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ucin1305893614.pdf (5.21 MB)
ETD Abstract Container
Abstract Header
Modular Context-Dependent Functional Networks for Associative Memory
Author Info
Sagar, Chandrika
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1305893614
Abstract Details
Year and Degree
2011, MS, University of Cincinnati, Engineering and Applied Science: Electrical Engineering.
Abstract
All mental function – perception, cognition or action – is, ultimately, based on memory and its appropriate recall. The question of how the brain learns memories and their associations has been one of the most debated and interesting topics of research by cognitive psychologists and neuroscientists. Experiments show that human memory is largely associative, working through association between entities seen in the real world. In such a memory, recall occurs when the system is presented with a partial cue for the content, which then triggers the rest of the memory by association. A very important aspect of human memory is that associations are highly context-dependent, allowing the brain to represent a very large body of knowledge concisely through different combinations of a relatively small set of memories. This can also be seen as the basis of the brain’s ability to generate novel ideas. The most successful computational models for associative memory are based on attractor dynamics in recurrent neural networks. However, relatively little work has been done on context-dependent associative memory. This thesis presents modular recurrent neural network architecture for context-dependent associative memory (CDAM) that provides a natural and biologically plausible way to represent context-dependence in the network dynamics. The simulations shown indicate that this system is capable of both exploitation (recalling previously learned memories in a context-appropriate way) and exploration (generating novel but sensible “memories” that can be seen as representing new ideas.) The role of noise in both exploitation and exploration is an especially intriguing issue, and is investigated systematically in the thesis.
Committee
Ali Minai, PhD (Committee Chair)
Raj Bhatnagar, PhD (Committee Member)
Carla Purdy, C, PhD (Committee Member)
Pages
98 p.
Subject Headings
Engineering
Keywords
context-dependent
;
CDAM
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Citations
Sagar, C. (2011).
Modular Context-Dependent Functional Networks for Associative Memory
[Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1305893614
APA Style (7th edition)
Sagar, Chandrika.
Modular Context-Dependent Functional Networks for Associative Memory.
2011. University of Cincinnati, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1305893614.
MLA Style (8th edition)
Sagar, Chandrika. "Modular Context-Dependent Functional Networks for Associative Memory." Master's thesis, University of Cincinnati, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1305893614
Chicago Manual of Style (17th edition)
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Document number:
ucin1305893614
Download Count:
355
Copyright Info
© 2011, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.