Can sleep protect memories from catastrophic forgetting?

González, Oscar C.; Sokolov, Yury; Bazhenov, Maxim

doi:10.1101/569038

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…Parts of a hierarchical network could also engage in mental simulations of future actions and outcomes [94] or other metacognitive processes underlying flexible intelligent behavior. Another fascinating idea is that ongoing, spontaneous dynamics during slow-wave sleep may play a protective role against catastrophic forgetting (overwriting old memories with new ones) and enable brain networks to undergo continual learning [95], or to enhance learning from limited experience [96], both of which remain a challenge for artificial systems.…”

Section: Computational Functions Of Local and Global Dynamicsmentioning

confidence: 99%

New perspectives on dimensionality and variability from large-scale cortical dynamics

Engel

Steinmetz

2019

Current Opinion in Neurobiology

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The neocortex is a multi-scale network, with intricate local circuitry interwoven into a global mesh of long-range connections. Neural activity propagates within this network on a wide range of temporal and spatial scales. At the micro scale, neurophysiological recordings reveal coordinated dynamics in local neural populations, which support behaviorally relevant computations. At the macro scale, neuroimaging modalities measure global activity fluctuations organized into spatiotemporal patterns across the entire brain. Here we review recent advances linking the local and global scales of cortical dynamics and their relationship to behavior. We argue that diverse experimental observations on the dimensionality and variability of neural activity can be reconciled by considering how activity propagates in space and time on multiple spatial scales.

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Section: Computational Functions Of Local and Global Dynamicsmentioning

confidence: 99%

New perspectives on dimensionality and variability from large-scale cortical dynamics

Engel

Steinmetz

2019

Current Opinion in Neurobiology

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“…We recently showed, using computer models, that sequences of cortical neurons trained in awake are replayed spontaneously during NREM sleep; this enhances the synaptic connections associated with the trained memory resulting in memory improvement (Wei et al, 2018). Furthermore, sleep replay during SWS is able to protect old memories from catastrophic forgetting associated with new learning (González et al, 2019;Krishnan et al, 2019). In this present study, we explored how external stimulation augments an internal and naturally occurring mechanism of memory reactivation, resulting in an enhanced memory consolidation process.…”

Section: The Mechanisms Of Strengthening Memories By Stimulation During Nrem Sleepmentioning

confidence: 99%

Stimulation Augments Spike Sequence Replay and Memory Consolidation during Slow-Wave Sleep

Wei

Marshall²,

Martinetz

et al. 2019

J. Neurosci.

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Newly acquired memory traces are spontaneously reactivated during slow-wave sleep (SWS), leading to the consolidation of recent memories. Empirical studies found that sensory stimulation during SWS can selectively enhance memory consolidation with the effect depending on the phase of stimulation. In this new study, we aimed to understand the mechanisms behind the role of sensory stimulation on memory consolidation using computational models implementing effects of neuromodulators to simulate transitions between awake and SWS sleep, and synaptic plasticity to allow the change of synaptic connections due to the training in awake or replay during sleep. We found that when closed-loop stimulation was applied during the Down states of sleep slow oscillation, particularly right before the transition from Down to Up state, it significantly affected the spatiotemporal pattern of the slow waves and maximized memory replay. In contrast, when the stimulation was presented during the Up states, it did not have a significant impact on the slow waves or memory performance after sleep. For multiple memories trained in awake, presenting stimulation cues associated with specific memory trace could selectively augment replay and enhance consolidation of that memory and interfere with consolidation of the others (particularly weak) memories. Our study proposes a synaptic-level mechanism of how memory consolidation is affected by sensory stimulation during sleep.

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Sleep prevents catastrophic forgetting in spiking neural networks by forming joint synaptic weight representations

Golden

Delanois

Šanda

et al. 2019

Preprint

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Artificial neural networks overwrite previously learned tasks when trained sequentially, a phenomenon known as catastrophic forgetting. In contrast, the brain learns continuously, and typically learns best when new learning is interleaved with periods of sleep for memory consolidation. In this study, we used spiking network to study mechanisms behind catastrophic forgetting and the role of sleep in preventing it. The network could be trained to learn a complex foraging task but exhibited catastrophic forgetting when trained sequentially on multiple tasks. New task training moved the synaptic weight configuration away from the manifold representing old tasks leading to forgetting. Interleaving new task training with periods of off-line reactivation, mimicking biological sleep, mitigated catastrophic forgetting by pushing the synaptic weight configuration towards the intersection of the solution manifolds representing multiple tasks. The study reveals a possible strategy of synaptic weights dynamics the brain applies during sleep to prevent forgetting and optimize learning.

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Can sleep protect memories from catastrophic forgetting?

Cited by 3 publications

References 49 publications

New perspectives on dimensionality and variability from large-scale cortical dynamics

New perspectives on dimensionality and variability from large-scale cortical dynamics

Stimulation Augments Spike Sequence Replay and Memory Consolidation during Slow-Wave Sleep

Sleep prevents catastrophic forgetting in spiking neural networks by forming joint synaptic weight representations

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