The function of a brain region is an emergent property of many cell types. The criteria needed to understand a network have been established in studies of invertebrate simple networks, but there has not yet been an attempt to provide such a full, mechanistic understanding of any network in the vertebrate brain. We believe that the time is now ripe for such an effort. Specifically, we propose to understand how the CA3 network in the hippocampus generates sharp-wave-ripples (SWR). These events are of great interest because of their cognitive function: they represent replay of episodic memory sequences and are required for subsequent memory recall, as demonstrated at the behavioral level. Our efforts to understand the SWR will build on previous work establishing the cell types of the hippocampus. However, to meet the criteria for understanding, a great deal of additional information about connectivity and intrinsic properties of cells must be obtained. We will use recently developed large-scale electrical and optical recording methods and ontogenetic to obtain this information. In addition, several new methods/tools will be developed. Notably, we propose to optimize a novel synapse localization optical method to obtain high-throughput cell type-specific information about the connective of the CA3 network. We will also construct the first full-scale computational model of the CA3 region of the hippocampus, in which every cell and synaptic connection is explicitly represented. This strictly data-driven, full-scale model will provide a widely applicable tool for synthesizing experimental results and testing our ability to understand the principles that underlie SWR generation.

Public Health Relevance

We propose to make the first attempt to fully understand a cognitively important event, called memory replay, in terms of the detailed properties of the brain cells involved. We will use cutting-edge large-scale recording technologies to study and manipulate identified cell types, and develop a novel method that will provide needed information about the connectivity between the neurons involved. Finally, we will construct the first full- scale computational of model of the brain area that produces the memory replay in which every cell is explicitly simulated. These powerful new approaches are likely to yield major insights into the principles by which the interactions of neurons gives rise to cognitive function, with important implications for memory disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
7U01NS090583-02
Application #
8935978
Study Section
Special Emphasis Panel ()
Program Officer
Gnadt, James W
Project Start
2014-09-30
Project End
2017-07-31
Budget Start
2015-09-01
Budget End
2016-07-31
Support Year
2
Fiscal Year
2015
Total Cost
$706,982
Indirect Cost
$113,888
Name
Stanford University
Department
Neurosurgery
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
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