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Corticostriatal dynamics encode the refinement of specific behavioral variability during skill learning.

Santos FJ, Oliveira RF, Jin X, Costa RM - Elife (2015)

Bottom Line: Animals trained to perform progressively faster sequences of lever presses to obtain reinforcement reduced variability in sequence frequency, but increased variability in an orthogonal feature (sequence duration).Corticostriatal plasticity was required for the reduction in frequency variability, but not for variability in sequence duration.These data suggest that during motor learning corticostriatal dynamics encode the refinement of specific behavioral features that change the probability of obtaining outcomes.

View Article: PubMed Central - PubMed

Affiliation: Champalimaud Neuroscience Programme, Fundação Champalimaud, Lisbon, Portugal.

ABSTRACT
Learning to perform a complex motor task requires the optimization of specific behavioral features to cope with task constraints. We show that when mice learn a novel motor paradigm they differentially refine specific behavioral features. Animals trained to perform progressively faster sequences of lever presses to obtain reinforcement reduced variability in sequence frequency, but increased variability in an orthogonal feature (sequence duration). Trial-to-trial variability of the activity of motor cortex and striatal projection neurons was higher early in training and subsequently decreased with learning, without changes in average firing rate. As training progressed, variability in corticostriatal activity became progressively more correlated with behavioral variability, but specifically with variability in frequency. Corticostriatal plasticity was required for the reduction in frequency variability, but not for variability in sequence duration. These data suggest that during motor learning corticostriatal dynamics encode the refinement of specific behavioral features that change the probability of obtaining outcomes.

No MeSH data available.


Significant correlation between variability of number of presses and duration, but not between variability of frequency and duration.Scatter plots of the paired values, variances and Fano factors, for frequency/duration and number of presses/duration. Each point corresponds to one session of one individual animal, with darker colors depicting later sessions. Line corresponds to the best linear fit of all the data, with the correspondent R2 value.DOI:http://dx.doi.org/10.7554/eLife.09423.007
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fig2s1: Significant correlation between variability of number of presses and duration, but not between variability of frequency and duration.Scatter plots of the paired values, variances and Fano factors, for frequency/duration and number of presses/duration. Each point corresponds to one session of one individual animal, with darker colors depicting later sessions. Line corresponds to the best linear fit of all the data, with the correspondent R2 value.DOI:http://dx.doi.org/10.7554/eLife.09423.007

Mentions: The mean frequency of each pressing bout (sequence frequency) decreased slightly (F8,152 = 2.372, p = 0.0195, Figure 2A), while the duration of each pressing bout (sequence duration) increased with training (F8,152 = 22.69, p < 0.0001, Figure 2B). Importantly, the sequence-to-sequence variability of the behavioral parameters (measured both by the variance and by the Fano factor, Figure 2C–F) was differentially modulated during training. While the variability of sequence frequency decreased significantly throughout training (variance: F8,152 = 4.450, p < 0.0001, Figure 2C; Fano factor: F8,152 = 5.343, p < 0.0001, Figure 2E), the variability of sequence duration significantly increased (variance: F8,152 = 11.15, p < 0.0001, Figure 2D; Fano factor: F8,152 = 16.86, p < 0.0001, Figure 2F). The sequence-to-sequence variability of these two behavioral features was independent as there was no correlation between the variability in sequence frequency and the variability in sequence duration (variance: R2 = 0.0135; Fano factor: R2 = 0.0119, Figure 2—figure supplement 1). This is in contrast with a strong correlation observed between variability in sequence duration and the variability in sequence length—number of presses (variance: R2 = 0.8710; Fano factor: R2 = 0.8839, Figure 2—figure supplement 1). The decrease in frequency variability cannot be explained by animals reaching a ceiling in pressing frequency, since the average frequency did not increase with training (it actually decreased slightly). Furthermore, frequency variability started stabilizing after session 4 where the target constrains are still rather loose (3 IPIs in less than 4 s) and this is a frequency that animals can reach in 78.91 ± 5.09% of the sequences at the end of training.10.7554/eLife.09423.006Figure 2.Variability of behavioral dimensions evolves independently as animals learn a motor task.


