Publications by authors named "Zhihui Lan"

3 Publications

  • Page 1 of 1

Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder.

J Psychiatr Res 2021 Jun 8;138:569-575. Epub 2021 May 8.

College of Education, Hangzhou Normal University, Hangzhou, 311121, China.

Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jpsychires.2021.05.010DOI Listing
June 2021

Curcumin protects murine lung mesenchymal stem cells from HO by modulating the Akt/Nrf2/HO-1 pathway.

J Int Med Res 2020 Apr;48(4):300060520910665

Department of Respiration, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, Jiangxi, China.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1177/0300060520910665DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132811PMC
April 2020

Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach.

Neuropsychiatr Dis Treat 2020 10;16:691-702. Epub 2020 Mar 10.

Center for Cognition and Brain Disorders, Institute of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University, Hangzhou 311121, People's Republic of China.

Purpose: In recent years, machine learning techniques have received increasing attention as a promising approach to differentiating patients from healthy subjects. Therefore, some resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used interregional functional connections as discriminative features. The aim of this study was to investigate ADHD-related spatially distributed discriminative features derived from whole-brain resting-state functional connectivity patterns using machine learning.

Patients And Methods: We measured the interregional functional connections of the R-fMRI data from 40 ADHD patients and 28 matched typically developing controls. Machine learning was used to discriminate ADHD patients from controls. Classification performance was assessed by permutation tests.

Results: The results from the model with the highest classification accuracy showed that 85.3% of participants were correctly identified using leave-one-out cross-validation (LOOV) with support vector machine (SVM). The majority of the most discriminative functional connections were located within or between the cerebellum, default mode network (DMN) and frontoparietal regions. Approximately half of the most discriminative connections were associated with the cerebellum. The cerebellum, right superior orbitofrontal cortex, left olfactory cortex, left gyrus rectus, right superior temporal pole, right calcarine gyrus and bilateral inferior occipital cortex showed the highest discriminative power in classification. Regarding the brain-behaviour relationships, some functional connections between the cerebellum and DMN regions were significantly correlated with behavioural symptoms in ADHD ( < 0.05).

Conclusion: This study indicated that whole-brain resting-state functional connections might provide potential neuroimaging-based information for clinically assisting the diagnosis of ADHD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2147/NDT.S239013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071874PMC
March 2020