Computational Study of Multisensory Gaze-Shift Planning
| dc.contributor.advisor | Crawford, John Douglas | |
| dc.creator | Daemi, Mehdi | |
| dc.date.accessioned | 2016-11-25T14:08:52Z | |
| dc.date.available | 2016-11-25T14:08:52Z | |
| dc.date.copyright | 2016-07-26 | |
| dc.date.issued | 2016-11-25 | |
| dc.date.updated | 2016-11-25T14:08:51Z | |
| dc.degree.discipline | Biology | |
| dc.degree.level | Doctoral | |
| dc.degree.name | PhD - Doctor of Philosophy | |
| dc.description.abstract | In response to appearance of multimodal events in the environment, we often make a gaze-shift in order to focus the attention and gather more information. Planning such a gaze-shift involves three stages: 1) to determine the spatial location for the gaze-shift, 2) to find out the time to initiate the gaze-shift, 3) to work out a coordinated eye-head motion to execute the gaze-shift. There have been a large number of experimental investigations to inquire the nature of multisensory and oculomotor information processing in any of these three levels separately. Here in this thesis, we approach this problem as a single executive program and propose computational models for them in a unified framework. The first spatial problem is viewed as inferring the cause of cross-modal stimuli, whether or not they originate from a common source (chapter 2). We propose an evidence-accumulation decision-making framework, and introduce a spatiotemporal similarity measure as the criterion to choose to integrate the multimodal information or not. The variability of report of sameness, observed in experiments, is replicated as functions of the spatial and temporal patterns of target presentations. To solve the second temporal problem, a model is built upon the first decision-making structure (chapter 3). We introduce an accumulative measure of confidence on the chosen causal structure, as the criterion for initiation of action. We propose that gaze-shift is implemented when this confidence measure reaches a threshold. The experimentally observed variability of reaction time is simulated as functions of spatiotemporal and reliability features of the cross-modal stimuli. The third motor problem is considered to be solved downstream of the two first networks (chapter 4). We propose a kinematic strategy that coordinates eye-in-head and head-on-shoulder movements, in both spatial and temporal dimensions, in order to shift the line of sight towards the inferred position of the goal. The variabilities in contributions of eyes and head movements to gaze-shift are modeled as functions of the retinal error and the initial orientations of eyes and head. The three models should be viewed as parts of a single executive program that integrates perceptual and motor processing across time and space. | |
| dc.identifier.uri | http://hdl.handle.net/10315/32728 | |
| dc.language.iso | en | |
| dc.rights | Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests. | |
| dc.subject | Cognitive psychology | |
| dc.subject.keywords | Decision making | |
| dc.subject.keywords | Reaction time | |
| dc.subject.keywords | Causal inference | |
| dc.subject.keywords | Cognition | |
| dc.subject.keywords | Kinematics | |
| dc.subject.keywords | Computational neuroscience | |
| dc.title | Computational Study of Multisensory Gaze-Shift Planning | |
| dc.type | Electronic Thesis or Dissertation |
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