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. 2023 Mar 28;42(3):112096.
doi: 10.1016/j.celrep.2023.112096. Epub 2023 Feb 22.

Locomotion-induced gain of visual responses cannot explain visuomotor mismatch responses in layer 2/3 of primary visual cortex

Anna Vasilevskaya  1 , Felix C Widmer  1 , Georg B Keller  1 , Rebecca Jordan  2
Affiliations

Locomotion-induced gain of visual responses cannot explain visuomotor mismatch responses in layer 2/3 of primary visual cortex

Anna Vasilevskaya et al. Cell Rep. .

Abstract

The aim of this work is to provide a comment on a recent paper by Muzzu and Saleem (2021), which claims that visuomotor mismatch responses in mouse visual cortex can be explained by a locomotion-induced gain of visual halt responses. Our primary concern is that without directly comparing these responses with mismatch responses, the claim that one response can explain the other appears difficult to uphold, more so because previous work finds that a uniform locomotion-induced gain cannot explain mismatch responses. To support these arguments, we analyze layer 2/3 calcium imaging datasets and show that coupling between visual flow and locomotion greatly enhances mismatch responses in an experience-dependent manner compared with halts in non-coupled visual flow. This is consistent with mismatch responses representing visuomotor prediction errors. Thus, we conclude that while feature selectivity might contribute to mismatch responses in mouse visual cortex, it cannot explain these responses.

Keywords: CP: Neuroscience; locomotion; neocortex; prediction error; predictive processing; primary visual cortex; vision.

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Conflict of interest statement

Declaration of interests The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Graphical summary of the key evidence that visuomotor mismatch responses in layer 2/3 of V1 arise from prediction error computation Prediction error computation consists of a subtractive (or divisive, see Spratling16) comparison between sensory input and a prediction of that sensory input, for instance based on movements like locomotion. This can be achieved using a balance of excitation and inhibition from sensory and prediction sources. The key pieces of evidence supporting the idea that visuomotor mismatch responses in layer 2/3 of V1 represent prediction error signals are as follows: (A) Mismatch responses cannot be replicated with the visual flow halts alone, uncoupled from locomotion.,, Here and in the subsequent panels of the figure, the black lines illustrate the mean population response of pyramidal cells in layer 2/3 of V1. (B) The responses cannot be explained by a uniform gain increase of visual responses during locomotion (explained in detail in the main text). The lines on the right illustrate the population responses to the different stimuli (orange: mismatch, gray: playback halt during stationary periods, purple: visual flow during locomotion, green: visual flow during stationary periods). (C) Responses likely cannot be explained by a surprise induced neuromodulatory signal, since calcium responses to local mismatches in small parts of the visual field evoke no pupil dilation (which is a proxy for neuromodulatory activity), but are equivalent in size to responses to full field mismatches (which do evoke pupil dilation). (D) Responses scale linearly with the degree of error between locomotion speed and visual flow speed., (E) Prediction errors should be computed from the difference between visual flow and locomotion speed, and visual flow and locomotion have opposing signs of influence on the membrane potential of layer 2/3 neurons, consistent with a subtractive comparison between the two sources of information. Somatostatin-positive interneurons are consistent with providing visually driven inhibition onto mismatch-responsive neurons. (F) Mismatch responses depend on the visuomotor coupling experience of the animal: mismatch responses are indistinguishable from passive visual flow halts if the animal is raised with no coupling between visual flow and locomotion.
Figure 2
Figure 2
Visuomotor coupling enhances mismatch responses in an experience-dependent manner (A) Schematics to show the three conditions in which responses to visual flow halts were assessed. The green line illustrates visual flow speed, and the purple line illustrates locomotion speed. Left: mice are stationary while observing a 1 s visual flow halt (playback halt, gray shading). Middle: mice are locomoting and observe a 1 s visual flow halt, but locomotion and visual flow are not coupled. Right: mice observe a 1 s visual flow halt while locomoting in a closed-loop condition. These events we refer to as visuomotor mismatches (orange shading). (B) Heatmaps of the average responses to visual flow halts corresponding to the three conditions in (A), sorted across 7,094 neurons. Top row: heatmaps were sorted independently for each condition. Bottom row: the same data but with heatmaps that were sorted according to the responses to playback (PB) halt, stationary (leftmost heatmap). Note, the correlations between responses in the different conditions were relatively low. (C) Average locomotion speed during the visual flow halt stimuli in each condition. (D) The correlation between locomotion speed and visual flow speed across the whole session was close to 0 in the open-loop condition and close to 1 in the closed-loop condition. Note, the only reason closed-loop correlation is less than 1 is due to the presentation of mismatches. (E) Population average responses to visual flow halt stimuli in the three conditions for mice raised with (left, coupled trained) and without (right, non-coupled trained) visuomotor coupling experience. Shading shows standard error of the mean. Lines below the plots indicate statistical differences between responses as color coded to the left (gray: not significant; black: p < 0.01; paired t test). The comparison being made for each line is indicated by the combination of colors on the left. (F) Mean responses to mismatch and PB halt during locomoting in coupled trained animals, in the early and late blocks (see STAR Methods) of closed-loop and open-loop sessions, respectively (where at least 7,000 neurons met the criterion of having at least three trials in a given condition). In the experimental paradigm, open-loop sessions always were always presented after closed-loop sessions. Thus, the longer the animal was exposed to an open-loop condition, the smaller the PB halt locomoting responses became. Error bars show standard error of the mean. n.s. p > 0.05, ∗∗∗p < 0.001, paired t test. (G) Population average responses to mismatch (orange) and PB halts during locomotion (purple) in coupled trained animals, in the early and late blocks (see STAR Methods) of closed-loop and open-loop sessions, respectively (where at least 7,000 neurons met the criterion of having at least three trials in a given condition). Shading shows standard error of the mean. Lines below the plots indicate statistical differences between responses as color coded to the left (gray: not significant; black: p < 0.01; paired t test). The comparison being made for each line is indicated by the combination of colors on the left.
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