Trait motivation is associated with Fusiform face area (FFA) gray matter volume in a Chinese sample
Poster No:
2084
Submission Type:
Late-Breaking Abstract Submission
Authors:
HangShek Lau1, Shan Xu1
Institutions:
1Beijing Normal University, Haidian, Beijing
First Author:
Co-Author:
Late Breaking Reviewer(s):
Eduardo Garza-Villarreal, M.D., Ph.D.
Universidad Nacional Autónoma de México campus Juriquilla
Juriquilla, Querétaro
Universidad Nacional Autónoma de México campus Juriquilla
Juriquilla, Querétaro
Introduction:
It has been increasingly recognized that the mind is highly integrative, with functional modules dynamically collaborating to support an animal's adaptive interactions with its environment (Bernard et al., 2005; Withagen, 2018). From this perspective, individual differences in traits may reflect distinct strategies for adapting to environmental demands and opportunities (Matthews, 2008; Gray, 1982; Matthews, 2017). However, it remains unclear whether these trait-like motivational dispositions extend their influence beyond explicit reward or threat processing to shape more general perceptual mechanisms. The present study examines face processing as a representative case of general perceptual processing and investigates whether trait motivation influences the structural characteristics of the face network-a well-defined neural system encompassing the fusiform face area (FFA), occipital face area (OFA), and superior temporal sulcus (STS) (Kanwisher et al., 1997; Haxby et al., 2000). Furthermore, we assess whether the association with trait motivation is reflected in face-selective activity within these regions and whether trait motivation correlate with general face recognition performance in an old-new task. We hypothesize that trait motivation is associated with face processing across neuroanatomical, functional, and behavioral dimensions.
Methods:
A total of 264 participants were recruited for the study. Due to the attrition of participants, all analyses were based on the maximum available sample sizes: VBM (n = 264), functional activity (n = 246), and behavioral experiment (n = 239). Trait motivation were assessed by BAS/BIS scale (Carver & White, 1994). Face-selective activation was defined as the contrast between faces and objects in the fMRI localizer task, where participants watched dynamic clips of faces or objects. Face recognition ability was assessed by a face recognition old-new task.Voxel-based morphometry (VBM) analysis was conducted using SPM8 and DARTEL to quantify gray matter volume. fMRI data were preprocessed using FSL, including motion correction, spatial smoothing, and normalization. Regions of interest (ROIs) in the bilateral FFA, OFA, and pSTS were defined based on previous research, and partial correlation analyses were conducted to examine the association between BIS/BAS scores and regional GMV (Bonferroni correction, p < 0.05). Furthermore, voxel-wise analyses were conducted separately for both VBM and functional activity, identifying clusters linked to trait motivation (uncorrected, p < 0.001). Behavioral analysis compared BIS scores between high and low face memory performers using t-tests.
Results:
Partial correlation analyses of ROIs revealed a significant positive correlation between BIS and mean gray matter volume (GMV) in the left and right FFA (rFFA: rpartial = 0.186, pBonferroni correction = 0.003; lFFA: partialr = 0.152, puncorrected = 0.014). Voxel-wise VBM analysis revealed significant positive GMV-BIS associations in voxel clusters within the bilateral fusiform gyrus and bilateral angular gyrus (p < 0.001, uncorrected, Table 1). To further investigate whether BIS is associated with face recognition performance, participants were divided into high and low face recognition groups based on a median split. After controlling for sex, age, and general memory performance, individuals with high face recognition performance exhibited significantly higher BIS scores (t (237) = -2.060, p = 0.040 Cohen's d = -0.257; Figure 1C), suggesting a positive relationship between BIS and face recognition ability.
·Figure 1
·Table 1
Conclusions:
The study found a positive link between BIS score and gray matter volume in the right FFA, a crucial face - network brain area. Complementing VBM results, those with high BIS showed better face recognition. Overall, these findings indicate that trait motivation differences are associated with face - processing differences, suggesting a potential connection between trait motivation and perception.
Emotion, Motivation and Social Neuroscience:
Social Cognition
Emotion and Motivation Other
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Univariate Modeling
Novel Imaging Acquisition Methods:
Anatomical MRI 2
BOLD fMRI
Perception, Attention and Motor Behavior:
Perception: Visual 1
Keywords:
ADULTS
Cognition
Cortex
MRI
Perception
STRUCTURAL MRI
Univariate
Vision
1|2Indicates the priority used for review
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Provide references using APA citation style.
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Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. (2000). The distributed human neural system for face perception. Trends in Cognitive Sciences, 4(6), 223–233. https://doi.org/10.1016/S1364-6613(00)01482-0
Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception. Journal of Neuroscience, 17(11), 4302–4311. https://doi.org/10.1523/JNEUROSCI.17-11-04302.1997
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Matthews, G., Lin, J., & Wohleber, R. (2017). Personality, Stress and Resilience: A Multifactorial Cognitive Science Perspective. Psychological Topics, 26(1), Article 1.
Withagen, R. (2018). Towards an ecological approach to emotions and the individual differences therein. New Ideas in Psychology, 51, 21–26. https://doi.org/10.1016/j.newideapsych.2018.04.004