AIMC Topic: Brain
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Diagnosis of Autism Spectrum Disorder (ASD) by Dynamic Functional Connectivity Using GNN-LSTM.
Sensors (Basel, Switzerland)
Dec 30, 2024
Early detection of autism spectrum disorder (ASD) is particularly important given its insidious qualities and the high cost of the diagnostic process. Currently, static functional connectivity studies have achieved significant results in the field of...
A density-based MS disease diagnosis model using the capuchin search algorithm and an ensemble of deep neural networks.
Scientific reports
Dec 30, 2024
Multiple sclerosis (MS) is a severe brain disease that permanently destroys brain cells, impacting vision, balance, muscle control, and daily activity. This research employs a weighted combination of deep neural networks and optimization techniques f...
Deep learning models reveal the link between dynamic brain connectivity patterns and states of consciousness.
Scientific reports
Dec 30, 2024
Decoding states of consciousness from brain activity is a central challenge in neuroscience. Dynamic functional connectivity (dFC) allows the study of short-term temporal changes in functional connectivity (FC) between distributed brain areas. By clu...
Direct perception of affective valence from vision.
Nature communications
Dec 30, 2024
Subjective feelings are thought to arise from conceptual and bodily states. We examine whether the valence of feelings may also be decoded directly from objective ecological statistics of the visual environment. We train a visual valence (VV) machine...
Free-space optical spiking neural network.
PloS one
Dec 30, 2024
Neuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter challenges related to processing speed and thermal dissipation. As an...
Biological mechanisms contradict AI consciousness: The spaces between the notes.
Bio Systems
Dec 28, 2024
The presumption that experiential consciousness requires a nervous system and brain has been central to the debate on the possibility of developing a conscious form of artificial intelligence (AI). The likelihood of future AI consciousness or devisin...
Performance metrics outperform physiological indicators in robotic teleoperation workload assessment.
Scientific reports
Dec 28, 2024
Robotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation ...
A proficient approach for the classification of Alzheimer's disease using a hybridization of machine learning and deep learning.
Scientific reports
Dec 28, 2024
Alzheimer's disease (AD) is a neurodegenerative disorder. It causes progressive degeneration of the nervous system, affecting the cognitive ability of the human brain. Over the past two decades, neuroimaging data from Magnetic Resonance Imaging (MRI)...
Chaotic recurrent neural networks for brain modelling: A review.
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous ac...
A novel way to use cross-validation to measure connectivity by machine learning allows epilepsy surgery outcome prediction.
NeuroImage
Dec 27, 2024
The rate of success of epilepsy surgery, ensuring seizure-freedom, is limited by the lack of epileptogenicity biomarkers. Previous evidence supports the critical role of functional connectivity during seizure generation to characterize the epileptoge...
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