CNS Articles

Articles listed below focus on analysis and applications of neural network systems originally developed by CELEST faculty, including ART, ARTMAP, and BCS/FCS.

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View-invariant object category learning, recognition, and search: How spatial and object attention are coordinated using surface-based attentional shrouds (2009)
Categories Topics: Biological Learning, Models: Modified ART,
Author(s) Grossberg, S. | Mingolla, E. | Fazl, A. |
Abstract How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are ...

GUI4GUI user guide (2009)
Categories Topics: Other, Applications: Other, Models: Other,
Abstract Frequently, a computer program requires input parameters to define a specific application prior to running it. For codes that require few input parameters, the usual method to define these parameters is to store them in a ...

Biased ART: A neural architecture that shifts attention toward previously disregarded features following an incorrect prediction (2009)
Categories Topics: Machine Learning, Models: ARTMAP,
Author(s) Carpenter, G.A. | Gaddam, C.S. |
Abstract Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved ...

Self-supervised ARTMAP (2009)
Categories Topics: Machine Learning, Models: ARTMAP,
Author(s) Amis, G.P. | Carpenter, G.A. |
Abstract Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input ...

ARTSCENE: A Neural System for Natural Scene Classification (2009)
Categories Topics: Image Analysis, Machine Learning, Models: Fuzzy ARTMAP, Modified ART,
Author(s) Grossberg, S. | Huang, T.R. |
Abstract How do humans rapidly recognize a scene? How can neural models capture this biological competence to achieve state-of-the-art scene classification? The ARTSCENE neural system classifies natural scene photographs by using ...

Speaker normalization using cortical strip maps: A neural model for steady state vowel categorization (2008)
Categories Topics: Speech and Hearing, Applications: Human-Machine Interface, Models: Fuzzy ARTMAP,
Author(s) Ames, H. | Grossberg, S. |
Abstract Auditory signals of speech are speaker dependent, but representations of language meaning are speaker independent. The transformation from speaker-dependent to speaker-independent language representations enables speech to ...

Temporal dynamics of decision-making during motion perception in the visual cortex (2008)
Categories Topics: Image Analysis, Models: Boundary Contour System,
Author(s) Grossberg, S. | Pilly, P.K. |
Abstract How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical ?decision neurons.? A ...

Unifying multiple knowledge domains using the ARTMAP information fusion system (2008)
Categories Topics: Image Analysis, Applications: Information Fusion, Models: ARTMAP,
Author(s) Carpenter, G.A. | Ravindran, A. |
Abstract Sensors working at different times, locations, and scales, and experts with different goals, languages, and situations, may produce apparently inconsistent image labels that are reconciled by their implicit underlying ...

KInNeSS: A modular framework for computational neuroscience (2008)
Categories Topics: Neural Hardware, Other, Models: Compartmental Modeling,
Author(s) Ames, H. | Gorchetchnikov, A. | Jasmin Leveille | Versace, M. |
Abstract Making use of very detailed neurophysiological, anatomical, and behavioral data to build biologically-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have ...

Spikes, synchrony, and attentive learning by laminar thalamocortical circuits (2008)
Categories Topics: Biological Learning, Models: Modified ART,
Author(s) Grossberg, S. | Versace, M. |
Abstract This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and ...

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