VS298 (Fall 06): Neural Computation - Revision history

Bruno: /* People */

2006-08-22T05:37:18Z

People

New page

== People ==

'''Professor:''' [http://redwood.berkeley.edu/bruno Bruno Olshausen]
* Email: baolshausen AT berkeley DOT edu
* Office: 10 Giannini, 3-1472
* Office hours: TBD

'''GSI:''' Amir Khosrowshahi
* Email: amirk AT berkeley DOT edu
* Office: 523 Minor, 3-5996
* Office hours: TBD

== Course description ==
This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.

This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience,'' in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - rather than their application to the analysis of neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.

==== Lectures ====
*Location: TBD
*Times: Two 1.5 hour lectures per week.

There will be an <font color="red">'''organizational meeting'''</font> at 4pm, Tuesday, August 29th, at the Redwood Center in 10 Giannini (red dot on this [http://redwood.berkeley.edu/wiki/Image:10_Giannini.jpeg map]). Class will begin the week of September 4th.

==== Email list and forum ====
* Please email the GSI to be added to the class email list.
* A bulletin board is provided [http://redwood.berkeley.edu/forum/viewforum.php?f=2 here] for discussion regarding lecture material, readings, and problem sets.

==== Grading ====
Based on weekly homework assignments (60%) and a final project (40%).

==== Required background====
Prerequisites are calculus, ordinary differential equations, basic probability and statistics, and linear algebra. Familiarity with programming in a high level language, ideally Matlab, is also required.

==== Textbooks ====
* ['''HKP'''] Hertz, J. and Krogh, A. and Palmer, R.G. ''Introduction to the theory of neural computation.'' [http://www.amazon.com/gp/product/0201515601/sr=8-1/qid=1155770696/ref=sr_1_1/103-4924722-3267011?ie=UTF8 Amazon]
* ['''DJCM'''] MacKay, D.J.C. ''Information Theory, Inference and Learning Algorithms.'' [http://www.inference.phy.cam.ac.uk/mackay/itila/book.html Available online] or [http://www.amazon.com/exec/obidos/redirect?tag=davidmackayca-20&path=tg/detail/-/0521642981/qid%3D1057850920/sr%3D1-4 Amazon]
* ['''DA'''] Dayan, P. and Abbott, L.F. ''Theoretical neuroscience: computational and mathematical modeling of neural systems.'' [http://www.amazon.com/gp/product/0262541858/ref=sr_11_1/103-4924722-3267011?ie=UTF8 Amazon]

Additional reading, such as primary source material, will be suggested on a lecture by lecture basis.

== [http://redwood.berkeley.edu/wiki/VS298:_Additional_resources Additional resources] ==
== [http://redwood.berkeley.edu/wiki/VS298:_Homework_assignments Homework] ==

== Syllabus ==

==== Introduction ====
# Theory and modeling in neuroscience
# Descriptive vs. functional models
# Turing vs. neural computation
* '''Reading''': '''HKP''' chapter 1

==== Linear neuron models ====

# Linear systems: vectors, matrices, linear neuron models
# Perceptron model and linear separability
* '''Reading''': '''HKP''' chapter 5, '''DJCM''' chapters 38-40

==== Supervised learning ====

# Perceptron learning rule
# Adaptation in linear neurons, Widrow-Hoff rule
# Objective functions and gradient descent
# Multilayer networks and backpropagation
* '''Reading''': '''HKP''' chapter 6, 7, '''DJCM''' chapters 38-40, 44

==== Reinforcement learning ====

# Theory of associative reward-penalty
# Models and critics
* '''Reading''': '''HKP''' chapter 8, '''DJCM''' chapter 36, '''DA''' chapter 9

==== Unsupervised learning ====

# Linear Hebbian learning and PCA, decorrelation
# Winner-take-all networks and clustering
# Sparse, distributed coding
* '''Reading''': '''HKP''' chapter 8, '''DJCM''' chapter 36, '''DA''' chapter 8, 10

==== Plasticity and cortical maps ====

# Self-organizing maps, Kohonen nets
# Models of experience dependent learning and cortical reorganization
* '''Reading''': '''HKP''' chapter 9, '''DA''' chapter 8

==== Recurrent networks ====

# Hopfield networks
# Pattern completion
# Line attractors and `bump circuits’
# Models of associative memory
* '''Reading''': '''HKP''' chapter 2-3, '''DJCM''' chapter 42, '''DA''' chapter 7

==== Probabilistic models and inference ====

# Probability theory and Bayes’ rule
# Learning and inference in generative models
# The mixture of Gaussians model
# Boltzmann machines
# Sparse coding and ‘ICA’
* '''Reading''': '''DJCM''' chapter 1-3, 20-24,41,43, '''DA''' chapter 10

==== Neural implementations ====

# Integrate-and-fire model
# Neural encoding and decoding
# Limits of precision in neurons
* '''Reading''': '''DA''' chapter 1-4, 5.4

Bruno: /* Course description */

2006-08-17T06:52:23Z

Course description

← Older revision		Revision as of 06:44, 17 August 2006
Line 14:		Line 14:
	This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.		This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.

