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Different modulation of common motor information in rat primary and secondary motor cortices.

Saiki A, Kimura R, Samura T, Fujiwara-Tsukamoto Y, Sakai Y, Isomura Y - PLoS ONE (2014)

Bottom Line: We found virtually no major differences between CFA and RFA neurons, regardless of neuron subtypes, not only in their basal spiking properties but also in the time-course, amplitude, and direction preference of their functional activation for simple forelimb movements.However, the RFA neurons, as compared with the CFA neurons, showed obviously a greater susceptibility of their functional activation to an alteration in a behavioral situation, a 'rewarding' response that leads to reward or a 'consummatory' response that follows reward water, which might be accompanied by some internal adaptations without affecting the motor outputs.Our results suggest that, although the CFA and RFA neurons commonly process fundamental motor information to properly control forelimb movements, the RFA neurons may be functionally differentiated to integrate motor information with internal state information for an adaptation to goal-directed behaviors.

View Article: PubMed Central - PubMed

Affiliation: Brain Science Institute, Tamagawa University, Machida, Tokyo, Japan; Graduate School of Brain Sciences, Tamagawa University, Machida, Tokyo, Japan; JST CREST, Chiyoda-ku, Tokyo, Japan.

ABSTRACT
Rodents have primary and secondary motor cortices that are involved in the execution of voluntary movements via their direct and parallel projections to the spinal cord. However, it is unclear whether the rodent secondary motor cortex has any motor function distinct from the primary motor cortex to properly control voluntary movements. In the present study, we quantitatively examined neuronal activity in the caudal forelimb area (CFA) of the primary motor cortex and rostral forelimb area (RFA) of the secondary motor cortex in head-fixed rats performing forelimb movements (pushing, holding, and pulling a lever). We found virtually no major differences between CFA and RFA neurons, regardless of neuron subtypes, not only in their basal spiking properties but also in the time-course, amplitude, and direction preference of their functional activation for simple forelimb movements. However, the RFA neurons, as compared with the CFA neurons, showed obviously a greater susceptibility of their functional activation to an alteration in a behavioral situation, a 'rewarding' response that leads to reward or a 'consummatory' response that follows reward water, which might be accompanied by some internal adaptations without affecting the motor outputs. Our results suggest that, although the CFA and RFA neurons commonly process fundamental motor information to properly control forelimb movements, the RFA neurons may be functionally differentiated to integrate motor information with internal state information for an adaptation to goal-directed behaviors.

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Time-course of functional activity in CFA and RFA neurons.A) An example of a neuron (CFA-FS) showing functional (task-related) activity. Spike activity was first aligned with the onset (0 s) of pull movements and then averaged in correct (left) and false start (right) trials. Black and red dots in raster plots represent spikes and cue onsets, respectively, in consecutive trials (correct, 20 trials; false start, 12 trials). Note the similar activity irrespective of cue presentation. B) Definition of task-related activity. The number of spikes during correct trials was plotted against task relevance (p in KS test, assuming a uniform distribution) for individual neurons (pull-aligned analysis). Black and gray dots represent the task-related (≥40 trials, ≥50 spikes, and p<1×10−6) and non-task-related (discarded) neurons, respectively. Insets illustrate two (poorly and well) task-related activities in the plot. C) Definition of Hold-, Push-, and Pull-type activities by peak position in push- and pull-aligned analyses. D,E) Functional activity for RS (D) and FS (E) subtypes in CFA and RFA. Each row represents normalized Gaussian-filtered spike activity for a single neuron, which was assigned to panel a (aligned with the end of push; vertical line at 0 s) or b (the onset of pull) according to statistical significance (smaller p value). The task-related neurons were sorted by the order of peak time position (early to late). Push-, Hold-, and Pull-type groups are indicated on the right side for further analyses. F) Correlation of trial-to-trial variability of spikes between two neurons. Left: an example of correlated trial-to-trial spike variability during hold-pull movements in an RS-RS neuron pair (recorded from different electrodes in CFA). Middle: populational distribution of correlation coefficient (r) in trial-to-trial variability. The r distribution was calculated from the original (upper) and shuffled (lower) data (200 trials for analysis) in all pairs of CFA-RS and CFA-RS neurons. Black and gray columns represent neuron pairs with and without statistical significance individually, respectively. Right: cumulative r distribution in all the pairs of CFA-RS and CFA-RS neurons (orange), of RFA-RS and RFA-RS neurons (green), and of CFA-RS and RFA-RS neurons (brown). Gray lines show distributions from their shuffled data. Note that there were only slight (but significant) differences between the original and shuffled data in the same areas.
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pone-0098662-g003: Time-course of functional activity in CFA and RFA neurons.A) An example of a neuron (CFA-FS) showing functional (task-related) activity. Spike activity was first aligned with the onset (0 s) of pull movements and then averaged in correct (left) and false start (right) trials. Black and red dots in raster plots represent spikes and cue onsets, respectively, in consecutive trials (correct, 20 trials; false start, 12 trials). Note the similar activity irrespective of cue presentation. B) Definition of task-related activity. The number of spikes during correct trials was plotted against task relevance (p in KS test, assuming a uniform distribution) for individual neurons (pull-aligned analysis). Black and gray dots represent the task-related (≥40 trials, ≥50 spikes, and p<1×10−6) and non-task-related (discarded) neurons, respectively. Insets illustrate two (poorly and well) task-related activities in the plot. C) Definition of Hold-, Push-, and Pull-type activities by peak position in push- and pull-aligned analyses. D,E) Functional activity for RS (D) and FS (E) subtypes in CFA and RFA. Each row represents normalized Gaussian-filtered spike activity for a single neuron, which was assigned to panel a (aligned with the end of push; vertical line at 0 s) or b (the onset of pull) according to statistical significance (smaller p value). The task-related neurons were sorted by the order of peak time position (early to late). Push-, Hold-, and Pull-type groups are indicated on the right side for further analyses. F) Correlation of trial-to-trial variability of spikes between two neurons. Left: an example of correlated trial-to-trial spike variability during hold-pull movements in an RS-RS neuron pair (recorded from different electrodes in CFA). Middle: populational distribution of correlation coefficient (r) in trial-to-trial variability. The r distribution was calculated from the original (upper) and shuffled (lower) data (200 trials for analysis) in all pairs of CFA-RS and CFA-RS neurons. Black and gray columns represent neuron pairs with and without statistical significance individually, respectively. Right: cumulative r distribution in all the pairs of CFA-RS and CFA-RS neurons (orange), of RFA-RS and RFA-RS neurons (green), and of CFA-RS and RFA-RS neurons (brown). Gray lines show distributions from their shuffled data. Note that there were only slight (but significant) differences between the original and shuffled data in the same areas.

