Cognitive & Neural Systems
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The steady expansion of neuroscience at Boston University (BU) has created the opportunity to pursue core educational and research missions of the former Cognitivea and Neural Systems Department within broader, university-wide initiatives.
As of Fall 2011, activities formerly coordinated within CNS have been distributed to other teaching and research units within Boston University. Although the CNS Department as such has been dissolved, the continuing Graduate Program in Cognitive & Neural Systems will serve doctoral and masters students who are already enrolled in CNS. A description of this program and its requirements can be found on the Graduate School of Arts & Sciences (GRS) Programs website.
This reorganization recognizes impressive strides in neural modeling and neural technology across many diverse academic units at BU, and promotes interactions of faculty from the former CNS Department with colleagues in other units.
Website: cns-web.bu.edu
All materials in OpenBU are subject to Title 17 of the U.S. Code.
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CAS/CNS Technical Reports [485]
Center for Adaptive Systems / Cognitive and Neural Systems technical reports series
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Engaging the articulators enhances perception of concordant visible speech movements
(American Speech-Language-Hearing Association, 2019-10-25)PURPOSE This study aimed to test whether (and how) somatosensory feedback signals from the vocal tract affect concurrent unimodal visual speech perception. METHOD Participants discriminated pairs of silent visual ... -
Contrast-sensitive perceptual grouping and object-based attention in the laminar circuits of primary visual cortex
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-03)Recent neurophysiological studies have shown that primary visual cortex, or Vl, does more than passively process image features using the feedforward filters suggested by Hubel and Wiesel. It also uses horizontal interactions ... -
A laminar cortical model of stereopsis and 3D surface perception: Closure and da Vinci stereopsis
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-09)A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface ... -
PointMap: A real-time memory-based learning system with on-line and post-training pruning
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-12)A memory-based learning system called PointMap is a simple and computationally efficient extension of Condensed Nearest Neighbor that allows the user to limit the number of exemplars stored during incremental learning. ... -
A Wireless Brain-Machine Interface for Real-Time Speech Synthesis
(Public Library of Science, 2009-12-9)BACKGROUND. Brain-machine interfaces (BMIs) involving electrodes implanted into the human cerebral cortex have recently been developed in an attempt to restore function to profoundly paralyzed individuals. Current BMIs for ... -
Hippocampal Conceptual Representations and Their Reward Value
(Frontiers Research Foundation, 2010-02-03) -
Mindboggle: Automated Brain Labeling with Multiple Atlases
(BioMed Central, 2005-10-5)BACKGROUND: To make inferences about brain structures or activity across multiple individuals, one first needs to determine the structural correspondences across their image data. We have recently developed Mindboggle as ... -
The Role of Edges and Line-Ends in Illusory Contour Formation
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-04)Illusory contours can be induced along directions approximately collinear to edges or approximately perpendicular to the ends of lines. Using a rating scale procedure we explored the relation between the two types of ... -
Fuzzy ART
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-12-15)Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks ... -
Spatial Pattern Learning, Catastophic Forgetting and Optimal Rules of Synaptic Transmission
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-03)It is a neural network truth universally acknowledged, that the signal transmitted to a target node must be equal to the product of the path signal times a weight. Analysis of catastrophic forgetting by distributed codes ...
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