AIMC Topic: Brain

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Decoding dynamic brain networks in Parkinson's disease with temporal attention.

Scientific reports
Detecting brief, clinically meaningful changes in brain activity is crucial for understanding neurological disorders. Conventional imaging analyses often overlook these subtle events due to computational demands. IMPACT (Integrative Multimodal Pipeli...

Menopausal hormone therapy and the female brain: Leveraging neuroimaging and prescription registry data from the UK Biobank cohort.

eLife
BACKGROUND: Menopausal hormone therapy (MHT) is generally thought to be neuroprotective, yet results have been inconsistent. Here, we present a comprehensive study of MHT use and brain characteristics in females from the UK Biobank.

Contrastive functional connectivity defines neurophysiology-informed symptom dimensions in major depression.

Cell reports. Medicine
Major depressive disorder (MDD) is highly heterogeneous, posing challenges for effective treatment due to complex interactions between clinical symptoms and neurobiological features. To address this, we apply contrastive principal-component analysis ...

Operationalizing postmortem pathology-MRI association studies in Alzheimer's disease and related disorders with MRI-guided histology sampling.

Acta neuropathologica communications
Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling that may miss critical areas affected by Alzheimer's disease and related disorders. Ultra-high reso...

A scientometric analysis of machine learning in schizophrenia neuroimaging: Trends and insights (2012-2024).

Journal of affective disorders
Machine learning applications in schizophrenia neuroimaging research have undergone significant evolution since 2012. However, a comprehensive scientometric analysis of this field has not yet been conducted. This study analyzed 315 original research ...

Functional connectome-based predictive modeling of suicidal ideation.

Journal of affective disorders
Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to ident...

Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy.

EBioMedicine
BACKGROUND: Valid non-invasive biomarkers for Parkinson's disease (PD) and Parkinson-plus syndrome (PPS) are urgently needed. Based on our recent self-supervised vision foundation model the Shift Window UNET TRansformer (Swin UNETR), which uses clini...

Advances in brain-targeted delivery strategies and natural product-mediated enhancement of blood-brain barrier permeability.

Journal of nanobiotechnology
The blood-brain barrier (BBB) represents a formidable challenge in the treatment of neurological disorders, as it restricts the passage of most therapeutic agents into the central nervous system (CNS). Research in brain-targeted delivery strategies a...

Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features.

BMC psychiatry
BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abno...