AIMC Topic: Brain

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Can MRI Be Used as a Sensor to Record Neural Activity?

Sensors (Basel, Switzerland)
Magnetic resonance provides exquisite anatomical images and functional MRI monitors physiological activity by recording blood oxygenation. This review attempts to answer the following question: Can MRI be used as a sensor to directly record neural be...

Brain Data Standards - A method for building data-driven cell-type ontologies.

Scientific data
Large-scale single-cell 'omics profiling is being used to define a complete catalogue of brain cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem: How do we organise...

Towards a versatile mental workload modeling using neurometric indices.

Biomedizinische Technik. Biomedical engineering
Researchers have been working to magnify mental workload (MWL) modeling for a long time. An important aspect of its modeling is feature selection as itĀ interprets bulky and high-dimensional EEG data and enhances the accuracy of the classification mod...

Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation across populations and dMRI acquisitions.

Medical image analysis
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections. White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts. It enable...

Computing personalized brain functional networks from fMRI using self-supervised deep learning.

Medical image analysis
A novel self-supervised deep learning (DL) method is developed to compute personalized brain functional networks (FNs) for characterizing brain functional neuroanatomy based on functional MRI (fMRI). Specifically, a DL model of convolutional neural n...

Continual task learning in natural and artificial agents.

Trends in neurosciences
How do humans and other animals learn new tasks? A wave of brain recording studies has investigated how neural representations change during task learning, with a focus on how tasks can be acquired and coded in ways that minimise mutual interference....

Rapid high-fidelity mapping using single-shot overlapping-echo acquisition and deep learning reconstruction.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a single-shot quantitative MRI technique called GRE-MOLED (gradient-echo multiple overlapping-echo detachment) for rapid mapping.

Extracting a Novel Emotional EEG Topographic Map Based on a Stacked Autoencoder Network.

Journal of healthcare engineering
Emotion recognition based on brain signals has increasingly become attractive to evaluate human's internal emotional states. Conventional emotion recognition studies focus on developing machine learning and classifiers. However, most of these methods...

The identification of interacting brain networks during robot-assisted training with multimodal stimulation.

Journal of neural engineering
Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual ...

Neurodegenerative disease of the brain: a survey of interdisciplinary approaches.

Journal of the Royal Society, Interface
Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseas...