NDLI: A synaptic learning rule based on the temporal coincidence of pre- and postsynaptic activity

Content Provider	IEEE Xplore Digital Library
Author	Denham, M.J. Denham, S.L.
Copyright Year	2001
Description	Author affiliation: Sch. of Comput., Plymouth Univ., UK (Denham, M.J.)
Abstract	In biological neural networks, synaptic connections and their modification by Hebbian forms of associative learning have been shown in recent years to have quite complex dynamic characteristics. It is clear that in building neural networks of "spiking" neurons for spatio-temporal pattern learning and recognition, such dynamic characteristics may play an important role. We review the neuroscientific evidence for the dynamic characteristics of learning and memory, and propose a computational associative learning rule which takes account of this evidence. We show that the application of this learning rule allows us to mimic in a computationally simple way certain characteristics of the biological learning process, in particular temporal asymmetry effects similar to those observed experimentally.
Sponsorship	Int. Neural Network Soc.
Starting Page	1
Ending Page	6
File Size	591604
Page Count	6
File Format	PDF
ISBN	0780370449
ISSN	10987576
DOI	10.1109/IJCNN.2001.938981
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biology computing Neurons Timing Frequency Adaptive systems Computer networks Biological neural networks Neural networks Character recognition Pattern recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Spike-Based Learning Rules and Stabilization of Persistent Neural Activity (2000)

Character Recognition using Spiking Neural Networks

Temporal pattern recognition using a spiking neural network with delays

Dynamics-based active learning for handwritten character recognition

Statistical approach to unsupervised recognition of spatio-temporal patterns by spiking neurons

Spike-Based Learning Rules and Stabilization of Persistent Neural Activity (2000)

A new approach to neural networks for character recognition

Spiking neural network for visual pattern recognition

Spike-Based Learning Rules and Stabilization of (2000)

A synaptic learning rule based on the temporal coincidence of pre- and postsynaptic activity

Similar Documents

Spike-Based Learning Rules and Stabilization of Persistent Neural Activity (2000)

Character Recognition using Spiking Neural Networks

Temporal pattern recognition using a spiking neural network with delays

Dynamics-based active learning for handwritten character recognition

Statistical approach to unsupervised recognition of spatio-temporal patterns by spiking neurons

Spike-Based Learning Rules and Stabilization of Persistent Neural Activity (2000)

A new approach to neural networks for character recognition

Spiking neural network for visual pattern recognition

Spike-Based Learning Rules and Stabilization of (2000)

A synaptic learning rule based on the temporal coincidence of pre- and postsynaptic activity