Brain structure and function

The human brain mosaic

Considerable overlap between men and women’s brains throughout their sample therefore authors wanted to shift away from sexually dimorphic brains

Brains should be conceptualised as mosaics of features some of which are more common in women and vice versa

Some small reliable sex/gender differences at population level

But brains are not sexually dimorphic

Cohen-Bendahan (2005)

Organising effects of sex hormones are maximal during certain sensitive periods during early development generally accepted that gestation weeks 8-24 are a key period although increasing evidence suggests additional sensitive periods exist

Hausmann

Proposed the progesterone-mediated decoupling hypothesis

P G GABA

High levels of progesterone reduce interhemispheric inhibition by supressing the excitatory neural response to glutamate and increasing the inhibitory neural response to GABA, the dominant hemisphere no longer supresses activity in the non-dominant hemisphere and the asymmetry is reduced

Work using PPI then showed that oestradiol was also important

Peters (1991)

On average the male brain is larger and heavier than the female brain but it is important to note the link to behaviour is unclear

There is also uncertainty surrounding the significance of absolute brain size compared to size/volume of specific areas, essentially suggesting while this is an obvious difference in brain structure it may not necessarily affect brain function as greatly

Ruigrok (2014)

Conducted a meta-analysis of post-mortem and imaging studies considering the whole-brain volume and density controlling for differences in body size

Males on average have larger intracranial volume (ICV) (12%), TBV (11%), cerebrum (10%), GM (9%), WM (13%), cerebral spinal fluid (CSF) (11.5%) and many more

Females have on average higher tissue density in the left frontal pole and larger volumes in the right frontal pole, inferior and middle frontal gyri - TD-LFP V-RFP IFG MFG

Authors have argued that these findings depend on the specific analysis and method by which sex/gender differences in body size are controlled (Schluter, 1992), suggesting these results could be a false positive

Sanchis-Segura (2019)

Investigated brain size they adjusted for differences in total intracranial volume (TIV) in five different ways, all TIV adjustments reduced sex differences but their results were very different to each other

Luders (2004)

Used 3D analytic techniques with MRI brain scans in a sample of 60 participants – women on average yielded greater cortical complexity scores than men, possibly off-setting differences in brain volume

Raznahan (2010)

Used MRI on 284ppt

FR POR

Frontal regions maturation was slower in men compared to women, supporting the female-favouring prefrontal-mediated cognition sex/gender difference

In the parietal-occipital regions men developed faster than women, supporting the male-favouring visuospatial tasks sex/gender difference

Ritchie (2018)

CV SCR A H! - PL

Neuroimaging study 5216 participants, men had greater cortical volume, women had greater cortical thickness particularly in parietal lobe, men had larger volumes in subcortical regions

And men have larger volume in the amygdala and hippocampus although hippocampus difference becomes non-significant when brain size is controlled for

Kulnych (1994)

Small scale MRI study of planum temporale (PT)

Men showed asymmetry (larger left PT compared to right), women did not

Finding has not been consistently replicated

Guadelupe (2015)

Data from three large MRI data sets (n=4160) and found a stronger leftward asymmetry in the PT for men compared to women

Sommer (2008)

Conducted a meta-analysis of 13 studies investigating planum temporale and found no sex/gender differences

Plowman (2012)

Clinical data also supports the lack of a sex/gender difference in the asymmetry of the PT we would expect a sex/gender difference in outcomes following a stroke/lesion to this area - found no sex/gender differences in the likelihood of aphasia

Allen

Women have higher GM:WM ratio consistently across all brain structures and lobes analysed

Study also showed effect of sex/gender was greater on WM than GM

Van der Linden (2017)

Women had higher GM:WM ratio throughout cortex

Joel (2015)

The human brain mosaic

Neuroimaging and self-reported sex/gender data taken from four samples, examined GM, WM and connectivity

Tried different analyses and imaging types to ensure results were not measure, analysis or sample dependent

LH LCL The distribution of GM volume showed the largest sex/gender differences in left hippocampus and left caudate lower

