AIMC Topic: Brain

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Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition.

eLife
Traditional models of reading lack a realistic simulation of the early visual processing stages, taking input in the form of letter banks and predefined line segments, making them unsuitable for modeling early brain responses. We used variations of t...

Neural Networks and Chemical Messengers: Insights into Tobacco Addiction.

Brain topography
This study investigates changes in resting-state networks (RSNs) associated with tobacco addiction (TA) and whether these changes reflect alterations in neurotransmitter systems. A total of 90 patients with TA and 46 healthy controls (HCs) matched fo...

Realistic Subject-Specific Simulation of Resting State Scalp EEG Based on Physiological Model.

Brain topography
Electroencephalography (EEG) recordings are widely used in neuroscience to identify healthy individual brain rhythms and to detect alterations associated with various brain diseases. However, understanding the cellular origins of scalp EEG signals an...

Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.

Journal of computer assisted tomography
OBJECTIVE: The aim of this study was to evaluate various radiomics-based machine learning classification models using the apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) maps for differentiating between low-grade gliomas (LGGs) and...

Automated seizure detection in epilepsy using a novel dynamic temporal-spatial graph attention network.

Scientific reports
Epilepsy is a neurological disorder characterized by recurrent seizures caused by excessive electrical discharges in brain cells, posing significant diagnostic and therapeutic challenges. Dynamic brain network analysis via electroencephalography (EEG...

New developments in imaging in ALS.

Journal of neurology
Neuroimaging in ALS has contributed considerable academic insights in recent years demonstrating genotype-specific topological changes decades before phenoconversion and characterising longitudinal propagation patterns in specific phenotypes. It has ...

Naturalistic acute pain states decoded from neural and facial dynamics.

Nature communications
Pain remains poorly understood in task-free contexts, limiting our understanding of its neurobehavioral basis in naturalistic settings. Here, we use a multimodal, data-driven approach with intracranial electroencephalography, pain self-reports, and f...

Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic-Ischemic Encephalopathy Injury.

Sensors (Basel, Switzerland)
Hypoxic-Ischemic Encephalopathy (HIE) occurs in patients who experience a decreased flow of blood and oxygen to the brain, with the optimal window for effective treatment being within the first six hours of life. This puts a significant demand on med...

Three-Dimensional Reconstruction of Serial Block-Face Scanning Electron Microscopy Using Semantic Segmentation based on Semi-Supervised Deep Learning.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
Serial block-face scanning electron microscopy (SBF-SEM) is employed to achieve high-resolution volume reconstructions and detailed ultrastructural analyses of complex organelles. The performance of SBF-SEM is evaluated according to the accuracy of s...

Cross study transcriptomic investigation of Alzheimer's brain tissue discoveries and limitations.

Scientific reports
Developing effective treatments for Alzheimer's disease (AD) likely requires a deep understanding of molecular mechanisms. Integration of transcriptomic datasets and developing innovative computational analyses may yield novel molecular targets with ...