AIMC Topic: Brain

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A transformer-based network with second-order pooling for motor imagery EEG classification.

Journal of neural engineering
. Electroencephalography (EEG) signals can reflect motor intention signals in the brain. In recent years, motor imagery (MI) based brain-computer interfaces (BCIs) have attracted the attention of neuroinformatics researchers. Numerous deep learning m...

Artificial intelligence driven neuropsychiatry: a systematic review of electroencephalography-based computational techniques for major depressive disorder prediction.

Neuroscience
Major Depressive Disorder is the most prominent global mental health issue impacting millions of individuals worldwide. Electroencephalogram signals capturing intricate brain dynamics have emerged as a promising modality for predicting depression. Th...

Predictive models of influenza A virus lethal disease yield insights from ferret respiratory tract and brain tissues.

Scientific reports
Collection of systemic tissues from influenza A virus (IAV)-infected ferrets at a fixed timepoint post-inoculation represents a frequent component of risk assessment activities to assess the capacity of IAV to replicate systemically. However, few stu...

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Scientific reports
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the aging global population, AD incidence and its socioeconomic burden are increasing. Developing effectiv...

Assessing changes in whole-brain structural connectivity in the unilateral 6-hydroxydopamine rat model of Parkinson's disease using diffusion imaging and tractography.

Journal of neural engineering
Parkinson's disease (PD) is a multifactorial, progressive neurodegenerative disease that has a profound impact on those it afflicts. Its hallmark pathophysiology is characterized by degeneration of dopaminergic (DA) neurons in the midbrain which trig...

Neuroimaging and biological markers of different paretic hand outcomes after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Hand dysfunction significantly affects independence after stroke, with outcomes varying across individuals. Exploring biomarkers associated with the paretic hand can improve the prognosis and guide personalized rehabilitation. However, wh...

Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics.

BMC medical imaging
INTRODUCTION: Accurate early prognostic prediction for acute ischemic stroke (AIS) is essential for guiding personalized treatment. This study aimed to assess the predictive value of radiomics features from whole-brain and infarct cerebral blood flow...

3BTRON: A Blood-Brain Barrier Recognition Network.

Communications biology
The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis. During ageing, the BBB undergoes structural alterations. Electron microscopy (EM) is the gold standard for studying the structural alterations of the brain vasculatu...

Intrinsic dynamic shapes responses to external stimulation in the human brain.

eLife
Sensory stimulation of the brain reverberates in its recurrent neural networks. However, current computational models of brain activity do not separate immediate sensory responses from this intrinsic dynamic. We apply a vector-autoregressive model wi...

Influence of cognitive networks and task performance on fMRI-based state classification using DNN models.

Scientific reports
Deep neural networks (DNNs) excel at extracting insights from complex data across various fields, however, their application in cognitive neuroscience remains limited, largely due to the lack of approaches with interpretability. Here, we employ two d...