This proposal is for the renewal of a predoctoral and postdoctoral training program in Quantitative Neuroscience at Princeton University. The way neuroscience research is carried out is rapidly changing and becoming much more dependent on, and engaged with, the physical, mathematical and information sciences. New technologies are providing data of unprecedented complexity and scale. fMRI and MEG map activated regions of the human brain with increasing resolution and temporal precision, while multi-electrode recording and optical imaging using voltage and calcium sensors provide detailed information on the spatial patterns of electrochemical activities in neural circuits and single neurons. Increasingly, the questions addressed with these technologies are systems level questions that concern the interactions of many components in networks. How sensory and motor information is represented across the activity of a population of neurons, how working memory and decisions are implemented in neural circuits, and how interacting biochemical pathways in a single synapse can coordinate plasticity and growth are all examples of contemporary network questions in neuroscience. The answers to such questions are not only of interest to basic scientists; they are also a necessary precursor to understanding disturbances of brain function in psychiatric disorders, and how these give rise to disturbances of mental function. While there has been tremendous progress in identifying disturbances of neurotransmitter function in psychiatric illness, this has not been matched by comparable progress in our understanding of how such disturbances produces disturbances of systems-level function that underlie clinical symptoms. Our training program in quantitative neuroscience addresses these changes and challenges by providing predoctoral and postdoctoral instruction and research opportunities in a combined curriculum of formal theoretical techniques and computational methods on the one hand and hands-on inquiry-based project laboratory experience on the other. This program is a cornerstone of Princeton's new Neurosciences Institute emphasizing neural coding and dynamics, bringing together faculty from Psychology, Biology, Physics, Chemistry, Engineering and other disciplines to provide a directed curriculum with cutting-edge technology for empowering future neuroscientists with quantitative methods. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Institutional National Research Service Award (T32)
Project #
2T32MH065214-06A1
Application #
7446942
Study Section
Special Emphasis Panel (ZMH1-ERB-Z (02))
Program Officer
Desmond, Nancy L
Project Start
2002-07-01
Project End
2013-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
6
Fiscal Year
2008
Total Cost
$325,994
Indirect Cost
Name
Princeton University
Department
Type
Organized Research Units
DUNS #
002484665
City
Princeton
State
NJ
Country
United States
Zip Code
08544
Cope, Elise C; LaMarca, Elizabeth A; Monari, Patrick K et al. (2018) Microglia Play an Active Role in Obesity-Associated Cognitive Decline. J Neurosci 38:8889-8904
Vodrahalli, Kiran; Chen, Po-Hsuan; Liang, Yingyu et al. (2018) Mapping between fMRI responses to movies and their natural language annotations. Neuroimage 180:223-231
Aly, Mariam; Chen, Janice; Turk-Browne, Nicholas B et al. (2018) Learning Naturalistic Temporal Structure in the Posterior Medial Network. J Cogn Neurosci 30:1345-1365
Miller, Kevin J; Botvinick, Matthew M; Brody, Carlos D (2017) Dorsal hippocampus contributes to model-based planning. Nat Neurosci 20:1269-1276
Srivastava, Vaibhav; Feng, Samuel F; Cohen, Jonathan D et al. (2017) A martingale analysis of first passage times of time-dependent Wiener diffusion models. J Math Psychol 77:94-110
Baldassano, Christopher; Chen, Janice; Zadbood, Asieh et al. (2017) Discovering Event Structure in Continuous Narrative Perception and Memory. Neuron 95:709-721.e5
Nguyen, Jeffrey P; Linder, Ashley N; Plummer, George S et al. (2017) Automatically tracking neurons in a moving and deforming brain. PLoS Comput Biol 13:e1005517
Chan, Stephanie C Y; Applegate, Marissa C; Morton, Neal W et al. (2017) Lingering representations of stimuli influence recall organization. Neuropsychologia 97:72-82
Song, Alexander; Charles, Adam S; Koay, Sue Ann et al. (2017) Volumetric two-photon imaging of neurons using stereoscopy (vTwINS). Nat Methods 14:420-426
Chen, Janice; Leong, Yuan Chang; Honey, Christopher J et al. (2017) Shared memories reveal shared structure in neural activity across individuals. Nat Neurosci 20:115-125

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