scholarly journals Sex Differences in Brain Structure Account for the Sexual Distinction on Balanced Time Perspective

2021 ◽  
Author(s):  
Tao Chen ◽  
Zhi Li ◽  
Ji-fang Cui ◽  
Jia Huang ◽  
Muireann Irish ◽  
...  
Keyword(s):  
Sex Differences ◽  
Cortical Thickness ◽  
Grey Matter ◽  
Time Perspective ◽  
Supplementary Motor Area ◽  
Motor Area ◽  
Human Cognition ◽  
Grey Matter Volume ◽  
Matter Volume ◽  
Balanced Time Perspective

Abstract Sex differences in behaviour and cognition have been widely observed, however, little is known about such differences in maintaining a balanced time perspective or their potential underlying neural substrates. To answer the above questions, two studies were conducted. In Study 1, time perspective was assessed in 1,913 college students, including 771 males and 1,092 females, and demonstrated that females had a significantly more balanced time perspective than males. In Study 2, 58 males and 47 females underwent assessment of time perspective and structural brain imaging. Voxel-based morphometry analysis and cortical thickness analysis were used to analyse the structural imaging data. Results showed that compared with males, females demonstrated a more balanced time perspective, which primarily related to lower grey matter volume in left precuneus, right cerebellum, right putamen and left supplementary motor area. Analysis of cortical thickness failed to reveal any significant sex differences. Furthermore, the sex difference in grey matter volume of left precuneus, right cerebellum, right putamen and left supplementary motor area could account for the difference in balanced time perspective between males and females. The findings deepen our understanding of sex differences in human cognition and their potential neural signature, and may inform tailored interventions to support a balanced time perspective in daily life.

Regional sex differences in grey matter volume are associated with sex hormones in the young adult human brain

NeuroImage ◽  
2010 ◽  
Vol 49 (2) ◽  
pp. 1205-1212 ◽  
Author(s):  
A. Veronica Witte ◽  
Markus Savli ◽  
Alexander Holik ◽  
Siegfried Kasper ◽  
Rupert Lanzenberger
Keyword(s):  
Sex Differences ◽  
Young Adult ◽  
Human Brain ◽  
Sex Hormones ◽  
Grey Matter ◽  
Grey Matter Volume ◽  
Adult Human Brain ◽  
Matter Volume ◽  
Adult Human

scholarly journals Sex classification using long-range temporal dependence of resting-state functional MRI time series

2019 ◽  
Author(s):  
Elvisha Dhamala ◽  
Keith W. Jamison ◽  
Mert R. Sabuncu ◽  
Amy Kuceyeski
Keyword(s):  
Sex Differences ◽  
Long Range ◽  
Resting State ◽  
Grey Matter ◽  
Machine Learning Algorithms ◽  
Grey Matter Volume ◽  
Temporal Dependence ◽  
Matter Volume ◽  
Human Connectome Project ◽  
Males And Females

AbstractA thorough understanding of sex differences, if any, that exist in the brains of healthy individuals is crucial for the study of neurological illnesses that exhibit differences in clinical and behavioural phenotypes between males and females. In this work, we evaluate sex differences in regional temporal dependence of resting-state brain activity using 195 male-female pairs (aged 22-37) from the Human Connectome Project. Male-female pairs are strictly matched for total grey matter volume. We find that males have more persistent long-range temporal dependence than females in regions within temporal, parietal, and occipital cortices. Machine learning algorithms trained on regional temporal dependence measures achieve sex classification accuracies of up to 81%. Regions with the strongest feature importance in the sex classification task included cerebellum, amygdala, frontal cortex, and occipital cortex. Additionally, we find that even after males and females are strictly matched on total grey matter volume, significant regional volumetric sex differences persist in many cortical and subcortical regions. Our results indicate males have larger cerebella, hippocampi, parahippocampi, thalami, caudates, and amygdalae while females have larger cingulates, precunei, frontal cortices, and parietal cortices. Sex classification based on regional volume achieves accuracies of up to 85%; cerebellum, cingulate cortex, and temporal cortex are the most important features. These findings highlight the important role of strict volume matching when studying brain-based sex differences. Differential patterns in regional temporal dependence between males and females identifies a potential neurobiological substrate underlying sex differences in functional brain activation patterns and the behaviours with which they correlate.

scholarly journals Effects of different intracranial volume correction methods on univariate sex differences in grey matter volume and multivariate sex prediction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Carla Sanchis-Segura ◽  
Maria Victoria Ibañez-Gual ◽  
Naiara Aguirre ◽  
Álvaro Javier Cruz-Gómez ◽  
Cristina Forn
Keyword(s):  
Sex Differences ◽  
Prediction Accuracy ◽  
Grey Matter ◽  
Grey Matter Volume ◽  
Intracranial Volume ◽  
Machine Learning Classifiers ◽  
Matter Volume ◽  
Morphological Differences ◽  
Gray Matter Volumes ◽  
Single Predictor

