ArticleBMC neuroscience2015
Summation of connectivity strengths in the visual cortex reveals stability of neuronal microcircuits after plasticity.
Article in BMC neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 14 citations in OpenAlex.
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6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundWithin sensory systems, neurons are continuously affected by environmental stimulation. Recently, we showed that, on cell-pair basis, visual adaptation modulates the connectivity strength between similarly tuned neurons to orientation and we suggested that, on a larger scale, the connectivity strength between neurons forming sub-networks could be maintained after adaptation-induced-plasticity. In the present paper, based on the summation of the connectivity strengths, we sought to examine how, within cell-assemblies, functional connectivity is regulated during an exposure-based adaptation.
resultsUsing intrinsic optical imaging combined with electrophysiological recordings following the reconfiguration of the maps of the primary visual cortex by long stimulus exposure, we found that within functionally connected cells, the summed connectivity strengths remain almost equal although connections among individual pairs are modified. Neuronal selectivity appears to be strongly associated with neuronal connectivity in a "homeodynamic" manner which maintains the stability of cortical functional relationships after experience-dependent plasticity.
conclusionsOur results support the "homeostatic plasticity concept" giving new perspectives on how the summation in visual cortex leads to the stability within labile neuronal ensembles, depending on the newly acquired properties by neurons.
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