Computations In Neural Systems: From Single Cell Membrane to Large Neural Networks

Psychology 506A - Fall 2009

- General Information.

• This course is intended to provide a basis for understanding how brains acquire, assimilate, store and retrieve information and how they compute adaptive responses to external inputs. Understanding these processes requires a basic working knowledge of both the theoretical principles and biological mechanisms underlying neural signaling, knowledge representation and data storage. The course begins with a review of the fundamentals of membrane physiology & neuronal excitability, synaptic transmission & synaptic plasticity, and the integrative properties of dendrites. This is followed by a discussion of associative (‘Hebbian’) learning in networks of neurons and on the mechanisms by which networks can be trained to produce an adaptive response. We then consider how information is ‘coded’ in the activities of single neurons and in the collective activity patterns of large networks of neurons. Finally, we explore how some specific models have been used to make sense of computation in the brain. Topics include the spatial representation in the hippocampus, consolidation and re-consolidation of memories, the transformation of neuronal representations and other examples of ‘higher’ cognitive functions.
  
• Syllabus and grading policies
• Intructor: Jean-Marc Fellous.
  Office Hour: Wednesdays after class, or by appointments, LSN 384.

- Readings.

- Slides and other material (protected, need password).