Publikationsdatum:
2010-01-30
Beschreibung:
Correlated spiking is often observed in cortical circuits, but its functional role is controversial. It is believed that correlations are a consequence of shared inputs between nearby neurons and could severely constrain information decoding. Here we show theoretically that recurrent neural networks can generate an asynchronous state characterized by arbitrarily low mean spiking correlations despite substantial amounts of shared input. In this state, spontaneous fluctuations in the activity of excitatory and inhibitory populations accurately track each other, generating negative correlations in synaptic currents which cancel the effect of shared input. Near-zero mean correlations were seen experimentally in recordings from rodent neocortex in vivo. Our results suggest a reexamination of the sources underlying observed correlations and their functional consequences for information processing.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2861483/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉 〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2861483/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Renart, Alfonso -- de la Rocha, Jaime -- Bartho, Peter -- Hollender, Liad -- Parga, Nestor -- Reyes, Alex -- Harris, Kenneth D -- DC-005787-01A1/DC/NIDCD NIH HHS/ -- DC009947/DC/NIDCD NIH HHS/ -- MH073245/MH/NIMH NIH HHS/ -- R01 DC009947/DC/NIDCD NIH HHS/ -- R01 DC009947-02/DC/NIDCD NIH HHS/ -- R01 MH073245/MH/NIMH NIH HHS/ -- R01 MH073245-05/MH/NIMH NIH HHS/ -- New York, N.Y. -- Science. 2010 Jan 29;327(5965):587-90. doi: 10.1126/science.1179850.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA. arenart@andromeda.rutgers.edu〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20110507" target="_blank"〉PubMed〈/a〉
Schlagwort(e):
Action Potentials
;
Algorithms
;
Animals
;
Cerebral Cortex/cytology/*physiology
;
Computer Simulation
;
Excitatory Postsynaptic Potentials
;
Inhibitory Postsynaptic Potentials
;
*Models, Neurological
;
Nerve Net/*physiology
;
Neural Inhibition
;
Neural Pathways/*physiology
;
Neurons/*physiology
;
Rats
;
Rats, Sprague-Dawley
;
Synapses/*physiology
;
*Synaptic Potentials
;
Synaptic Transmission
Print ISSN:
0036-8075
Digitale ISSN:
1095-9203
Thema:
Biologie
,
Chemie und Pharmazie
,
Informatik
,
Medizin
,
Allgemeine Naturwissenschaft
,
Physik
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