MS Proposal by Dolly Seeburger

Event Details
  • Date/Time:
    • Thursday July 1, 2021
      4:00 pm - 6:00 pm
  • Location: Atlanta, GA; REMOTE
  • Phone:
  • URL: Bluejeans
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Summaries

Summary Sentence: Identifying the Neural Mechanisms of Zone State Performance using Time-varying Functional Connectivity Methods

Full Summary: No summary paragraph submitted.

Name: Dolly Seeburger 

Master's Thesis Proposal Meeting

Date: Thursday, July 1st, 2021

Time: 4 pm eastern

Location: https://bluejeans.com/5732089742

 

Advisor: Eric Schumacher, Ph.D. (Georgia Tech)

 

Thesis Committee Members:

Shella Keilholz, Ph.D. (Georgia Tech and Emory)

Dobromir Rahnev, Ph.D. (Georgia Tech)
Eric Schumacher, Ph.D. (Georgia Tech)

 

Title: Identifying the Neural Mechanisms of Zone State Performance using Time-varying Functional Connectivity Methods.  

 

Abstract:

To successfully achieve our goals and perform optimally in many tasks, we need to control our attention and sustain it. Some people think of attention as a light switch – it’s either on or off, but a better metaphor is to equate attention to a candle that flickers –even when it is lit, its flame varies. This is reflected in subjective accounts of people claiming to feel focused or “in the zone” from one moment to being “zoned-out” in another. Early studies of sustained attention using fMRI compute correlation across the duration of the scan for regions of the brain which can last from minutes up to an hour. This assumption is problematic because like a flickering candle, researchers have found evidence of moment-to-moment fluctuations in the neural systems of attention (Chang & Glover, 2010; Majeed et al., 2011; Liu & Dyun, 2013). As a result, there has been contradictive studies claiming that large-scale networks like default mode network (DMN) and task positive network (TPN) can both support and be detrimental to performance.

 

To tackle this limitation, this study will employ two methods of time-varying functional connectivity, co-activation patterns (CAPs) and quasi periodic-pattern (QPP) to examine the interaction between the large-scale brain networks that are involved in zone state performance during a finger tapping task. The first level of analysis, using CAPs, aims to investigate moment-to-moment fluctuations in the attention networks within an individual. The main prediction is that there will be certain brain states that are more prevalent in in-the-zone epochs and others that are more prevalent in out-of-the-zone epochs. The second level analysis, using QPP, seeks to identify differences in stable performance versus unstable performance across time within an individual. I hypothesize that DMN and the TPN will be more anti-correlated in in-the-zone runs than out-of-the-zone runs within a subject.

 

If the results are as predicted, it elucidates how inter-regional functional connectivity supports sustained attention within an individual. This can lead us to a better neural mechanistic understanding of what facilitates attention in order to achieve better performance.

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In Campus Calendar
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Graduate Studies

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Faculty/Staff, Public, Graduate students, Undergraduate students
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Other/Miscellaneous
Keywords
MS Proposal
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Jun 24, 2021 - 11:35am
  • Last Updated: Jun 24, 2021 - 11:35am