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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp015138jh30x
Title: A Shared Space in Thought: Similarity Approaches to Analyzing fMRI Data
Authors: Johnson, Peter
Advisors: Norman, Kenneth
Department: Psychology
Class Year: 2016
Abstract: Most experiments in psychology rely on stimuli far removed from real life. By isolating very specific features, we are also able to isolate very specific functions in the brain. However, something important is lost in this abstraction. Ultimately, we are interested in mechanisms of thought as they exist in our everyday lives. In this paper, I explore ways to analyze fMRI data in complex, naturalistic stimuli—in this case an episode of a TV show—that will allow us to see how the brain represents features of this data. First, I examine how inter-subject similarity changes over time and in response to movie features. I explore how different similarity metrics demonstrate different structural features in the shared representation among viewers. A Multi-Voxel Classification Analysis is used to extend this result of common representational structure in similar stimuli by evaluating the relative dissimilarity of opposing feature representations. By showing reliable classification of scenes with only the activation patterns of other participants, this establishes that the shared neural patterns do correspond to shared representation. Finally, I turn to representational similarity analysis (RSA) in order to quantify the specific contributions of the individual features. Also discussed are complexities in measuring significance with permutation tests which, when ignored, can lead to massively overestimating significance in these analyses.
Extent: 53 pages
URI: http://arks.princeton.edu/ark:/88435/dsp015138jh30x
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Psychology, 1930-2016

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