The laminar organization of 'index' versus 'attribute' coding in neocortex

新皮质中“索引”与“属性”编码的层状组织

基本信息

  • 批准号:
    10205913
  • 负责人:
  • 金额:
    $ 198.83万
  • 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
  • 起止时间:
    2021-04-15 至 2024-03-31
  • 项目状态:
    已结题

项目摘要

We propose a circuit-level principal underlying how brains acquire 'episodic' memories and reprocess them into compact, efficient 'schemas': The attributes or 'contents' of experience are represented primarily in the deeper layers of neocortex (NC), whereas the superficial layers are dedicated to encoding the contexts in which the attributes occur. Synaptic associations between superficial context codes and deep attribute codes permit contexts to evoke appropriate attribute output hence enabling memory recall and predictive behavior. The hippocampus (HC) is essential for acquisition of memories and for their reprocessing into efficient, schematic representations of the world. NC exhibits dense local but sparse long-range connectivity, which severely limits its ability to make rapid, long-range associations. HC likely solves this dilemma by merging the totality of the brain's current internal state (i.e., sensory input and internal variables such as hunger, fear, current goals) into a unique, 'index' code that is projected to NC, and associated with its current, distributed, attribute representation. Retrieval of an index code evokes the corresponding attributes. Such HC-orchestrated retrieval may enable the gradual rewiring of NC circuitry in a manner that captures the overall statistics of experience, much the same way as deep, artificial, neural networks learn incrementally by small connection weight adjustments directed by the overall statistics of the input. Our hypothesis on the laminar division of labor in this process is based on the facts that HC output is directed primarily to upper layers of NC, which implements a 'spatial' coding scheme that is lost after HC lesions; and that the deeper layers of NC frequently exhibit more robust responsiveness to and discrimination of sensory inputs than the superficial ones. We propose to record cellular level, neural ensemble activity simultaneously from deep and superficial layers in primary and association cortex, using high-density, electrophysiological recording. First, we attempt to establish the 'attribute vs index' principal by showing that deep cells shift their firing locations with shifts in the relevant sensory attributes, whereas superficial cells do not. Next we test the hypothesis that, as NC accumulates large amounts of diverse experience, attribute representations in deeper layers becomes sparser and more categorically organized, whereas superficial layer coding is relatively unchanged. To accomplish this, we employ a recent chemogenetic advance that enables us to acquire large amounts of resting-state cellular data, in which we expect the predicted changes will be most easily observed. We also explore the statistics of excitatory-inhibitory cell functional connectivity that may underlie such coding statistics changes. The expected advances in understanding cortical memory and schema encoding circuits will ultimately improve clinical assessment of, and intervention in memory and cognitive disorders.
我们提出了大脑如何获得“情景”记忆和再加工的电路级原理

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Learning in deep neural networks and brains with similarity-weighted interleaved learning.
Cortical reactivation of spatial and non-spatial features coordinates with hippocampus to form a memory dialogue.
  • DOI:
    10.1038/s41467-023-43254-7
  • 发表时间:
    2023-11-27
  • 期刊:
  • 影响因子:
    16.6
  • 作者:
    Chang, HaoRan;Esteves, Ingrid M;Neumann, Adam R;Mohajerani, Majid H;McNaughton, Bruce L
  • 通讯作者:
    McNaughton, Bruce L
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BRUCE L MCNAUGHTON其他文献

BRUCE L MCNAUGHTON的其他文献

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{{ truncateString('BRUCE L MCNAUGHTON', 18)}}的其他基金

Bottom-Up, Top-Down, and Local Interactions in the Generation and Consolidation of Cortical Representations of Sequential Experience
顺序经验的皮层表征的生成和巩固中的自下而上、自上而下和局部交互
  • 批准号:
    10658227
  • 财政年份:
    2023
  • 资助金额:
    $ 198.83万
  • 项目类别:
Training Program in Learning and Memory
学习和记忆培训计划
  • 批准号:
    10165831
  • 财政年份:
    2019
  • 资助金额:
    $ 198.83万
  • 项目类别:
Training Program in Learning and Memory
学习和记忆培训计划
  • 批准号:
    9890008
  • 财政年份:
    2019
  • 资助金额:
    $ 198.83万
  • 项目类别:
Training Program in Learning and Memory
学习和记忆培训计划
  • 批准号:
    10634564
  • 财政年份:
    2019
  • 资助金额:
    $ 198.83万
  • 项目类别:
Training Program in Learning and Memory
学习和记忆培训计划
  • 批准号:
    10406177
  • 财政年份:
    2019
  • 资助金额:
    $ 198.83万
  • 项目类别:
Hebb Marr Networks the Hippocampus and Spatial Memory
赫布·马尔将海马体和空间记忆联系起来
  • 批准号:
    8054031
  • 财政年份:
    2010
  • 资助金额:
    $ 198.83万
  • 项目类别:
CELL ASSEMBLIES, PHASE SEQUENCES AND MEMORY DYNAMICS
单元组件、相序和内存动态
  • 批准号:
    6530800
  • 财政年份:
    1998
  • 资助金额:
    $ 198.83万
  • 项目类别:
CELL ASSEMBLIES, PHASE SEQUENCES AND MEMORY DYNAMICS
单元组件、相序和内存动态
  • 批准号:
    6165123
  • 财政年份:
    1998
  • 资助金额:
    $ 198.83万
  • 项目类别:
CELL ASSEMBLIES, PHASE SEQUENCES AND MEMORY DYNAMICS
单元组件、相序和内存动态
  • 批准号:
    2591675
  • 财政年份:
    1998
  • 资助金额:
    $ 198.83万
  • 项目类别:
CELL ASSEMBLIES, PHASE SEQUENCES AND MEMORY DYNAMICS
单元组件、相序和内存动态
  • 批准号:
    6363618
  • 财政年份:
    1998
  • 资助金额:
    $ 198.83万
  • 项目类别:

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