NDLI: The toad optic tectum as a recurrent on-center off-surround neural net with quenching threshold

Content Provider	IEEE Xplore Digital Library
Author	Betts, B.
Copyright Year	1988
Description	Author affiliation: Univ. of Southern California, Los Angeles, CA, USA (Betts, B.)
Abstract	The authors demonstrate that the toad optic tectum has memory and can implement a recurrent on-center off-sound neural net with quenching threshold. The main addition to previous tectal models is the quenching threshold, which is defined as a threshold that determines which features are transferred into memory. This implies that the memory is efferently organized, that is, that it stores prey and mate features. An alternative, afferently organized model would store all R2 and R3 input in separate memories and provide a selection mechanism to determine what information is transferred out of memory and is integrated to form efferent commands. The author's model augments the quenching threshold mechanism by demonstrating that TP inhibition can rely on the differential sensitivity of R2 and R3 cells to suppress selectively certain features from memory. In this way, it can modulate the quality as well as the quantity of features stored in memory.
Starting Page	47
Ending Page	54
File Size	574983
Page Count	8
File Format	PDF
DOI	10.1109/ICNN.1988.23911
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1988-07-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain Neural networks Nervous system
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

Dual encoding as a means of improving neural net performance

Joining distributed pattern processing and homeostatic plasticity in recurrent on-center off-surround shunting networks: noise, saturation, short-term memory, synaptic scaling, and bdnf (2011).

Training asymptotically stable recurrent neural networks

A study on the bursting firing phenomena in neural network with the hardware neuron model

Neuron layer with reciprocal inhibition as a mechanism of random choice

Combinational neural net for adaptive filtering

Matcher neural networks

After-hyperpolarization currents and. (2010).

A Study of Corporate Financial Crisis Prediction System: Based on BP Artificial Neural Network

The toad optic tectum as a recurrent on-center off-surround neural net with quenching threshold

Similar Documents

Dual encoding as a means of improving neural net performance

Joining distributed pattern processing and homeostatic plasticity in recurrent on-center off-surround shunting networks: noise, saturation, short-term memory, synaptic scaling, and bdnf (2011).

Training asymptotically stable recurrent neural networks

A study on the bursting firing phenomena in neural network with the hardware neuron model

Neuron layer with reciprocal inhibition as a mechanism of random choice

Combinational neural net for adaptive filtering

Matcher neural networks

After-hyperpolarization currents and. (2010).

A Study of Corporate Financial Crisis Prediction System: Based on BP Artificial Neural Network

The toad optic tectum as a recurrent on-center off-surround neural net with quenching threshold