Welche Themen interessieren euch, welche Studien fandet ihr besonders interessant in der Woche, welche Neuigkeiten gibt es, die interessant für eine Diskussion wären und was beschäftigt euch gerade?
Welche interessanten Artikel gibt es auf euren Blogs oder auf den Blogs anderer? Welches Thema sollte noch im Blog diskutiert werden?
Eine Studie in der Zeitung NeuroImage stellt Gehirnscans mit neuen Verfahren dar, die die Unterschiede zwischen Männern und Frauen untersuchen:
The female brain contains a larger proportion of gray matter tissue, while the male brain comprises more white matter. Findings like these have sparked increasing interest in studying dimorphism of the human brain: the general effect of gender on aspects of brain architecture. To date, the vast majority of imaging studies is based on unimodal MR images and typically limited to a small set of either gray or white matter regions-of-interest. The morphological content of magnetic resonance (MR) images, however, strongly depends on the underlying contrast mechanism. Consequently, in order to fully capture gender-specific morphological differences in distinct brain tissues, it might prove crucial to consider multiple imaging modalities simultaneously. This study introduces a novel approach to perform such multimodal classification incorporating the relative strengths of each modality-specific physical aperture to tissue properties. To illustrate our approach, we analyzed multimodal MR images (T1-, T2-, and diffusion-weighted) from 121 subjects (67 females) using a linear support vector machine with a mass-univariate feature selection procedure. We demonstrate that the combination of different imaging modalities yields a significantly higher balanced classification accuracy (96%) than any one modality by itself (83%–88%). Our results do not only confirm previous morphometric findings; crucially, they also shed new light on the most discriminative features in gray-matter volume and microstructure in cortical and subcortical areas. Specifically, we find that gender disparities are primarily distributed along brain networks thought to be involved in social cognition, reward-based learning, decision-making, and visual-spatial skills.
Quelle: Decoding gender dimorphism of the human brain using multimodal anatomical and diffusion MRI data
Aus der Studie:
The gray matter segments of the T1-weighted images included in the multimodal approach revealed a marked anterior–posterior gradient in classifier weights (Fig. 4) in conjunction with a remarkable lateralization in cortical regions (Fig. 5). In contrast, subcortical disparities were distributed rather bilaterally. Strikingly, the anterior–posterior gradient is dominated by differences in the frontal lobe. There were virtually no disparities in postcentral parts of the brain with the exception of TPJ and pSTS. Interestingly, Allen et al. (2003) already described the occipital lobe as the least sexually dimorphic region since they found no significant difference in gray matter volumes in females and males. They argue that most of this brain region has relatively low levels of sex steroid receptors (Goldstein et al., 2001). By contrast, disparities in the frontal lobe were found in all aspects of prefrontal areas, i.e., in the medial, lateral as well as orbital parts. Based on sex steroid receptor density, Goldstein et al. (2001) predicted that the prefrontal regions as well as the parietal cortices should exhibit a high degree of sexual dimorphism. Our findings with respect to contributing brain networks might be suggestive of sex differences in terms of social cognition, reward-based learning, decision-making, and visual-spatial skills. The effects observed within the right and left nuclei caudate also corroborate previous observations (Giedd et al., 1996; Good et al., 2001; Luders et al., 2009). Interestingly though, while previous studies have primarily reported proportionately more gray matter in women rather than in men (reviewed in Luders and Toga, 2010), our approach also allowed us to identify regions that seem indicative of the opposite effect. More specifically, although receiving lower weights on average (Fig. 5), we detected several regions that showed relatively more gray matter in male than in female brains. These regions included the right anterior insular cortex, the right lateral as well as the left OFC (Figs. 2 and 4), and the right pSTS (Fig. 2). Relatively higher FA values in men as compared to women were found in the left entorhinal cortex (Fig. 3), indicating differences in cortical microstructure. It has long been known that efferent fibers exiting the piriform lobe primarily target the mOFC, the lOFC as well as the hippocampus. We found all of these regions to differ between women and men.
Es wurden also anscheinend gerade in den Gebieten, die eine hohe Steroidrezeptorendichte aufwiesen, Geschlechterunterschiede gefunden. Was genau das ist, was durch die Theorie, dass Geschlechtsunterschiede durch bestimmte Hormone verursacht werden, vorhergesagt wird. Es wäre auch wenig verständlich, dass wir entsprechende Rezeptoren in unserem Gehirn haben, diese dann aber nicht auf die Hormone reagieren. Und diese sind eben bei Männern und Frauen in verschiedenen Dosierungen vorhanden.
Zu den Unterschieden im Gehirn hatte ich hier auch schon etwas geschrieben:
Die Methoden zur Erkennung der Gehirnstrukturen werden immer mehr verbessert werden. Funktionelle Magnetresonanztomographie (fMRT) hat sicherlich ihre Schwächen, aber die Methode wird immer weiter korrigiert. Es werden sich damit auch immer mehr Belege für Geschlechterunterschiede finden.
Alles Evolution 