2 options
Neural object representation spaces and their metric properties.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Drucker, Daniel M.
- Language:
- English
- Subjects (All):
- Cognitive psychology.
- Neurosciences.
- 0317.
- 0633.
- Penn dissertations--Psychology.
- Psychology--Penn dissertations.
- Local Subjects:
- Penn dissertations--Psychology.
- Psychology--Penn dissertations.
- 0317.
- 0633.
- Physical Description:
- 143 pages
- Contained In:
- Dissertation Abstracts International 70-10B.
- System Details:
- Mode of access: World Wide Web.
- text file
- Summary:
- A central focus of cognitive neuroscience is identification of the neural codes that represent stimulus dimensions. This dissertation investigates the relationship between stimulus similarity for several sets of parameterized shapes and the evoked patterns of activity in the brain. First, it is shown that patterns of neural activity associated with these parameterized shapes at both focal and distributed scales in object-responsive regions of cortex are highly isomorphic with behavioral measures of their stimulus similarity. Lateral and ventral portions of the lateral occipital complex are found to have differences in their tuning and the spatial scales of patterns of neural representation, based on the observed results of within-voxel adaptation and across-voxel distributed pattern analyses. Second, a new methodology is developed to distinguish between independent and conjoint neural representation of dimensions by examining the metric of two-dimension additivity. The assumptions of the method are examined as are optimizations. Finally, it is shown that the method produces the expected result for fMRI data collected from ventral occipito-temporal cortex while subjects viewed sets of shapes predicted to be represented by conjoint or independent neural tuning.
- Notes:
- Thesis (Ph.D. in Psychology) -- University of Pennsylvania, 2009.
- Source: Dissertation Abstracts International, Volume: 70-10, Section: B, page: 6019.
- Adviser: Geoffrey K. Aguirre.
- Local Notes:
- School code: 0175.
- ISBN:
- 9781109428476
- Access Restriction:
- Restricted for use by site license.
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