Perceptual learning evidence for an interval- and modality invariant representation of subsecond time
Yu, C.; Xiong, Y.-Z.; Guan, S.-C.
Show abstract
A central theme in time perception research is whether subsecond timing relies on a dedicated centralized clock, or on distributed neural temporal dynamics. A fundamental constraint is the interval- and modality-specificity in perceptual learning of temporal interval discrimination (TID), which argues against a dedicated centralized clock, but is more consistent with multiple distributed mechanisms. Here we demonstrated an abstract, interval- and modality-invariant, representation of subsecond time in the brain. Participants practiced TID at a specific interval (100 ms), and received exposure to a transfer interval (200 ms), or to a different auditory/visual modality, through training of an orthogonal task. This double training enabled complete transfer of TID learning to the untrained interval, and mutual complete transfer between visual and auditory modalities. These results demonstrate an interval- and modality-invariant representation of subsecond time, which resembles a centralized clock, on top of the known distributed timing mechanisms and their readout and integration.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The role of temporal coherence and temporal stability in the build-up of auditory grouping 95%
- Robust spatial ventriloquism effect and aftereffect under memory interference 95%
- Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales 94%
Similar papers in this journal
- Rhythmic Entrainment Echoes In Auditory Perception 95%
- Salience-dependent disruption of sustained auditory attention can be inferred from evoked pupil responses and neural tracking of task-irrelevant sounds 95%
- Dissociable Pupil and Oculomotor Markers of Attention Allocation and Distractor Suppression during listening 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.