neural networks research group
areas
demos
people
projects
publications
software
Computational Neuroscience
A computational model is a complete description of how a neural system functions, and in that sense the ultimate specification of neuroscience theory. The models are constrained by and validated with existing experimental data, and then used to generate predictions for further biological experiments. Our work in this area focuses on understanding the visual cortex, episodic and associative memory, aphasic and dyslexic impairments of the lexical system, and language impairments in schizophrenia.
People
James A. Bednar
Yoonsuck Choe
Judah De Paula
Igor Farkas
Andrea Haessley
Stefanie Jegelka
Risto Miikkulainen
Mark Moll
Enrique Muro
Manish Saggar
Yaron Silberman
Joseph Sirosh
Yiu Fai Sit
Tal Tversky
Vinod Valsalam
Publications
1-5
6-10
11-15
16-20
21-25
26-30
31-35
36-40
41-45
46-50
51-55
56-58
View All 58
Computational Predictions on the Receptive Fields and Organization of V2 for Shape Processing
(2009)
Memory Processes in Perceptual Decision Making
(2008)
Developing Complex Systems Using Evolved Pattern Generators
(2007)
A Computational Model of the Signals in Optical Imaging with Voltage-Sensitive Dyes
(2007)
System Identification for the Hodgkin-Huxley Model using ArtificialNeural Networks
(2007)
Projects
1-5
6-10
View All 10
Trichromatic LISSOM
Neural Network Models of Schizophrenic Language
Self-Organization of Directional Selectivity
PGLISSOM: Perceptual Grouping in a Self-Organizing Map of Spiking Neurons
GLISSOM: Modeling Large Cortical Maps
Software
SIGNALSIM
LISSOM
SOFM
PGLISSOM
DISLEX
Demos
A Subsymbolic Model of Schizophrenic Language