Maxversace
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Boston University Department of Cognitive and Neural Systems (CNS) Technology Lab
editThe Technology Lab at the Department of Cognitive and Neural Systems at Boston University was founded in 2001. The Technology Lab fosters the development of neural network models directly derived from scientific research. The Lab also facilitates the transfer of the resulting technologies to industrial applications.
The Tech Lab develops brain-based software for large-scale applications, ranging from remote sensing to text mining. The CNS Technology Lab website provides a software repository for algorithms, data sets, articles, news, and links about neural methods and applications.
Director: Gail Carpenter
Assistant Director: Massimiliano Versace
Affiliated faculty: Suchi Gopal Grossberg Stephen Grossberg Ennio Mingolla
Postdocs: Heather Ames Sai Gaddam Praveen Pilly
Students: Sean Lorenz, Santiago Oliveira, Robert Thijs Kozma, Arun Ravindran, Charles Wong
Current software available for downloads:
- Simple cells This is a one-dimensional stand-alone implementation of the Grossberg and Todorović model of a cortical simple cell.
- Fuzzy ARTMAP This package contains an implementation of Fuzzy ARTMAP and provides a graphical user interface (GUI) as well as command line utilities to simulate the training and testing of a Fuzzy ARTMAP network.
- Biased ARTMAP Biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error.
- Self-supervised ARTMAP Self-Supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns.
- CONFIGR CONFIGR (CONtour FIgure and GRound) is a model that performs long-range contour completion on large-scale images. CONFIGR accomplishes this through a mechanism that fills-in both figure and ground via complementary process.
- MODE MOtion DEcision (MODE) model is a neural model of perceptual decision-making that discriminates the direction of an ambiguous motion stimulus and simulates behavioral and physiological data obtained from macaques performing motion discrimination tasks.
- Diffusive filling-in The package provides a GUI interface to control luminance of COCE stimulus components which have impact on the model’s output. The software can be run from matlab command line by typing Filling_in at the prompt. Necessary documentation as well as source code is provided
- Complement coding Complement Coding takes as input a vector of feature values, each with an associated lower and upper limit used for normalization. It normalizes each feature value and calculates its complement.
- KiNnNeSS KInNeSS is an open source neural simulation software package that allows to design, simulate and analyze the behavior of networks of hundreds to thousands of branched multi-compartmental neurons with realistic biophysical properties .
- The SMART network This entry contains the software, implemented in the KDE Integrated NeuroSimulation Software (KInNeSS ) that simulates the Synchronous Matching Adaptive Resonance Theory. SMART was first described in Grossberg and Versace (2008): Spikes, synchrony, and attentive learning by laminar thalamo-cortical circuits.
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July 2009
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Please refrain from introducing inappropriate pages to Wikipedia. Doing so is not in accordance with our policies. For more information about creating articles, you may want to read Wikipedia:Your first article. If you would like to experiment, please use the sandbox. Thank you. Do not upload, or create any further pages that have copyright or image use policy issues. Nja247 10:35, 30 July 2009 (UTC)
Hello, Maxversace, and welcome to Wikipedia! I hope you like the place and decide to stay. Here are some pages you might find helpful:
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