AI Medical Compendium Journal:
Cognitive neurodynamics

Showing 1 to 10 of 18 articles

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

Cognitive neurodynamics
One of the areas where artificial intelligence (AI) technologies are used is the detection and diagnosis of mental disorders. AI approaches, including machine learning and deep learning models, can identify early signs of bipolar disorder, schizophre...

Predicting an EEG-Based hypnotic time estimation with non-linear kernels of support vector machine algorithm.

Cognitive neurodynamics
Our ability to measure time is vital for daily life, technology use, and even mental health; however, separating pure time perception from other mental processes (like emotions) is a research challenge requiring precise tests to isolate and understan...

On the ability of standard and brain-constrained deep neural networks to support cognitive superposition: a position paper.

Cognitive neurodynamics
The ability to coactivate (or "superpose") multiple conceptual representations is a fundamental function that we constantly rely upon; this is crucial in complex cognitive tasks requiring multi-item working memory, such as mental arithmetic, abstract...

Cognitive workload estimation using physiological measures: a review.

Cognitive neurodynamics
Estimating cognitive workload levels is an emerging research topic in the cognitive neuroscience domain, as participants' performance is highly influenced by cognitive overload or underload results. Different physiological measures such as Electroenc...

Coincidence detection and integration behavior in spiking neural networks.

Cognitive neurodynamics
UNLABELLED: Recently, the interest in spiking neural networks (SNNs) remarkably increased, as up to now some key advances of biological neural networks are still out of reach. Thus, the energy efficiency and the ability to dynamically react and adapt...

An EEG-based marker of functional connectivity: detection of major depressive disorder.

Cognitive neurodynamics
Major depressive disorder (MDD) is a prevalent psychiatric disorder globally. There are many assays for MDD, but rapid and reliable detection remains a pressing challenge. In this study, we present a fusion feature called P-MSWC, as a novel marker to...

ADHD/CD-NET: automated EEG-based characterization of ADHD and CD using explainable deep neural network technique.

Cognitive neurodynamics
UNLABELLED: In this study, attention deficit hyperactivity disorder (ADHD), a childhood neurodevelopmental disorder, is being studied alongside its comorbidity, conduct disorder (CD), a behavioral disorder. Because ADHD and CD share commonalities, di...

Investigation of the mechanism of action of deep brain stimulation for the treatment of Parkinson's disease.

Cognitive neurodynamics
Parkinson's disease (PD) is a severe, progressive, neurological disorder. PD is not a single disease, but rather resembles a syndrome. PD includes two types of pathogenesis (i.e., classical PD and new PD). Clinically, PD patients present with a range...

Spectral analysis and Bi-LSTM deep network-based approach in detection of mild cognitive impairment from electroencephalography signals.

Cognitive neurodynamics
Mild cognitive impairment (MCI) is a neuropsychological syndrome that is characterized by cognitive impairments. It typically affects adults 60 years of age and older. It is a noticeable decline in the cognitive function of the patient, and if left u...

Machine learning with multimodal neuroimaging data to classify stages of Alzheimer's disease: a systematic review and meta-analysis.

Cognitive neurodynamics
In recent years, Alzheimer's disease (AD) has been a serious threat to human health. Researchers and clinicians alike encounter a significant obstacle when trying to accurately identify and classify AD stages. Several studies have shown that multimod...