Extended Data Fig. 2: Cortical neurons exhibit variable coding properties across timescales from minutes to days.

(a) Maps for two example mice, showing how mean lateral displacements in cells’ centroid positions across multiple imaging sessions depended on their locations in the field of view. Across most of the field of view, mean displacements were <1 pixel, corresponding to <4 μm. To determine these displacements, we first computed the maximum projection image (MPI) of the Ca²⁺ video from each session. Using the MPI from the first session as a reference, we computationally aligned it to the MPI from each of the other sessions. We then computed the spatial cross-correlation function between patches of the MPI containing ≥10 cells from the first session (patch size: 256 μm × 256 μm) and MPIs from each of the other sessions. For each session other than the first, we determined the displacement of a patch to be the argument of the cross-correlation function that yielded its maximum value. We averaged these displacements across all sessions after the first. By examining all possible MPI patches (spaced 64 μm apart) in this way, we created the maps shown. Scale bars: 1 mm. (b) Two-dimensional probability distribution of cells’ daily lateral displacements from their mean position, averaged across all days and imaged neurons (21,570 cells) from N = 6 mice (Methods). About 50% of the time, cells had a displacement of zero pixels from their mean position; 98.5% of the time these displacements were ≤1 pixel (4 μm). (c) Cumulative distribution of cells’ mean displacements (averaged over all sessions) from their mean positions across the entire experiment. Red dashed line indicates that 95.4% of cells had a mean displacement of ≤5 μm. (d) Cumulative distribution of the lateral separations between nearest neighbour cell pairs. Red dashed line indicates that only 2% of nearest neighbour cell pairs were within 5 μm of each other. (e) Among 18,528 cells with significant d’ values on one or more sessions for encoding the trial-type in the stimulus period (P < 0.01; permutation test; N = 94–354 trials), 41% of these had significant d’ values in only one half-session, split nearly evenly between the first (21%) and second (20%) half-sessions. Whereas in trial-shuffled data, only 10% of the cells had this variable coding, a highly significant difference from the real data (P<0.001) indicating that trial-shuffling diluted the temporal concentration of trials in which cells had coding responses. In real data, 91% of the 18,528 cells retained significant coding in one or both halves of the full sessions in which they displayed significant coding (P<0.01; permutation test; 40–175 trials). But in trial-shuffled data, only 51% of the cells retained this coding in one or both half-sessions, a highly significant difference from real data (***P<0.001; permutation test; 94–354 trials), again showing that in real data cells had temporally concentrated coding epochs far more than expected by chance. All s.d. values on the above percentages of cells were estimated as counting errors and were 0.1–0.4%. (f) Some neurons had coding properties that varied across days. For 4 example cells (from areas PPC, MV, V1 and PPC, from top to bottom), shown are traces of the neuron’s fluorescence intensity (z-scored values of ΔF/F₀) as a function of time across 5 imaging sessions. Vertical dashed lines mark transitions between successive sessions. Insets show maximum projection images of the example neurons from each session. Values of d’ denote the fidelity with which one can distinguish the two visual stimuli based on the binarized event train of the cell’s Ca²⁺ activity (Methods). In f and g, values of d’ coloured red are those for which the stimuli cannot be significantly distinguished, as determined using a permutation test over the set of stimulus trials and requiring P<0.01 for significance. (g) Some cells had coding properties that varied within the 1-h sessions. Shown are fluorescence traces (z-scored values of ΔF/F₀) for 4 cells (from areas LV, V1, MV and LV, from top to bottom) as a function of time across one session. We measured d’ values of single neurons for distinguishing the two visual stimuli during the first and second halves of each session based on their binarized Ca²⁺ event traces. Neurons that actively fired across the session exhibited variability in their visual coding, as did cells that were active during only a portion of the imaging session. Insets: Example Ca²⁺ event images show that the same cells were imaged in the first and second halves of each session. (h) Histograms showing the numbers of days that neurons from each area significantly encoded the visual stimulus-type (permutation test over the set of stimulus trials; requiring P<0.01 for significance), for all cells that did so in at least one session (solid bars) and for the subset of these cells with statistically significant levels of Ca²⁺ activity in every imaging session (hashed bars). (i) Map of neurons from an example mouse, with each cell’s colour denoting the number of days the cell significantly encoded the visual-stimulus type. Cells with different day-to-day reliabilities of stimulus-encoding were interspersed across the field of view. Scale bar: 1 mm. (j) Scatter plot in which, for every individual cell (blue data points), the d’ value for stimulus discrimination during the first half of each imaging session is plotted against the d’ value for the second half of the same session. (k) Scatter plot in which, for every cell (blue data points), the mean d’ value for stimulus discrimination (averaged over all sessions) is plotted against the range of d’ values determined for the same cell across all sessions. (l) Scatter plot in which, for every cell (blue data points), the mean difference between the d’ values for stimulus discrimination determined for the first and second halves of each session is plotted against the s.d. of the d’ values determined for the same cell across all sessions. Variability in d’ values within a session was highly correlated (r = 0.81) with variability across sessions, suggesting some neurons have greater intrinsic variability in the fidelity of stimulus encoding than others.