Selective representations of texture and motion in mouse higher visual areas

WITHDRAWN: Visual information is broadcast among cortical areas in discrete channels

“…The imaging regions were matched for retinotopy so that the neurons in the simultaneously imaged areas had overlapping receptive fields ( RFs ). Calcium signals were used to infer probable spike trains for each neuron, as our previous study (Yu et al, 2022). We mapped RFs for individual neurons and populations using small patches of drifting gratings (Figure S1B, C).…”

“…Calcium imaging processing was carried out using custom MATLAB codes (Yu et al, 2022). Two-photon calcium imaging was motion corrected using Suit2p subpixel registration module (Pachitariu et al, 2016).…”

“…Studies of longer-range, millimeter-scale networks typically lack cellular resolution, but there are general biases observed. Neurons in V1 and HVAs respond to diverse visual stimuli (Yu et al, 2022; Vries et al, 2020) and are sensitive to a broad range of features including orientation and spatiotemporal frequencies (Andermann et al, 2011; Marshel et al, 2011). Although individual V1 neurons broadcast axonal projections to multiple HVAs (Han et al, 2018), the spatiotemporal frequency preferences of these feedforward projections generally match those of the target HVAs (Glickfeld et al, 2013; Han and Bonin, 2023).…”

“…In the current study, we investigated the degree of discreteness of the V1-HVA functional networks in direction and frequency information processing, by measuring the noise correlations ( NC , also called spike count correlation Vinci et al (2016)) between functional tuning groups of neurons. Functional tuning groups were defined using an unbiased clustering approach (Han et al, 2022; Yu et al, 2022; Baden et al, 2016). Large field-of-view ( FOV ) calcium imaging enables us to densely sample across millimeter cortical space, which allows us to simultaneously observe large and dense samples of neurons in these tuning groups to analyze NCs within- and-across cortical areas (Yu et al, 2021; Stirman et al, 2016).…”

Top-down perceptual inference shaping the activity of early visual cortex

“…The learned representation is nonlinear therefore standard techniques suitable for establishing linear response properties [40] are not suitable to characterize the sensitivities of model V2 neurons. Inspired by extensive evidence supporting that V2 neurons are sensitive to texture-like structures [16, 20, 41], we used synthetic texture patches to explore the properties of the V2 representation that TDVAE learned on natural images [42].…”