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New Criteria for Synchronization of Multilayer Neural Networks via Aperiodically Intermittent Control.

Computational intelligence and neuroscience
In this paper, the globally asymptotic synchronization of multi-layer neural networks is studied via aperiodically intermittent control. Due to the property of intermittent control, it is very hard to deal with the effect of time-varying delays and a...

Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals.

PloS one
Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrat...

Generalisable machine learning models trained on heart rate variability data to predict mental fatigue.

Scientific reports
A prolonged period of cognitive performance often leads to mental fatigue, a psychobiological state that increases the risk of injury and accidents. Previous studies have trained machine learning algorithms on Heart Rate Variability (HRV) data to det...

Compact Wideband Double-Slot Microstrip Feed Engraved TEM Horn Strip Antennas on a Multilayer Substrate Board for in Bed Resting Body Positions Determination Based on Artificial Intelligence.

Sensors (Basel, Switzerland)
In this paper, a horn-shaped strip antenna exponentially tapered carved on a multilayer dielectric substrate for an indoor body position tracking system is proposed. The performance of the proposed antenna was verified by testing it as a tracking sta...

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.

Journal of neurosurgery
OBJECTIVE: Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state...

Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest.

Brain research
OBJECTIVE: To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point.

Classification of Mental Stress Levels using EEG Connectivity and Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Classifying mental stress is important as it helps in identifying the type and severity of stress, which can inform the most appropriate treatment or intervention. In this study, we propose utilizing electroencephalography (EEG) signals with convolut...

STELA: a community-centred approach to norm elicitation for AI alignment.

Scientific reports
Value alignment, the process of ensuring that artificial intelligence (AI) systems are aligned with human values and goals, is a critical issue in AI research. Existing scholarship has mainly studied how to encode moral values into agents to guide th...

A review of ADHD detection studies with machine learning methods using rsfMRI data.

NMR in biomedicine
Attention deficit hyperactivity disorder (ADHD) is a common mental health condition that significantly affects school-age children, causing difficulties with learning and daily functioning. Early identification is crucial, and reliable and objective ...

Multitask Learning for Joint Diagnosis of Multiple Mental Disorders in Resting-State fMRI.

IEEE transactions on neural networks and learning systems
Facing the increasing worldwide prevalence of mental disorders, the symptom-based diagnostic criteria struggle to address the urgent public health concern due to the global shortfall in well-qualified professionals. Thanks to the recent advances in n...