AIMC Topic: Brain

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Creative experiences and brain clocks.

Nature communications
Creative experiences may enhance brain health, yet metrics and mechanisms remain elusive. We characterized brain health using brain clocks, which capture deviations from chronological age (i.e., accelerated or delayed brain aging). We combined M/EEG ...

Rehabilitation, neuroplasticity, and machine learning: Approaching artificial intelligence for equitable health systems.

Neuroscience
Recently, technology has evolved significantly in the rehabilitation process for neurological disorders and neurodegenerative diseases, focusing on neuroplasticity. Neuroplasticity, as a fundamental base of brain rehabilitation, is the change in the ...

Centiloid values from deep learning-based CT parcellation: a valid alternative to freesurfer.

Alzheimer's research & therapy
BACKGROUND: Amyloid PET/CT is essential for quantifying amyloid-beta (Aβ) deposition in Alzheimer's disease (AD), with the Centiloid (CL) scale standardizing measurements across imaging centers. However, MRI-based CL pipelines face challenges: high c...

petBrain: a new pipeline for amyloid, Tau tangles and neurodegeneration quantification using PET and MRI.

Alzheimer's research & therapy
INTRODUCTION: Quantification of amyloid plaques (A), neurofibrillary tangles (T), and neurodegeneration (N) using PET and MRI is critical for Alzheimer's disease (AD) diagnosis and prognosis. Existing pipelines face limitations regarding processing t...

Enhanced image registration based brain tumour segmentation using optical particle swarm intelligence technique with Resnet Inceptionv2 HCNN.

Scientific reports
A brain tumor is the deadliest disease to cause sudden death, affecting billions of people worldwide. Artificial Intelligence (AI) powered technologies play a vital role in screening medical images to identify brain-suspecting tissue regions of attai...

Advanced MRI based Alzheimer's diagnosis through ensemble learning techniques.

Scientific reports
Alzheimer's Disease is a condition that affects the brain and causes changes in behavior and memory loss while making it hard to carry out tasks properly. It's vital to spot the illness early, for effective treatment. MRI technology has advanced in d...

Efficient and robust temporal processing with neural oscillations modulated spiking neural networks.

Nature communications
The brain exhibits rich dynamical properties that underpin its remarkable temporal processing capabilities. However, spiking neural networks (SNNs) inspired by the brain have not yet matched their biological counterparts in temporal processing and re...

TFDISNet: Temporal-frequency domain-invariant and domain-specific feature learning network for enhanced auditory attention decoding from EEG signals.

Biomedical physics & engineering express
Auditory Attention Decoding (AAD) from Electroencephalogram (EEG) signals presents a significant challenge in brain-computer interface (BCI) research due to the intricate nature of neural patterns. Existing approaches often fail to effectively integr...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.

Journal of neural engineering
Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as mild cognitive impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture st...

Energy constraints and neural strategy transitions in Alzheimer's: A game-theoretic model.

Journal of theoretical biology
While many mechanisms have been proposed to drive Alzheimer's disease, particularly the accumulation of amyloid plaques and hyperphosphorylation of tau proteins, emerging evidence suggests that they may be the byproducts of earlier damage rather than...