[HTML][HTML] Machine learning and artificial intelligence in neuroscience: A primer for researchers
F Badrulhisham, E Pogatzki-Zahn, D Segelcke… - Brain, Behavior, and …, 2024 - Elsevier
Artificial intelligence (AI) is often used to describe the automation of complex tasks that we
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …
Neuro‐educational leadership: Pioneering educational leadership through neuroscience research
Educators have been increasingly focused on the concept of educational leadership in the
context of global educational reform. With the emergence of neuroscience, there is potential …
context of global educational reform. With the emergence of neuroscience, there is potential …
Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression
Though sertraline is commonly prescribed in patients with major depressive disorder (MDD),
its superiority over placebo is only marginal. This is in part due to the neurobiological …
its superiority over placebo is only marginal. This is in part due to the neurobiological …
Oxytocin enhances the triangular association among behavior, resting‐state, and task‐state functional connectivity
Considerable advances in the role of oxytocin (OT) effect on behavior and the brain network
have been made, but the effect of OT on the association between inter‐individual differences …
have been made, but the effect of OT on the association between inter‐individual differences …
Can intelligence affect alcohol-, smoking-, and physical activity-related behaviors? A Mendelian randomization study
People with high levels of intelligence are more aware of risk factors, therefore choosing a
healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies …
healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies …
Generalizable and replicable brain-based predictions of cognitive functioning across common psychiatric illness
A primary aim of computational psychiatry is to establish predictive models linking individual
differences in brain functioning with symptoms. In particular, cognitive impairments are …
differences in brain functioning with symptoms. In particular, cognitive impairments are …
Survey on Human-Vehicle Interactions and AI Collaboration for Optimal Decision-Making in Automated Driving
AJM Muzahid, X Zhao, Z Wang - arXiv preprint arXiv:2412.08005, 2024 - arxiv.org
The capabilities of automated vehicles are advancing rapidly, yet achieving full autonomy
remains a significant challenge, requiring ongoing human cognition in decision-making …
remains a significant challenge, requiring ongoing human cognition in decision-making …
Reliable and generalizable brain-based predictions of cognitive functioning across common psychiatric illness
A primary aim of precision psychiatry is the establishment of predictive models linking
individual differences in brain functioning with clinical symptoms. In particular, cognitive …
individual differences in brain functioning with clinical symptoms. In particular, cognitive …
[HTML][HTML] Dissecting symptom-linked dimensions of resting-state electroencephalographic functional connectivity in autism with contrastive learning
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized
by social interaction deficits, communication difficulties, and restricted/repetitive behaviors or …
by social interaction deficits, communication difficulties, and restricted/repetitive behaviors or …
Prediction of individual performance and verbal intelligence scores from resting‐state fMRI in children and adolescents
N He, C Kou - International Journal of Developmental …, 2024 - Wiley Online Library
The neuroimaging basis of intelligence remains elusive; however, there is a growing body of
research employing connectome‐based predictive modeling to estimate individual …
research employing connectome‐based predictive modeling to estimate individual …