Cortical mechanisms of learned spatial-temporal sequence coding

学习时空序列编码的皮质机制

• 批准号: 8978909
• 负责人: Jeffrey Peter Gavornik
• 金额: $ 24.81万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8978909
• 关键词: Accounting; Animal Model; Animals; Architecture; Area; Behavior; Behavioral; Brain; Brain region; Calcium; Characteristics; Chemosensitization; Code; Cognitive; Cognitive deficits; Computational Technique; Computer Simulation; Data; Electrophysiology (science); Elements; Goals; Image; Individual; Learning; Mediating; Mental disorders; Mentors; Microscopy; Molecular; Mus; Nature; Neocortex; Neuronal Plasticity; Neurons; Output; Patient Self-Report; Pattern; Perception; Pharmacology; Phase; Play; Population; Process; Research; Research Proposals; Retina; Role; Sensory; Series; Specificity; Stimulus; Stream; Synapses; Synaptic plasticity; Techniques; Testing; Training; Transgenic Organisms; Visual; Visual Cortex; area striata; base; design; information processing; neuromechanism; optogenetics; relating to nervous system; research study; response; sequence learning; tool development; two-photon

The brain continually processes streams of information that are coded at the neural level by temporal sequences of spiking activity. From this activity, the brain is able to extract behaviorally relevant data and form internal representations of the external world used, in turn, to create behavioral output. The brain also uses its internal state to make predictions about how external stimuli will change; these predictions play a critical role in executive behavioral planning. It is not known how this processing is accomplished in the brain. Establishing the relationship between activity sequences, plasticity and the neural coding of these internal representations will greatly inform our understanding of normal brain function and is necessary to understand the cognitive deficits associated with mental disorders. Since animals cannot self-report their cognitive state it is very difficult to explore the high-level neural mechanisms of sequence learning using animal models. Generally speaking, the neocortex is organized according to a single common plan that imparts a characteristic local architecture and there is evidence suggesting that brain regions acquire functional differentiation as a result of their specific inputs. In this framework, visual cortex is “visual” primarily because it connects to the retina and all regions of cortex are capable of solving similar information processing problems. This suggests that the same basic mechanisms used to learn sequences in “higher” cortical regions should exist within “lower” regions as well and leads to the hypothesis that primary sensory areas should contain the mechanisms necessary to locally encode sequence representations. A series of experiments testing this hypothesis demonstrate that it is possible to entrain visual sequences in primary visual cortex with both temporal and spatial precision. This research aims to fully characterize and understand the mechanistic nature of this learning and its consequences for cortical processing. The proposed experiments are designed to test the hypothesis that visual sequence learning is encoded by NMDAR mediated synaptic plasticity between populations of neurons spread across the cortical layers locally within V1 using a combination of electrophysiological observation, 2- photon microscopy, pharmacological and optogenetic manipulation, and computational modeling.

大脑不断地处理信息流，这些信息流在神经水平上通过时间序列编码。 尖峰活动的序列。从这种活动中，大脑能够提取行为相关的数据和形式 外部世界的内部表征，反过来，创造行为输出。大脑也会利用它的 预测外部刺激将如何变化;这些预测在 执行行为规划目前尚不清楚这种处理在大脑中是如何完成的。建立 活动序列、可塑性和这些内部表征的神经编码之间的关系 将极大地告知我们对正常大脑功能的理解，并且对于理解认知功能是必要的。 与精神障碍有关的缺陷。 由于动物不能自我报告它们的认知状态，因此很难探索高水平的神经系统。 使用动物模型的序列学习机制。一般来说，大脑皮层是有组织的 根据一个单一的共同计划，赋予当地建筑特色，并有证据表明， 这表明大脑区域由于其特定的输入而获得功能分化。在这 在这个框架中，视觉皮层是“视觉的”，主要是因为它连接到视网膜，皮层的所有区域都是 能够解决类似的信息处理问题。这表明相同的基本机制 用于学习序列的“高级”皮层区域也应该存在于“低级”区域， 假设初级感觉区域应该包含局部编码序列所必需的机制 表示。一系列的实验验证了这一假设，表明它是可能的， 序列在初级视觉皮层的时间和空间精度。 本研究的目的是充分描述和理解这种学习的机制性质， 皮层处理的后果。所提出的实验旨在检验以下假设： 视觉序列学习是由NMDAR介导的神经元群体之间的突触可塑性编码的 使用电生理学观察、2- 光子显微术、药理学和光遗传学操作以及计算建模。