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

• 批准号: 10205913
• 负责人: BRUCE L MCNAUGHTON
• 金额: $ 198.83万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 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
• 来源: https://reporter.nih.gov/project-details/10205913
• 关键词: 3-Dimensional; Adaptive Behaviors; Aging; Behavior; Body Weight Changes; Brain; Categories; Cells; Characteristics; Clinical assessments; Code; Cognition; Cognition Disorders; Cognitive deficits; Complex; Coupling; Data; Disease; Electrophysiology (science); Episodic memory; Event; Exhibits; Fright; Goals; Hippocampal Formation; Hippocampus (Brain); Hunger; Image; Intelligence; Intervention; Knowledge; Lead; Lesion; Light; Link; Location; Memory; Memory Disorders; Memory impairment; Motor; Mus; Neocortex; Neurons; Output; Pattern; Process; Property; Recurrence; Rest; Retrieval; Scheme; Schizophrenia; Sensory; Silicon; Sleep; Structure; Supporting Cell; Synapses; Testing; Trauma; Weight; Work; artificial neural network; association cortex; autism spectrum disorder; base; density; detector; experience; experimental study; improved; indexing; information processing; learning network; memory acquisition; memory recall; neural circuit; relating to nervous system; sensory discrimination; sensory input; statistics; theories; trend; two-photon

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

Learning in deep neural networks and brains with similarity-weighted interleaved learning.

• DOI: 10.1073/pnas.2115229119
• 发表时间: 2022-07-05
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Saxena, Rajat;Shobe, Justin L.;McNaughton, Bruce L.
• 通讯作者: McNaughton, Bruce L.

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: NATURE COMMUNICATIONS
• 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