Corticostriatal dynamics encode the refinement of specific behavioral variability during skill learning.

Santos FJ, Oliveira RF, Jin X, Costa RM - Elife (2015)

Significant correlation between variability of number of presses and duration, but not between variability of frequency and duration.Scatter plots of the paired values, variances and Fano factors, for frequency/duration and number of presses/duration. Each point corresponds to one session of one individual animal, with darker colors depicting later sessions. Line corresponds to the best linear fit of all the data, with the correspondent R2 value.DOI:http://dx.doi.org/10.7554/eLife.09423.007
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4616249&req=5

fig2s1: Significant correlation between variability of number of presses and duration, but not between variability of frequency and duration.Scatter plots of the paired values, variances and Fano factors, for frequency/duration and number of presses/duration. Each point corresponds to one session of one individual animal, with darker colors depicting later sessions. Line corresponds to the best linear fit of all the data, with the correspondent R2 value.DOI:http://dx.doi.org/10.7554/eLife.09423.007
Mentions: The mean frequency of each pressing bout (sequence frequency) decreased slightly (F8,152 = 2.372, p = 0.0195, Figure 2A), while the duration of each pressing bout (sequence duration) increased with training (F8,152 = 22.69, p < 0.0001, Figure 2B). Importantly, the sequence-to-sequence variability of the behavioral parameters (measured both by the variance and by the Fano factor, Figure 2C–F) was differentially modulated during training. While the variability of sequence frequency decreased significantly throughout training (variance: F8,152 = 4.450, p < 0.0001, Figure 2C; Fano factor: F8,152 = 5.343, p < 0.0001, Figure 2E), the variability of sequence duration significantly increased (variance: F8,152 = 11.15, p < 0.0001, Figure 2D; Fano factor: F8,152 = 16.86, p < 0.0001, Figure 2F). The sequence-to-sequence variability of these two behavioral features was independent as there was no correlation between the variability in sequence frequency and the variability in sequence duration (variance: R2 = 0.0135; Fano factor: R2 = 0.0119, Figure 2—figure supplement 1). This is in contrast with a strong correlation observed between variability in sequence duration and the variability in sequence length—number of presses (variance: R2 = 0.8710; Fano factor: R2 = 0.8839, Figure 2—figure supplement 1). The decrease in frequency variability cannot be explained by animals reaching a ceiling in pressing frequency, since the average frequency did not increase with training (it actually decreased slightly). Furthermore, frequency variability started stabilizing after session 4 where the target constrains are still rather loose (3 IPIs in less than 4 s) and this is a frequency that animals can reach in 78.91 ± 5.09% of the sequences at the end of training.10.7554/eLife.09423.006Figure 2.Variability of behavioral dimensions evolves independently as animals learn a motor task.

Bottom Line: Animals trained to perform progressively faster sequences of lever presses to obtain reinforcement reduced variability in sequence frequency, but increased variability in an orthogonal feature (sequence duration).Corticostriatal plasticity was required for the reduction in frequency variability, but not for variability in sequence duration.These data suggest that during motor learning corticostriatal dynamics encode the refinement of specific behavioral features that change the probability of obtaining outcomes.

View Article: PubMed Central - PubMed

Affiliation: Champalimaud Neuroscience Programme, Fundação Champalimaud, Lisbon, Portugal.

ABSTRACT
Learning to perform a complex motor task requires the optimization of specific behavioral features to cope with task constraints. We show that when mice learn a novel motor paradigm they differentially refine specific behavioral features. Animals trained to perform progressively faster sequences of lever presses to obtain reinforcement reduced variability in sequence frequency, but increased variability in an orthogonal feature (sequence duration). Trial-to-trial variability of the activity of motor cortex and striatal projection neurons was higher early in training and subsequently decreased with learning, without changes in average firing rate. As training progressed, variability in corticostriatal activity became progressively more correlated with behavioral variability, but specifically with variability in frequency. Corticostriatal plasticity was required for the reduction in frequency variability, but not for variability in sequence duration. These data suggest that during motor learning corticostriatal dynamics encode the refinement of specific behavioral features that change the probability of obtaining outcomes.

No MeSH data available.