In this proposal we request continuation of support for the Methods in Computational Neuroscience Course offered annually at the Marine Biological Laboratory since 1988. The goal of this course is to train 24 advanced students and post-doctoral fellows per year in the fundamental issues in computational neuroscience, providing them with analytical tools to assist in their studies. The course has several unique features, which would be hard if not impossible to duplicate in a university setting. First, it continues to attract and educate students from a broad range of established disciplines that impact on neuroscience, including biology, cognitive science, computer science, mathematics, physics and engineering. Secondly, as a means to providing a coherent and relatively complete perspective on the growing field of computational neuroscience, students are exposed to a large visiting faculty, drawn from leaders in the field, as well as receiving instruction and guidance from the course directors, resident faculty and course assistants. It is unlikely that such a combination of faculty could be convened for a similar course in a university setting. Finally, the course provides students with access to state-of-art computational techniques and computer hardware essential in the simulation of neural systems from a detailed cellular through more abstract systems level. The course is an intensive 4-week lecture/laboratory series. Each of the first three weeks is organized around a theme, both conceptually and in terms of the mathematical tools developed. Week 1 addresses neural coding. In Week 2, we examine how computation emerges from the dynamical properties of single neurons and networks. Week 3 focuses on learning and uses methods from learning theory, estimation and control theory. Most of the final week is devoted to individual projects.
We aim to show students how combined experimental and theoretical approaches can lead to breakthroughs and make them familiar with the analytic methods and computational tools that they will need for success.

Public Health Relevance

Diseases of the nervous system can be devastating. Understanding the fundamental basis for these diseases can eventually lead to cures. Computational approaches in neuroscience are beginning to shed light on the basis of neuropsychiatric and neurological diseases exhibiting periodicity or cyclicity which include Bipolar Disorder, Schizophrenia, Seasonal Affective Disorder, Klein-Levin Syndrome, Sleep Disorders, Binging, Epilepsy, Multiple Sclerosis, Jet-Lag and Headache. The course on Methods in Computational Neuroscience presented in this proposal is an intensive program, taught by leaders in the field, dedicated to training investigators in this area. This program, now entering its 22nd year, has already produced many skilled investigators who are making significant contributions in their studies on diseases of the nervous system.
The aim of the current proposal is to continue training such investigators for the future,

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Education Projects (R25)
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Special Emphasis Panel (ZMH1-ERB-S (04))
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Desmond, Nancy L
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Marine Biological Laboratory
Woods Hole
United States
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Nguyen, Dieu My T; Roper, Mark; Mircic, Stanislav et al. (2017) Grasshopper DCMD: An Undergraduate Electrophysiology Lab for Investigating Single-Unit Responses to Behaviorally-Relevant Stimuli. J Undergrad Neurosci Educ 15:A162-A173
Kristensen, Anders S; Hansen, Kasper B; Naur, Peter et al. (2016) Pharmacology and Structural Analysis of Ligand Binding to the Orthosteric Site of Glutamate-Like GluD2 Receptors. Mol Pharmacol 89:253-62
Nishi, Rae; CastaƱeda, Edward; Davis, Graeme W et al. (2016) The Global Challenge in Neuroscience Education and Training: The MBL Perspective. Neuron 92:632-636
Okubo, Tatsuo S; Mackevicius, Emily L; Payne, Hannah L et al. (2015) Growth and splitting of neural sequences in songbird vocal development. Nature 528:352-7
Dagda, Ruben K; Thalhauser, Rachael M; Dagda, Raul et al. (2013) Using crickets to introduce neurophysiology to early undergraduate students. J Undergrad Neurosci Educ 12:A66-74
Roberts, C B; Best, J A; Suter, K J (2006) Dendritic processing of excitatory synaptic input in hypothalamic gonadotropin releasing-hormone neurons. Endocrinology 147:1545-55