Considerable overlap was present with most individuals being characterised by aspects of an average female brain and an average male brain

The heterogeneity of the human brain and the huge overlap between the forms that brains of males and females can take can be fully appreciated when looking at the entire brain

Stark (2007)

FC TC

Post-mortem tissue study found higher number of neurons in the frontal and temporal cortex of men than women and higher number of cell bodies in male neocortices

Witelsone (1995)

TL

Calculated number of neurons per unit of volume to estimate neuronal density, it was 11% higher in women in the temporal lobe

Alonso-Nanclares (2007)

< SD in TN Women showed lower synaptic density in all areas of the temporal neocortex

This may be reflective of a more complex network in men but this study was limited both by a small sample size n= 8 and the inclusion of epileptic participants so this finding might partly reflect synaptic reorganisation effects on synaptic density

Allen

Splenium larger CC section in women compared to men

Habib (1991)

Posterior midbody larger CC section in women compared to men

Witelsone (1989)

Isthmus larger CC section in women compared to men

Allen (2002)

Larger CC sections in men

Oppenheim (1987)

Found no sex/gender differences in CC section

Ardekani (2013)

Large MRI study n=316, found CC larger in women

Shiino (2017)

Conducted additional analyses on Ardekani dataset and supported these findings of larger CC sections in women

Eliot (2021)

Most studies on sex/gender differences in the corpus callosum included <100 participants so were likely underpowered and not able to detect the estimate effect size

Ingalhalikar (2014)

n=949

Men exhibited greater intra-hemispheric structural connectivity

Women exhibited greater interhemispheric structural connectivity

Why was this study inconsistent with similar studies, can’t be bigger sample as smaller studies (Hanggi et al. 2014) reveal similar pattern of differences but also show this was due to brain size sex/gender differences

This study did not control for brain size a factor known to vary according to sex/gender and influence structural connectivity

Tunc (2016)

n=900 DTI study collected neurocognitive measures

M S EF Men = greater connectivity with the motor, sensory and executive function networks and had more intra-hemispheric connectivity

M A SC Women = greater connectivity within networks associated with memory, attention and social cognition and had more inter-hemispheric connectivity

Westerhausen (2003)

CC - AGSR CC

Found higher FA throughout CC in men, and lower MD in anterior genu subregion of CC in men

Results from other studies have been inconsistent with some demonstrating higher FA in CC in women – others find no sex/gender differences in global FA and MD

Takao (2014)

Sex/gender differences in WM microstructure become non-significant after controlling for differences

McGlone

Men with RH lesions showed comparable verbal IQ to controls

Both RH and LH lesions in women resulted in lower verbal IQ

McGlone

Men with RH lesions poorer performance in a spatial task than men with LH lesions and women with RH lesions

Women are more bilateral and smaller FCA and men more lateralised i.e. bigger FCA

Weekes (1995)

Degree of lateralisation/asymmetry seemed to correlate with sex role identification particularly masculinity – but this is a correlation so we cannot make assumptions about causation

Hirnstein (2019)

Meta-analysis showed overall males slightly more lateralised

Hodgetts (2022)

No sex/gender differences for language-related FCAs

Proverbio (2010)

Used EEG to assess FCAs for face processing, visual tasks evidence less consistent than auditory/language (left hemispheric tasks)

Hampson (2015)

CAH

Congenital Adrenal Hyperplasia a genetic condition characterised by an under production of cortisol and an overproduction of androgens (including testosterone)

CAH is also characterised by an increased likelihood of left-handedness suggesting that prenatal/early exposure to androgens causes a shift towards right hemispheric dominance - associated with stronger language lateralisation to LH so not a simple overall shift to RH dominance

Forget (1994)

Cisgender men and trans women show different patterns of FCAs despite same sex chromosomes

Forget

Transgender women show similar patterns of FCAs as cisgender women

Hausmann (2000)

Investigated effects of sex hormones on FCAs by testing naturally cycling women on lateralised tasks at different points in their cycle - compared to data from men and post-menopausal women