	~~Relation to MCB 262:~~ This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience,'' in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - rather than their application to the analysis of neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.		This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience,'' in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - rather than their application to the analysis of neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.

	==== Lectures ====		==== Lectures ====

Bruno: /* Course description */

2006-08-17T06:51:41Z

Course description

← Older revision		Revision as of 06:43, 17 August 2006
Line 14:		Line 14:
	This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.		This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.

	Relation to MCB 262: This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience,'' in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - ~~as opposed~~ to ~~how they are used to analyze~~ neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.		Relation to MCB 262: This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience,'' in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - rather than their application to the analysis of neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.

	==== Lectures ====		==== Lectures ====

Bruno: /* Course description */

2006-08-17T06:10:50Z

Course description

← Older revision		Revision as of 06:02, 17 August 2006
Line 14:		Line 14:
	This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.		This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.

	Relation to MCB 262: This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience, in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - as opposed to how they are used to analyze neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.		Relation to MCB 262: This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience,'' in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - as opposed to how they are used to analyze neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.

	==== Lectures ====		==== Lectures ====

Bruno: /* Course description */

2006-08-17T06:08:07Z

Course description

← Older revision		Revision as of 06:00, 17 August 2006
Line 12:		Line 12:

	== Course description ==		== Course description ==
	This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide ""hands-on" experience in using these models.		This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.

	This course ~~compliments~~ MCB 262, ''Advanced Topics in Systems Neuroscience,		Relation to MCB 262: This course differs from MCB 262, ''Advanced Topics in Systems Neuroscience, in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - as opposed to how they are used to analyze neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.
	~~year will be a "trial version"~~ of ~~the course~~ - ~~the plan is~~ to ~~offer it other year~~, interleaving with

	==== Lectures ====		==== Lectures ====

Bruno: /* Course description */

2006-08-17T05:51:36Z

Course description

← Older revision		Revision as of 05:43, 17 August 2006
Line 12:		Line 12:

	== Course description ==		== Course description ==
	This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide ""hands-on"" experience in using these models.		This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide ""hands-on" experience in using these models.

	This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience,"		This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience,
	year will be a "trial version" of the course - the plan is to offer it other year, interleaving with		year will be a "trial version" of the course - the plan is to offer it other year, interleaving with

Bruno: /* Course description */

2006-08-17T05:50:44Z

Course description

← Older revision		Revision as of 05:42, 17 August 2006
Line 12:		Line 12:

	== Course description ==		== Course description ==
	This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide "hands-on" experience in using these models.		This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide ""hands-on"" experience in using these models.

	This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience'',		This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience,"
	year will be a "trial version" of the course - the plan is to offer it other year, interleaving with		year will be a "trial version" of the course - the plan is to offer it other year, interleaving with

Bruno: /* Course description */

2006-08-17T05:49:08Z

Course description

← Older revision		Revision as of 05:41, 17 August 2006
Line 12:		Line 12:

	== Course description ==		== Course description ==
	This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide "hands-on" experience in using these models. This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience'',		This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide "hands-on" experience in using these models.

			This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience'',
	year will be a "trial version" of the course - the plan is to offer it other year, interleaving with		year will be a "trial version" of the course - the plan is to offer it other year, interleaving with

Bruno: /* Course description */

2006-08-17T05:48:36Z

Course description

← Older revision		Revision as of 05:40, 17 August 2006
Line 12:		Line 12:

	== Course description ==		== Course description ==
	This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students~~, especially those in neuroscience and psychology,~~ with the theoretical ~~underpinnings of~~ models used in neuroscience and psychology, and to provide "hands-on" experience in using these models.		This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide "hands-on" experience in using these models. This course compliments MCB 262, ''Advanced Topics in Systems Neuroscience'',
			year will be a "trial version" of the course - the plan is to offer it other year, interleaving with

	==== Lectures ====		==== Lectures ====

Bruno: /* Course description */

2006-08-17T05:29:17Z

Course description

← Older revision		Revision as of 05:21, 17 August 2006
Line 12:		Line 12:

	== Course description ==		== Course description ==
	This is a 3-unit course that provides an introduction to ~~theoretical aspects~~ of neural computation.		This is a 3-unit course that provides an introduction to theory of neural computation. The goal is to familiarize students, especially those in neuroscience and psychology, with the theoretical underpinnings of models used in neuroscience and psychology, and to provide "hands-on" experience in using these models.


	==== Lectures ====		==== Lectures ====
Line 25:		Line 26:

	==== Grading ====		==== Grading ====
	~~There will~~ weekly homework assignments and a final project.		Based on weekly homework assignments (60%) and a final project (40%).

	==== Required background====		==== Required background====