Zang YF papers

Eur Child Adolesc Psychiatry. 2024 Apr 25. doi: 10.1007/s00787-024-02422-w. Online ahead of print.

ABSTRACT

Impaired basic academic skills (e.g., word recognition) are common in children with Attention Deficit Hyperactivity Disorder (ADHD). The underlying neuropsychological and neural correlates of impaired Chinese reading skills in children with ADHD have not been substantially explored. Three hundred and two children with ADHD (all medication-naïve) and 105 healthy controls underwent the Chinese language skill assessment, and 175 also underwent fMRI scans (84 ADHD and 91 controls). Between-group and mediation analyses were applied to explore the interrelationships of the diagnosis of ADHD, cognitive dysfunction, and impaired reading skills. Five ADHD-related brain functional networks, including the default mode network (DMN) and the dorsal attention network (DAN), were built using predefined regions of interest. Voxel-based group-wise comparisons were performed. The ADHD group performed worse than the control group in word-level reading ability tests, with lower scores in Chinese character recognition (CR) and word chains (WS) (all P < 0.05). With full-scale IQ and sustained attention in the mediation model, the direct effect of ADHD status on the CR score became insignificant (P = 0.066). The underlying neural correlates for the orthographic knowledge (OT) and CR differed between the ADHD and the control group. The ADHD group tended to recruit more DMN regions to maintain their reading performance, while the control group seemed to utilize more DAN regions. Children with ADHD generally presented impaired word-level reading skills, which might be caused by impaired sustained attention and lower IQ. According to the brain functional results, we infer that ADHD children might utilize a different strategy to maintain their orthographic knowledge and character recognition performance.

PMID:38662058 | DOI:10.1007/s00787-024-02422-w

Sci Bull (Beijing). 2024 Mar 6:S2095-9273(24)00150-6. doi: 10.1016/j.scib.2024.03.006. Online ahead of print.

ABSTRACT

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

PMID:38519398 | DOI:10.1016/j.scib.2024.03.006

Hum Brain Mapp. 2024 Mar;45(4):e26636. doi: 10.1002/hbm.26636.

ABSTRACT

Parietal alpha activity shows a specific pattern of phasic changes during working memory. It decreases during the encoding and recall phases but increases during the maintenance phase. This study tested whether online rTMS delivered to the parietal cortex during the maintenance phase of a working memory task would increase alpha activity and hence improve working memory. Then, 46 healthy volunteers were randomly assigned to two groups to receive 3-day parietal 10 Hz online rTMS (either real or sham, 3600 pulses in total) that were time-locked to the maintenance phase of a spatial span task (180 trials in total). Behavioral performance on another spatial span task and EEG signals during a change detection task were recorded on the day before the first rTMS (pretest) and the day after the last rTMS (posttest). We found that rTMS improved performance on both online and offline spatial span tasks. For the offline change detection task, rTMS enhanced alpha activity within the maintenance phase and improved interference control of working memory at both behavioral (K score) and neural (contralateral delay activity) levels. These results suggested that rTMS with alpha frequency time-locked to the maintenance phase is a promising way to boost working memory.

PMID:38488458 | PMC:PMC10941606 | DOI:10.1002/hbm.26636