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| Campus | Bryn Mawr |
| Semester | Fall 2024 |
| Registration ID | PSYCB265001 |
| Course Title | Computational Neuroscience |
| Credit | 1.00 |
| Department | Neuroscience |
| Instructor | Shin,Yeon Soon |
| Times and Days | TTh 02:40pm-04:00pm
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| Room Location | CAN315 |
| Additional Course Info | Class Number: 2923 This course introduces students to the field of computational neuroscience. Computational neuroscience uses mathematical models to understand the information carried in the brain at many scales: a single neuron, synaptic connections between neurons, and populations of neurons. Mathematical models help us gain a precise understanding of the dynamics of our nervous system and make better predictions by running simulations of the system. In this course, students will learn key concepts and topics in computational neuroscience. Topics include neural encoding and decoding, artificial neural networks, reinforcement learning, and Bayesian probability theories. They will gain hands-on experience formulating the mental processes in the brain in terms of mathematical equations and writing computer codes in programming languages such as Python and MATLAB to simulate these processes. Prerequisites: Introductory Psychology (PSYC B101 or PSYC H100), or Introduction to Neuroscience (NEUR H100). Approach: Scientific Investigation (SI); Haverford: C: Physical and Natural Processes (C) ( ) Enrollment Cap: 24. This is not for Freshmen. |
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