Abstract Sex differences in 116 local gray matter volumes (GMVOL) were assessed in 444 males and 444 females without correcting for total intracranial volume (TIV) or after adjusting the data with the scaling, proportions, power-corrected proportions (PCP), and residuals methods. The results confirmed that only the residuals and PCP methods completely eliminate TIV-variation and result in sex-differences that are “small” (∣d∣ < 0.3). Moreover, as assessed using a totally independent sample, sex differences in PCP and residuals adjusted-data showed higher replicability ($$\approx $$ ≈ 93%) than scaling and proportions adjusted-data $$( \approx $$ ( ≈ 68%) or raw data ($$\approx $$ ≈ 45%). The replicated effects were meta-analyzed together and confirmed that, when TIV-variation is adequately controlled, volumetric sex differences become “small” (∣d∣ < 0.3 in all cases). Finally, we assessed the utility of TIV-corrected/ TIV-uncorrected GMVOL features in predicting individuals’ sex with 12 different machine learning classifiers. Sex could be reliably predicted (> 80%) when using raw local GMVOL, but also when using scaling or proportions adjusted-data or TIV as a single predictor. Conversely, after properly controlling TIV variation with the PCP and residuals’ methods, prediction accuracy dropped to $$\approx $$ ≈ 60%. It is concluded that gross morphological differences account for most of the univariate and multivariate sex differences in GMVOL

scholarly journals Late chronotype is linked to greater cortical thickness in the left fusiform and entorhinal gyri

2021 ◽  
Author(s):  
Michal Rafal Zareba ◽  
Magdalena Fafrowicz ◽  
Tadeusz Marek ◽  
Ewa Beldzik ◽  
Halszka Oginska ◽  
...  
Keyword(s):  
White Matter ◽  
Cortical Thickness ◽  
Grey Matter ◽  
Brain Regions ◽  
Affective Processing ◽  
Grey Matter Volume ◽  
Imaging Data ◽  
White Matter Volume ◽  
Matter Volume ◽  
Anatomical Basis

Abstract Humans can be classified as early, intermediate and late chronotypes based on the preferred sleep and wakefulness patterns. The anatomical basis of these distinctions remains largely unexplored. Using magnetic resonance imaging data from 113 healthy young adults (71 females), we aimed to replicate cortical thickness and grey matter volume chronotype differences reported earlier in the literature using a greater sample size, as well as to explore the volumetric white matter variation linked to contrasting circadian phenotypes. Instead of comparing the chronotypes, we correlated the individual chronotype scores with their morphometric brain measures. The results revealed one cluster in the left fusiform and entorhinal gyri showing increased cortical thickness with increasing preference for eveningness, potentially providing an anatomical substrate for chronotype-sensitive affective processing. No significant results were found for grey and white matter volume. We failed to replicate cortical thickness and volumetric grey matter distinctions in the brain regions reported in the literature. Furthermore, we found no association between white matter volume and chronotype. Thus, while this study confirms that circadian preference is associated with specific structural substrates, it adds to the growing concerns that reliable and replicable neuroimaging research requires datasets much larger than those commonly used.

scholarly journals Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies

NeuroImage ◽  
2010 ◽  
Vol 53 (3) ◽  
pp. 1135-1146 ◽  
Author(s):  
Anderson M. Winkler ◽  
Peter Kochunov ◽  
John Blangero ◽  
Laura Almasy ◽  
Karl Zilles ◽  
...  
Keyword(s):  
Cortical Thickness ◽  
Grey Matter ◽  
Imaging Genetics ◽  
Grey Matter Volume ◽  
Matter Volume

scholarly journals Author Correction: Effects of different intracranial volume correction methods on univariate sex differences in grey matter volume and multivariate sex prediction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Carla Sanchis-Segura ◽  
Maria Victoria Ibañez-Gual ◽  
Naiara Aguirre ◽  
Álvaro Javier Cruz-Gómez ◽  
Cristina Forn
Keyword(s):  
Sex Differences ◽  
Grey Matter ◽  
Grey Matter Volume ◽  
Intracranial Volume ◽  
Volume Correction ◽  
Matter Volume

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Structural abnormalities in gyri of the prefrontal cortex in individuals with schizophrenia and their unaffected siblings

2010 ◽  
Vol 196 (2) ◽  
pp. 150-157 ◽  
Author(s):  
Michael P. Harms ◽  
Lei Wang ◽  
Carolina Campanella ◽  
Kristina Aldridge ◽  
Amanda J. Moffitt ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Cortical Thickness ◽  
Grey Matter ◽  
Genetic Factors ◽  
Inferior Frontal Gyrus ◽  
Familial Risk ◽  
Grey Matter Volume ◽  
Genetic Contribution ◽  
Matter Volume ◽  
Structural Abnormalities

