Locomotion-dependent remapping of distributed cortical networks

Abstract

The interactions between neocortical areas are fluid and state-dependent, but how individual neurons couple to cortex-wide network dynamics remains poorly understood. We correlated the spiking of neurons in primary visual (V1) and retrosplenial (RSP) cortex to activity across dorsal cortex, recorded simultaneously by widefield calcium imaging. Neurons were correlated with distinct and reproducible patterns of activity across the cortical surface; while some fired predominantly with their local area, others coupled to activity in distal areas. The extent of distal coupling was predicted by how strongly neurons correlated with the local network. Changes in brain state triggered by locomotion strengthened affiliations of V1 neurons with higher visual and motor areas, while strengthening distal affiliations of RSP neurons with sensory cortices. Thus, the diverse coupling of individual neurons to cortex-wide activity patterns is restructured by running in an area-specific manner, resulting in a shift in the mode of cortical processing during locomotion.

Fig. 1. Neurons exhibit diverse affiliations with global networks.

a, Example imaging field and recording probe design. b, Example waveforms from three recorded units. Fast-spiking units (FS, putative interneurons) could be distinguished from regular-spiking units (RS) by their waveform. c, Example spike trains for 14 units recorded in V1 (left) and histogram of firing rates (right). d, Left: example spike-triggered activity map (SpAM) for unit recorded in V1, registered to the Allen Brain Atlas (outlined) using stereotaxically placed skull landmarks. Right: the unit’s spike train was convolved with an exponential decay fit from the calcium data (black), plotted with the fluorescence trace from a pixel in V1 (top) and in hindlimb somatosensory cortex (S1HL, bottom). Individual pixels with correlation values not significantly different from zero are transparent (Pearson correlation, P values Benjamini–Hochberg corrected, with significance threshold set at a 5% false-positive rate). e, Same as d, for a simultaneously recorded V1 unit (Pearson correlation, P values Benjamini–Hochberg corrected, with significance threshold set at a 5% false-positive rate). f, Example population SpAMs for recordings taken in V1 (top) and RSP (bottom), whereby the summed spiking activity was correlated with activity in each pixel across the cortex. g, Two-dimensional correlation coefficients between individual SpAMs and the population SpAM for recordings in V1 and RSP. Spike trains were randomized to calculate shuffled SpAMs (gray). For V1 units, 73% of SpAMs were significantly correlated and 11% were significantly anticorrelated with the population SpAM (calculated as percent of units that fall outside the 95% confidence interval of shuffled SpAM distribution). In RSP, 65% and 11% of neurons were significantly correlated or anticorrelated with the population SpAM, respectively (calculated as percent of units that fall outside the 95% confidence interval of shuffled SpAM distribution). h, FS units (putative interneurons) had SpAMs significantly more similar to the population SpAMs than RS units (as measured by two-dimensional correlation, see Methods; means indicated with arrows, two-sided t-test, P = 1 × 10⁻⁴, T = 3.8, degrees of freedom (df) = 354). i, Mean Pearson correlations with various cortical areas for all recorded V1 units, sorted by correlation with V1. j, Same as i, for RSP units, sorted by Pearson correlation with RSP.

Fig. 2. Units uncoupled to local activity were more probably affiliated with global networks.

a, A unit’s population coupling is the correlation between the spiking of a given cell and the sum of spikes from all other simultaneously recorded neurons. Population coupling is shown for five units recorded in V1. b, Example SpAMs for four V1 units (Pearson correlation). Top: population SpAM with recording site circled in red. All SpAMs were aligned to the Allen Brain Atlas (overlaid). A unit’s z-scored population coupling is shown in black, and its 2D correlation with the population SpAM in blue. c, Same as b, for example units recorded in RSP. d, Population coupling versus unit’s SpAM 2D correlation with the population SpAM. High-coupled units had SpAMs more similar to the population SpAM, while the SpAM values of low-coupled units were more diverse in both V1 (linear regression, slope = 0.44, R = 0.18, P = 0.02) and RSP (linear regression, slope = 0.92, R = 0.45, P = 1 × 10⁻⁹). e, Mean (top row) and variance (bottom) of SpAMs for the highest-coupled (left) and lowest-coupled (right) V1 units (Pearson correlations). The low-coupled V1 units exhibited common affiliation motifs with RSP, S1HL and M1HL, a lateral parietal area, and barrel S1. SpAMs were z-scored before averaging. f, Same as e, for recordings in RSP (Pearson correlations). Common affiliation motifs included secondary motor cortex, S1HL and M1HL, barrel cortex, and a lateral parietal area.

