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Sun, J. V.

Publications and source records attributed to Sun, J. V..

2 recordsLinked to original sources

Rhythmic motor activity alleviates auditory attentional blinks

Effective sensory processing relies on both attention and the motor system, yet whether motor activity could provide attention-like functions to regulate perception remains unknown. We hypothesized that rhythmic motor signals could provide phasic regulation of prioritizing and sampling perceptual targets. Using an auditory attentional blink paradigm that created a temporal deficit in selective attention, we found that temporally aligned finger tapping improved the probe detection during the attentional blink window but impaired performance when attentional resources were abundant. Furthermore, transcranial alternating current stimulation (tACS) over the right sensorimotor cortex alleviated attentional blink when the probe was close to the peak of the stimulation, whereas stimulation over the left aggravated attentional blink when the probe was close to the trough. These results suggest that the motor system is a resource-dependent rhythmic regulator of attentional sampling. Motor signals can override attentional bottlenecks, suggesting the motor system as an active shaper of cognitive processes.

neuroscience↗

Perceptual tri-stability, measured and fitted as emergent from a model for bistable alternations

The human auditory system in attempting to decipher ambiguous sounds appears to resort to perceptual exploration as evidenced by multi-stable perceptual alternations. This phenomenon has been widely investigated via the auditory streaming paradigm, employing ABA_ triplet sequences with much research focused on perceptual bi-stability with the alternate percepts as either a single integrated stream or as two simultaneous distinct streams. We extend this inquiry with experiments and modeling to include tri-stable perception. Here, the segregated percepts may involve a foreground/background distinction. We collected empirical data from participants engaged in a tri-stable auditory task, utilizing this dataset to refine a neural mechanistic model that had successfully reproduced multiple features of auditory bi-stability. Remarkably, the model successfully emulated basic statistical characteristics of tri-stability without substantial modification. This model also allows us to demonstrate a parsimonious approach to account for individual variability by adjusting the parameter of either the noise level or the neural adaptation strength.

neuroscience↗