Abstract
Stimulus discrimination depends on the selectivity and variability of neural responses, as well as the size and correlation structure of the responsive population. For direction discrimination in visual cortex, only the selectivity of neurons has been well characterized across development. Here we show in ferrets that at eye opening, the cortical response to visual stimulation exhibits several immaturities, including a high density of active neurons that display prominent wave-like activity, a high degree of variability and strong noise correlations. Over the next three weeks, the population response becomes increasingly sparse, wave-like activity disappears, and variability and noise correlations are markedly reduced. Similar changes were observed in identified neuronal populations imaged repeatedly over days. Furthermore, experience with a moving stimulus was capable of driving a reduction in noise correlations over a matter of hours. These changes in variability and correlation contribute significantly to a marked improvement in direction discriminability over development.
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Acknowledgements
We would like to thank D. Ouimet and V. Hoke for technical and surgical assistance, and R. Corlew for administrative support. This research was supported by US National Institutes of Health grants EY011488 (D.F.), EY022001 (G.B.S.), 5T32HG003284 (A.J.S.) and Bernstein Focus Neurotechnology grant 01GQ0840 (M.K.), as well as the Max Planck Florida Institute.
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G.B.S., A.S., M.K. and D.F. designed the study, analyzed the results and wrote the paper. G.B.S. performed the acute and longitudinal GCaMP imaging. Y.M.E. developed the method for longitudinal imaging. S.D.V.H. originally acquired the motion training data and prepared these data for the additional analyses reported here.
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Supplementary Figure 1 Responses in identified neurons imaged repeatedly over days.
(a) Six representative neurons imaged on Day 0 (P30), Day 3 (P33), and Day 5 (P35). Scale bar is 50 µm. (b) Responses for individual neurons highlighted in a. Left column: Response to 8 directional stimuli, averaged across trials. Right column: Tuning curves fit with a 2-peaked Gaussian. Horizontal line indicates the mean response to a blank stimulus.
Supplementary Figure 2 Development of orientation and direction selective responses in identified neurons over days.
(a,c) Orientation preference is stable over days in longitudinally imaged animals. (b,d) Direction preference is stable in the majority of neurons, whereas a subset of cells exhibit 180 degree reversals. Red dashed lines indicate 180 degree shift from d0. (e) Orientation selectivity increases over days in identified neurons. Red dot indicates mean across neurons (s.e.m. error bars are smaller than marker). (f) DSI increases from the initial to final imaging session. Neurons with negative initial DSI (black symbols, mean indicated by green dot) reversed their direction preference over imaging sessions, but on average do not show an increase in selectivity. Neurons that maintain a preferred direction (positive initial DSI, blue symbols, mean indicated by red dot) exhibit significantly increased selectivity over days. Error bars indicating s.e.m. are smaller than markers for mean. Panels d & f are re-plotted from Figure 5 to facilitate comparison with orientation preference and selectivity.
Supplementary Figure 3 Evolution of noise correlation matrix and relative preferred direction over five days of development.
Cells are sorted by their preferred direction on the last day. (a-c): Noise correlation on day 0, day 3, and day 5. (d-f): Angular difference between cell pairs on day 0, day 3, and day 5. Correlations generally decrease from day 0 to day 5, with a prominent decrease in sets of cells sharing a preferred direction (cells 1 to 40).
Supplementary Figure 4 Initial noise correlations are higher for pairs that will ultimately adopt similar preferred directions.
(a) Cartoon depicting possible relationships in pairwise angular preference across imaging sessions, re-plotted from Figure 6. (b) Pairwise noise correlations during initial imaging as function of pairwise angular difference in preferred direction. Colored squares indicate regions of plot classified as S-S, S-O, O-O, and O-S, and quantified in Figure 6d,e.
Supplementary Figure 5 Possible scenarios for the maturation of direction discriminability.
