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2020-12
Dissecting the midlife crisis: Disentangling social, personality and demographic determinants in social brain anatomy
Functional idiosyncrasy has a shared topography with group-level connectivity alterations in autism
The default network of the human brain is associated with perceived social isolation
Historical and cross-disciplinary trends in the biological and social sciences reveal an accelerating adoption of advanced analytics
What matters and what is possible in neuroimaging meta-analyses (of psychopathy).
2020-10
Neuroimaging: into the Multiverse
Inference and Prediction Diverge in Biomedicine
Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function.
2020-09
Sex-specific lesion topographies explain outcomes after acute ischemic stroke
Population variability in social brain morphology:links to socioeconomic status and health disparity
2020-08
Beyond brain age: Empirically-derived proxy measures of mental health
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets.
Generative lesion pattern decomposition of cognitive impairment after stroke
Prediction, Not Association, Paves the Road to Precision Medicine
Meta-matching: a simple framework to translate phenotypic predictive models from big to small data
Hidden population modes in social brain morphology: Its parts are more than its sum
Myeloarchitecture gradients in the human insula: Histological underpinnings and association to intrinsic functional connectivity.
2020-07
Population variability in social brain morphology for social support, household size and friendship satisfaction
Inferring disease subtypes from clusters in explanation space.
Patterns of autism symptoms: hidden structure in the ADOS and ADI-R instruments.
Phenotypical predictors of Restless Legs Syndrome in pregnancy and their association with basal ganglia and the limbic circuits
Neurocognitive patterns dissociating semantic processing from executive control are linked to more detailed off-task mental time travel.
Molecular signatures of cognition and affect
Bringing proportional recovery into proportion: Bayesian modelling of post-stroke motor impairment.
Hemispheric specialization within the inferior parietal lobe across cognitive domains
2020-06
Shared and unique brain network features predict cognition, personality and mental health in childhood
Dark control: The default mode network as a reinforcement learning agent.
The Neurobiology of Social Distance.
2020-05
Predictive Pattern Classification Can Distinguish Gender Identity Subtypes from Behavior and Brain Imaging.
General Principles of Gene Dosage Effects on Brain Structure
What Can Machine Learning Do for Psychiatry
2020-04
Autism spectrum heterogeneity: fact or artifact?
Meta-analytic evidence for a joint neural mechanism underlying response inhibition and state anger.
Neuropsychiatric copy number variants exert shared effects on human brain structure
Analysing brain networks in population neuroscience: a case for the Bayesian philosophy
Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists.
2020-03
Multi-scale network regression for brain-phenotype associations.
Not one model fits all: unfairness in RSFC-based prediction of behavioral data in African American
10,000 social brains: sex differentiation in human brain anatomy
2020-02
Fasting alters the gut microbiome with sustained blood pressure and body weight reduction in metabolic syndrome patients
Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.
2019-12
Clusters in Explanation Space: Inferring disease subtypes from model explanations.
2019-11
Distinct functional roles of the mirror neuron system and the mentalizing system.
Myeloarchitecture gradients in the human insula serve as blueprints for its diverse connectivity and function
2019-09
Deep learning for brains?: Different linear and nonlinear scaling in UK Biobank brain images vs. machine-learning datasets
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