ORCID Profile
0000-0002-0872-3276
Current Organisation
Nanyang Technological University
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Publisher: IEEE
Date: 07-2013
Publisher: Springer Science and Business Media LLC
Date: 19-04-2021
DOI: 10.1038/S41598-021-87789-5
Abstract: Stroke leads to both regional brain functional disruptions and network reorganization. However, how brain functional networks reconfigure as task demand increases in stroke patients and whether such reorganization at baseline would facilitate post-stroke motor recovery are largely unknown. To address this gap, brain functional connectivity (FC) were examined at rest and motor tasks in eighteen chronic subcortical stroke patients and eleven age-matched healthy controls. Stroke patients underwent a 2-week intervention using a motor imagery-assisted brain computer interface-based (MI-BCI) training with or without transcranial direct current stimulation (tDCS). Motor recovery was determined by calculating the changes of the upper extremity component of the Fugl–Meyer Assessment (FMA) score between pre- and post-intervention ided by the pre-intervention FMA score. The results suggested that as task demand increased (i.e., from resting to passive unaffected hand gripping and to active affected hand gripping), patients showed greater FC disruptions in cognitive networks including the default and dorsal attention networks. Compared to controls, patients had lower task-related spatial similarity in the somatomotor–subcortical, default–somatomotor, salience/ventral attention–subcortical and subcortical–subcortical connections, suggesting greater inefficiency in motor execution. Importantly, higher baseline network-specific FC strength (e.g., dorsal attention and somatomotor) and more efficient brain network reconfigurations (e.g., somatomotor and subcortical) from rest to active affected hand gripping at baseline were related to better future motor recovery. Our findings underscore the importance of studying functional network reorganization during task-free and task conditions for motor recovery prediction in stroke.
Publisher: Elsevier BV
Date: 05-2022
DOI: 10.1016/J.SCHRES.2021.06.011
Abstract: The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data. We found that the naive 3D CNN models outperformed the pretrained 2D CNN models and the handcrafted feature-based machine learning approach using support vector machine during both cross-validation and testing on an independent dataset. Multimodal neuroimaging-based models accomplished performance superior to models based on a single modality. Furthermore, we identified brain grey matter and white matter regions critical for illness classification at the in idual- and group-level which supported the salience network and striatal dysfunction hypotheses in schizophrenia. Our findings underscore the potential of CNN not only to automatically uncover and integrate multimodal 3D brain imaging features for schizophrenia identification, but also to provide relevant neurobiological interpretations which are crucial for developing objective and interpretable imaging-based probes for prognosis and diagnosis in psychiatric disorders.
Publisher: IEEE
Date: 12-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-09-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: IEEE
Date: 07-2018
Publisher: IEEE
Date: 07-2020
Publisher: JMIR Publications Inc.
Date: 14-06-2019
DOI: 10.2196/13869
Abstract: Exposure therapy is highly effective for social anxiety disorder. However, there is room for improvement. This is a first attempt to examine the feasibility of an arousal feedback–based exposure therapy to alleviate social anxiety symptoms in an analogue adult s le. A randomized, pilot, proof-of-concept trial was conducted to evaluate the acceptability, safety, and preliminary efficacy of our treatment program. Sessions were administered once a week for 4 weeks (1 hour each) to an analogue s le of 50 young adults who reported at least minimal social anxiety symptoms. Participants in both intervention and waitlist control groups completed assessments for social anxiety symptoms at the baseline, week 5, and week 10. Most participants found the intervention acceptable (82.0%, 95% CI 69.0%-91.0%). Seven (14.9%, 95% CI 7.0%-28.0%) participants reported at least one mild adverse event over the course of study. No moderate or serious adverse events were reported. Participants in the intervention group demonstrated greater improvements on all outcome measures of public speaking anxiety from baseline to week 5 as compared to the waitlist control group (Cohen d=0.61-1.39). Effect size of the difference in mean change on the overall Liebowitz Social Anxiety Scale was small (Cohen d=0.13). Our results indicated that it is worthwhile to proceed to a larger trial for our treatment program. This new medium of administration for exposure therapy may be feasible for treating a subset of social anxiety symptoms. Additional studies are warranted to explore its therapeutic mechanisms. ClinicalTrials.gov NCT02493010 t2/show/NCT02493010
Publisher: IEEE
Date: 07-2013
Publisher: IEEE
Date: 07-2010
Publisher: IEEE
Date: 08-2010
Publisher: IEEE
Date: 08-2015
Publisher: Public Library of Science (PLoS)
Date: 18-03-2019
Publisher: Springer Science and Business Media LLC
Date: 23-08-2017
DOI: 10.1038/S41598-017-08928-5
Abstract: Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been used in stroke rehabilitation, though their combinatory effect is unknown. We investigated brain plasticity following a combined MI-BCI and tDCS intervention in chronic subcortical stroke patients with unilateral upper limb disability. Nineteen patients were randomized into tDCS and sham-tDCS groups. Diffusion and perfusion MRI, and transcranial magnetic stimulation were used to study structural connectivity, cerebral blood flow (CBF), and corticospinal excitability, respectively, before and 4 weeks after the 2-week intervention. After quality control, thirteen subjects were included in the CBF analysis. Eleven healthy controls underwent 2 sessions of MRI for reproducibility study. Whereas motor performance showed comparable improvement, long-lasting neuroplasticity can only be detected in the tDCS group, where white matter integrity in the ipsilesional corticospinal tract and bilateral corpus callosum was increased but sensorimotor CBF was decreased, particularly in the ipsilesional side. CBF change in the bilateral parietal cortices also correlated with motor function improvement, consistent with the increased white matter integrity in the corpus callosum connecting these regions, suggesting an involvement of interhemispheric interaction. The preliminary results indicate that tDCS may facilitate neuroplasticity and suggest the potential for refining rehabilitation strategies for stroke patients.
Publisher: Springer Science and Business Media LLC
Date: 19-03-2019
DOI: 10.1007/S00702-019-01993-2
Abstract: Actigraphy is a non-invasive method of monitoring circadian rhythms and motor activity. We systematically reviewed extant evidence until September 2018 pertaining to actigraphy use in schizophrenia, its clinical/biological correlates and posit future research directions. Within 38 included studies involving 2700 subjects, patients with schizophrenia generally have lower motor activity levels, poorer sleep quality and efficiency, increased sleep fragmentation and duration compared with healthy controls. Lowered motor activity and longer sleep duration in patients were associated with greater severity of negative symptoms. Less structured motor activity and decreased sleep quality were associated with greater severity of positive symptoms, worse cognitive functioning involving attention and processing speed, illness chronicity, higher antipsychotic dose, and poorer quality of life. Correlations of actigraphic measures with biological factors are sparse with inconclusive results. Future studies with larger s le sets may adopt a multimodal, longitudinal approach which examines both motor and sleep activity, triangulates clinical, actigraphic and biological measures to clarify their inter-relationships and inform risk prediction of illness onset, course, and treatment response over time.
No related grants have been discovered for Cuntai Guan.