Bayesian time perception

Rhodes, Darren (2016). Bayesian time perception. University of Birmingham. Ph.D.

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Abstract

Time is an elemental dimension of human perception, cognition and action. Innumerable studies have investigated the perception of time over the last 100 years, but the computational basis for the processing of temporal information remains unknown. This thesis aims to understand the mechanisms underlying the perceived timing of stimuli. We propose a novel Bayesian model of when stimuli are perceived that is consistent with the predictive coding framework – such a perspective to how the brain deals with temporal information forms the core of this thesis. We theorize that that the brain takes prior expectations about when a stimulus might occur in the future (prior distribution) and combines it with current sensory evidence (likelihood function) in order to generate a percept of perceived timing (posterior distribution). In Chapters 2-4, we use human psychophysics to show that the brain may bias perception such that slightly irregularly timed stimuli as reported as more regular. In Chapter 3, we show how an environment of irregularity can cause regularly timed sequences to be perceived as irregular whilst Chapter 4 shows how changes in the reliability of a signal can cause an increased attraction towards expectation.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):