BackgroundThe relatives of individuals with schizophrenia exhibit deficits of overall frontal lobe volume, consistent with a genetic contribution to these deficits.AimsTo quantify the structure of gyral-defined subregions of prefrontal cortex in individuals with schizophrenia and their siblings.MethodGrey matter volume, cortical thickness, and surface area of the superior, middle and inferior frontal gyri were measured in participants with schizophrenia and their unaffected (non-psychotic) siblings (n = 26 pairs), and controls and their siblings (n = 40 pairs).ResultsGrey matter volume was reduced in the middle and inferior frontal gyri of individuals with schizophrenia, relative to controls. However, only inferior frontal gyrus volume was also reduced in the unaffected siblings of those with schizophrenia, yielding a volume intermediate between their affected siblings and controls.ConclusionsThe structure of subregions of the prefrontal cortex may be differentially influenced by genetic factors in schizophrenia, with inferior frontal gyrus volume being most related to familial risk.

scholarly journals Late chronotype is linked to greater cortical thickness in the left fusiform and entorhinal gyri

2021 ◽  
Author(s):  
Michal Rafal Zareba ◽  
Magdalena Fafrowicz ◽  
Tadeusz Marek ◽  
Ewa Beldzik ◽  
Halszka Oginska ◽  
...  
Keyword(s):  
White Matter ◽  
Cortical Thickness ◽  
Grey Matter ◽  
Brain Regions ◽  
Affective Processing ◽  
Grey Matter Volume ◽  
Imaging Data ◽  
White Matter Volume ◽  
Matter Volume ◽  
Anatomical Basis

Abstract Humans can be classified as early, intermediate and late chronotypes based on the preferred sleep and wakefulness patterns. The anatomical basis of these distinctions remains largely unexplored. Using magnetic resonance imaging data from 113 healthy young adults (71 females), we aimed to replicate cortical thickness and grey matter volume chronotype differences reported earlier in the literature using a greater sample size, as well as to explore the volumetric white matter variation linked to contrasting circadian phenotypes. Instead of comparing the chronotypes, we correlated the individual chronotype scores with their morphometric brain measures. The results revealed one cluster in the left fusiform and entorhinal gyri showing increased cortical thickness with increasing preference for eveningness, potentially providing an anatomical substrate for chronotype-sensitive affective processing. No significant results were found for grey and white matter volume. We failed to replicate cortical thickness and volumetric grey matter distinctions in the brain regions reported in the literature. Furthermore, we found no association between white matter volume and chronotype. Thus, while this study confirms that circadian preference is associated with specific structural substrates, it adds to the growing concerns that reliable and replicable neuroimaging research requires datasets much larger than those commonly used.

scholarly journals Individual differences in brain structure and self-reported empathy in children

2021 ◽  
Author(s):  
Katherine Olivia Bray ◽  
Elena Pozzi ◽  
Nandita Vijayakumar ◽  
Sally Richmond ◽  
Camille Deane ◽  
...  
Keyword(s):  
Individual Differences ◽  
Cortical Thickness ◽  
Brain Structure ◽  
Grey Matter ◽  
Region Of Interest ◽  
Preliminary Evidence ◽  
Cognitive Empathy ◽  
Empathic Concern ◽  
Grey Matter Volume ◽  
Matter Volume

Empathy refers to the understanding and sharing of others’ emotions and comprises cognitive and affective components. Empathy is important for social functioning, and alterations in empathy have been demonstrated in many developmental/psychiatric disorders. While several studies have examined associations between empathy and brain structure in adults, few have investigated this relationship in children. Investigating associations between empathy and brain structure during childhood will help us develop a deeper understanding of the neural correlates of empathy across the lifespan.125 children (66 female, mean age 10 years) underwent MRI brain scans. Grey matter volume and cortical thickness from T1-weighted structural images were examined using the CAT12 toolbox within SPM12. Children completed questionnaire measures of empathy (cognitive empathy, affective empathy: affective sharing, empathic concern, empathic distress).In hypothesised region of interest analyses, individual differences in affective and cognitive empathy were related to grey matter volume in the insula and the precuneus. Although these relationships were of similar strength to those found in previous research, they did not survive correction for the total number of models computed. While no significant findings were detected between grey matter volume and empathy in exploratory whole-brain analysis, associations were found between cortical thickness and empathic concern in the right precentral gyrus.This study provides preliminary evidence that individual differences in self-reported empathy in children may be related to aspects of brain structure. Findings highlight the need for more research investigating the neurobiological correlates of empathy in children.

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