AIMC Topic: Brain

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Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.

IEEE transactions on neural networks and learning systems
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectiv...

Deep Geometric Learning With Monotonicity Constraints for Alzheimer's Disease Progression.

IEEE transactions on neural networks and learning systems
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for clinical diagnosis and treatment. For this, numerous studies have imple...

Temporal interactions between neural proxies for memory recall, negative affect, and emotion regulation in major depression.

Molecular psychiatry
Dysfunction in emotion regulation (ER) and autobiographical memory are components of major depressive disorder (MDD). However, little is known about how they mechanistically interact with mood disturbances in real time. Using machine learning-based n...

Effects of Renal Function on the Multimodal Brain Networks Affecting Mild Cognitive Impairment Converters in End-Stage Renal Disease.

Academic radiology
RATIONALE AND OBJECTIVES: Cognitive decline is common in End-Stage Renal Disease (ESRD) patients, yet its neural mechanisms are poorly understood. This study investigates structural and functional brain network reconfiguration in ESRD patients transi...

Increased Global and Regional Connectivity in Propofol-induced Unconsciousness: Human Intracranial Electroencephalography Study.

Anesthesiology
BACKGROUND: The conscious state is maintained through intact communication between brain regions. However, studies on global and regional connectivity changes in unconscious state have been inconsistent. These inconsistencies could arise from unclear...

Radiomics across modalities: a comprehensive review of neurodegenerative diseases.

Clinical radiology
Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational ...

LGFormer: integrating local and global representations for EEG decoding.

Journal of neural engineering
Electroencephalography (EEG) decoding is challenging because of its temporal variability and low signal-to-noise ratio, which complicate the extraction of meaningful information from signals. Although convolutional neural networks (CNNs) effectively ...

Asymmetric Adaptive Heterogeneous Network for Multi-Modality Medical Image Segmentation.

IEEE transactions on medical imaging
Existing studies of multi-modality medical image segmentation tend to aggregate all modalities without discrimination and employ multiple symmetric encoders or decoders for feature extraction and fusion. They often overlook the different contribution...

Amyloid-β Deposition Prediction With Large Language Model Driven and Task-Oriented Learning of Brain Functional Networks.

IEEE transactions on medical imaging
Amyloid- positron emission tomography can reflect the Amyloid- protein deposition in the brain and thus serves as one of the golden standards for Alzheimer's disease (AD) diagnosis. However, its practical cost and high radioactivity hinder its applic...