AIMC Topic: Brain

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Enhancing the early detection of Alzheimer's disease using an integrated CNN-LSTM framework: A robust approach for fMRI-based multi-stage classification.

PloS one
Alzheimer's Disease poses a significant challenge as a progressive and irreversible neurological condition striking the elderly population. Its incurable nature correlates with a significant rise in death rates. However, early detection can slow its ...

Neural and behavioral reinstatement jointly reflect retrieval of narrative events.

Nature communications
When recalling past events, patterns of gaze position and neural activity resemble those observed during the original experience. We hypothesized that these two phenomena, known as gaze reinstatement and neural reactivation, are linked through a comm...

Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study.

Translational psychiatry
Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain...

AlzFormer: Multi-modal framework for Alzheimer's classification using MRI and graph-embedded demographics guided by adaptive attention gating.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is the most common neurodegenerative progressive disorder and the fifth-leading cause of death in older people. The detection of AD is a very challenging task for clinicians and radiologists due to the complex nature of this ...

Deep learning approach for screening neonatal cerebral lesions on ultrasound in China.

Nature communications
Timely and accurate diagnosis of severe neonatal cerebral lesions is critical for preventing long-term neurological damage and addressing life-threatening conditions. Cranial ultrasound is the primary screening tool, but the process is time-consuming...

Non-genetic neuromodulation with graphene optoelectronic actuators for disease models, stem cell maturation, and biohybrid robotics.

Nature communications
Light can serve as a tunable trigger for neurobioengineering technologies, enabling probing, control, and enhancement of brain function with unmatched spatiotemporal precision. Yet, these technologies often require genetic or structural alterations o...

Embodied intelligence paradigm for human-robot communication.

Science robotics
Animals leverage their full embodiment to achieve multimodal, redundant, and subtle communication. To achieve the same for robots, they must similarly exploit their brain-body-environment interactions or their embodied intelligence. To advance this a...

Unraveling Microstructural and Macrostructural Brain Age Dynamics in Multiple Sclerosis.

Neurology(R) neuroimmunology & neuroinflammation
BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), neurodegeneration results from the interplay between disease-specific pathology and normal aging. Conventional MRI captures morphologic changes in neurodegeneration, while quantitative MRI (qMRI)...

Efficient neural encoding as revealed by bilingualism.

Proceedings of the National Academy of Sciences of the United States of America
The remarkable human capacity for bilingual and multilingual acquisition raises fundamental questions about how the brain develops efficient systems for processing multiple languages. In this study, we used neural network models trained on natural sp...