To thrive in dynamic environments, animals can generate flexible behavior and rapidly adapt responses to a changing context and internal state. Examples of behavioral flexibility include faster stimulus responses when attentive and slower responses when distracted. Contextual  modulations may occur early in the cortical hierarchy and may be implemented via afferent projections from top-down pathways or neuromodulation onto sensory cortex . However, the computational mechanisms mediating the effects of such projections are not known. Here, we investigate the effects of afferent projections on the information processing speed of cortical circuits. Using a biologically plausible model based on recurrent networks of excitatory and inhibitory neurons arranged in cluster, we classify the effects of cell-type specific perturbations on the circuit 's stimulus-processing capability. We found that perturbations differentially controlled processing speed, leading to counterintuitive effects such as improved performance with increased input variance. Our theory explains the effects of all perturbations in terms of gain modulation, which controls the timescale of the circuit dynamics. We tested our model using large-scale electrophysiological recordings from the visual hierarchy in freely running mice, where  a decrease in single-cell  gain during locomotion explained the observed acceleration of visual processing speed . Our results establish a novel theory of cell-type specific perturbations linking connectivity, dynamics, and information processing via gain modulations .
To thrive in dynamic environments, animals must be capable of rapidly and flexibly adapting behavioral responses to a changing context and internal state. Examples of behavioral flexibility include faster stimulus responses when attentive and slower responses when distracted. Contextual or state-dependent modulations may occur early in the cortical hierarchy and may be implemented via top-down projections from cortico-cortical or neuromodulatory pathways . However, the computational mechanisms mediating the effects of such projections are not known. Here, we introduce a theoretical framework to classify the effects of cell-type specific top-down perturbations on the information processing speed of cortical circuits. Our theory demonstrates that perturbation effects on stimulus processing can be predicted by intrinsic gain modulation, which controls the timescale of the circuit dynamics. Our theory leads to counter-intuitive effects such as improved performance with increased input variance. We tested the model predictions using large-scale electrophysiological recordings from the visual hierarchy in freely running mice, where we found that a decrease in single-cell intrinsic gain during locomotion led to an acceleration of visual processing . Our results establish a novel theory of cell-type specific perturbations , applicable to top-down modulation as well as optogenetic and pharmacological manipulations. Our theory links connectivity, dynamics, and information processing via gain modulation .
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can generate flexible behavior and rapidly adapt
must be capable of rapidly and flexibly adapting behavioral
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or state-dependent
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afferent projections from top-down pathways or neuromodulation onto sensory cortex
top-down projections from cortico-cortical or neuromodulatory pathways
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investigate
introduce a theoretical framework to classify
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afferent projections
cell-type specific top-down perturbations
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Using a biologically plausible model based on recurrent networks of excitatory and inhibitory neurons arranged in cluster, we classify the effects of cell-type specific perturbations on the circuit 's stimulus-processing capability. We found that perturbations differentially controlled processing speed, leading to counterintuitive
Our theory demonstrates that perturbation effects on stimulus processing can be predicted by intrinsic gain modulation, which controls the timescale of the circuit dynamics. Our theory leads to counter-intuitive
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Our theory explains the effects of all perturbations in terms of gain modulation, which controls the timescale of the circuit dynamics. We tested our model
We tested the model predictions
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we found that
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intrinsic
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explained the observed
led to an
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speed
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linking
, applicable to top-down modulation as well as optogenetic and pharmacological manipulations. Our theory links
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modulations
modulation