bastivkl / gender_fmri

Gender differences in brain functional connectivity for relational processing using the HCP dataset.

relational_differences_gender_fmri

Gender differences in brain functional connectivity for relational processing using the HCP dataset.

Authors

Xiaowei Zhang, Sebastian Völkl, Shruti-Raj-Vansh-Singh, Didem Katircilar

Abstract

Relational processing refers to the encoding of similarities among a class of events and individual-item processing refers to the encoding of item-specific information. There are different objects that have the same geometric properties such as shape but differ in their material properties such as texture (Hunt & Einstein, 1981). For example, an orange and a tennis ball have a similar shape, but their texture can help us to distinguish them (Podrebarack et al., 2014). Functional magnetic resonance imaging (fMRI) is widely used to detect the level of activation of regions of the brain in response to specific stimuli and tasks. The measurement of the interactions of multiple regions that are engaged simultaneously in a task is functional connectivity. Such functional connectivity can be used to predict participant identification (Venkatesh & Jaja, 2019). In addition to that, gender has a crucial role to understand how the brain operates different cognitive functions. There are recent neuroimaging studies which show that brain connectivity varies across gender (Acer & İçer, 2020). The lateral occipital cortex is responsible for shape perception (Podrebarack et al., 2014), while the left inferior occipital cortex (IOC) and the fusiform gyrus play a critical role in texture perception (Stylianou-Korsness et al., 2010). Moreover, the frontoparietal network, possibly executed by the basal ganglia, shows activation during perceptual decision-making (Keuken et al., 2014). Therefore, our current study will use Human Connectome Project (HCP) relational task dataset to test whether functional connectivity can be used to predict gender and identify functional connectivity (FC) features that are most predictive of gender. In the current research, we aim to gain more insight into how the male and female brain operates during shape and texture perception and the decision-making process based on the perception of geometric or material properties of objects.

By Xiaowei Zhang, Shruti-Raj-Vansh-Singh, Didem Katircilar and Sebastian Völkl.