AIMC Topic: Brain

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Altered static and dynamic functional network connectivity and combined Machine learning in asthma.

Neuroscience
Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. Previous neuroimaging studies have shown structural and functional abnormalities in the brains of individuals with asthma. However, earlier research h...

Leveraging advanced graph neural networks for the enhanced classification of post anesthesia states to aid surgical procedures.

PloS one
Anesthesia plays a pivotal role in modern surgery by facilitating controlled states of unconsciousness. Precise control is crucial for safe and pain-free surgeries. Monitoring anesthesia depth accurately is essential to guide anesthesiologists, optim...

Specific expression and common potential therapeutic drugs in different brain regions of major depressive disorder patients: bioinformatics analysis.

Journal of affective disorders
Major depressive disorder (MDD) is a prevalent and debilitating mental health condition characterized by persistent feelings of sadness and loss of interest. Despite its high prevalence, the underlying molecular mechanisms remain poorly understood. T...

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Neuroscience
Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline in its later stages, severely impacting daily lives. Consequently, early diagnosis and accurate ass...

Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.

Neuroscience
The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning due to memory loss, cognitive decline, and behavioral problems. By using synchrosqueezing representat...

Decoding of lexical items and grammatical features in EEG: A cross-linguistic study.

Neuropsychologia
Diverse evidence supports the theory that bilingual language users have language-invariant representations of concepts and grammatical forms such as argument structure. Here we extend that work to test the representation of morphosyntactic features a...

ConnectomeAE: Multimodal brain connectome-based dual-branch autoencoder and its application in the diagnosis of brain diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Exploring the dependencies between multimodal brain networks and integrating node features to enhance brain disease diagnosis remains a significant challenge. Some work has examined only brain connectivity changes in patient...

Associations among white matter microstructural changes and the development of emotional reactivity and regulation in infancy.

Molecular psychiatry
Deficits in emotional reactivity and regulation assessed in infancy, including high levels of negative emotionality (NE), low positive emotionality (PE) and low soothability, can predict future affective and behavioral disorders. White matter (WM) tr...

AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.

IEEE transactions on cybernetics
The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals. However, current works primarily align the distributions of ...

Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.

IEEE transactions on cybernetics
The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial feature...