Computational Neuroscience
PHYSICS 231
Subject & Catalog Number
Course Information
Description
Follows trends in modern brain theory, focusing on local neuronal circuits as basic computational modules. Explores the relation between network architecture, dynamics, and function. Introduces tools from information theory, statistical inference, and the learning theory for the study of experience-dependent neural codes. Specific topics: computational principles of early sensory systems; adaptation and gain control in vision, dynamics of recurrent networks; feature selectivity in cortical circuits; memory; learning and synaptic plasticity; noise and chaos in neuronal systems.
Course Notes
Also offered as Neuro 231 and MCB 231. Cannot be taken for credit as Physics 231 if Neuro 231 or MCB 231 is already complete.
School
Faculty of Arts & Sciences
Credits
4
Cross Reg
Available for Harvard Cross Registration
Department
Physics
Course Component
Lecture
Subject
Physics
Grading Basis
FAS Letter Graded
Course Requirements
Cannot be taken for credit if MCB 231 or NEURO 231 completed or in progress.
Exam/Final Deadline
May 7, 2026
General Education
N/A
Quantitative Reasoning with Data
N/A
Divisional Distribution
Science & Engineering & Applied Science
Course Level
Primarily for Graduate Students
