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Intentional Control of Cognitive Dynamics

Pavlov Garcia, Olivia C

Abstract Details

2015, MA, University of Cincinnati, Arts and Sciences: Psychology.
The relationship between network architecture and behavior may offer a framework with which to examine the many influences of cognition. Real and artificial networks have been studied extensively to understand this reciprocal relationship. Here, methods developed to examine the output of artificial networks were applied to analyze human reading performance. The core hypothesis is that cognitive influences such as word frequency, intention, and task difficulty should all yield patterns of performance change that corresponded to changes observed when the connection strengths of an artificial network are altered. An artificial network simulation was performed, explicitly testing the influence of connection strength on network output distributions. When connection strength among the network components was high, the output distribution was less skewed than when connection strength was weaker. In a series of three experiments, distributions of human responses from a Lexical Decision reading task were examined for changes consistent with the simulation study pattern. Word frequency has historically been implicated with connection strength, and was the first cognitive influence examined. In Experiment 1, a word frequency manipulation resulted in distributional changes such that distributions of responses to high frequency items were less skewed than those to low frequency items; consistent with the pattern found when connection strength was weakened. After establishing the efficacy of the analyses as applied to human response distributions, intentional influence was examined and was also postulated to operate like a control parameter. Experiment 2 induced an intention manipulation, and found that with the intention to read quickly participants’ response distributions were less skewed than with the intention to read accurately. InExperiment 3, intentionality and task difficulty differentially interacted to impact distributional skew. Distributions were most skewed when participants adopted the intention to perform accurately and the task was difficult. Together, all three cognitive influences impacted performance similarly, in a manner consistent with manipulating connection strength in an artificial network. These findings may offer a framework in which intentions and other cognitive influences may be conceptualized as control parameters governing the dynamic organization of flexible, functional neurophysiological networks.
John Holden, Ph.D. (Committee Chair)
Sheila Fleming, Ph.D. (Committee Member)
Michael Riley, Ph.D. (Committee Member)
60 p.

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Citations

  • Pavlov Garcia, O. C. (2015). Intentional Control of Cognitive Dynamics [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1446547138

    APA Style (7th edition)

  • Pavlov Garcia, Olivia. Intentional Control of Cognitive Dynamics. 2015. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1446547138.

    MLA Style (8th edition)

  • Pavlov Garcia, Olivia. "Intentional Control of Cognitive Dynamics." Master's thesis, University of Cincinnati, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1446547138

    Chicago Manual of Style (17th edition)