Signal propagation in cortical networks: a digital signal processing approach

This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characteriz...

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Main Authors: Francisco A Rodrigues, Luciano da F Costa
Format: Article
Language:English
Published: Frontiers Media S.A. 2009-07-01
Series:Frontiers in Neuroinformatics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/neuro.11.024.2009/full
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spelling doaj-914bcc86eadc4f48b2817bc410e3078c2020-11-24T21:03:12ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962009-07-01310.3389/neuro.11.024.2009610Signal propagation in cortical networks: a digital signal processing approachFrancisco A Rodrigues0Luciano da F Costa1University of São PauloUniversity of São PauloThis work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks.http://journal.frontiersin.org/Journal/10.3389/neuro.11.024.2009/fullnetworkscorticocortical networksdigital signal processinggraphs
collection DOAJ
language English
format Article
sources DOAJ
author Francisco A Rodrigues
Luciano da F Costa
spellingShingle Francisco A Rodrigues
Luciano da F Costa
Signal propagation in cortical networks: a digital signal processing approach
Frontiers in Neuroinformatics
networks
corticocortical networks
digital signal processing
graphs
author_facet Francisco A Rodrigues
Luciano da F Costa
author_sort Francisco A Rodrigues
title Signal propagation in cortical networks: a digital signal processing approach
title_short Signal propagation in cortical networks: a digital signal processing approach
title_full Signal propagation in cortical networks: a digital signal processing approach
title_fullStr Signal propagation in cortical networks: a digital signal processing approach
title_full_unstemmed Signal propagation in cortical networks: a digital signal processing approach
title_sort signal propagation in cortical networks: a digital signal processing approach
publisher Frontiers Media S.A.
series Frontiers in Neuroinformatics
issn 1662-5196
publishDate 2009-07-01
description This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks.
topic networks
corticocortical networks
digital signal processing
graphs
url http://journal.frontiersin.org/Journal/10.3389/neuro.11.024.2009/full
work_keys_str_mv AT franciscoarodrigues signalpropagationincorticalnetworksadigitalsignalprocessingapproach
AT lucianodafcosta signalpropagationincorticalnetworksadigitalsignalprocessingapproach
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