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Analysis of Fluctuation-Induced Firing in the Presence of Inhibition
Found in: Neural Networks, IEEE - INNS - ENNS International Joint Conference on
By Chris Christodoulou, Trevor G Clarkson, John G Taylor, Guido Bugmann
Issue Date:July 2000
pp. 3115
This paper examines the computational role of inhibition as it moves towards balancing concurrent excitation using the biologically inspired Temporal Noisy-Leaky Integrator (TNLI) neuron model. The TNLI incorporates hyperpolarizing inhibition with negative...
 
Neural architectures for thinking, reasoning and being conscious
Found in: Neural Networks, IEEE - INNS - ENNS International Joint Conference on
By John G. Taylor, Matthew Hartley
Issue Date:June 2009
pp. 3104-3110
The human mind crucially thinks and reasons, all the while being conscious. Possible architectures to achieve the first two of these attributes are proposed, the first of these being based on those for the mental simulation loop suggested as being at the b...
 
Brain Informatics
Found in: IEEE Intelligent Systems
By Ning Zhong,Jeffrey M. Bradshaw,Jiming Liu,John G. Taylor
Issue Date:September 2011
pp. 16-21
Brain informatics (BI) is an emerging interdisciplinary and multidisciplinary research field that focuses on studying the mechanisms underlying the human information processing system. BI investigates the essential functions of the brain, ranging from perc...
 
Towards Understanding Images of the Mind
Found in: Neural Networks, IEEE - INNS - ENNS International Joint Conference on
By John G. Taylor
Issue Date:July 2000
pp. 1177
An important technique used in analyzing PET and fMRI, that of structural modeling, is briefly described, and the problems this presents in bridging the gap to the underlying neural networks described. Recent structural models for some tasks are summarized...
 
The Hidden Layer Associative Memory Model of Hippocampus
Found in: Neural Networks, IEEE - INNS - ENNS International Joint Conference on
By Winfried A. Fellenz, John G. Taylor
Issue Date:July 2000
pp. 2205
A recent model for fast associative memory [3] has shown to be an efficient solution to the storage of binary patterns and the recall from incomplete input. We extend this model to include more biological realistic constraints to serve as a model for the h...
 
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