CRCNS: Neural computations underlying sequence memory consolidation in sleep
CRCNS: Neural computations underlying sequence memory consolidation in sleep
批准号:
10646435
负责人:
MAKSIM V BAZHENOV
金额:
$35.24万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-08-10 至 2025-05-31
关键词:
AddressAnimalsBehaviorBehavioralBiophysical ProcessBrainChildhoodCollaborationsCommunicationComplexComputer ModelsCoupledDataData SetDevelopmentElectroencephalographyElementsEventExhibitsFoundationsGenerationsGoalsHippocampusHumanIndividualInstructionIntelligenceInterventionKnowledgeLearningMeasurementMediatingMedicineMemoryMental DepressionMental disordersMethodsModelingMotorMusNeocortexNeurobiologyNeuronsOutcomePatientsPerformancePhasePlayPost-Traumatic Stress DisordersPrincipal InvestigatorPropertyPsyche structureResearch PersonnelRetrievalRoleRunningSchizophreniaSensoryShapesSleepSlow-Wave SleepSynapsesTechniquesTestingTextureTimeTrainingTravelWeightWhole-Genome Shotgun SequencingWorkawakecognitive performancedata modelingdensityexecutive functionexperienceexperimental studyfascinateflexibilitygenetic manipulationimprovedin vivoinsightmemory consolidationneocorticalneuralneural networknoveloutcome predictionplace fieldspreservationprogramsreceptive fieldresponsesequence learningsimulationverbal
中文摘要
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英文摘要
The ability to store and retrieve sequentially related information is arguably the foundation of intelligent
behavior. It allows us to predict the outcomes of sensory situations, to achieve goals by generating
sequences of motor actions, to 'mentally' explore the possible outcomes of different navigational or motor
choices, and ultimately to communicate through complex verbal sequences generated by flexibly chaining
simpler elemental sequences learned in childhood. Sleep extracts invariant features from the learned
information, leading to the generation of explicit knowledge and insight. Despite remarkable progress,
including work by PI and co-PI of this project, many critical questions remain about role of sleep in memory
and learning. Here we propose to address these questions through the development of computational
models that are probed and validated through in vivo experiments in mice. We will explore the hippocampal
(HC) and neocortical (NC) mechanisms underlying how sequences are acquired and subsequently
consolidated through off-line replay during Slow Wave Sleep (SWS) in a manner that minimizes
interference between overlapping and/or reversed sequences and how NC may chain sequence fragments
together. We combine computer modelling (Bazhenov) of spiking neural networks that mimic awake and
SWS brain dynamics, including NC slow oscillations and HC Sharp Wave Ripples (SWR), with high density
neural ensemble recordings (McNaughton) in mice, in a controlled behavioral setting including sequence
learning and subsequent, chemogenetically induced SWS, which makes it possible to observe how learned
sequence representations in NC evolve spontaneously over prolonged periods of SWS. The PIs have been
collaborating on and discussing this topic for the past several years, resulting in specific hypotheses that
can be explored in real brains. The project outcome will provide a better understanding of how knowledge
is extracted from experience, what brain circuits are involved and how brain dynamics are shaped by the
development of a rich internal model of the world, including the ability to predict the outcomes of current
situations and one's own actions in that context.
RELEVANCE (See instructions):
The ability to store and retrieve sequentially related information is the foundation of intelligent behavior and
brain executive function. Deficits in this ability, resulting from disruption of brain circuits, are seen in
depression, schizophrenia and PTSD. Better understanding of the mechanisms and brain dynamics
underlying the acquisition, consolidation and retrieval of sequential information will lead to interventions to
improve cognitive performance, memory and learning in healthy subjects and patients with mental illness.
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Sleep-like unsupervised replay reduces catastrophic forgetting in artificial neural networks.
类似睡眠的无监督重放减少了人工神经网络中的灾难性遗忘。
DOI:
10.1038/s41467-022-34938-7
发表时间:
2022-12-15
期刊:
NATURE COMMUNICATIONS
影响因子:
16.6
作者:
[Tadros, Timothy, Krishnan, Giri P., Ramyaa, Ramyaa, Bazhenov, Maxim]
通讯作者:
Bazhenov, Maxim
DOI:
10.1371/journal.pcbi.1010628
发表时间:
2022-11
期刊:
PLoS computational biology
影响因子:
4.3
作者:
[]
通讯作者:
DOI:
10.1038/s42256-021-00430-y
发表时间:
2022-01
期刊:
NATURE MACHINE INTELLIGENCE
影响因子:
23.8
作者:
[Luczak, Artur, McNaughton, Bruce L., Kubo, Yoshimasa]
通讯作者:
Kubo, Yoshimasa
Role of Sleep in Formation of Relational Associative Memory
睡眠在关系联想记忆形成中的作用
DOI:
10.1523/jneurosci.2044-21.2022
发表时间:
2022
期刊:
The Journal of Neuroscience
影响因子:
--
作者:
[Tadros, Timothy, Bazhenov, Maxim]
通讯作者:
Bazhenov, Maxim
DOI:
10.1016/j.isci.2023.105970
发表时间:
2023-02-17
期刊:
ISCIENCE
影响因子:
5.8
作者:
[Esteves, Ingrid M., Chang, HaoRan, Neumann, Adam R., McNaughton, Bruce L.]
