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Title: How the brain grasps tools : fMRI & motion-capture investigations
Author: Knights, Ethan
ISNI:       0000 0004 8501 8217
Awarding Body: University of East Anglia
Current Institution: University of East Anglia
Date of Award: 2019
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Humans' ability to learn about and use tools is considered a defining feature of our species, with most related neuroimaging investigations involving proxy 2D picture viewing tasks. Using a novel tool grasping paradigm across three experiments, participants grasped 3D-printed tools (e.g., a knife) in ways that were considered to be typical (i.e., by the handle) or atypical (i.e., by the blade) for subsequent use. As a control, participants also performed grasps in corresponding directions on a series of 3D-printed non-tool objects, matched for properties including elongation and object size. Project 1 paired a powerful fMRI block-design with visual localiser Region of Interest (ROI) and searchlight Multivoxel Pattern Analysis (MVPA) approaches. Most remarkably, ROI MVPA revealed that hand-selective, but not anatomically overlapping tool-selective, areas of the left Lateral Occipital Temporal Cortex and Intraparietal Sulcus represented the typicality of tool grasping. Searchlight MVPA found similar evidence within left anterior temporal cortex as well as right parietal and temporal areas. Project 2 measured hand kinematics using motion-capture during a highly similar procedure, finding hallmark grip scaling effects despite the unnatural task demands. Further, slower movements were observed when grasping tools, relative to non-tools, with grip scaling also being poorer for atypical tool, compared to non-tool, grasping. Project 3 used a slow-event related fMRI design to investigate whether representations of typicality were detectable during motor planning, but MVPA was largely unsuccessful, presumably due to a lack of statistical power. Taken together, the representations of typicality identified within areas of the ventral and dorsal, but not ventro-dorsal, pathways have implications for specific predictions made by leading theories about the neural regions supporting human tool-use, including dual visual stream theory and the two-action systems model.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available