September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Still Rough Around the Edges – Effects of Age and Individual Differences on Neural Network Organization in Young Adults
Author Affiliations
  • Daniel Elbich
    The Pennsylvania State UniversitySocial, Life, and Engineering Sciences Imaging Center
  • Suzy Scherf
    The Pennsylvania State UniversitySocial, Life, and Engineering Sciences Imaging Center
Journal of Vision September 2018, Vol.18, 933. doi:10.1167/18.10.933
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      Daniel Elbich, Suzy Scherf; Still Rough Around the Edges – Effects of Age and Individual Differences on Neural Network Organization in Young Adults. Journal of Vision 2018;18(10):933. doi: 10.1167/18.10.933.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Researchers tend to think of adults as face recognition experts, given the more than 10 years of experience honing this skill. However, recent evidence indicates that there is a vast range of individual differences in face recognition abilities even among typically developing young adults. Importantly, the vast majority of work on face recognition abilities is done with participants who are emerging adults, who are ages 18-25 years, when face recognition skills are still developing (see Germine et al., 2011). In this presentation, I will describe findings from functional and diffusion neuroimaging experiments (all conducted with the same participants) that reveal how age and individual differences in performance relate to variations in underlying neural network organization for face processing. A group of 40 emerging adults completed tasks of both unfamiliar and familiar face recognition outside the scanner that are reliable tools for measuring individual differences in recognition performance (see Elbich & Scherf, 2017). These participants were then scanned using fMRI, as they passively viewed faces and other visual categories, and diffusion MRI. We report that when controlling for the age-related effects in behavior, we still observed individual differences in behavior that were significantly related to functional neural network organization. Specifically, better recognizers exhibited a larger proportion of activated nodes in the face processing network and distinct patterns of directed functional connections among these nodes. In addition, the results from the dMRI study revealed some age-related declines in diffusivity in the long-range fiber tracts that connect face processing regions (ILF, IFOF) as well as age-independent associations between better recognition behavior and decreasing diffusivity. Together, these findings reveal that performance differences in face recognition among emerging adults are related to both ongoing age-related changes as well as individual differences in neural network organization.

Meeting abstract presented at VSS 2018

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