Computational Neuroscience course

  • Computational Neuroscience is being offered as a Discipline Elective at the Department of Computer Science and Information Systems (CSIS) for Semester II AY 2022-23.

  • Course Code: CS F433 Bulletin Index: Pg. !V-66 (BTech); Pg. !V-107 (MTech)

  • Included in subjects listed under Minor in Data Science - Pg. !V-82

  • Target student population (year(s) & discipline(s)):

      • 3rd/4th yr Undergraduate (UG) of Computer Science & Information Systems (CSIS)/Electrical, Electronics & Instrumentation/Mechanical Engineering, Biological Science, Physics, Mathematics. Higher Degree (HD) Students of CSIS

  • Is the proposed course a discipline elective?

      • Discipline Elective for UG CSIS; Data Science Minor; Open Elective for UG of abovementioned disciplines; Discipline Elective for HD CSIS

  • Any Pre-requisites? : None other than the compulsory Maths courses

  • COURSE HANDOUT ATTACHED BELOW

  • Course Description in Bulletin Pg. VI - 38: (See BULLETIN BELOW)

CS F433 Computational Neuroscience 3 0 3

Biophysics of action potentials, local field potentials (LFP) and electroencephalogram (EEG), and their recording and analysis techniques; modelling a neuron - starting with the Nobel-prize winning Hodgkin-Huxley model; information processing in neural populations; synaptic mechanisms and learning by association; meso- and macro-scale neural population networks and their dynamics; modelling of neurological disorders as observed in higher level brain signals such as the LFP, EEG, functional magnetic resonance imaging (FMRI); validation of neural models with data. Alongside theory, students will be introduced to software tools (using python/Matlab/C based on student preferences) to simulate neural computations and models.

BITS-Pilani-Academic-Bulletin-2022-23.pdf
CourseHandout_Computationalneuroscience-SemII-AY2022-23.pdf