scholarly journals Morphometrical brain markers of sex difference

2020 ◽  
Author(s):  
Daniel Brennan ◽  
Tingting Wu ◽  
Jin Fan
Keyword(s):  
Sex Difference ◽  
Brain Structure ◽  
Brain Structures ◽  
Brain Regions ◽  
Developmental Period ◽  
Support Vector ◽  
Imaging Data ◽  
Image Intensity ◽  
Males And Females ◽  
Critical Developmental Period

AbstractMany major neuropsychiatric pathologies, some of which appear in adolescence, show differentiated prevalence, onset, and symptomatology across the biological sexes. Therefore, mapping differences in brain structure between males and females during this critical developmental period may provide information about the neural mechanisms underlying the dimorphism of these pathologies. Utilizing a large dataset collected through the Adolescent Brain Cognitive Development study, we investigated the differences of adolescent (9-10 years old) male and female brains (n = 8325) by using a linear Support-Vector Machine Classifier to predict sex based on morphometry and image intensity values of structural brain imaging data. The classifier correctly classified the sex of 86% individuals with the insula, the precentral and postcentral gyri, and the pericallosal sulcus as the most discernable features. The role of these significant dimorphic features in psychopathology was explored by testing them as mediators between sex and clinical symptomology. The results demonstrate the existence of morphometrical brain markers of sex difference.Significance StatementMany psychiatric pathologies express differently across the sexes. Therefore, an understanding of the differences in brain structure between males and females during the critical developmental period of adolescence may provide the insights about the dimorphism of clinical symptomology and the general functions of the dimorphic brain structures. Using machine learning, we successfully classified males and females with a high accuracy based on morphometry and image intensity data extracted from structural MRI scans. The features which significantly contributed to classification were examined to determine brain regions which are dimorphic during adolescence. The relevance of these brain regions to the expression of psychopathology symptoms was also explored.

scholarly journals Morphometrical Brain Markers of Sex Difference

2021 ◽  
Author(s):  
Daniel Brennan ◽  
Tingting Wu ◽  
Jin Fan
Keyword(s):  
Sex Difference ◽  
Support Vector Machine Classifier ◽  
Developmental Period ◽  
Neural Mechanisms ◽  
Support Vector ◽  
Imaging Data ◽  
Large Dataset ◽  
Males And Females ◽  
Brain Imaging Data ◽  
Critical Developmental Period

Abstract Many major neuropsychiatric pathologies, some of which appear in adolescence, show differentiated prevalence, onset, and symptomatology across the biological sexes. Therefore, mapping differences in brain structure between males and females during this critical developmental period may provide information about the neural mechanisms underlying the dimorphism of these pathologies. Utilizing a large dataset collected through the Adolescent Brain Cognitive Development study, we investigated the differences of adolescent (9–10 years old) male and female brains (n = 8325) by using a linear Support-Vector Machine Classifier to predict sex based on morphometry and image intensity values of structural brain imaging data. The classifier correctly classified the sex of 86% individuals with the insula, the precentral and postcentral gyri, and the pericallosal sulcus as the most discernable features. These results demonstrate the existence of complex, yet robustly measurable morphometrical brain markers of sex difference.

scholarly journals The Antennal Pathway of Dragonfly Nymphs, from Sensilla to the Brain

Insects ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 886
Author(s):  
Silvana Piersanti ◽  
Manuela Rebora ◽  
Gianandrea Salerno ◽  
Sylvia Anton
Keyword(s):  
Brain Structure ◽  
Antennal Lobe ◽  
Sensory Information ◽  
Brain Structures ◽  
Brain Regions ◽  
Adult Brain ◽  
Published Data ◽  
Antennal Sensilla ◽  
Aquatic Life ◽  
The Brain

Dragonflies are hemimetabolous insects, switching from an aquatic life style as nymphs to aerial life as adults, confronted to different environmental cues. How sensory structures on the antennae and the brain regions processing the incoming information are adapted to the reception of fundamentally different sensory cues has not been investigated in hemimetabolous insects. Here we describe the antennal sensilla, the general brain structure, and the antennal sensory pathways in the last six nymphal instars of Libellula depressa, in comparison with earlier published data from adults, using scanning electron microscopy, and antennal receptor neuron and antennal lobe output neuron mass-tracing with tetramethylrhodamin. Brain structure was visualized with an anti-synapsin antibody. Differently from adults, the nymphal antennal flagellum harbors many mechanoreceptive sensilla, one olfactory, and two thermo-hygroreceptive sensilla at all investigated instars. The nymphal brain is very similar to the adult brain throughout development, despite the considerable differences in antennal sensilla and habitat. Like in adults, nymphal brains contain mushroom bodies lacking calyces and small aglomerular antennal lobes. Antennal fibers innervate the antennal lobe similar to adult brains and the gnathal ganglion more prominently than in adults. Similar brain structures are thus used in L. depressa nymphs and adults to process diverging sensory information.

