Differentiating Visual from Response Sequencing during Long-term Skill Learning

Abstract

The dual-system model of sequence learning posits that during early learning there is an advantage for encoding sequences in sensory frames; however, it remains unclear whether this advantage extends to long-term consolidation. Using the serial RT task, we set out to distinguish the dynamics of learning sequential orders of visual cues from learning sequential responses. On each day, most participants learned a new mapping between a set of symbolic cues and responses made with one of four fingers, after which they were exposed to trial blocks of either randomly ordered cues or deterministic ordered cues (12-item sequence). Participants were randomly assigned to one of four groups (n = 15 per group): Visual sequences (same sequence of visual cues across training days), Response sequences (same order of key presses across training days), Combined (same serial order of cues and responses on all training days), and a Control group (a novel sequence each training day). Across 5 days of training, sequence-specific measures of response speed and accuracy improved faster in the Visual group than any of the other three groups, despite no group differences in explicit awareness of the sequence. The two groups that were exposed to the same visual sequence across days showed a marginal improvement in response binding that was not found in the other groups. These results indicate that there is an advantage, in terms of rate of consolidation across multiple days of training, for learning sequences of actions in a sensory representational space, rather than as motoric representations.

Binding During Sequence Learning Does Not Alter Cortical Representations of Individual Actions

“…quence production, temporally adjacent responses develop a high degree of correlation in their response speeds, consistent with participants binding multiple responses together under a unified command to reduce computational complexity (see also Verstynen et al, 2012;Ramkumar et al, 2016;Lynch et al, 2017). Using a multivariate pattern analysis approach based on the cross-validated Mahalanobis estimator, we also replicated previous studies showing that cortical motor areas reliably distinguish between activation patterns of individually cued finger responses (Ejaz et al, 2015).…”

“…The first 32 trials were excluded to remove the exponential decay as it distorts the autocorrelation analysis (Verstynen et al, 2012). The linear trend was then removed by regression and the residuals were used to calculate the autocorrelation function for lags 1 through 31, following the same procedure as described previously (Verstynen et al, 2012;Lynch et al, 2017).…”

“…This produces faster responses to items within a set, as well as a correlation in responses within bound sets due to their shared upstream command ( Fig. 1C; Verstynen et al, 2012;Acuna et al, 2014;Lynch et al, 2017).…”

Binding during sequence learning does not alter cortical representations of individual actions

“…The first 32 trials were excluded to remove the exponential decay as it distorts 448 the autocorrelation analysis (Verstynen et al, 2012). The linear trend was then removed by 449 regression and the residuals were used to calculate the autocorrelation function for lags 1 through 450 31, following the same procedure as described in (Verstynen et al, 2012;Lynch et al, 2017). 451…”