Mouse Motor Cortex Coordinates the Behavioral Response to Unpredicted Sensory Feedback

Abstract

Motor cortex (M1) lesions result in motor impairments, yet how M1 contributes to the control of movement remains controversial. To investigate the role of M1 in sensory guided motor coordination, we trained mice to navigate a virtual corridor using a spherical treadmill. This task required directional adjustments through spontaneous turning, while unexpected visual offset perturbations prompted induced turning. We found that M1 is essential for execution and learning of this visually guided task. Turn-selective layer 2/3 and layer 5 pyramidal tract (PT) neuron activation was shaped differentially with learning but scaled linearly with turn acceleration during spontaneous turns. During induced turns, however, layer 2/3 neurons were activated independent of behavioral response, while PT neurons still encoded behavioral response magnitude. Our results are consistent with a role of M1 in the detection of sensory perturbations that result in deviations from intended motor state and the initiation of an appropriate corrective response.

Figure 1

Performance in a Visually Guided Virtual Reality Navigation Task Is Motor Cortex Dependent (A) Mice were trained to control movement in a virtual environment through locomotion on the spherical treadmill. Upon reaching the target at the end of the corridor, mice received a water reward. A blue laser was directed at left and right motor cortex in rapid alternation for optogenetic inhibition of neuronal activity via excitation of vGAT+ interneurons. (B) Top: schematic of the tunnel with three example traversals at the beginning of training (day 1, tunnel is not drawn to scale, length-to-width ratio: 5:1). Bottom: schematic of the tunnel with three example traversals from an expert mouse (day 8). With increasing performance of the mice, we increased the length of the tunnel to increase the difficulty of the task (length-to-width ratio: 30:1). (C) Average performance as a function of training days (fraction of time spent running in the direction of the target, see STAR Methods) in mice with (blue, n = 12 mice) and without (black, n = 22 mice) motor cortex inhibition. Here, data from all three groups of mice with different inhibition laser power levels (1 mW, 2 mW, and 10 mW) are pooled (see also Figure S1E). Error bars indicate SEM over mice. Dashed black line marks chance performance. ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 10⁻³; Wilcoxon rank sum test. Mice trained with photoinhibition did not significantly improve performance as opposed to the control group (day 1 versus day 8; with photoinhibition: p = 0.17, n = 12 mice; without photoinhibition: p < 10⁻⁶, n = 22 mice; Wilcoxon rank sum test). (D) Photoinhibition decreased performance in expert mice (n = 15 mice). ^∗p < 0.05; Wilcoxon rank sum test. Error bars indicate SEM over mice. Dashed black line marks chance performance.

Figure 2

Motor Cortex Inhibition Delays Visually Guided Corrective Turns (A) Mice spontaneously turn left and right as they learn to traverse the virtual corridor. The amplitude of spontaneous turns increased over the course of training (days 1 to 8) for both left (blue) and right (red) turns. Shading indicates SEM over turns. Turns per day, left: 184 ± 27; right: 186 ± 28 (mean ± SD, n = 22 mice). (B) Average acceleration during spontaneous turns increased with training (p < 10⁻⁸, R² = 0.19, n = 22 mice; linear trend analysis; see STAR Methods). Error bars indicate SEM over mice (n = 22 mice). (C) Speed profiles of the spontaneous turns without inhibition of motor cortex (left panel, n = 14 mice) and the spontaneous turns initiated during inhibition of motor cortex (right panel, n = 14 mice, data from the same mice as in left panel), executed on performance testing days in expert mice, sorted by maximum speed. Motor cortex inhibition did not prevent mice from executing spontaneous turns. Color indicates turning speed. (D) Average speed profile of turns without (black) and with (blue) bilateral inhibition of motor cortex. Same data as shown in (C). Shading indicates SEM over mice (n = 14 mice). Note that turning speed with or without motor cortex inhibition was not different in a window 3 s after turn onset (marked by dashed lines). n.s., not significant; Wilcoxon rank sum test. (E) Average speed profiles during corrective turns to the left (blue) and right (red) induced by visual offset perturbations over the course of training (days 3 to 8, the first 2 days did not have visual offset perturbations, left turns: n = 632, 666, 688, 803, 776, 884; right turns: 675, 687, 725, 806, 749, 907 in 22 mice, respectively). Shading indicates SEM over turns. Turns per day, left: 34 ± 4; right: 34 ± 4 (mean ± SD). (F) Acceleration during corrective turns induced by visual offset perturbations increased over the course of training (p < 10⁻⁵, R² = 0.15, n = 22 mice; linear trend analysis; see STAR Methods). Error bars indicate SEM over mice (n = 22 mice). (G) Speed profile of 321 visual offset perturbation-induced corrective turns in expert mice that had reached plateau performance without (left panel, n = 14 mice, data from same mice as in C) and with (right panel, 353 trials, n = 14 mice, data from the same mice as in left panel) inhibition of motor cortex concurrent with visual offset perturbation for 3 s (blue bar). Turns are sorted by latency to peak velocity. In a subset of trials (55% ± 5%, mean ± SEM, see STAR Methods), mice delayed their corrective turn response until after motor cortex inhibition ceased. Color indicates turning speed. (H) Average speed profile of visual offset perturbation-induced corrective turns without (black) and with (blue) bilateral inhibition of motor cortex for 3 s starting concurrently with the visual offset perturbation (time 0). Same data as shown in (G). Shading indicates SEM over mice (n = 14 mice). Turning speed was lower with motor cortex inhibition (0 s – 3 s after perturbation onset). ^∗∗p < 0.01; Wilcoxon rank sum test.

