AI Medical Compendium Journal:
Behavioural brain research

Showing 1 to 10 of 18 articles

Academic-related stressors predict depressive symptoms in graduate students: A machine learning study.

Behavioural brain research
BACKGROUND: Graduate students face higher depression rates worldwide, which were further exacerbated during the COVID-19 pandemic. This study employed a machine learning approach to predict depressive symptoms using academic-related stressors.

Depression diagnosis: EEG-based cognitive biomarkers and machine learning.

Behavioural brain research
Depression is a complex mental illness that has significant effects on people as well as society. The traditional techniques for the diagnosis of depression, along with the potential of nascent biomarkers especially EEG-based biomarkers, are studied....

Automated analysis of a novel object recognition test in mice using image processing and machine learning.

Behavioural brain research
The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' obs...

A generative adaptive convolutional neural network with attention mechanism for driver fatigue detection with class-imbalanced and insufficient data.

Behavioural brain research
Over the past few years, fatigue driving has emerged as one of the main causes of traffic accidents, necessitating the development of driver fatigue detection systems. However, many existing methods involves tedious manual parameter tunings, a proces...

Volumetric Alterations of the Hippocampal Subfields in Major Depressive Disorder with and without Suicidal Ideation.

Behavioural brain research
Major depressive disorder (MDD) is often accompanied with suicidal ideation (SI). Previous studies suggested that MDD patients who experienced suicidal attempts (SA) exhibited smaller hippocampal volume than those without SA. The hippocampus consists...

A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks.

Behavioural brain research
BACKGROUND: It has been recently shown that deep learning models exhibited remarkable performance of representing functional Magnetic Resonance Imaging (fMRI) data for the understanding of brain functional activities. With hierarchical structure, dee...

What is neurorepresentationalism? From neural activity and predictive processing to multi-level representations and consciousness.

Behavioural brain research
This review provides an update on Neurorepresentationalism, a theoretical framework that defines conscious experience as multimodal, situational survey and explains its neural basis from brain systems constructing best-guess representations of sensat...

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness.

Behavioural brain research
Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data owne...

Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.

Behavioural brain research
Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task specific; where reach training only improves reaching, step training only improves stepping and stand t...

A simple three layer excitatory-inhibitory neuronal network for temporal decision-making.

Behavioural brain research
Humans and animals do not only keep track of time intervals but they can also make decisions about durations. Temporal bisection is a psychophysical task that is widely used to assess the latter ability via categorization of durations as short or lon...