scholarly journals Review of Twin and Family Studies on Neuroanatomic Phenotypes and Typical Neurodevelopment

2007 ◽  
Vol 10 (5) ◽  
pp. 683-694 ◽  
Author(s):  
J. Eric Schmitt ◽  
Lisa T. Eyler ◽  
Jay N. Giedd ◽  
William S. Kremen ◽  
Kenneth S. Kendler ◽  
...  
Keyword(s):  
Brain Structure ◽  
Emotional Regulation ◽  
Behavioral Genetics ◽  
Genetic Relationships ◽  
Twin Studies ◽  
Brain Regions ◽  
Phenotypic Variance ◽  
Imaging Data ◽  
Brain Volumes ◽  
Large Brain

AbstractThis article reviews the extant twin studies employing magnetic resonance imaging data (MRI), with an emphasis on studies of populationbased samples. There have been approximately 75 twin reports using MRI, with somewhat under half focusing on typical brain structure. Of these, most are samples of adults. For large brain regions such as lobar volumes, the heritabilities of large brain volumes are consistently high, with genetic factors accounting for at least half of the phenotypic variance. The role of genetics in generating individual differences in the volumes of small brain regions is less clear, mostly due to a dearth of information, but rarely because of disagreement between studies. Multivariate analyses show strong genetic relationships between brain regions. Cortical regions involved in language, executive function, and emotional regulation appear to be more heritable than other areas. Studies of brain shape also show significant, albeit lower, genetic effects on population variance. Finally, there is evidence of significant genetically mediated relationships between intelligence and brain structure. At present, the majority of twin imaging studies are limited by sample sizes small by the standards of behavioral genetics; nevertheless the literature at present represents a pioneering effort in the pursuit of answers to many challenging neurobiological questions.

scholarly journals Modulatory interactions between the default mode network and task positive networks in resting-state

2014 ◽  
Author(s):  
Xin Di ◽  
Bharat B. Biswal
Keyword(s):  
Basal Ganglia ◽  
Default Mode Network ◽  
Resting State ◽  
Brain Structures ◽  
Brain Regions ◽  
Salience Network ◽  
Imaging Data ◽  
Default Mode ◽  
Task Positive Network ◽  
And Task

The two major brain networks, i.e. the default mode network (DMN) and the task positive network, typically reveal negative and variable connectivity in resting-state. In the present study, we examined whether the connectivity between the DMN and different components of the task positive network were modulated by other brain regions by using physiophysiological interaction (PPI) on resting-state functional magnetic resonance imaging data. Spatial independent component analysis was first conducted to identify components that represented networks of interest, including the anterior and posterior DMNs, salience, dorsal attention, left and right executive networks. PPI analysis was conducted between pairs of these networks to identify networks or regions that showed modulatory interactions with the two networks. Both network-wise and voxel-wise analyses revealed reciprocal positive modulatory interactions between the DMN, salience, and executive networks. Together with the anatomical properties of the salience network regions, the results suggest that the salience network may modulate the relationship between the DMN and executive networks. In addition, voxel-wise analysis demonstrated that the basal ganglia and thalamus positively interacted with the salience network and the dorsal attention network, and negatively interacted with the salience network and the DMN. The results demonstrated complex modulatory interactions among the DMNs and task positive networks in resting-state, and suggested that communications between these networks may be modulated by some critical brain structures such as the salience network, basal ganglia, and thalamus.

scholarly journals Modulatory interactions between the default mode network and task positive networks in resting-state

2014 ◽  
Author(s):  
Xin Di ◽  
Bharat B. Biswal
Keyword(s):  
Basal Ganglia ◽  
Default Mode Network ◽  
Resting State ◽  
Brain Structures ◽  
Brain Regions ◽  
Salience Network ◽  
Imaging Data ◽  
Default Mode ◽  
Task Positive Network ◽  
And Task

The two major brain networks, i.e. the default mode network (DMN) and the task positive network, typically reveal negative and variable connectivity in resting-state. In the present study, we examined whether the connectivity between the DMN and different components of the task positive network were modulated by other brain regions by using physiophysiological interaction (PPI) on resting-state functional magnetic resonance imaging data. Spatial independent component analysis was first conducted to identify components that represented networks of interest, including the anterior and posterior DMNs, salience, dorsal attention, left and right executive networks. PPI analysis was conducted between pairs of these networks to identify networks or regions that showed modulatory interactions with the two networks. Both network-wise and voxel-wise analyses revealed reciprocal positive modulatory interactions between the DMN, salience, and executive networks. Together with the anatomical properties of the salience network regions, the results suggest that the salience network may modulate the relationship between the DMN and executive networks. In addition, voxel-wise analysis demonstrated that the basal ganglia and thalamus positively interacted with the salience network and the dorsal attention network, and negatively interacted with the salience network and the DMN. The results demonstrated complex modulatory interactions among the DMNs and task positive networks in resting-state, and suggested that communications between these networks may be modulated by some critical brain structures such as the salience network, basal ganglia, and thalamus.

