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.

Numerical Comparisons and Sex-Related Brain Connectivity

“…Similar behavioral performance with significant sex-related differences in the underlying brain activation patterns while performing cognitive tasks both in healthy (e.g., Bell et al, 2006;Li et al, 2017;Riley et al, 2018) and patients suffering from different pathological conditions (e.g., Kasher et al, 2019) had been previously reported. These contradictory findings seem to be supported by a sex-related distinct functional brain organization favoring adaptive processing strategies that converge into the goal of maximizing efficient use of task-demanded cognitive resources.…”

Comparing diffuse optical tomography and functional magnetic resonance imaging signals during a cognitive task: pilot study

“…44 The measured activation patterns can only be projected onto structural MRI, which is performed on the individual subject, when external landmarks are required for cranio-cerebral correlations with the 10 − 10∕10 − 20 electrode placement system. 45 An approach would be to create a finite element for a standard brain template [46][47][48] or subject-specific MR scans, 49,50 which forward model considering different optical properties for each brain layer, which could minimize the reconstruction errors and improve spatial accuracy.…”

“…57 The present work allows a GLM analysis voxel-by-voxel over reconstructed DOT images for each molecule HbO and HbR to be made, unlike other authors who applied GLM analysis prior to the reconstruction of the images. 46,48 …”

Effect of emotions on risk taking, dishonesty and social cognition in college emerging adults

“…Por otra parte, al analizar el desempeño de los adultos emergentes en la toma de riesgo bajo distintos estados emocionales, en primer lugar, observamos que los hombres, independientemente del tipo de inducción emocional, tomaron más riesgos que las mujeres. Este sesgo en función del sexo para el comportamiento de riesgo también ha sido reportado por otros grupos (Li et al, 2016;Pilatti, Rivarola Montejano et al, 2017). Al respecto, distintos estudios han evidenciado diferencias neuroanatómicas, neurocognitivas y neuroendócrinas específicas en función del sexo durante el desarrollo, desde la niñez a la adultez emergente (Gur y Gur, 2016;Herting et al, 2018;Ingalhalikar et al, 2014;Peper, Koolschijn y Crone, 2013;Roalf et al, 2014).…”