eTheses Repository

Bayesian time perception

Rhodes, Darren (2016)
Ph.D. thesis, University of Birmingham.

Loading
PDF (4Mb)Accepted Version

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:Ph.D. thesis.
Supervisor(s):Di Luca, Max
School/Faculty:Colleges (2008 onwards) > College of Life & Environmental Sciences
Department:School of Psychology
Subjects:BF Psychology
Institution:University of Birmingham
ID Code:6608
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
Export Reference As : ASCII + BibTeX + Dublin Core + EndNote + HTML + METS + MODS + OpenURL Object + Reference Manager + Refer + RefWorks
Share this item :
QR Code for this page

Repository Staff Only: item control page