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Link to original content: https://pubmed.ncbi.nlm.nih.gov/25314898/
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Clinical Trial
. 2014 Oct 15:5:5255.
doi: 10.1038/ncomms6255.

Motor contributions to the temporal precision of auditory attention

Benjamin Morillon  1 , Charles E Schroeder  2 , Valentin Wyart  3
Affiliations
Clinical Trial

Motor contributions to the temporal precision of auditory attention

Benjamin Morillon et al. Nat Commun. .

Abstract

In temporal-or dynamic-attending theory, it is proposed that motor activity helps to synchronize temporal fluctuations of attention with the timing of events in a task-relevant stream, thus facilitating sensory selection. Here we develop a mechanistic behavioural account for this theory by asking human participants to track a slow reference beat, by noiseless finger pressing, while extracting auditory target tones delivered on-beat and interleaved with distractors. We find that overt rhythmic motor activity improves the segmentation of auditory information by enhancing sensitivity to target tones while actively suppressing distractor tones. This effect is triggered by cyclic fluctuations in sensory gain locked to individual motor acts, scales parametrically with the temporal predictability of sensory events and depends on the temporal alignment between motor and attention fluctuations. Together, these findings reveal how top-down influences associated with a rhythmic motor routine sharpen sensory representations, enacting auditory 'active sensing'.

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Figures

Figure 1
Figure 1. Experimental design and main effect of motor tracking.
Experiment 1: (a) Rhythmic sequences of 20 pure tones were presented binaurally on each trial. Four reference tones preceded an alternation of eight target and eight distractor tones of variable frequencies. Targets occurred in phase with the preceding references, whereas distractors occurred in antiphase. Participants had to decide whether the mean frequency of targets was higher or lower than the reference frequency. In the listen condition, participants performed the task without moving before the end of the sequence. In the motor-tracking condition, participants performed the task while expressing the reference beat by moving their index finger. (b) Average categorization performance in the motor-tracking and listen conditions. (c) Contributions of targets and distractors to the decision in the motor-tracking (white bars) and listen (grey bars) conditions. Sensory gains were estimated for each target and distractor tone using a multivariate logistic regression of choice against a weighted sum of the information provided by each tone, expressed in relative distance from the reference frequency. Sensory gains were pooled separately across targets and distractors. Error bars indicate s.e.m. Stars/NS indicate significant/nonsignificant differences (n=21; paired t-tests or t-tests against zero; *P<0.05).
Figure 2
Figure 2. Motor-tracking-locked rhythmic gain model.
(a) Description of the model. First row: rhythmic motor tracking in phase with the reference beat throughout the sequence. Second row: references. Third row: targets presented in phase with the reference beat. Dark grey lines indicate the temporal distance between the motor act and the onset of the target. Fourth row: distractors presented in antiphase with the reference beat. Light grey lines indicate the temporal distance between the motor act and the onset of the distractor. Fifth row: gains assigned to successive targets and distractors. (b–d) Experimental validation of the model. (b) Target/distractor gains sorted according to their temporal distance to motor acts (SSI; dashed lines correspond to the listen condition). (c) Detail of the model-predicted best (ϕ=0) and worst (ϕ=π) octile, and comparison with the listen condition. (d) Upper panel: between-subject distributions of SSI for which the gain is maximally modulated (0: in-phase, π: antiphase). Lower panel: behavioral variability explained by taking SSI into account. (Shaded) error bars indicate s.e.m. Stars/NS indicate significant/nonsignificant differences (n=21; paired t-tests or t-tests against zero; *P<0.05).
Figure 3
Figure 3. Influence of acoustic rhythmicity.
Experiment 2: four references preceded an alternation of nine distractors and eight targets. Target and/or distractor sequences were either presented in a rhythmic or jittered manner. As in experiment 1, the task was divided into listen and motor-tracking conditions. (a) Average categorization performance in the motor-tracking and listen conditions, averaged across the different rhythmicity conditions. (b) Contributions of targets and distractors to the decision in the motor-tracking (white bars) and listen (grey bars) conditions, averaged across the different rhythmicity conditions. (c) Contribution of targets to the decision, detailed for each condition. T/t indicates target rhythmic/jittered conditions, D/d distractor rhythmic/jittered conditions and white/grey bars motor-tracking/listen conditions. (d) Additional results in the motor-tracking condition, averaged across the different rhythmicity conditions. Upper panel: angle histograms of SSI at which the gain is maximally modulated (0: in-phase, π: antiphase). Lower panel: behavioral variability explained by taking SSI into account. (Shaded) error bars indicate s.e.m. Stars/NS indicate significant/nonsignificant differences (n=18; paired t-tests or t-tests against zero; *P<0.05).
Figure 4
Figure 4. Influence of attention-motor coupling.
Experiment 3: in contrast to experiment 1, distractors occurred in phase with the preceding reference tones (and motor acts), whereas targets occurred in antiphase with the reference tones. This design allowed to temporally dissociate motor tracking and temporal attention: participants pressed their index finger in phase with distractors while paying attention to targets. (a) Average categorization performance in the motor-tracking and listen conditions. (b) Contributions of targets and distractors to the decision in the motor-tracking (white bars) and listen (grey bars) conditions. Error bars indicate s.e.m. NS indicates nonsignificant differences (n=21; paired t-tests; *P<0.05).
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