NeuroImageNeurosciencePeer-reviewed journal article
Attentional effects on local V1 microcircuits explain selective V1-V4 communication
Christini KatsanevakiiD, André M. BastosiD, Hayriye CagnaniD, Conrado A. BosmaniD, Karl John FristoniD, Pascal FriesiD
Abstract
Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modeled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing. HIGHLIGHTSO_LIWe model selective visual attention in macaques using Dynamic Causal Modeling. C_LIO_LIIntrinsic V1 modulation can explain attention effects in V1-V4 communication. C_LIO_LIModulation of superficial and granular inhibition is key to induce the effects. C_LIO_LIThose modulations increase V1-V4 communication in a feedforward manner. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/484223v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1cc79a7org.highwire.dtl.DTLVardef@146e6bdorg.highwire.dtl.DTLVardef@1d6bd6borg.highwire.dtl.DTLVardef@12dd663_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: non-human primate
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 14
- FWCI
- 2.09
- Field percentile
- top 13%
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