scholarly journals Musical skills can be decoded from magnetic resonance images

2020 ◽  
Author(s):  
Tuomas Puoliväli ◽  
Tuomo Sipola ◽  
Anja Thiede ◽  
Marina Kliuchko ◽  
Brigitte Bogert ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Brain Structure ◽  
Structural Changes ◽  
Musical Instrument ◽  
Structural Features ◽  
Brain Regions ◽  
Magnetic Resonance Images ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
The Brain

AbstractLearning induces structural changes in the brain. Especially repeated, long-term behaviors, such as extensive training of playing a musical instrument, are likely to produce characteristic features to brain structure. However, it is not clear to what extent such structural features can be extracted from magnetic resonance images of the brain. Here we show that it is possible to predict whether a person is a musician or a non-musician based on the thickness of the cerebral cortex measured at 148 brain regions encompassing the whole cortex. Using a supervised machine learning technique called support vector machines, we achieved significant (κ = 0.321, p < 0.001) agreement between the actual and predicted participant groups of 30 musicians and 85 non-musicians. The areas contributing to the prediction were mostly in the frontal, parietal, and occipital lobes of the left hemisphere. Our results suggest that decoding an acquired skill from magnetic resonance images of brain structure is feasible to some extent. Further, the distribution of the areas that were informative in the classification, which mostly, but not entirely overlapped with earlier findings, implies that decoding-based analyses of structural properties of the brain can reveal novel aspects of musical aptitude.

Neuroanatomical and Morphological Trait Clusters in the Ant Genus Pheidole: Evidence for Modularity and Integration in Brain Structure

2015 ◽  
Vol 85 (1) ◽  
pp. 63-76 ◽  
Author(s):  
Iulian Ilieş ◽  
Mario L. Muscedere ◽  
James F.A. Traniello
Keyword(s):  
Social Information Processing ◽  
Brain Structure ◽  
Developmental Trajectories ◽  
Size Variation ◽  
Brain Evolution ◽  
Brain Structures ◽  
Interspecific Variation ◽  
Distinct Species ◽  
Brain Regions ◽  
Brain Organization

A central question in brain evolution concerns how selection has structured neuromorphological variation to generate adaptive behavior. In social insects, brain structures differ between reproductive and sterile castes, and worker behavioral specializations related to morphology, age, and ecology are associated with intra- and interspecific variation in investment in functionally different brain compartments. Workers in the hyperdiverse ant genus Pheidole are morphologically and behaviorally differentiated into minor and major subcastes that exhibit distinct species-typical patterns of brain compartment size variation. We examined integration and modularity in brain organization and its developmental patterning in three ecotypical Pheidole species by analyzing intra- and interspecific morphological and neuroanatomical covariation. Our results identified two trait clusters, the first involving olfaction and social information processing and the second composed of brain regions regulating nonolfactory sensorimotor functions. Patterns of size covariation between brain compartments within subcastes were consistent with levels of behavioral differentiation between minor and major workers. Globally, brains of mature workers were more heterogeneous than brains of newly eclosed workers, suggesting diversified developmental trajectories underscore species- and subcaste-typical brain organization. Variation in brain structure associated with the striking worker polyphenism in our sample of Pheidole appears to originate from initially differentiated brain templates that further diverge through species- and subcaste-specific processes of maturation and behavioral development.

scholarly journals Beyond Bilingualism: multilingual experience correlates with caudate volume

2017 ◽  
Author(s):  
Alexis Hervais-Adelman ◽  
Natalia Egorova ◽  
Narly Golestani
Keyword(s):  
Significant Relationship ◽  
Brain Structure ◽  
Brain Structures ◽  
Brain Regions ◽  
Language Management ◽  
Caudate Nuclei ◽  
Brain Structure And Function ◽  
Left Caudate ◽  
Language Control ◽  
And Function

