Results 171 to 180 of about 270,788 (377)

Six artificial intelligence innovation strategies applied to autism spectrum disorder research: A narrative review

Pediatric Investigation, EarlyView.
Six artificial intelligence strategies advance autism research from tool optimization to paradigm shift: causal modeling, spatiotemporal networks, multimodal integration, digital twins, social cognition mapping, collaborative learning, and context‐aware interventions for precision care.
Ting Zhang, Zhenkun Cao, Wei Li, Zhihai Lv   +3 more
wiley   +1 more source

Functional connectivity between the thalamus and visual cortex under eyes closed and eyes open conditions: A resting‐state fMRI study

, 2009
Qihong Zou, Xiangyu Long, Xi‐Nian Zuo, Chao‐Gan Yan, Chaozhe Zhu, Yihong Yang, Dongqiang Liu, Yong He, Yu‐Feng Zang   +8 more
openalex   +2 more sources

High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials [PDF]

, 2017
Zhaoyue Shi, Ruiqi Wu, Pai-Feng Yang, Feng Wang, Tung-Lin Wu, Arabinda Mishra, Li Min Chen, John C. Gore   +7 more
openalex   +1 more source

Predicting Pharmacological Treatment Response in Migraine Using AI/ML: A Scoping Review of the Evidence and Future Directions

Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, EarlyView.
ABSTRACT The treatment of migraine is hampered by inter‐individual variability, leading to an inefficient “trial and error” approach. Artificial intelligence (AI) and machine learning (ML) offer a path towards precision medicine by predicting therapeutic outcomes.
Martina Giacon, Salvatore Terrazzino
wiley   +1 more source

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

, 2016
Tingting Xu, Kathryn R. Cullen, Bryon A. Mueller, Mindy Westlund Schreiner, Kelvin O. Lim, S. Charles Schulz, Keshab K. Parhi   +6 more
openalex   +1 more source

The nuisance of nuisance regression: Spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity

NeuroImage, 2013
M. Hallquist, K. Hwang, B. Luna
semanticscholar   +1 more source

Hippocampal subfield differences in people with and without recreational ketamine use: Insights from multi‐modal neuroimaging

Addiction, EarlyView.
Abstract Background and aims Recreational ketamine use has increased globally and is associated with psychiatric and cognitive concerns. The hippocampus in preclinical models shows damage and working‐memory disruption with repeated dosing. However, whether specific hippocampal subregions may differ in people with chronic ketamine use remains unclear ...
Yi‐Hsuan Liu, Chia‐Chun Hung, Marc N. Potenza, Kun‐Hsien Chou, Pei‐Lin Lee, Chu‐Chung Huang, Chiang‐Shan R. Li, Tony Szu‐Hsien Lee, Ching‐Po Lin   +8 more
wiley   +1 more source

Mathematics anxiety: Effects of age, gender and culture

British Journal of Educational Psychology, EarlyView.
Abstract Background Many studies have indicated that mathematics anxiety is a significant problem for many people and is an important topic for research. Mathematics anxiety is multidimensional. In particular, it is important to distinguish between worry and emotionality components, and between trait and state anxiety.
Ann Dowker
wiley   +1 more source

Reward network connectivity “at rest” is associated with reward sensitivity in healthy adults: A resting-state fMRI study [PDF]

, 2019
Jesús Adrián‐Ventura, Víctor Costumero, María Antonia Parcet, César Ávila   +3 more
openalex   +1 more source

Unveiling the factors of aesthetic preferences with explainable AI

British Journal of Psychology, EarlyView.
Abstract The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences.
Derya Soydaner, Johan Wagemans
wiley   +1 more source