title: Are there gender differences in young vs. aging brains under risk decision-making? An optical brain imaging study.
abstract: Few research publications have reported on gender-dependent neural correlates of risk decision-making in older adults. In this study, we utilized functional near-infrared spectroscopy (fNIRS) to comprehensively investigate both age- and gender-dependent differences in neural correlates in response to a well-utilized risk decision-making protocol, the Balloon Analog Risk Task (BART). A newly-developed technique, atlas-guided diffuse optical tomography (atlas-DOT), was used to image the prefrontal cortices (PFC) of healthy subjects in two age groups (25-40 years; 60-92 years) using BART stimulation. The behavioral measures and brain activations imaged by atlas-DOT were recorded and compared for both age groups. Three-factor analysis of variance was conducted to include all effects of age (young, old), gender (male, female), case (win, lose) and their interactions for both behavioral and hemodynamic responses. The results indicated age differences in cortical activation patterns, activation amplitudes, and brain-behavior correlations. Larger areas of cortical activation with reduced amplitudes in the PFC were observed in older adults when they performed BART. Brain-behavior correlations indicated that young adults took more risks, whereas older adults were more risk-averse. Results also revealed a gender effect in young adults, but not in older adults. Both male and female older adults demonstrated strong PFC responses and the same risk-averse patterns under lose outcomes. This is the first study to examine the neural correlates of risk decisions in older adults by optical brain imaging.
authors.affiliation: Department of Bioengineering, Joint Graduate Program between University of Texas at Arlington and University of Texas Southwestern Medical Center, University of Texas at Arlington, Arlington, TX, 76019, USA.|Department of Neurology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA.
authors.forename: Lin
authors.initials: L
authors.lastname: Li
authors.affiliation: Cook Children's Medical Center, Fort Worth, TX, 76104, USA.
authors.forename: Mary
authors.initials: M
authors.lastname: Cazzell
authors.affiliation: Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Zeng
authors.affiliation: Department of Bioengineering, Joint Graduate Program between University of Texas at Arlington and University of Texas Southwestern Medical Center, University of Texas at Arlington, Arlington, TX, 76019, USA. hanli@uta.edu.
authors.forename: Hanli
authors.identifier: 0000-0002-9312-5691
authors.initials: H
authors.lastname: Liu
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology* / Q000523:psychology; D000704:Analysis of Variance; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology*; D005260:Female; D006439:Hemodynamics / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D012309:Risk-Taking; D012727:Sex Characteristics; D019265:Spectroscopy, Near-Infrared; D041622:Tomography, Optical
keywords: Age effect; Functional near-infrared spectroscopy; Gender effect; Neural correlates; Optical brain imaging; Risk decision-making