Courses: BioE332
Large-scale neural modeling

Catalog Description: Emphasis is on modeling neural systems at the circuit level, ranging from feature maps in neocortex to episodic memory in hippocampus. Simulation exercises explore the roles of cellular properties, synaptic plasticity, spike synchrony, rhythmic activity, recurrent connectivity, and noise and heterogeneity; quantitative techniques are introduced to analyze and predict network behavior. Students work in teams of two and run models in real-time on neuromorphic hardware developed for this purpose.

Modeling Project BioE332 students, Sridhar Devarajan (Neurosci) and Brian Percival (EE), demoing their modeling project on dynamic routing through neuronal coherence. [Winter 2007]

Course Details: Based on weekly three-hour labs (simulation exercises) performed in groups of two. Accompanying lectures provide the background needed to understand and perform these labs. Modeling projects that build on these lessons can be performed in the Spring Quarter through arrangement with the instructor.

Prerequisites: Biology students should have a differential equations course (e.g., Math 42); no background in engineering is required. Engineering students should have a neurobiology course (e.g., Bio 20); otherwise the instructor's permission is required. Undergraduates need the instructor's permission.

Goals: Link structure to function by developing circuit-level computational models of the nervous system. These models are studied in weekly lab exercises.

Target Audience: This course is intended to draw students from multiple disciplines with an interest in interdisciplinary approaches. Students are encouraged to pool their expertise in different areas by working in groups of two.

BioE332—Winter 2010



Class Time: Weds & Fri 12:50-2:05pm
Location (as of 1/4/2010): Gates 100
Lab Time: Mon 2-5pm or Tues 8:30-11:30am
Lab Location: Alway 206
Office Hours:
- Professor Boahen: Tuesday 12 - 1 pm (Clark W125)
- TA: Friday 2:10 - 3:30 pm (Clark W1.3, next to W125)

Class notes

Lecture 1 Overview
Lecture 2 Synapse
Lecture 3 Integrate-&-Fire Neuron
Lecture 4 Positive Feedback
Lecture 5 Adaptive Neuron
Lecture 6 Bursting Neuron
Lecture 7 Phase Response
Lecture 8 Two-Neuron Interaction
Lecture 9 Synchrony and Inhibition
Lecture 10 Delay Model of Synchrony
Lecture 11 Attention Intro
Lecture 12 Attention and Neuromodulation (Addendum)
Lecture 13 Spike Timing-Dependent Plasticity
Lecture 14 Feedforward Synapses
Lecture 15 Recurrent Synapses
Lecture 16 Limits of STDP
Lecture 17 Storing Patterns
Lecture 18 Recalling Patterns
Lecture 19 System Hardware
Lecture 20 Neurogrid


Lab 1 Synapse Lab (Block diagram - SVG, PNG)
Lab 2 Neuron Lab (Block diagram - SVG, PNG)
Lab 3 Adapting–Bursting Lab (Block diagram - SVG, PNG)
Lab 4 Phase Response Lab (Block diagram - SVG, PNG)
Lab 5 Synchrony Lab (Block diagram - SVG, PNG)
Lab 6 Attention Lab (Block diagram - SVG, PNG)
Lab 7 STDP Lab (Block diagram - SVG, PNG)
Lab 8 Plasticity Enhanced Synchrony Lab (Block diagram - SVG, PNG)
Lab 9 Associative Recall (Block diagram - SVG, PNG)
Lab 10 In-Depth Investigations


Lab 1

Lab 2

Lab 3

Lab 4

Lab 6

Previous Years