通讯作者:
McNaughton, Bruce L.
共 7 条
Role of coordinated multi-area reactivations during transitions between automatic and flexible behaviors.
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批准号:10721280
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项目类别:
-
资助金额:$296.51万
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财政年份:2023
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负责人:MAKSIM V BAZHENOV
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依托单位:
CRCNS: Switching antennal lobe dynamic regime via olfactory and mechanical signal
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批准号:10645219
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项目类别:
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资助金额:$35.55万
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财政年份:2022
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负责人:MAKSIM V BAZHENOV
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依托单位:
CRCNS: Switching antennal lobe dynamic regime via olfactory and mechanical signal
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批准号:10612145
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项目类别:
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资助金额:$39.01万
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财政年份:2022
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负责人:MAKSIM V BAZHENOV
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依托单位:
CRCNS: Neural computations underlying sequence memory consolidation in sleep
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批准号:10447795
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项目类别:
-
资助金额:$35.53万
-
财政年份:2020
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负责人:MAKSIM V BAZHENOV
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依托单位:
Integrated Biophysical and Neural Model of Electrical Stimulation Effects
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批准号:10472493
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项目类别:
-
资助金额:$88.75万
-
财政年份:2019
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负责人:MAKSIM V BAZHENOV
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依托单位:
Integrated Biophysical and Neural Model of Electrical Stimulation Effects
-
批准号:10670301
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项目类别:
-
资助金额:$88.9万
-
财政年份:2019
-
负责人:MAKSIM V BAZHENOV
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依托单位:
Integrated Biophysical and Neural Model of Electrical Stimulation Effects
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批准号:10217272
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项目类别:
-
资助金额:$91.02万
-
财政年份:2019
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负责人:MAKSIM V BAZHENOV
-
依托单位:
Label-free 4D optical detection of neural activity
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批准号:9056250
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项目类别:
-
资助金额:$23.13万
-
财政年份:2015
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负责人:MAKSIM V BAZHENOV
-
依托单位:
CRCNS: Multiple roles of inhibition in the olfactory system
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批准号:8436620
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项目类别:
-
资助金额:$28.45万
-
财政年份:2012
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负责人:MAKSIM V BAZHENOV
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依托单位:
CRCNS: Multiple roles of inhibition in the olfactory system
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批准号:8856198
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项目类别:
-
资助金额:$25.9万
-
财政年份:2012
-
负责人:MAKSIM V BAZHENOV
-
依托单位:
CRCNS: Multiple roles of inhibition in the olfactory system
-
批准号:9091558
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项目类别:
-
资助金额:$26.49万
-
财政年份:2012
-
负责人:MAKSIM V BAZHENOV
-
依托单位:
CRCNS: Multiple roles of inhibition in the olfactory system
-
批准号:8492062
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项目类别:
-
资助金额:$26.08万
-
财政年份:2012
-
负责人:MAKSIM V BAZHENOV
-
依托单位:
CRCNS: Multiple roles of inhibition in the olfactory system
-
批准号:8676774
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项目类别:
-
资助金额:$27.53万
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财政年份:2012
-
负责人:MAKSIM V BAZHENOV
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依托单位:
Cortical mechanisms and functional role of slow sleep oscillations
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批准号:8119074
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项目类别:
-
资助金额:$30.93万
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财政年份:2008
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负责人:MAKSIM V BAZHENOV
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依托单位:
Cortical mechanisms and functional role of slow sleep oscillations
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批准号:7353002
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项目类别:
-
资助金额:$32.45万
-
财政年份:2008
-
负责人:MAKSIM V BAZHENOV
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依托单位:
Cortical mechanisms and functional role of slow sleep oscillations
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批准号:7685294
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项目类别:
-
资助金额:$31.69万
-
财政年份:2008
-
负责人:MAKSIM V BAZHENOV
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依托单位:
Cortical mechanisms and functional role of slow sleep oscillations
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批准号:7936901
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项目类别:
-
资助金额:$31.31万
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财政年份:2008
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负责人:MAKSIM V BAZHENOV
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依托单位:
Mechanisms for Odor Coding in the Olfactory System
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批准号:6775025
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项目类别:
-
资助金额:$32.59万
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财政年份:2004
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负责人:MAKSIM V BAZHENOV
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依托单位:
Mechanisms for Odor Coding in the Olfactory System
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批准号:7174726
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项目类别:
-
资助金额:$30.9万
-
财政年份:2004
-
负责人:MAKSIM V BAZHENOV
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依托单位:
Mechanisms for Odor Coding in the Olfactory System
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批准号:7365115
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项目类别:
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资助金额:$7.48万
-
财政年份:2004
-
负责人:MAKSIM V BAZHENOV
-
依托单位:
海外基金