AbstractThe multilingual brain implements mechanisms that serve to select the appropriate language as a function of the communicative environment. Engaging these mechanisms on a regular basis appears to have consequences for brain structure and function. Studies have implicated the caudate nuclei as important nodes in polyglot language control processes, and have also shown structural differences in the caudate nuclei in bilingual compared to monolingual populations. However, the majority of published work has focused on the categorical differences between monolingual and bilingual individuals, and little is known about whether these findings extend to multilingual individuals, who have even greater language control demands. In the present paper, we present an analysis of the volume and morphology of the caudate nuclei, putamen, pallidum and thalami in 75 multilingual individuals who speak three or more languages. Volumetric analyses revealed a significant relationship between multilingual experience and right caudate volume, as well as a marginally-significant relationship with left caudate volume. Vertex-wise analyses revealed a significant enlargement of dorsal and anterior portions of the left caudate nucleus, known to have connectivity with executive brain regions, as a function of multilingual expertise. These results suggest that multilingual expertise might exercise a continuous impact on brain structure, and that as additional languages beyond a second are acquired, the additional demands for linguistic and cognitive control result in modifications to brain structures associated with language management processes.

Cognitive reserve attenuates age-related cognitive decline in the context of putatively accelerated brain ageing in schizophrenia-spectrum disorders

2019 ◽  
Vol 50 (9) ◽  
pp. 1475-1489 ◽  
Author(s):  
Tamsyn E. Van Rheenen ◽  
Vanessa Cropley ◽  
Birgitte Fagerlund ◽  
Cassandra Wannan ◽  
Jason Bruggemann ◽  
...  
Keyword(s):  
Brain Structure ◽  
Cognitive Reserve ◽  
Brain Structures ◽  
Brain Regions ◽  
Schizophrenia Spectrum Disorders ◽  
Clinical Indicators ◽  
Age Related ◽  
Schizophrenia Spectrum ◽  
Brain Ageing ◽  
Fluid Reasoning

AbstractBackgroundIn schizophrenia, relative stability in the magnitude of cognitive deficits across age and illness duration is inconsistent with the evidence of accelerated deterioration in brain regions known to support these functions. These discrepant brain–cognition outcomes may be explained by variability in cognitive reserve (CR), which in neurological disorders has been shown to buffer against brain pathology and minimize its impact on cognitive or clinical indicators of illness.MethodsAge-related change in fluid reasoning, working memory and frontal brain volume, area and thickness were mapped using regression analysis in 214 individuals with schizophrenia or schizoaffective disorder and 168 healthy controls. In patients, these changes were modelled as a function of CR.ResultsPatients showed exaggerated age-related decline in brain structure, but not fluid reasoning compared to controls. In the patient group, no moderation of age-related brain structural change by CR was evident. However, age-related cognitive change was moderated by CR, such that only patients with low CR showed evidence of exaggerated fluid reasoning decline that paralleled the exaggerated age-related deterioration of underpinning brain structures seen in all patients.ConclusionsIn schizophrenia-spectrum illness, CR may negate ageing effects on fluid reasoning by buffering against pathologically exaggerated structural brain deterioration through some form of compensation. CR may represent an important modifier that could explain inconsistencies in brain structure – cognition outcomes in the extant literature.

scholarly journals Disrupted metabolic connectivity in dopaminergic and cholinergic networks at different stages of dementia from 18F-FDG PET brain persistent homology network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tun-Wei Hsu ◽  
Jong-Ling Fuh ◽  
Da-Wei Wang ◽  
Li-Fen Chen ◽  
Chia-Jung Chang ◽  
...  
Keyword(s):  
Algebraic Topology ◽  
Fdg Pet ◽  
Persistent Homology ◽  
Network Connectivity ◽  
Brain Regions ◽  
Imaging Data ◽  
Cholinergic Pathways ◽  
Positron Emission ◽  
Metabolic Connectivity ◽  
Neurochemical Changes

AbstractDementia is related to the cellular accumulation of β-amyloid plaques, tau aggregates, or α-synuclein aggregates, or to neurotransmitter deficiencies in the dopaminergic and cholinergic pathways. Cellular and neurochemical changes are both involved in dementia pathology. However, the role of dopaminergic and cholinergic networks in metabolic connectivity at different stages of dementia remains unclear. The altered network organisation of the human brain characteristic of many neuropsychiatric and neurodegenerative disorders can be detected using persistent homology network (PHN) analysis and algebraic topology. We used 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging data to construct dopaminergic and cholinergic metabolism networks, and used PHN analysis to track the evolution of these networks in patients with different stages of dementia. The sums of the network distances revealed significant differences between the network connectivity evident in the Alzheimer’s disease and mild cognitive impairment cohorts. A larger distance between brain regions can indicate poorer efficiency in the integration of information. PHN analysis revealed the structural properties of and changes in the dopaminergic and cholinergic metabolism networks in patients with different stages of dementia at a range of thresholds. This method was thus able to identify dysregulation of dopaminergic and cholinergic networks in the pathology of dementia.

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