Fig. 3. Global affiliation patterns are state-specific.

a, Fluorescence traces from three areas overlaid with running speed, and spike rasters of RS (black) and FS (orange) units recorded in V1 (left) and RSP (right). b, Average SpAM for units recorded in V1 during quiescence (left) and locomotion (right) (SpAMs calculated using Pearson correlation, N = 100 units). c, SpAMs (Pearson correlation) for five simultaneously recorded V1 units during quiescence (Q; left) and locomotion (L; right). The effect of running on a unit’s change in firing rate is indicated in black (relative to quiescence) and the 2D correlation of its quiescence versus locomotion SpAMs is shown in blue. Increases or decreases in firing rate during locomotion were not necessarily associated with higher or lower SpAM correlations. Red circle indicates recording location. d, Same as b, for all RSP units (Pearson correlation, N = 153 units). e, Same as c for example RSP units (Pearson correlation). f, Histogram of the 2D correlation between each unit’s SpAM during quiescence and during locomotion (N = 100 units in V1, N = 153 units in RSP). RSP SpAMs remapped more extensively than V1 units upon locomotion. Units whose activity was suppressed by more than 50% during locomotion were excluded to avoid including any noise-dominated maps in these analyses, but including all data did not affect the main trend. g, Pairwise 2D correlations of V1 SpAMs during quiescence and locomotion. V1 SpAMs become more similar to one another during locomotion (N = 100 units, two-sided paired t-test, P = 1 × 10⁻⁵, t = 4.4, df = 698). Right: pairwise 2D correlations of V1 SpAMs during quiescence versus locomotion. Lines were weighted by the magnitude of the pair’s change between the two conditions (N = 100 units; thin, light gray lines: small change; thick, black lines: large change). h, Same as g, for RSP (N = 153 units, 2D correlation). RSP units’ SpAMs become less similar to one another during locomotion (N = 153 units, two-sided paired t-test, P= 4 × 10⁻¹⁰, t = 6.3, df = 960). i, Average of V1 population SpAMs during locomotion (left), quiescence (middle) and their difference (right, N = 5 mice, Pearson correlations). j, Average of RSP population SpAMs during locomotion (left), quiescence (middle) and their difference (right, N = 5 mice, Pearson correlations). k, Average difference between V1 and RSP population SpAMs (Pearson correlations) during locomotion and quiescence for different cortical areas (error bars s.e.m.). Corr., correlation.

Fig. 4. Locomotion triggers a reorganization of RSP global affiliations.

a, Firing rates of RS and FS neurons increase during locomotion in V1 (left, N = 108 RS units, N = 10 FS units) and decrease for FS units in RSP (right, N = 131 RS units, N = 34 FS units). Many RSP FS units were strongly suppressed by locomotion. Means are indicated with arrows. b, Pairwise spiking Pearson correlations in V1 and RSP drop significantly during locomotion compared with quiescence (pairwise two-sided t-test, bars denote standard deviation, N = 1,461 V1 pairs, N = 4,724 pairs). This could not be accounted for by the drop in firing rate in RSP units during locomotion (Q’, spike-rate corrected Pearson correlation; see Methods). Pearson correlations during passive wakefulness (P) were higher than in unmoving animals (Q), and Pearson correlations in aroused animals (A) were significantly lower than in both quiescent and passive animals, but not as low as in locomoting animals (Bonferroni-corrected two-sided t-test). c, Spike correlations (Pearson) during quiescence and locomotion for all V1 and RSP units. d, During locomotion, high-coupled RSP units were more probably suppressed (Bonferroni-corrected two-sided t-test). The effect of locomotion on V1 units was not related to population coupling. FS units indicated in orange. e, Top row: average SpAMs of locomotion-suppressed FS units in RSP during quiescence and locomotion (Pearson correlation). Bottom row: average SpAMs of RSP units anti-correlated with locomotion-suppressed FS units, during quiescence and locomotion (Pearson correlation). f, Top: 2D correlation with population SpAM for locomotion-suppressed units during quiescence and locomotion (N = 15 units). Bottom: 2D correlation with population SpAM for units anti-correlated with locomotion-suppressed units (N = 13 units). These SPAMs were anti-correlated with the population SpAM during quiescence but became more similar to it during locomotion. g, Average SpAM difference (locomotion – quiescence, bars denote standard deviation) for the population of cells anti-correlated with locomotion-suppressed FS units (N = 13 units).

Fig. 5. Schematic of change in affiliation patterns.

a, Schematic of V1 dynamics during quiescence versus locomotion. Internal correlations are highest during locomotion but drop during quiescence. b, Schematic of RSP dynamics during quiescence versus locomotion. Internal correlations are highest during quiescence but drop during locomotion, and units become more strongly affiliated with outside areas, including V1 and SC.