Liu, Ruizhe
(2020)
The neural basis for symbolic numbers: multi-constituent neural networks and the connectivity.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
This is the latest version of this item.
Abstract
We are able to understand numbers in various formats. For instance, we can read Arabic numerals (defined as the visual code in the current study) from a book and talk about these numbers (the verbal code). We can use our hands to express a number (the manual code). We can also compare the number of jellybeans in different jars without actually counting them (the semantics). How does the human brain represent these different number codes? Existing findings show that the number codes might be locally represented by unique brain regions. However, different number codes might be tightly connected to each other, e.g., one might be internally saying the number word when seeing an Arabic numeral and this potential integration between number codes has not been thoroughly explored in previous studies. Here, we used a number code localizer task to first examine the neural representation of the four number codes separately. Specifically, adults and third to fourth graders were asked to complete a number comparison task (the semantic task) and a phonological comparison (the verbal task) task in an MRI scanner. The stimuli were either Arabic numerals (the visual code) or hand images (the manual code) displaying different numbers. The contrast between different number codes yielded multiple unique brain regions supporting the neural representation of each number code. We then tested the context-dependent connectivity among all the brain regions yielded by the contrasting analyses and found that some brain regions were involved in representing more than one number code. The results stand against the localist view and support the notion that the neural representation of each number code is distributed
among a network consisting of brain regions unique to each number code as well as brain regions common to several number codes.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
8 June 2020 |
Date Type: |
Publication |
Defense Date: |
30 March 2020 |
Approval Date: |
8 June 2020 |
Submission Date: |
8 April 2020 |
Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
Number of Pages: |
120 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Dietrich School of Arts and Sciences > Psychology |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
symbolic numbers, numerical processing, fMRI, neural network, context-dependent connectivity |
Date Deposited: |
08 Jun 2020 16:37 |
Last Modified: |
08 Jun 2022 05:15 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/38845 |
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