Neuronal Physiology and Plasticity
Code and credits: MB214, (3:0)
Course webpage: http://mbu.iisc.ac.in/~mb214/
Instructors: Rishikesh Narayanan
Duration: Aug–Dec. Semester
Syllabus: Neuronal and synaptic physiology: exquisite insights from simple systems; history of technical advances: electrophysiology, imaging and computation; history of conceptual advances: excitable membranes, action potentials, ion channels, oscillations, synapses, behavioral neurophysiology; complexities of the mammalian neuron; dendritic structure; dendritic ion channels; active properties of dendrites; dendritic spikes and backpropagating action potentials; heterogeneity, diversity and degeneracy in the nervous system; hippocampus as an ideal system for assessing learning and memory; synaptic plasticity: short-term plasticity, long-term potentiation and depression; mechanisms underlying synaptic plasticity; intrinsic plasticity; mechanisms underlying intrinsic plasticity; issues in the credit-assignment problem on mechanisms behind learning and memory.
Books and references
1. “Foundations of Cellular Neurophysiology” by Daniel Johnston and Samuel Wu, MIT Press, 1995.
2. “Neuroscience” by Dale Purves, George J. Augustine, David Fitzpatrick, William C. Hall, Anthony-Samuel LaMantia, Richard D. Mooney, Michael L. Platt, Leonard E. White, Oxford University Press, 2017.
3. “The Hippocampus Book” by Per Andersen, Richard Morris, David Amaral, Tim Bliss and John O'Keefe. Oxford University Press, 2006.
4. “Dendrites” by Greg Stuart, Nelson Spruston and Michael Hausser. Oxford University Press, 2016.
5. “Synapses” by W. Maxwell Cowan, Thomas C. Südhof, Charles F. Stevens, The Johns Hopkins University Press, 2003.
6. “The synaptic organization of the brain” by Gordon Shepherd, Oxford University Press, 2004.
7. “Rhythms of the Brain” by Gyorgy Buzsaki, Oxford University Press, 2006.
Theoretical and computational neuroscience
Code and credits: MB208, (3:1)
Course webpage: http://mbu.iisc.ac.in/~mb208/
Instructors: Rishikesh Narayanan and S. P. Arun
Duration: Jan–Apr. Semester
Syllabus: Need for and role of theory and computation in neuroscience; various scales of modeling; ion channel models; single neuron models; network and multiscale models; models of neural plasticity; oscillations in neural systems; central pattern generators; single neuron oscillators; oscillators as nonlinear dynamical systems; information representation; neural encoding and decoding; population codes; hierarchy and organization of sensory systems; receptive field and map modeling; case studies, computational laboratory and projects.
Prerequisites: MB214 (or basic exposure to ion channels and their functions), basic knowledge of linear algebra, probability, statistics and ordinary differential equations, and some programming knowledge.
Books and references
a. Peter Dayan and L. F. Abbott, Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, The MIT press, 2005.
b. Christof Koch and Idan Segev (Eds), Methods in Neuronal Modeling: From Ions to Networks, The MIT press, second edition, 1998.
c. Eric De Schutter (Ed.), Computational modeling methods for neuroscientists, The MIT press, 2009.
d. Eugene Izhikevich, Dynamical systems in neuroscience: the geometry of excitability and bursting, The MIT press, 2006.
e. Kenji Doya, Shin Ishii, Alexandre Pouget, Rajesh PN Rao (Eds), Bayesian Brain: Probabilistic Approaches to Neural Coding, The MIT press, 2007.
Courses offered in previous semesters