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Speaker:

Prof. Dr. Fred H. Hamker

Abstract:

This course provides an introduction into computational neuroscience. It comprises basic knowledge about simulating biophysical models of single cells as well as a systems neuroscience approach to understand and model the role of different brain areas. Particularly, I will focus on the primary brain structure relevant for executive processes, learning and decision making – the basal ganglia.
 
First, I introduce biophysical models of single cells that are constructed using electrical circuits composed of resistors, capacitors, and voltage and current sources. This knowledge is then used to build integrate-and-fire as well as the Hodgkin-Huxley models. Second, I discuss learning rules and introduce to the role of dopamine in learning. Third, I discuss a few systems level approaches modeling the interaction of different brain areas. Fourth, I present and discuss computational models of the basal ganglia including their role in working memory and cognitive control.

 
Disciplines:
 
Computational Neuroscience, Cognitive Computational Neuroscience, Cognitive Science

References:

• Dayan, P. & Abbott, L., Theoretical Neuroscience, MIT Press, 2001
• Vitay, J., Hamker, F.H. (2010) A computational model of the influence of basal ganglia on memory retrieval in rewarded visual memory tasks. Frontiers in Computational Neuroscience, 4:13.
• O’Reilly, R. C., and Frank, M. J. (2006). Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia. Neural. Comput. 18, 283–328.
• Frank MJ, Samanta J, Moustafa AA, Sherman SJ (2007) Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonism. Science 318:1309 –1312.