A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

Abstract

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes the cortical activity of nearly 60,000 neurons from six visual areas, four layers, and 12 transgenic mouse lines in a total of 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons on the basis of joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.

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Fig. 1: A standardized systems neuroscience data pipeline to map visual responses.
Fig. 2: Neurons exhibit diverse responses to visual stimuli.
Fig. 3: Tuning properties reveal functional differences across areas and Cre lines.
Fig. 4: Population correlations have heterogeneous impact on decoding performance.
Fig. 5: Neural activity is extremely variable, and this variability is not accounted for by running behavior.
Fig. 6: Correlated response variability reveals functional classes of neurons.
Fig. 7: Validation of class labels by model performance.

Data availability

This is an openly available dataset, accessible via a dedicated web portal (http://observatory.brain-map.org/visualcoding), and a Python-based API, the AllenSDK (http://alleninstitute.github.io/AllenSDK).

Code availability

Code for analyses presented in this paper is available at https://github.com/alleninstitute/visual_coding_2p_analysis.

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Acknowledgements

We thank the Animal Care, Transgenic Colony Management, and Lab Animal Services for mouse husbandry. We thank Z. J. Huang of Cold Spring Harbor Laboratory for use of the Fezf2-CreER line. We thank D. Denman, J. Siegle, Y. Billeh, and A. Arkhipov for critical feedback on the manuscript. This work was supported by the Allen Institute and in part by NSF DMS-1514743 (E.S.B.), the Falconwood Foundation (C.K.), the Center for Brains, Minds & Machines funded by NSF Science and Technology Center Award CCF-1231216 (C.K.), the Natural Sciences and Engineering Research Council of Canada (S.J.), NIH grant DP5OD009145 (D.W.), NSF CAREER Award DMS-1252624 (D.W.), Simons Investigator Award in Mathematical Modeling of Living Systems (D.W.), and NIH grant 1R01EB026908-01 (M.A.B., D.W.). We thank A. Jones for providing the critical environment that enabled our large-scale team effort. We thank the Allen Institute founder, Paul G. Allen, for his vision, encouragement, and support.

Author information

S.E.J.d.V., M.A.B., K.R., M.G., T.K., S.M., S.O., J.W., H.Z., C.D., L.N., A.B., J.W.P., R.C.R. and C.K. conceived of and designed the experiment. J.A.L., T.K., P.H., A.L., C.S., D.S. and C.F. built and maintained the hardware. S.E.J.d.V., J.A.L., M.A.B., G.K.O., D.F., N.C., L.K., W.W., D.W., R.V., C.B., B.B., T.D., J.G., T.G., S.J., N.K., C.L., F. Lee, F. Long, J.P., N.S., D.M.W., J.Z. and L.N. developed algorithms and software, including the SDK and website. K.R., N. Berbesque, N. Bowles, S.C., L.C., A.C., S.D.C., M.E., N.G., F.G., R.H., L.H., U.K., J.L., J.D.L., R.L., E.L., L.L., J.L., K.M., T.N., M.R., S.S., C.W. and A.W. collected data. J.A.L., P.A.G., S.E.J.d.V. and M.A.B. supervised the work. S.E.J.d.V., J.A.L., M.A.B., G.K.O., M.O., N.C., P.L., D.M., J.S., E.S.B. and R.V. analyzed data. C.T. and W.W. provided project administration. S.E.J.d.V., J.A.L. and M.A.B. wrote the paper with input from P.A.G., G.K.O., M.O., N.C., P.L., D.M., R.C.R., M.G. and C.K.

Correspondence to Saskia E. J. de Vries or Jerome A. Lecoq or Michael A. Buice.

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Extended data

Extended Data Fig. 1 Spontaneous and evoked event magnitude.

a, Pawplot and box plots summarizing the mean event magnitude for neurons during the 5 minute spontaneous activity (mean luminance gray) stimulus. For a description of the visualization see Fig. 3. The box shows the quartiles of the data, and the whiskers extend to 1.5 times the interquartile range. Points outside this range are shown as outliers. See Extended Data Figure 3 for sample sizes. b, Pawplot and box plots summarizing the maximum evoked event magnitude for neurons’ responses to drifting gratings. See Extended Data Figure 3 for sample sizes.

Extended Data Fig. 2 Response visualizations.