Mentions: Data in the text and figures are expressed as the mean ± s.d. (unless otherwise mentioned) and sample number (n). When applicable, we used appropriate statistical tests: i.e., t-test (for data analyses in Figs. 2A, 3D (see text), 4B, 5B, 6A,B, and 7A,B), paired t-test (Fig. 5B), Kolmogorov-Smirnov (KS) test (Figs. 2C,E, 3B,D-F 4B, 6B, and 7B), two-way ANOVA (Fig. 7C), and F-test for s.d. difference (Fig. 7A,B). See Results for details.


Different modulation of common motor information in rat primary and secondary motor cortices.

Saiki A, Kimura R, Samura T, Fujiwara-Tsukamoto Y, Sakai Y, Isomura Y - PLoS ONE (2014)

Time-course of functional activity in CFA and RFA neurons.A) An example of a neuron (CFA-FS) showing functional (task-related) activity. Spike activity was first aligned with the onset (0 s) of pull movements and then averaged in correct (left) and false start (right) trials. Black and red dots in raster plots represent spikes and cue onsets, respectively, in consecutive trials (correct, 20 trials; false start, 12 trials). Note the similar activity irrespective of cue presentation. B) Definition of task-related activity. The number of spikes during correct trials was plotted against task relevance (p in KS test, assuming a uniform distribution) for individual neurons (pull-aligned analysis). Black and gray dots represent the task-related (≥40 trials, ≥50 spikes, and p<1×10−6) and non-task-related (discarded) neurons, respectively. Insets illustrate two (poorly and well) task-related activities in the plot. C) Definition of Hold-, Push-, and Pull-type activities by peak position in push- and pull-aligned analyses. D,E) Functional activity for RS (D) and FS (E) subtypes in CFA and RFA. Each row represents normalized Gaussian-filtered spike activity for a single neuron, which was assigned to panel a (aligned with the end of push; vertical line at 0 s) or b (the onset of pull) according to statistical significance (smaller p value). The task-related neurons were sorted by the order of peak time position (early to late). Push-, Hold-, and Pull-type groups are indicated on the right side for further analyses. F) Correlation of trial-to-trial variability of spikes between two neurons. Left: an example of correlated trial-to-trial spike variability during hold-pull movements in an RS-RS neuron pair (recorded from different electrodes in CFA). Middle: populational distribution of correlation coefficient (r) in trial-to-trial variability. The r distribution was calculated from the original (upper) and shuffled (lower) data (200 trials for analysis) in all pairs of CFA-RS and CFA-RS neurons. Black and gray columns represent neuron pairs with and without statistical significance individually, respectively. Right: cumulative r distribution in all the pairs of CFA-RS and CFA-RS neurons (orange), of RFA-RS and RFA-RS neurons (green), and of CFA-RS and RFA-RS neurons (brown). Gray lines show distributions from their shuffled data. Note that there were only slight (but significant) differences between the original and shuffled data in the same areas.
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Related In: Results  -  Collection

