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Differentiating self-reported imager...

Seiler, Brian D.

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Differentiating self-reported imagery abilities with functional magnetic resonance imaging.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Differentiating self-reported imagery abilities with functional magnetic resonance imaging./
Author:	Seiler, Brian D.
Description:	359 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
Contained By:	Dissertation Abstracts International76-06B(E).
Subject:	Neurosciences. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3672965
ISBN:	9781321505429

Differentiating self-reported imagery abilities with functional magnetic resonance imaging.
Seiler, Brian D.

Differentiating self-reported imagery abilities with functional magnetic resonance imaging. - 359 p.

Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.

Thesis (Ph.D.)--University of South Carolina, 2014.

Motor imagery (MI), a top-down knowledge-driven process involving the deliberate cognitive simulation or rehearsal of an action without engaging in overt physical movements, shares the same neural networks as movement execution improving motor learning and enhancing performance of motor tasks. The capacity to form images is not universal, and is a variable, moderating factor of neural activity impacting intervention effectiveness and distinguishing between individual imagery abilities. Measuring imagery abilities through self-report measures (i.e., MIQ-3 and VMIQ-2) is common, but the importance of behavioral and neuroimaging techniques have also been highlighted. Despite the robustness of these questionnaires, few studies have investigated their biological validity. This is surprising given that these questionnaires are frequently used to determine participants' imagery abilities and adopting them in the neuroscience literature for screening purposes. Therefore, two studies were conducted to help extend present MI theories by examining the convergent validity of self-report questionnaires through fMRI. In the first study, 17 females aged 18-30 screened by the MIQ-3 as having good imagery abilities were recruited to examine the construct validity of the MIQ-3. Following an fMRI simulation session, participants were scanned to determine the neural networks active during KI, IVI, and EVI of the arm rotation task of the MIQ-3. Results revealed common and distinct brain activity providing initial biological validation for the imagery abilities delineated in the MIQ-3. For study two, an additional 17 participants aged 18-30 were screened as having poor imagery abilities. The task and procedure were identical to the previous study. As expected, both good and poor imagers had peak activations in the inferior parietal lobule and motor-related areas. Inter-group comparisons revealed that good imagers had greater activation in the frontal, parietal and premotor areas. By contrast, poor imagers recruited a wider neural network (i.e., middle frontal gyrus and subcortical areas). Overall, both studies provide central evidence for common and divergent neural networks of imagery abilities defined in the sport sciences. Future research should expand this body of literature to other tasks and male participants as well as investigate imagery abilities used to create cognitive and affective image content.

ISBN: 9781321505429Subjects--Topical Terms:

588700
Neurosciences.

Differentiating self-reported imagery abilities with functional magnetic resonance imaging.
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500 $a Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
500 $a Adviser: Eva Monsma.
502 $a Thesis (Ph.D.)--University of South Carolina, 2014.
520 $a Motor imagery (MI), a top-down knowledge-driven process involving the deliberate cognitive simulation or rehearsal of an action without engaging in overt physical movements, shares the same neural networks as movement execution improving motor learning and enhancing performance of motor tasks. The capacity to form images is not universal, and is a variable, moderating factor of neural activity impacting intervention effectiveness and distinguishing between individual imagery abilities. Measuring imagery abilities through self-report measures (i.e., MIQ-3 and VMIQ-2) is common, but the importance of behavioral and neuroimaging techniques have also been highlighted. Despite the robustness of these questionnaires, few studies have investigated their biological validity. This is surprising given that these questionnaires are frequently used to determine participants' imagery abilities and adopting them in the neuroscience literature for screening purposes. Therefore, two studies were conducted to help extend present MI theories by examining the convergent validity of self-report questionnaires through fMRI. In the first study, 17 females aged 18-30 screened by the MIQ-3 as having good imagery abilities were recruited to examine the construct validity of the MIQ-3. Following an fMRI simulation session, participants were scanned to determine the neural networks active during KI, IVI, and EVI of the arm rotation task of the MIQ-3. Results revealed common and distinct brain activity providing initial biological validation for the imagery abilities delineated in the MIQ-3. For study two, an additional 17 participants aged 18-30 were screened as having poor imagery abilities. The task and procedure were identical to the previous study. As expected, both good and poor imagers had peak activations in the inferior parietal lobule and motor-related areas. Inter-group comparisons revealed that good imagers had greater activation in the frontal, parietal and premotor areas. By contrast, poor imagers recruited a wider neural network (i.e., middle frontal gyrus and subcortical areas). Overall, both studies provide central evidence for common and divergent neural networks of imagery abilities defined in the sport sciences. Future research should expand this body of literature to other tasks and male participants as well as investigate imagery abilities used to create cognitive and affective image content.
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