Figure 3

Calcium Response of Layer 2/3 and Layer 5 PT Neurons in Motor Cortex Scales Linearly with Amplitude of Spontaneous Turns (A) Top: calcium activity of one layer 2/3 neuron that was preferentially active during contraversive turns (black line) and one layer 2/3 neuron that was preferentially active during ipsiversive turns (gray line). Bottom: the mouse’s rotational acceleration. Times of positive acceleration mark contraversive turns (blue line and shading) and negative values mark ipsiversive turns (red line and shading). (B) Average change in fluorescence aligned on contraversive (blue) and ipsiversive (red) turns throughout training (days 1 to 8) for the two neurons shown in (A). Shading indicates SEM over turns (number of contraversive turns: n = 1,654; ipsiversive turns: n = 1,668). (C) To record the activity of layer 2/3 excitatory neurons, we injected AAV2/1-EF1α-GCaMP6f into vGAT-Cre x ROSA-LSL-tdTomato mice (n = 8). (D) We split all spontaneous turns recorded throughout training (days 1 to 8) into bins of high (black line) and low (gray line) acceleration. Shading indicates SEM over turns (number of turns for high acceleration bin: n = 6,174; low acceleration bin: n = 14,018). (E) Larger turns were associated with higher neuronal activity. Average population activity of layer 2/3 neurons for the turns shown in (D) (n = 1,154 neurons). Colors as in (D). Shading indicates SEM over neurons. (F) Average population activity of layer 2/3 neurons as a function of acceleration of the spontaneous turn. Error bars indicate SEM over neurons (n = 1,154). Dashed black line is a linear fit to the data. Shading marks bins used for the turning and activity traces in (A) and (B). ^∗∗∗p < 10⁻³, R² = 0.08, n = 1,154 neurons; linear trend analysis (see STAR Methods). n.s., not significant, lowest bin is not different from zero; Student’s t test. (G) To record the activity of layer 5 PT neurons, we injected conditional AAV2/1-DIO-EF1α-GCaMP6f into Sim1(KJ18)-Cre mice (n = 11 mice). (H) As in (D), but for the layer 5 PT experiments (number of turns for high acceleration bin: n = 5,764; low acceleration bin: n = 21,865). (I) As in (E), but for layer 5 PT neurons (n = 560 neurons). (J) As in (F), but for layer 5 PT neurons. ^∗∗∗p < 10⁻³, R² = 0.04, n = 560 neurons; linear trend analysis (see STAR Methods).

Figure 4

With Training Activity in Layer 2/3 Decreases and Increases in Layer 5 PT Neurons (A) Top: average turn response of a layer 2/3 neuron during a contraversive turn (left) during the first 4 days of training (early, pale blue, n = 804 turns) and the last 4 days of training (late, dark blue, n = 818 turns); and the average turn responses of another neuron during ipsiversive turns (right) early (pale red, n = 819 turns) and late (dark red, n = 873 turns) in training. Bottom: average turning speed traces corresponding to the data shown in the top panels. Shading indicates SEM over turns. (B) Average layer 2/3 responses during contraversive (blue) and ipsiversive (red) turns early (days 1 to 4) and late (days 5 to 8) in training. Responses during contraversive turns decrease with training. Error bars indicate SEM over neurons (n = 1,154 neurons). ^∗p < 0.05, ^∗∗∗p < 10⁻³, n.s., not significant; paired Student’s t test. (C) Average absolute Pearson’s correlation coefficient of layer 2/3 activity and turning velocity early (days 1 to 4) and late (days 5 to 8) in training. n.s., not significant; paired Student’s t test. (D) As in (A), but for two layer 5 PT neurons (number of early contraversive turns: n = 592; late contraversive turns: n = 898; early ipsiversive turns: n = 590 turns; late ipsiversive turns: n = 899). (E) As in (B), but for layer 5 PT neurons (n = 560 neurons). ^∗∗p < 0.01, ^∗∗∗p < 10⁻³, n.s., not significant; paired Student’s t test. (F) As in (C), but for layer 5 PT neurons. ^∗∗∗p < 10⁻³; paired Student’s t test.

Figure 5

Activity during Spontaneous Turns Is Higher when the Turn Is Taken Toward the Target (A) Average activity during spontaneous turns in layer 2/3 neurons as a function of the heading in a window −0.625 s to −0.125 s preceding the turn. Turns were acceleration matched (see STAR Methods and Figure S8) and binned such that a negative prior heading indicates a turn toward the target and a positive prior heading a turn away from the target. In this analysis, we included data from all training days (days 1 to 8). Error bars indicate SEM over turns. Horizontal gray line and shading is the average response and SEM over turns. ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 10⁻³; Student’s t test against the center bin. Bins that are not significant are not marked. (B) As in (A), but for layer 5 PT neurons.

