WITHDRAWN: Visual information is broadcast among cortical areas in discrete channels

Yu, Yiyi; Stirman, Jeffery N.; Dorsett, Christopher R.; Smith, Spencer LaVere

doi:10.1101/2023.12.24.573101

Cited by 2 publications

(1 citation statement)

References 58 publications

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“…Thus, V1 neurons are most likely to synapse with other V1 neurons that share similar orientation 1,3,35 or direction tuning 1,3 and exhibit correlated responses to natural stimuli 2,4 . Indeed, there is evidence that this like-for-like bias extends beyond primary visual cortex, with higher noise-correlations observed across higher-visual areas between neurons with similar tuning properties, suggesting that information is propagated both within and across cortical regions in distinct, segregated channels 36 .…”

Section: Discussionmentioning

confidence: 99%

Prediction of future input explains lateral connectivity in primary visual cortex

Klavinskis-Whiting,

Fristed,

Singer

et al. 2024

Preprint

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Neurons in primary visual cortex (V1) show a remarkable functional specificity in their pre- and postsynaptic partners. Recent work has revealed a variety of wiring biases describing how the short- and long-range connections of V1 neurons relate to their tuning properties. However, it is less clear whether these connectivity rules are based on some underlying principle of cortical organization. Here, we show that the functional specificity of V1 connections emerges naturally in a recurrent neural network optimized to predict upcoming sensory inputs for natural visual stimuli. This temporal prediction model reproduces the complex relationships between the connectivity of V1 neurons and their orientation and direction preferences, the tendency of highly connected neurons to respond more similarly to natural movies, and differences in the functional connectivity of excitatory and inhibitory V1 populations. Together, these findings provide a principled explanation for the functional and anatomical properties of early sensory cortex.

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Section: Discussionmentioning

confidence: 99%

Prediction of future input explains lateral connectivity in primary visual cortex

Klavinskis-Whiting,

Fristed,

Singer

et al. 2024

Preprint

View full text Add to dashboard Cite

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Functional organization and natural scene responses across mouse visual cortical areas revealed with encoding manifolds

Dyballa,

Field,

Stryker

et al. 2024

Preprint

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We have created "encoding manifolds" to reveal the overall responses of a brain area to a variety of stimuli. Encoding manifolds organize response properties globally: each point on an encoding manifold is a neuron, and nearby neurons respond similarly to the stimulus ensemble in time. We previously found, using a large stimulus ensemble including optic flows, that encoding manifolds for the retina were highly clustered, with each cluster corresponding to a different ganglion cell type. In contrast, the topology of the V1 manifold was continuous. Now, using responses of individual neurons from the Allen Institute Visual Coding-Neuropixels dataset in the mouse, we infer encoding manifolds for V1 and for five higher cortical visual areas (VISam, VISal, VISpm, VISlm, and VISrl). We show here that the encoding manifold topology computed only from responses to various grating stimuli is also continuous, not only for V1 but also for the higher visual areas, with smooth coordinates spanning it that include, among others, orientation selectivity and firing-rate magnitude. Surprisingly, the encoding manifold for gratings also provides information about natural scene responses. To investigate whether neurons respond more strongly to gratings or natural scenes, we plot the log ratio of natural scene responses to grating responses (mean firing rates) on the encoding manifold. This reveals a global coordinate axis organizing neurons' preferences between these two stimuli. This coordinate is orthogonal (i.e., uncorrelated) to that organizing firing rate magnitudes in VISp. Analyzing layer responses, a preference for gratings is concentrated in layer 6, whereas preference for natural scenes tends to be higher in layers 2/3 and 4. We also find that preference for natural scenes dominates the responses of neurons that prefer low (0.02 cpd) and high (0.32 cpd) spatial frequencies, rather than intermediate ones (0.04 to 0.16 cpd). Conclusion: while gratings seem limited and natural scenes unconstrained, machine learning algorithms can reveal subtle relationships between them beyond linear techniques.

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

Cited by 2 publications

References 58 publications

Prediction of future input explains lateral connectivity in primary visual cortex

Prediction of future input explains lateral connectivity in primary visual cortex

Functional organization and natural scene responses across mouse visual cortical areas revealed with encoding manifolds

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