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pone-0098662-g003: Time-course of functional activity in CFA and RFA neurons.A) An example of a neuron (CFA-FS) showing functional (task-related) activity. Spike activity was first aligned with the onset (0 s) of pull movements and then averaged in correct (left) and false start (right) trials. Black and red dots in raster plots represent spikes and cue onsets, respectively, in consecutive trials (correct, 20 trials; false start, 12 trials). Note the similar activity irrespective of cue presentation. B) Definition of task-related activity. The number of spikes during correct trials was plotted against task relevance (p in KS test, assuming a uniform distribution) for individual neurons (pull-aligned analysis). Black and gray dots represent the task-related (≥40 trials, ≥50 spikes, and p<1×10−6) and non-task-related (discarded) neurons, respectively. Insets illustrate two (poorly and well) task-related activities in the plot. C) Definition of Hold-, Push-, and Pull-type activities by peak position in push- and pull-aligned analyses. D,E) Functional activity for RS (D) and FS (E) subtypes in CFA and RFA. Each row represents normalized Gaussian-filtered spike activity for a single neuron, which was assigned to panel a (aligned with the end of push; vertical line at 0 s) or b (the onset of pull) according to statistical significance (smaller p value). The task-related neurons were sorted by the order of peak time position (early to late). Push-, Hold-, and Pull-type groups are indicated on the right side for further analyses. F) Correlation of trial-to-trial variability of spikes between two neurons. Left: an example of correlated trial-to-trial spike variability during hold-pull movements in an RS-RS neuron pair (recorded from different electrodes in CFA). Middle: populational distribution of correlation coefficient (r) in trial-to-trial variability. The r distribution was calculated from the original (upper) and shuffled (lower) data (200 trials for analysis) in all pairs of CFA-RS and CFA-RS neurons. Black and gray columns represent neuron pairs with and without statistical significance individually, respectively. Right: cumulative r distribution in all the pairs of CFA-RS and CFA-RS neurons (orange), of RFA-RS and RFA-RS neurons (green), and of CFA-RS and RFA-RS neurons (brown). Gray lines show distributions from their shuffled data. Note that there were only slight (but significant) differences between the original and shuffled data in the same areas.
Mentions: Data in the text and figures are expressed as the mean ± s.d. (unless otherwise mentioned) and sample number (n). When applicable, we used appropriate statistical tests: i.e., t-test (for data analyses in Figs. 2A, 3D (see text), 4B, 5B, 6A,B, and 7A,B), paired t-test (Fig. 5B), Kolmogorov-Smirnov (KS) test (Figs. 2C,E, 3B,D-F 4B, 6B, and 7B), two-way ANOVA (Fig. 7C), and F-test for s.d. difference (Fig. 7A,B). See Results for details.

Bottom Line: We found virtually no major differences between CFA and RFA neurons, regardless of neuron subtypes, not only in their basal spiking properties but also in the time-course, amplitude, and direction preference of their functional activation for simple forelimb movements.However, the RFA neurons, as compared with the CFA neurons, showed obviously a greater susceptibility of their functional activation to an alteration in a behavioral situation, a 'rewarding' response that leads to reward or a 'consummatory' response that follows reward water, which might be accompanied by some internal adaptations without affecting the motor outputs.Our results suggest that, although the CFA and RFA neurons commonly process fundamental motor information to properly control forelimb movements, the RFA neurons may be functionally differentiated to integrate motor information with internal state information for an adaptation to goal-directed behaviors.

View Article: PubMed Central - PubMed

Affiliation: Brain Science Institute, Tamagawa University, Machida, Tokyo, Japan; Graduate School of Brain Sciences, Tamagawa University, Machida, Tokyo, Japan; JST CREST, Chiyoda-ku, Tokyo, Japan.

ABSTRACT
Rodents have primary and secondary motor cortices that are involved in the execution of voluntary movements via their direct and parallel projections to the spinal cord. However, it is unclear whether the rodent secondary motor cortex has any motor function distinct from the primary motor cortex to properly control voluntary movements. In the present study, we quantitatively examined neuronal activity in the caudal forelimb area (CFA) of the primary motor cortex and rostral forelimb area (RFA) of the secondary motor cortex in head-fixed rats performing forelimb movements (pushing, holding, and pulling a lever). We found virtually no major differences between CFA and RFA neurons, regardless of neuron subtypes, not only in their basal spiking properties but also in the time-course, amplitude, and direction preference of their functional activation for simple forelimb movements. However, the RFA neurons, as compared with the CFA neurons, showed obviously a greater susceptibility of their functional activation to an alteration in a behavioral situation, a 'rewarding' response that leads to reward or a 'consummatory' response that follows reward water, which might be accompanied by some internal adaptations without affecting the motor outputs. Our results suggest that, although the CFA and RFA neurons commonly process fundamental motor information to properly control forelimb movements, the RFA neurons may be functionally differentiated to integrate motor information with internal state information for an adaptation to goal-directed behaviors.

Show MeSH