Computational morphometry of magnetic resonance images represents a powerful tool for studying macroscopic differences in human brains. In the present study (N participants = 829), we combined different techniques and measures of brain morphology to investigate one of the most compelling topics in neuroscience: sexual dimorphism in human brain structure. When accounting for overall larger male brains, results showed limited sex differences in gray matter volume (GMV) and surface area. On the other hand, we found larger differences in cortical thickness, favoring both males and females, arguably as a result of region-specific differences. We also observed higher values of fractal dimension, a measure of cortical complexity, for males versus females across the four lobes. In addition, we applied source-based morphometry, an alternative method for measuring GMV based on the independent component analysis. Analyses on independent components revealed higher GMV in fronto-parietal regions, thalamus and caudate nucleus for females, and in cerebellar- temporal cortices and putamen for males, a pattern that is largely consistent with previous findings.

Del Mauro, G., Del Maschio, N., Sulpizio, S., Fedeli, D., Perani, D., Abutalebi, J. (2022). Investigating sexual dimorphism in human brain structure by combining multiple indexes of brain morphology and source-based morphometry. BRAIN STRUCTURE AND FUNCTION, 227(1), 11-21 [10.1007/s00429-021-02376-8].

Investigating sexual dimorphism in human brain structure by combining multiple indexes of brain morphology and source-based morphometry

Sulpizio S.;
2022

Abstract

Computational morphometry of magnetic resonance images represents a powerful tool for studying macroscopic differences in human brains. In the present study (N participants = 829), we combined different techniques and measures of brain morphology to investigate one of the most compelling topics in neuroscience: sexual dimorphism in human brain structure. When accounting for overall larger male brains, results showed limited sex differences in gray matter volume (GMV) and surface area. On the other hand, we found larger differences in cortical thickness, favoring both males and females, arguably as a result of region-specific differences. We also observed higher values of fractal dimension, a measure of cortical complexity, for males versus females across the four lobes. In addition, we applied source-based morphometry, an alternative method for measuring GMV based on the independent component analysis. Analyses on independent components revealed higher GMV in fronto-parietal regions, thalamus and caudate nucleus for females, and in cerebellar- temporal cortices and putamen for males, a pattern that is largely consistent with previous findings.
Articolo in rivista - Articolo scientifico
Cortical thickness; Fractal dimension; Gray matter volume; Sex differences; Source-based morphometry; Surface area;
English
16-set-2021
2022
227
1
11
21
open
Del Mauro, G., Del Maschio, N., Sulpizio, S., Fedeli, D., Perani, D., Abutalebi, J. (2022). Investigating sexual dimorphism in human brain structure by combining multiple indexes of brain morphology and source-based morphometry. BRAIN STRUCTURE AND FUNCTION, 227(1), 11-21 [10.1007/s00429-021-02376-8].
File in questo prodotto:
File Dimensione Formato  
Del Mauro-2022-Brain Struct Funct-preprint.pdf

accesso aperto

Descrizione: Methods paper
Tipologia di allegato: Submitted Version (Pre-print)
Licenza: Altro
Dimensione 1.96 MB
Formato Adobe PDF
1.96 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/403977
Citazioni
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 3
Social impact