The role of dentate gyrus input-output computations in episodic memory
The role of dentate gyrus input-output computations in episodic memory
批准号:
10386138
负责人:
Antoine David Madar
金额:
$7.11万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-11-01 至 2024-10-31
关键词:
AddressAlzheimer&aposs DiseaseAnatomyAnimalsAnxietyAreaAxonBehavioralBrainBrain regionCalciumCellsCognition DisordersComputer ModelsConflict (Psychology)ConfusionData SetDendritesDiscriminationDiseaseDoctor of PhilosophyEnvironmentEpisodic memoryEventFamiliarityFreezingFrightGoalsHippocampus (Brain)ImageImpairmentIndividualInheritedInvestigationKnowledgeLearningMajor Depressive DisorderMeasuresMemoryMemory impairmentMental DepressionMethodsMusNeocortexNeurologicNeuronsOutputParahippocampal GyrusPathologicPatternPhasePhysiologyPlayPopulationPost-Traumatic Stress DisordersProcessReportingResearchResearch Project GrantsResearch ProposalsResolutionRetrievalRoleSchizophreniaSliceSourceSpecificityStimulusSymptomsTemporal Lobe EpilepsyTestingTrainingTransfectionTransgenic MiceViralWorkautism spectrum disordercognitive functionconditioned feardentate gyrusentorhinal cortexexperienceexperimental studyin vivoin vivo evaluationmathematical modelmemory consolidationmemory encodingmemory recallmemory retrievalnervous system disorderneuronal cell bodynovelpost-traumatic stresspreventrelating to nervous systemspatiotemporaltheoriestherapy designtwo-photonvirtual environment
中文摘要
项目总结
记忆的一个关键特征是记忆力辨别,即区分我们大脑中相似事件的能力
过去和防止类似情况之间的混淆。海马齿状回(DG)是大脑
已知的在这一认知功能中起中心作用的区域。三十年来,DG神经元网络一直是
假设支持助记识别,方法是在
内存编码。在这一观点中,DG的作用是消除类似的上游皮质表征的歧义
事件,将传入活动的相似模式在它们到达之前转换为不同的输出模式
将海马区下游区域存储为记忆。计算模型表明,解剖学
DG网络的生理学可以使DG执行模式分离,以及最近的实验研究
证明了隔离的DG能够执行某些形式的模式分离。然而,一个直接的
DG在体内进行这种计算的证据仍然难以捉摸。因此,核心信条是
记忆编码过程中DG的模式分离是记忆辨别的基础机制
从未被直接测试过。此外,DG在记忆提取或巩固过程中的作用也不清楚。
因此,这项研究项目的总体目标是:1)在体内测试DG是否进行模式分离或
其他计算和2)确定编码和检索期间的DG计算如何支持助记符
歧视。测量像DG这样的网络的计算需要了解其同步
输入和输出,这是在体内从未在单细胞分辨率下实现的。为了解决这一困难,我
将在行为老鼠身上使用多平面双光子钙成像,以便同时记录活动
大量DG输出神经元的动力学和以其为靶点的皮质轴突的活动
树枝状结构。为了研究记忆辨别的基础,我们需要比较神经元的表征
不同但相似的经历。为此,将放置经过训练以在虚拟环境中导航的老鼠
在几个参数变化不同的新环境中。实验1将包括记录DG输入
和输出,而小鼠探索一系列的环境,重复几天以确定如何
随着熟悉度的增加,计算也在不断发展。在实验2中,将增加一个显式助记成分:a
新的环境将与可怕的刺激和单个老鼠辨别这一点的能力相关联
来自另一个相似但中性的背景将被测量。这将允许确定哪些计算
是由DG在编码和回忆过程中执行的,以及它们与上下文歧视的关系:如果理论是
正确地说,编码过程中的模式分离程度应该与识别量相关。
最后,对这个丰富的数据集的分析将有助于约束更详细的情节记忆理论,以及
向理解记忆障碍迈出了重要的一步,这些障碍是许多认知障碍的症状。
英文摘要
PROJECT SUMMARY
A critical feature of memory is mnemonic discrimination, the ability to distinguish between similar events in our
past and prevent confusion between similar situations. The dentate gyrus (DG) of the hippocampus is a brain
region known to play a central part in this cognitive function. For thirty years, the DG neuronal network has been
hypothesized to support mnemonic discrimination by performing a computation called "pattern separation" during
memory encoding. In this view, the role of the DG is to disambiguate upstream cortical representations of similar
events, transforming similar patterns of incoming activity into dissimilar output patterns, before they reach
downstream hippocampal areas to be stored as memories. Computational modelling suggests that the anatomy
and physiology of the DG network could allow DG to perform pattern separation, and recent experimental studies
demonstrated that the isolated DG is able to perform some forms of pattern separation. However, a direct
demonstration that DG performs such computation in vivo remains elusive. Consequently, the central tenet that
pattern separation in DG during memory encoding is the mechanism underlying mnemonic discrimination has
never been directly tested. Moreover, the role of DG during memory retrieval or consolidation is also unclear.
The general goals of this research project are thus to 1) test in vivo whether DG performs pattern separation or
other computations and 2) determine how DG computations during encoding and retrieval support mnemonic
discrimination. Measuring the computations of a network like DG requires knowledge about its simultaneous
inputs and outputs, which has never been achieved in vivo at a single-cell resolution. To resolve this difficulty, I
will use multiplane two-photon calcium imaging in behaving mice in order to simultaneously record activity
dynamics of a large population of DG output neurons and the activity of the cortical axons that target their
dendrites. To investigate the basis of mnemonic discrimination, one needs to compare neuronal representations
of different but similar experiences. To this end, mice trained to navigate in a virtual environment will be placed
in several novel environments of parametrically varied similarity. Experiment-1 will consist of recording DG inputs
and outputs while mice explore a sequence of environments, repeated over several days to determine how
computations evolve as familiarity increases. In experiment-2, an explicit mnemonic component will be added: a
new environment will be associated to a fearful stimulus and the ability of individual mice to discriminate this
context from another similar but neutral one will be measured. This will allow to determine what computations
are performed by DG during encoding and recall and how they relate to context discrimination: if the theory is
correct, the degree of pattern separation during encoding should correlate to the amount of discrimination.
Finally, the analysis of this rich dataset will help constrain more detailed theories of episodic memory, an
instrumental step towards understanding memory impairments symptomatic of numerous cognitive disorders.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
The role of dentate gyrus input-output computations in episodic memory
-
批准号:10481838
-
项目类别:
-
资助金额:$7.41万
-
财政年份:2021
-
负责人:Antoine David Madar
-
依托单位: