Probabilistic model of onset detection explains paradoxes in human time perception

Area of Science:

• Cognitive Neuroscience
• Computational Psychology
• Psychophysics

Background:

• Motor preparation activity precedes voluntary actions by 1-2 seconds, but conscious awareness is limited to ~0.25 seconds.
• The principle of attention prior entry suggests attended stimuli are perceived faster, yet electrophysiological studies show minimal neural timing differences.

Purpose of the Study:

• To propose a computational model explaining discrepancies in time perception literature.
• To reconcile the timing of motor preparation awareness with neural activity.
• To explain the conflict between psychophysical attention effects and electrophysiological data.

Main Methods:

• Development of a basic computational model.
• Application of signal detection theory principles.
• Probabilistic modeling of stimulus onset detection.

Main Results:

• The model naturally predicts the limited conscious awareness of early motor preparation.
• The model accounts for the lack of significant neural timing differences for attended versus unattended stimuli.
• The probabilistic approach resolves apparent paradoxes in time perception.

Conclusions:

• A signal detection theoretic framework provides a unified explanation for puzzling findings in time perception.
• Probabilistic onset detection is key to understanding conscious awareness and attentional effects on perception.
• The model offers a parsimonious explanation for complex temporal phenomena.