Conventional tuning curves for drifting grating responses for one neuron. a, Direction tuning plotted at the preferred temporal frequency (4 Hz) (mean ± sem across 15 trials). Dotted line represents the mean response to the blank sweep. b, Temporal frequency tuning plotted at the preferred grating direction (270°) (mean ± sem). c, Heatmap of the direction and temporal frequency responses for cell, showing any possible interaction of direction and temporal frequency. d, All 15 trials at the preferred direction and temporal frequency, 2 second grating presentation is indicated by pink shading. The mean event magnitude is represented by intensity of the dot to the right of the trial. e, All trials are clustered, with the strongest response in the center and weaker responses on the outside. f, Clusters are plotted on a “Star plot”. Arms indicated the direction of grating motion, arcs indicate the temporal frequency of the grating, with the lowest in the center and the highest at the outside. Clusters of red dots are located at the intersection and arms and arcs, representing the trial responses at that condition. Tuning curves for static gratings for one neuron. g, Orientation tuning plotted at the preferred spatial frequency (0.04 cpd) for each of the four phases. (mean ± sem across 50 trials) Dotted line represents the mean response to the blank sweep. h, Spatial frequency tuning plotted at the preferred orientation (90°) for each of the four phases (mean ± sem). i, Heatmap of the orientation and spatial frequency at the preferred phase j, All trials at the preferred orientation, spatial frequency and phase, the 250 ms grating presentation is indicated by pink shading. The mean event magnitude is represented by the intensity of the dot to the right of the trial. k, All trials are clustered, with the strongest response in the center and weaker responses on the outside. l, Clusters are placed on a “Fan plot”. Arms represent the orientation and arcs represent the spatial frequency of the grating. At each intersection, there are four lobes of clustered dots, one for each phase at that grating condition. Responses to natural scenes for one neuron. m, Responses to each image presented (mean ± sem across 50 trials). Dotted line represents the mean response to the blank sweep. n, All trials of the image which elicited the largest mean response, the 250ms image presentation is indicated by pink shading. The mean event magnitude is represented by the intensity of the dot to the right of the trial. Trials are sorted o, and are plotted on a “Corona plot” p, Each ray represents the response to one image, with the strongest response on the inside and weaker responses at the outside. Responses to natural movies for one neuron. q, Responses of one neuron’s response to each of 10 trials of the natural movie. r, Responses are plotted on a “Track plot”. Each red ring represents the activity of the cell to one trial, proceed clockwise from the top of the track. The outer blue track represents the mean response across all ten trials.

Extended Data Fig. 3 Responsiveness to drifting gratings.

a, Table summarizing the numbers of experiments (expts) and neurons imaged for each Cre line, layer, area combination in response to drifting grating stimulus and the number, and percent, of neurons that were responsive to the drifting grating stimulus. b, Strip plots of the percent of neurons responsive to the drifting grating stimulus for each experiment.

Extended Data Fig. 4 Responsiveness to static gratings.

a, Table summarizing the numbers of experiments and neurons imaged for each Cre line, layer, area combination in response to static grating stimulus and the number, and percent, of neurons that were responsive to the static grating stimulus. b, Strip plots of the percent of neurons responsive to the static grating stimulus for each experiment.

Extended Data Fig. 5 Responsiveness to locally sparse noise.

a, Table summarizing the numbers of experiments (expts) and neurons imaged for each Cre line, layer, area combination in response to locally sparse noise stimulus and the number, and percent, of neurons that were responsive to the locally sparse noise stimulus. b, Strip plots of the percent of neurons responsive to the locally sparse noise stimulus for each experiment.

Extended Data Fig. 6 Responsiveness to natural scenes.

a, Table summarizing the numbers of experiments (expts) and neurons imaged for each Cre line, layer, area combination in response to locally sparse noise stimulus and the number, and percent, of neurons that were responsive to the locally sparse noise stimulus. b, Strip plots of the percent of neurons responsive to the locally sparse noise stimulus for each experiment.

Extended Data Fig. 7 Responsiveness to natural movies.

a, Table summarizing the numbers of experiments (expts) and neurons imaged for each Cre line, layer, area combination in response to any of the natural movie stimuli and the number, and percent, of neurons that were responsive to the natural movie stimuli. b, Strip plots of the percent of neurons responsive to the natural movie stimuli for each experiment.

Extended Data Fig. 8 Populations for running correlation analysis.

Table summarizing the number of experiments and neurons, for each Cre line, layer, area combination, included in the running correlation analysis. These are from sessions in which the mouse was running between 20–80% of the time.

Extended Data Fig. 9 Populations for wavelet model analysis.

Table summarizing the number of experiments and neurons for each Cre line, layer, area combination for which wavelet models were fit. The neurons had to be present in all three imaging sessions to be included.

Supplementary information

Supplementary Information

Supplementary Figs. 1–24.

Reporting Summary

Supplementary Table 1

Table of transgenic lines. Description of transgenic driver and reporter lines used in this study.

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de Vries, S.E.J., Lecoq, J.A., Buice, M.A. et al. A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex. Nat Neurosci 23, 138–151 (2020). https://doi.org/10.1038/s41593-019-0550-9

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