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Mapping Underlying Dynamic Effective Connectivity In Neural Systems Using The Deconvolved Neuronal Activity

Baik, Seo Hyon (2010) Mapping Underlying Dynamic Effective Connectivity In Neural Systems Using The Deconvolved Neuronal Activity. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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ABSTRACTMAPPING UNDERLYING DYNAMIC EFFECTIVE CONNECTIVITY IN NEURAL SYSTEMS USING THE DECONVOLVED NEURONALACTIVITYSeo Hyon Baik, PhDUniversity of Pittsburgh, 2010Event-related functional magnetic resonance imaging (fMRI) has emerged as a tool for studying the functioning of the human brain. The study on fMRI supplies information on the underlying mechanism of the human brain, such as how a brain in good shape functions, how a brain affected by different diseases works, how a brain struggles to recover after damage and how different stimuli can modulate this recovery process.The variable of interest is the neuronal activities given a stimulus, however the signalbeing quantified by MRI scanner is the blood oxygenation level-dependent (BOLD) response which is the subordinate repercussion of the underlying neuronal activity such as local changes in blood flow, volume and oxygenation level that takes place within a few second of changes in neuronal activity. From this point of view, one may think that the neuronal-activity-based and BOLD-based studies would be dissimilar in yielding information on the underlying mechanism of the human brain. This dissertation is devoted primarily to estimating underlying neuronal activities given a stimuli. In particular, we develop a method of estimating intrinsic neuronal signals and haemodynamic responses under thefact that a BOLD response is expressed as a convolution of the underlying neuronal signaland the haemodynamic response function. We also present differences between the use of estimated neuronal signals and of observed BOLD responses in investigating causal relationships among heterogeneous brain regions using an ordinary vector autoregressive model.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Baik, Seo Hyonshb6@pitt.eduSHB6
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairGleser, Leon Jgleser@pitt.eduGLESER
Committee MemberKrafty, Robertkrafty@pitt.eduKRAFTY
Committee MemberThompson, Wesley
Committee MemberCheng, Yuyucheng@pitt.eduYUCHENG
Date: 28 September 2010
Date Type: Completion
Defense Date: 28 July 2010
Approval Date: 28 September 2010
Submission Date: 18 August 2010
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Statistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: deconvolution of underlying neuronal signals; effective connectivity
Other ID:, etd-08182010-214622
Date Deposited: 10 Nov 2011 20:00
Last Modified: 15 Nov 2016 13:49


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