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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
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