Age- and gender-related differences in the cortical anatomical network

By Gaolang Gong, Pedro Rosa-Neto, Felix Carbonell, Zhang John Chen, Yong He, Alan C. Evans. Journal of Neuroscience, 2009

613 citations recorded by the source corpus.

Neuroanatomical differences attributable to aging and gender have been well documented, and these differences may be associated with differences in behaviors and cognitive performance. However, little is known about the dynamic organization of anatomical connectivity within the cerebral cortex, which may underlie population differences in brain function. In this study, we investigated age and sex effects on the anatomical connectivity patterns of 95 normal subjects ranging in age from 19 to 85 years. Using the connectivity probability derived from diffusion magnetic resonance imaging tractography, we characterized the cerebral cortex as a weighted network of connected regions. This approach captures the underlying organization of anatomical connectivity for each subject at a regional level. Advanced graph theoretical analysis revealed that the resulting cortical networks exhibited “small-world” character (i.e., efficient information transfer both at local and global scale). In particular, the precuneus and posterior cingulate gyrus were consistently observed as centrally connected regions, independent of age and sex. Additional analysis revealed a reduction in overall cortical connectivity with age. There were also changes in the underlying network organization that resulted in decreased local efficiency, and also a shift of regional efficiency from the parietal and occipital to frontal and temporal neocortex in older brains. In addition, women showed greater overall cortical connectivity and the underlying organization of their cortical networks was more efficient, both locally and globally. There were also distributed regional differences in efficiency between sexes. Our results provide new insights into the substrates that underlie behavioral and cognitive differences in aging and sex.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/c0d9a28a48d624a82abf714994127ae80f266f2c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Olaf Sporns
2. Yong He
3. Xi-Nian Zuo
4. D. Bassett
5. E. Bullmore
6. Alan C. Evans
7. Jinhui Wang
8. Michael P. Milham

In Radiology, Nuclear Medicine and Imaging

1. Olaf Sporns
2. Yong He
3. Xi-Nian Zuo
4. D. Bassett
5. Alan C. Evans
6. E. Bullmore
7. Jinhui Wang
8. Chaogan Yan

Citations in the corpus

• Exploring mechanisms of spontaneous functional connectivity in MEG: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations (2014, methodology): “The structural brain networks used in the model were estimated from diffusion tensor imaging (DTI) data using a modified version of already published methods (Gong et al., 2009) (see Fig.”
• Multisensory Stimulation in Stroke Rehabilitation (2012, background): “It is proposed that it should be mandatory to take gender into account when designing experiments or interpreting results of brain connectivity/network in health and disease (Gong et al., 2009, 2011).”
• Brain graphs: graphical models of the human brain connectome. (2011, background): “…including behavioral variability (Bassett et al. 2009), cognitive ability (Li et al. 2009, van den Heuvel et al. 2009), shared genetic factors (Smit et al. 2008), genetic information (Schmitt et al. 2008), age (Meunier et al. 2008, Micheloyannis et al. 2009), and gender (Gong et al. 2009).”
• Functional connectivity hubs in the human brain (2011, positive): “Higher brain connectivity in females was also reported by diffusion magnetic resonance imaging (MRI) tractography studies that showed greater overall anatomical connectivity in the female than in the male brain (Gong et al., 2009).”
• Graph-Based Network Analysis of Resting-State Functional MRI (2010, positive): “…as highly modular small-world architectures capable of efficiently transferring information at a low wiring cost as well as formatting highly connected hub regions (Salvador et al., 2005; Achard et al., 2007; He et al., 2007, 2009b; Chen et al., 2008b; Hagmann et al., 2008; Gong et al., 2009a).”
• Networks of anatomical covariance (2013, methodology): “…employ diffusion-weighted imaging (DWI) and tractography to examine structural connectivity as a white matter (WM) phenomenon (Behrens et al., 2007; Gong et al., 2009a, 2011; Hofer and Frahm, 2006; Iturria-Medina, 2013; Jbabdi et al., 2007; Le Bihan and Johansen-Berg, 2012; Raj and Chen, 2011;…”
• Sex differences in the structural connectome of the human brain (2013, background): “Although SCs of genders have displayed small-world architecture with broad-scale characteristics (34, 35), sex differences in network efficiency have been reported (36), with women having greater overall cortical connectivity (37).”
• Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex (2012, methodology): “Such integrated metrics mathematically correspond to the areas under the metric curve and have been applied in recent brain network studies (Bassett et al., 2008; Gong et al., 2009a; He et al., 2007, 2008).”
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• Growing together and growing apart: Regional and sex differences in the lifespan developmental trajectories of functional homotopy (2010, methodology): “Age-related changes in global homotopic connectivity Following developmental studies of human brain morphometry and tractography (Good et al., 2001; Toga et al., 2006; Gong et al., 2009), we examined age-related changes in global homotopic RSFC indexed by mean VMHC (calculated for gray matter only).”
• Test-retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures (2012, background): “…can be altered in mental disease (Bassett et al., 2008; Rubinov et al., 2009; Supekar et al., 2008; Wang et al., 2009), is affected by age and sex (Gong et al., 2009; Micheloyannis et al., 2009; Tian et al., 2011) and can undergo rapid plastic changes (Achard and Bullmore, 2007; Polanía et al.,…”
• Characterization of Cerebral White Matter Properties Using Quantitative MRI Stains (2011, background): “One study investigated connectivity properties as a function of age and gender in adults (ages 19–85 years) and found reduced connectivity properties with age and in men (Gong et al., 2009).”
• PANDA: a pipeline toolbox for analyzing brain diffusion images (2013, methodology): “Each row or column of the matrix represents a cortical region of the AAL template (Gong et al., 2009a,b).”
• Hemisphere- and gender-related differences in small-world brain networks: A resting-state functional MRI study (2011, methodology): “However, in a study by Gong et al. (2009b), the cortical networks of females were more efficient both locally and globally.”
• Network-based statistic: Identifying differences in brain networks (2010, background): “…(Wang et al., 2009), multiple sclerosis (He et al., 2009) and schizophrenia (Bassett et al., 2008, 2009; Liu et al., 2008; Rubinov et al., 2009) as well as associations with age and gender (Gong et al., 2009; Wang et al., 2010), and intelligence (van den Heuvel et al., 2009; Li et al., 2009).”