the neuronal mechanisms that rule memory destabilization and its boundary conditions remain elusive. Using two distinct computational models that combine Hebbian plasticity and synaptic downscaling, we show that homeostatic plasticity can function as a destabilization mechanism, accounting for behavioral results of protein synthesis inhibition upon reactivation with different reexposure times. Furthermore, by performing systematic reviews, we identify a series of overlapping molecular mechanisms between memory destabilization and synaptic downscaling, although direct experimental links between both phenomena remain scarce. In light of these results, we propose a theoretical framework where memory destabilization can emerge as an epiphenomenon of homeostatic adaptations prompted by memory retrieval.

Notch signalling becomes transiently attenuated during long-term memory consolidation in adult Wistar rats

2007 ◽  
Vol 88 (3) ◽  
pp. 342-351 ◽  
Author(s):  
Lisa Conboy ◽  
Claire M. Seymour ◽  
Marco P. Monopoli ◽  
Niamh C. O’Sullivan ◽  
Keith J. Murphy ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
Wistar Rats ◽  
Notch Signalling ◽  
Long Term Memory ◽  
Term Memory

scholarly journals From cognitive to neural models of working memory

2007 ◽  
Vol 362 (1481) ◽  
pp. 761-772 ◽  
Author(s):  
Mark D'Esposito
Keyword(s):  
Working Memory ◽  
Functional Neuroimaging ◽  
Empirical Studies ◽  
Brain Regions ◽  
Cognitive Models ◽  
Neural Mechanisms ◽  
Long Term Memory ◽  
Cognitive Mechanisms ◽  
Internal Representations ◽  
Active Maintenance

Working memory refers to the temporary retention of information that was just experienced or just retrieved from long-term memory but no longer exists in the external environment. These internal representations are short-lived, but can be stored for longer periods of time through active maintenance or rehearsal strategies, and can be subjected to various operations that manipulate the information in such a way that makes it useful for goal-directed behaviour. Empirical studies of working memory using neuroscientific techniques, such as neuronal recordings in monkeys or functional neuroimaging in humans, have advanced our knowledge of the underlying neural mechanisms of working memory. This rich dataset can be reconciled with behavioural findings derived from investigating the cognitive mechanisms underlying working memory. In this paper, I review the progress that has been made towards this effort by illustrating how investigations of the neural mechanisms underlying working memory can be influenced by cognitive models and, in turn, how cognitive models can be shaped and modified by neuroscientific data. One conclusion that arises from this research is that working memory can be viewed as neither a unitary nor a dedicated system. A network of brain regions, including the prefrontal cortex (PFC), is critical for the active maintenance of internal representations that are necessary for goal-directed behaviour. Thus, working memory is not localized to a single brain region but probably is an emergent property of the functional interactions between the PFC and the rest of the brain.

scholarly journals Methods for Assessment of Memory Reactivation

2018 ◽  
Vol 30 (8) ◽  
pp. 2175-2209 ◽  
Author(s):  
Shizhao Liu ◽  
Andres D. Grosmark ◽  
Zhe Chen
Keyword(s):  
Statistical Methods ◽  
Memory Consolidation ◽  
Slow Wave Sleep ◽  
Brain Regions ◽  
Weighted Distance ◽  
Memory Reactivation ◽  
Statistical Dependency ◽  
Stored Information ◽  
Robust Statistical Methods ◽  
Population Decoding

It has been suggested that reactivation of previously acquired experiences or stored information in declarative memories in the hippocampus and neocortex contributes to memory consolidation and learning. Understanding memory consolidation depends crucially on the development of robust statistical methods for assessing memory reactivation. To date, several statistical methods have seen established for assessing memory reactivation based on bursts of ensemble neural spike activity during offline states. Using population-decoding methods, we propose a new statistical metric, the weighted distance correlation, to assess hippocampal memory reactivation (i.e., spatial memory replay) during quiet wakefulness and slow-wave sleep. The new metric can be combined with an unsupervised population decoding analysis, which is invariant to latent state labeling and allows us to detect statistical dependency beyond linearity in memory traces. We validate the new metric using two rat hippocampal recordings in spatial navigation tasks. Our proposed analysis framework may have a broader impact on assessing memory reactivations in other brain regions under different behavioral tasks.

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