Distributed fading memory for stimulus properties in the primary visual cortex

  • It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (<= ~20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs.
Author:Danko NikolićORCiDGND, Stefan Häusler, Wolf SingerORCiDGND, Wolfgang Maass
Parent Title (English):PLoS biology
Place of publication:Lawrence, Kan.
Document Type:Article
Date of Publication (online):2009/12/22
Date of first Publication:2009/12/22
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2010/01/27
Issue:(12): e1000260
Page Number:19
First Page:1
Last Page:19
Copyright Nikolic et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Sammlung Biologie / Sondersammelgebiets-Volltexte
Licence (German):License LogoCreative Commons - Namensnennung 3.0