Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI

Abstract

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

Keywords: Gender difference; Generalized q-sampling imaging (GQI); Graph theoretical analysis; Network-based statistical (NBS) analysis; Structural connectome.

Fig. 1

Schematic of the pipeline for creating the brain structural connectivity matrix and network using GQI.

Fig. 2

Higher topological measures were found in teenage male brain networks with GQI, including (a) clustering coefficient, (b) normalized clustering coefficient, (c) local efficiency, (d) normalized characteristic path length, (e) transitivity, and (f) small-worldness index (p < 0.05).

Fig. 3

In the results of network-based statistical analysis, (a) more intrahemispheric, local, short-range, within-lobe connectivity was found in teenage males, especially within bilateral frontal lobes and parieto-occipital lobes, (b) while more interhemispheric, long-range connectivity was found in teenage females, especially between bilateral frontal lobes and between bilateral frontal to contralateral parieto-occipital lobes (p < 0.05). The nodes with the same color represent the same module. Node size represents the degree of information, with bigger nodes indicating a higher degree.