(a) Possible scenarios for the maturation of single cell discriminability. Stimuli to be discriminated are moving gratings with opposite directions of motion. Early cortex (left): Response distribution of a single cell for a left moving grating (blue) and a right moving grating (red). Mean responses are indicated by vertical lines. Direction selectivity is commonly defined as the difference of mean responses divided by their sum. Single trial discriminability of motion direction critically depends on the fraction of overlap between the two distributions. If the overlap is close to 100%, discriminability is close to 0. If the overlap is small, discriminability is close to 1. During development, discriminability can improve by shifting the mean responses apart, i.e. by increasing the cell’s direction selectivity (right, upper). However, discriminability can also improve by reducing the response variance (without changing the selectivity; right, lower). (b) Possible scenarios for the maturation of multi-cell discriminability, here for a population of two neurons. Early cortex (left): Response distribution for a left (blue) and a right moving grating (red). Assuming response fluctuations follow a Gaussian statistics, the bivariate distributions have elliptic shapes (marking the 95% confidence region for the response distributions). Mean response vectors are marked by dots. In the shown example both cells are tuned for the same stimulus direction and their noise correlation is positive. As in the single cell case, discriminability depends on the fraction of overlap between the two distributions. This fractional overlap can decrease over development as cells become more selective (right, upper), as the overall magnitude of fluctuations decreases (right, middle) or as noise correlations become smaller (right, lower).
Supplementary Figure 6 Individual neurons increase discriminability despite reduced selectivity due to decreased variability.
(a) Discriminability increases significantly over days in identified neurons. (b) The majority of neurons exhibit increased discriminability over days (light blue). These neurons are analyzed further in panels c-i. (c) Of the neurons exhibiting increased discriminability over days, the majority also display increased direction selectivity (HS cells, red), whereas a subset show decreased selectivity over days (LS cells, blue). (d) In LS cells, neither the preferred nor the null response changes significantly. (e) HS neurons achieve enhanced selectivity both through an increase in the preferred response and a decrease in the null response. (f) Variability decreases significantly for both LS and HS groups, however variability decreases to a greater extent in cells without increased selectivity (blue) than in those where selectivity increases (red). (g) For LS cells, only the change in variance contributes positively to the increase in discriminability. (h) For HS cells, both the decreased variance and the increased selectivity contribute significantly to increased discriminability, with the change in mean response providing a significantly greater contribution. (i) Changes in variance provide a significantly greater contribution to improved discriminability in LS vs. HS neurons.
Supplementary Figure 7 Noise correlations decrease asymmetrically in longitudinally imaged animals.
Correlations decrease over imaging sessions to a larger extent in S-S vs. S-O pairs. Likewise, the decrease in correlations is larger in O-S vs. O-O pairs. Change in correlations are normalized within animal to the change exhibited by S-S pairs. (*) indicates MW test, p<0.01. Error bars indicate s.e.m.
Supplementary Figure 8 Change in response variance vs. change in selectivity.
(a) Distribution of standard deviation of response to preferred stimulus for all cells, pre- and post-training. Variance of response does not change significantly over motion training. (b) Response variance is calculated across the preferred orientation before and after training. Each point represents the average change for a single field of view. (c) Overall change in standard deviation for each training type. (d) Same as (b), but for the orientation orthogonal to the preferred orientation. (e) Same as (c), but for the orthogonal orientation. Error bars represent +/- 1 SEM.
Supplementary Figure 9 Single neuron response distributions across age groups.
Distribution of activity levels over all stimulus conditions with stimulus means subtracted (see Eqn. 8, 9, Methods) for 10 representative and randomly selected cells from the naive (a), immature (b), and mature (c) populations of cells.
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Supplementary Text and Figures
Supplementary Figures 1–9 and Supplementary Tables 1–6 (PDF 5740 kb)
Supplementary Video 1: Wave-like responses to drifting grating stimuli at eye opening.
Response to two presentations of drifting grating stimuli with the same orientation, drifting in opposite directions. Movie is shown at 2x real-time. Stimulus presentation and direction are indicated by arrow in upper left. Scale bar is 50 μm. 512 × 256 images with a 1:2 aspect ratio were acquired at 60 Hz, downsampled to 15 Hz and resized to 512 × 512 by bilinear interpolation. Images were then filtered in x-y by a 2×2 pixel radius mean filter, Z-scored relative to the mean and standard deviation of the blank stimulus, and clipped at 0 to 4 Z-units. (AVI 28536 kb)
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Smith, G., Sederberg, A., Elyada, Y. et al. The development of cortical circuits for motion discrimination. Nat Neurosci 18, 252–261 (2015). https://doi.org/10.1038/nn.3921
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DOI: https://doi.org/10.1038/nn.3921
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