Dataset Information

Learning enhances the relative impact of top-down processing in the visual cortex.

ABSTRACT: Theories have proposed that, in sensory cortices, learning can enhance top-down modulation by higher brain areas while reducing bottom-up sensory drives. To address circuit mechanisms underlying this process, we examined the activity of layer 2/3 (L2/3) excitatory neurons in the mouse primary visual cortex (V1) as well as L4 excitatory neurons, the main bottom-up source, and long-range top-down projections from the retrosplenial cortex (RSC) during associative learning over days using chronic two-photon calcium imaging. During learning, L4 responses gradually weakened, whereas RSC inputs became stronger. Furthermore, L2/3 acquired a ramp-up response temporal profile, potentially encoding the timing of the associated event, which coincided with a similar change in RSC inputs. Learning also reduced the activity of somatostatin-expressing inhibitory neurons (SOM-INs) in V1 that could potentially gate top-down inputs. Finally, RSC inactivation or SOM-IN activation was sufficient to partially reverse the learning-induced changes in L2/3. Together, these results reveal a learning-dependent dynamic shift in the balance between bottom-up and top-down information streams and uncover a role of SOM-INs in controlling this process.

SUBMITTER: Makino H

PROVIDER: S-EPMC4523093 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Learning enhances the relative impact of top-down processing in the visual cortex.

Makino Hiroshi H Komiyama Takaki T

Nature neuroscience 20150713 8

Theories have proposed that, in sensory cortices, learning can enhance top-down modulation by higher brain areas while reducing bottom-up sensory drives. To address circuit mechanisms underlying this process, we examined the activity of layer 2/3 (L2/3) excitatory neurons in the mouse primary visual cortex (V1) as well as L4 excitatory neurons, the main bottom-up source, and long-range top-down projections from the retrosplenial cortex (RSC) during associative learning over days using chronic tw ...[more]

PMID: 26167904

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Project description:Unified visual perception relies on the integration of bottom-up and top-down inputs in the primary visual cortex (V1), with top-down inputs known to provide behavior-related modulation on visual processing. However, the organization of top-down inputs in V1 remains unclear. Here, using optogenetics-assisted circuit mapping, we characterized how multiple top-down inputs from higher-order cortical and thalamic areas engage excitatory and inhibitory neurons in V1. Systematic layer- and cell-type-specific profiling of the innervation properties of top-down inputs ultimately revealed that each top-down input employs a unique laminar profile when innervating V1. These profiles partially overlap in superficial layers, bypass layer 4 (L4), and clearly segregate upon reaching deep layers. Specifically, inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) preferentially activate L6 neurons, while inputs from the ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) activate L5 neurons. Having defined the inputs, we conducted independent optogenetic activation studies and discovered that ORBvl and LP inputs selectively activate two types of pyramidal neurons (Pyrs) in L5: Pyr <-- ORBvl and Pyr <-- LP neurons, each with specific electrophysiological properties and gene expression profiles. Retrograde mapping subsequently revealed that Pyr <-- ORBvl neurons preferentially innervate subcortical areas and Pyr <-- LP neurons innervate cortical areas, indicating parallel processing of ORBvl and LP inputs in Pyr-type-specific subnetworks. Further, we found mutual inhibition between these two subnetworks, as LP inputs indirectly inhibit Pyr <-- ORBvl neurons and ORBvl inputs inhibit Pyr <-- LP neurons through local inhibitory neurons. Our study thus deepens understanding of the neuronal mechanisms involved in top-down modulation of visual processing by providing a valuable resource characterizing the layer- and cell-type-specific organization of top-down inputs in V1 and by revealing that L5 Pyr-type-specific subnetworks engage in parallel processing of corticocortical and thalamocortical top-down inputs.

Dataset Information

Learning enhances the relative impact of top-down processing in the visual cortex.

Publications

Learning enhances the relative impact of top-down processing in the visual cortex.

Similar Datasets

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