Histed, M. H. | bioRxiv Science

bioRxiv2018

Different inhibitory interneuron cell classes make distinct contributions to visual perception

While recent work has revealed how different inhibitory interneurons influence cortical responses to sensory stimuli, little is known about how their activity contributes to sensory perception. Here, we optogenetically stimulated different genetically defined interneurons (parvalbumin (PV), somatostatin (SST), vasoactive intestinal peptide (VIP)) in visual cortex (V1) of mice working at threshold in contrast increment or decrement detection tasks. The visual stimulus was paired with optogenetic stimulation to assess how enhancing V1 inhibitory neuron activity synchronously during cortical responses altered task performance. PV or SST activation impaired, while VIP stimulation improved, contrast increment detection. Notably, PV or SST stimulation also impaired contrast decrement detection, when opsin-evoked inhibition would exaggerate stimulus-evoked decrements in firing rate, and thus might improve performance. The impairment produced by PV or SST stimulation persisted throughout many weeks of testing. In contrast mice learned to reliably detect VIP activation in the absence of natural visual stimulation. Thus, different inhibitory signals make distinct contributions to visual contrast perception.

neuroscience↗

bioRxiv2017

Feedforward inhibition allows input summation to vary in recurrent cortical networks

Brain computations depend on how neurons transform inputs to spike outputs. Here, to understand input-output transformations in cortical networks, we recorded spiking responses from visual cortex (V1) of awake mice of either sex while pairing sensory stimuli with optogenetic perturbation of excitatory and parvalbumin-positive inhibitory neurons. We found V1 neurons average responses were primarily additive (linear). We used a recurrent cortical network model to determine if these data, as well as past observations of nonlinearity, could be described by a common circuit architecture. The model showed cortical input-output transformations can be changed from linear to sublinear with moderate ([~]20%) strengthening of connections between inhibitory neurons, but this change depends on the presence of feedforward inhibition. Thus, feedforward inhibition, a common feature of cortical circuitry, enables networks to flexibly change their spiking responses via changes in recurrent connectivity.\n\nSignificance statementBrains are made up of neural networks that process information by receiving input activity and transforming those inputs into output activity. We use optogenetic manipulations in awake mice to expose how a transformation in a cortical network depends on internal network activity. Combining numerical simulations with our observations uncovers that transformation depend critically on feedforward inhibition - the fact that inputs to the cortex often make strong connections on both excitatory and inhibitory neurons.

neuroscience↗