Figure 6

Visual Offset Perturbations Activate Layer 2/3 Neurons Independent of the Amplitude of the Induced Turn (A) We split visual offset perturbation-induced turns recorded throughout training (days 3 to 8) into bins of high (black) and low (gray) accelerations. Shading indicates SEM over turns (number of turns for high acceleration bin: n = 402; low acceleration bin: n = 659). (B) Average response in layer 2/3 neurons for the high (black line) and low (gray line) acceleration turns as defined in (A). Both low and high acceleration result in almost identical activation of layer 2/3 neurons (n = 1,154 neurons). (C) Average population response of layer 2/3 neurons as a function of acceleration of the induced turn. Error bars indicate SEM over neurons (n = 1,154 neurons). Dashed black line is a linear fit to the data. Shading marks bins used for the turning and activity traces in (A) and (B). ^∗∗∗p < 10⁻³, Student’s t test of first bin versus no response; n.s.,: not significant, paired Student’s t test of first versus last bin. We found no evidence of a linear trend (p = 0.86, R² = 10⁻⁶, n = 1,154 neurons; linear trend analysis; see STAR Methods). (D) As in (A), but for layer 5 PT experiments (number of turns for high acceleration bin: n = 966; low acceleration bin: n = 1,167). (E) As in (B), but for layer 5 PT neurons (n = 560 neurons). (F) As in (C), but for layer 5 PT neurons (n = 560 neurons). ^∗∗∗p < 10⁻³; Student’s t test of first bin versus no response. ^∗∗∗p < 10⁻³; paired Student’s t test of first versus last bin. Linear trend analysis (see STAR Methods) indicated a significant linear trend (p < 10⁻⁷, R² = 0.01, n = 560 neurons).

Figure 7

Spontaneous Turn-Responsive Cells Are Also Activated during Visual Offset Perturbation-Induced Turns (A) Time course of average fluorescence of all layer 2/3 neurons (n = 1,154 neurons) during spontaneous contraversive (left) and ipsiversive (right) turns executed throughout training (days 1 to 8). Neurons are sorted by their selectivity during contraversive turns. (B) Average neuronal activity of contraversive neurons (marked by blue and red box in A) during spontaneous contraversive (blue) and ipsiversive (red) turns. Shading indicates SEM over neurons (n = 616). (C) Pearson’s correlation coefficient of the population vector during contraversive and ipsiversive turns as a function of time around turn onset (black line, gray shading marks standard deviation over turns). Horizontal green lines mark mean (solid) and standard deviation (dashed) of random correlation. Horizontal black line marks time bins in which correlation is significantly different from chance (gray indicates bins that are not significant). (D) Same as (A), but for visual offset perturbation-induced turns executed during training days 3 to 8. Sorting of neurons is the same as in (A). (E) Same as (B), but for visual offset perturbation-induced turns executed during training days 3 to 8. Initially, contraversive neurons are activated during both contraversive and ipsiversive induced turns. (F) Same as (C), but for visual offset perturbation-induced turns. Correlation of population vectors during induced turns is initially positive and only becomes negative approximately 2 s after onset of the visual offset perturbation. (G) Same as (A), but for layer 5 PT neurons (n = 560 neurons). (H) Same as (B), but for layer 5 PT neurons (n = 229 neurons, as selected in G). (I) Same as (C), but for layer 5 PT neurons. (J) Same as (D), but for layer 5 PT neurons. (K) Same as (E), but for layer 5 PT neurons. (L) Same as (F), but for layer 5 PT neurons. In contrast to layer 2/3, we find no evidence of a positive correlation of population vectors in layer 5 PT neurons.

Figure 8

Activity Patterns for Spontaneous Contra- and Ipsiversive Turns Are Co-activated in Layer 2/3 during Visual Offset Perturbation-Induced Turns (A) Projections of the population vector during spontaneous contraversive (blue) and spontaneous ipsiversive (red) executed throughout training (days 1 to 8) onto the plane spanned by the population vector 1 s after turn onset during spontaneous contraversive and spontaneous ipsiversive turns. Origin of the coordinate system is the mean population vector preceding turns. Shading of the maker indicates time relative to turn onset. We then projected the population activity vector during induced contraversive (cyan) and induced ipsiversive turns (magenta) executed during training days 3 to 8 onto the same coordinate system. Black crosses mark the first bin with the first significant change in turning velocity following visual offset perturbation. Error bars indicate SEM over turns. Dashed black line marks line of unity. (B) As in (A), but for layer 5 PT responses. (C) Model for the response of motor cortex to unexpected feedback perturbations. In an initial phase of the response, multiple assemblies of neurons, the activity of which we speculate corresponds to different motor plans, are co-activated and primed in layer 2/3. These assemblies could be separately driven by sensory evidence, and potentially directly compete. At a later time, during the movement selection phase of the response, the dominant activation pattern of layer 2/3 can recruit the corresponding assembly in layer 5 that then drives a behavioral response by activating subcortical motor control centers.