Cycle confirmed using saliva sampling

Found interaction between cycle phase and FCAs in all tasks indicative of general reduction in FCAs during the high progesterone luteal phase

But FCAs were stable across time in postmenopausal women and men, similar result found in follow-up studies using different types of lateralised tasks

Weis

Investigated the progesterone-mediated decoupling hypothesis using fMRI and functional connectivity analyses during the same cognitive tasks

LIFG - Most significant activation during word-matching located in left interior frontal gyrus - exerted a strong inhibitory influence over the right IFG that was significantly stronger during menstrual phase, low E and low P

High levels of oestradiol were associated with a reduction in interhemispheric inhibition in both cycle phases

Weis

Oestradiol can also reduce functional connectivity between heterotopic regions

Jordan (2002)

Mental rotation

IPS SPL IPL IS PA - Women exhibited significant bilateral activity in the intraparietal sulcus, superior and inferior parietal lobe, inferior sulcus and premotor areas

RPOS LIPS LSPL - Men exhibited activation in the right parieto-occipital sulcus, left intraparietal sulcus and the left superior parietal lobule

Important to note there were no performance differences between men and women of this sample – suggests men and women use different strategies to complete the task

Unclear from these studies whether the activation differences are innate or acquired (reflective of different learning environments)

Weissman-Fogel

For tasks requiring cognitive control of emotions there are no resting state functional connectivity differences

Koch (2007)

N-back task in either a negative emotion condition (negative olfactory stimulation) or a neural condition

Impaired working memory for both

PA PA Men = activity in prefrontal and parietal areas

A OC Women = activity in amygdala and orbitofrontal cortices

Similar findings reported using other emotion paradigms and other neuroimaging methods (Cahill et al., 2001)

Butler (2006)

Mental rotation

DMPC Women = activity in dorsalmedial prefrontal cortex (top-down effortful processing)

BGP SC Men = activity in basal ganglia precuneus and sensory cortices (bottom-up automatic processing)

PIVC Functional connectivity analysis showed accurate performance was associated with deactivation of the parieto-insular vestibular cortex in men only

Butler (2007)

Test mental rotation with emotion regulation

< VACC -I-DACC Only women showed a suppression of activity in the ventral anterior cingulate cortex and an inverse correlation of activity between the ventral and dorsal anterior cingulate cortices

Suggests sex/gender differences in task-related functional connectivity may partly reflect sex/gender differences in the strategies used to complete the task, women’s suppression likely reflects greater cognitive effort consistent with top-down approach

Biswal (1995)

Resting-state functional connectivity – low-frequency oscillations of the fMRI BOLD signal thought to reflect spontaneous neural activity

Laird (2011)

DMPC VMPC PCC P LPC

Differences in functional connectivity of the default mode resting state network compromised of the dorsal and ventral medial prefrontal cortex the posterior cingulate cortex, precunens and lateral parietal cortex

Raichle (2015)

Resting-state functional connectivity - initially thought to underpin spontaneous cognition but it has also been implicated in integrating processing across multiple networks

Ritchie (2018)

Stronger functional connectivity in DMN of women n=5000

Eliot (2021)

Analysis method on brain activity/functional connectivity may influence results (differing results for the 1000 functional connectomes project)

Weis

Sex/gender differences exist but are small and there is considerable overlap

Few studies have included sex hormonal factors in their analysis and those that have show that functional activity varies across the cycle

Weis

Used a machine learning approach to asses how accurately an AI algorithm can classify brains as male or female based on their rs-fMRI data

Whole brain classification was high in all cases (75-65%), no region reached 100% accuracy

Hjelmervik (2014)

Used rs-fMRI to investigate sex/gender differences and menstrual cycle effects in a number of resting state networks

Women higher functional connectivity in two resting state networks particularly in frontal regions, no effect of cycle phase

Weis

Default Mode Network functional connectivity stable in men but fluctuated in women

Increased connectivity in the left PFC during the menstrual phase compared to other cycle phases

Auditory showed higher connectivity in men but no cycle phase difference

Suggests frontal areas may be more sensitive to hormonal fluctuations