Spatial perception is a highly complex hierarchical problem. There are several parts of the brain that directly participate in spatial processing and code for different kinds of spatial reference frames. These regions work together to produce a complete, consistent representation of the environment. The goal of this study is to better understand the relationships and possible interactions between the egocentric (relative to animal's body) spatial reference frame in the parietal cortex and the allocentric (relative to the world) frame in the hippocampus, and to look for """"""""signatures"""""""" in the activity of either region that mark transitions between alternative spatial frames in the other region. [The candidate plans] to collect data simultaneously from large numbers of parietal and hippocampal neurons of a rat running on a track with variable shape to study the properties of firing activity in these regions and their responses to the changing geometry of the track. [He plans] to test the hypothesis that firing activity in parietal cortex is correlated with firing activity in CA1. In addition, [he] will work on mastering and extending a set of software tools based on the adaptive filtering algorithm, used in Dr. Frank's laboratory, which allows accurate description of real time dynamics of neural spiking activity ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32NS054425-02
Application #
7173894
Study Section
Special Emphasis Panel (ZRG1-F02A (20))
Program Officer
Babcock, Debra J
Project Start
2006-01-01
Project End
2008-12-31
Budget Start
2007-01-01
Budget End
2007-12-31
Support Year
2
Fiscal Year
2007
Total Cost
$58,036
Indirect Cost
Name
University of California San Francisco
Department
Physiology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Babichev, Andrey; Dabaghian, Yuri A (2018) Topological Schemas of Memory Spaces. Front Comput Neurosci 12:27
Babichev, Andrey; Dabaghian, Yuri (2017) Transient cell assembly networks encode stable spatial memories. Sci Rep 7:3959
Basso, Edward; Arai, Mamiko; Dabaghian, Yuri (2016) Gamma Synchronization Influences Map Formation Time in a Topological Model of Spatial Learning. PLoS Comput Biol 12:e1005114
Babichev, Andrey; Ji, Daoyun; Mémoli, Facundo et al. (2016) A Topological Model of the Hippocampal Cell Assembly Network. Front Comput Neurosci 10:50
Dabaghian, Y (2016) Maintaining Consistency of Spatial Information in the Hippocampal Network: A Combinatorial Geometry Model. Neural Comput 28:1051-71
Dabaghian, Yuri; Brandt, Vicky L; Frank, Loren M (2014) Reconceiving the hippocampal map as a topological template. Elife 3:e03476
Dabaghian, Y; Memoli, F; Frank, L et al. (2012) A topological paradigm for hippocampal spatial map formation using persistent homology. PLoS Comput Biol 8:e1002581