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Bioengineering
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Recent Technologies in Neuroimaging and Brain Intervention of PDs
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Recent Technologies in Neuroimaging and Brain Intervention of PDs

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 9148

Special Issue Editor

Prof. Dr. Zhen Yuan

E-Mail Website
Guest Editor
Faculty of Health Sciences, University of Macau, Taipa, Macau, China
Interests: neuroimaging; cognitive aging & brain disorders; biomedical optics and optical molecular imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Psychiatric disorders (PDs) cause behavioral or mental dysfunctions that might disturb your thinking, mood, and behaviors. In particular, PDs demonstrate a significant distress or impairment of your brain functioning. PDs mainly include attention-deficit/hyperactivity disorder, personality disorders, depression and anxiety, bipolar disorder, autism spectrum disorder, schizophrenia spectrum, insomnia, behavioral addiction, obsessive compulsive and other related disorders, etc.

To date, it is very challenging to use traditional imaging tools such as computed tomography or ultrasound to detect the brain deficits of psychiatric disorders. Meanwhile, due to significant individual differences and the complexity of human behaviors, it is very hard to inspect the cognitive neural mechanism by using animal models when trying to understand the pathogenesis of various PDs. Therefore, it is essential to develop new cognitive test paradigms and use advanced clinical neuroimaging techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG) magnetoencephalography (MEG), functional near-infrared spectroscopy, and PET to identify the novel therapeutic targets for the diagnosis and treatment of PDs.

The aims and scope of this Special Issue are to exhibit the new multifaceted technologies in neuroimaging and brain interventions of PDs. All types of manuscripts are welcome to be submitted to this Special Issue, from review articles to basic and clinical studies related to PDs. It is expected that the main findings of this topic will pave a new way for the functional detection and effective intervention of different PDs.

Prof. Dr. Zhen Yuan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neuroimage
  • functional MRI
  • electroencephalography
  • magnetoencephalography
  • psychiatric disorder
  • brain intervention

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Published Papers (4 papers)

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Research

14 pages, 3152 KiB  
Article
Aberrant Flexibility of Dynamic Brain Network in Patients with Autism Spectrum Disorder
by Hui Zhang, Dehong Peng, Shixiong Tang, Anyao Bi and Yicheng Long
Bioengineering 2024, 11(9), 882; https://doi.org/10.3390/bioengineering11090882 - 30 Aug 2024
Viewed by 1287
Abstract
Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders whose pathobiology remains elusive. This study aimed to investigate the possible neural mechanisms underlying ASD using a dynamic brain network model and a relatively large-sample, multi-site dataset. Resting-state functional magnetic resonance imaging data [...] Read more.
Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders whose pathobiology remains elusive. This study aimed to investigate the possible neural mechanisms underlying ASD using a dynamic brain network model and a relatively large-sample, multi-site dataset. Resting-state functional magnetic resonance imaging data were acquired from 208 ASD patients and 227 typical development (TD) controls, who were drawn from the multi-site Autism Brain Imaging Data Exchange (ABIDE) database. Brain network flexibilities were estimated and compared between the ASD and TD groups at both global and local levels, after adjusting for sex, age, head motion, and site effects. The results revealed significantly increased brain network flexibilities (indicating a decreased stability) at the global level, as well as at the local level within the default mode and sensorimotor areas in ASD patients than TD participants. Additionally, significant ASD-related decreases in flexibilities were also observed in several occipital regions at the nodal level. Most of these changes were significantly correlated with the Autism Diagnostic Observation Schedule (ADOS) total score in the entire sample. These results suggested that ASD is characterized by significant changes in temporal stabilities of the functional brain network, which can further strengthen our understanding of the pathobiology of ASD. Full article
(This article belongs to the Special Issue Recent Technologies in Neuroimaging and Brain Intervention of PDs)
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15 pages, 3022 KiB  
Article
Effects of rTMS Intervention on Functional Neuroimaging Activities in Adolescents with Major Depressive Disorder Measured Using Resting-State fMRI
by Fengmei Lu, Qian Cui, Yang Zou, Yuanhong Guo, Wei Luo, Yue Yu, Jingjing Gao, Xiao Cai, Linna Fu, Shuai Yuan, Juan Huang, Yajun Zhang, Jing Xie, Wei Sheng, Qin Tang, Qing Gao, Zongling He and Huafu Chen
Bioengineering 2023, 10(12), 1374; https://doi.org/10.3390/bioengineering10121374 - 29 Nov 2023
Cited by 4 | Viewed by 2722
Abstract
Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional [...] Read more.
Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional neuroimaging changes induced by rTMS in adolescents with MDD. A total of ten sessions of rTMS were administrated to the L-DLPFC in thirteen adolescents with MDD once a day for two weeks. All of them were scanned using resting-state functional magnetic resonance imaging at baseline and after rTMS treatment. The regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and the subgenual anterior cingulate cortex (sgACC)-based functional connectivity (FC) were computed as neuroimaging indicators. The correlation between changes in the sgACC-based FC and the improvement in depressive symptoms was also analyzed. After rTMS treatment, ReHo and ALFF were significantly increased in the L-DLPFC, the left medial prefrontal cortex, bilateral medial orbital frontal cortex, and the left ACC. ReHo and ALFF decreased mainly in the left middle occipital gyrus, the right middle cingulate cortex (MCC), bilateral calcarine, the left cuneus, and the left superior occipital gyrus. Furthermore, the FCs between the left sgACC and the L-DLPFC, the right IFGoper, the left MCC, the left precuneus, bilateral post-central gyrus, the left supplementary motor area, and the left superior marginal gyrus were enhanced after rTMS treatment. Moreover, the changes in the left sgACC-left MCC FC were associated with an improvement in depressive symptoms in early improvers. This study showed that rTMS treatment in adolescents with MDD causes changes in brain activities and sgACC-based FC, which may provide basic neural biomarkers for rTMS clinical trials. Full article
(This article belongs to the Special Issue Recent Technologies in Neuroimaging and Brain Intervention of PDs)
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13 pages, 1824 KiB  
Article
Functional Changes of White Matter Are Related to Human Pain Sensitivity during Sustained Nociception
by Hui He, Lan Hu, Saiying Tan, Yingjie Tang, Mingjun Duan, Dezhong Yao, Guocheng Zhao and Cheng Luo
Bioengineering 2023, 10(8), 988; https://doi.org/10.3390/bioengineering10080988 - 21 Aug 2023
Cited by 2 | Viewed by 1519
Abstract
Pain is considered an unpleasant perceptual experience associated with actual or potential somatic and visceral harm. Human subjects have different sensitivity to painful stimulation, which may be related to different painful response pattern. Excellent studies using functional magnetic resonance imaging (fMRI) have found [...] Read more.
Pain is considered an unpleasant perceptual experience associated with actual or potential somatic and visceral harm. Human subjects have different sensitivity to painful stimulation, which may be related to different painful response pattern. Excellent studies using functional magnetic resonance imaging (fMRI) have found the effect of the functional organization of white matter (WM) on the descending pain modulatory system, which suggests that WM function is feasible during pain modulation. In this study, 26 pain sensitive (PS) subjects and 27 pain insensitive (PIS) subjects were recruited based on cold pressor test. Then, all subjects underwent the cold bottle test (CBT) in normal (26 degrees temperature stimulating) and cold (8 degrees temperature stimulating) conditions during fMRI scan, respectively. WM functional networks were obtained using K-means clustering, and the functional connectivity (FC) was assessed among WM networks, as well as gray matter (GM)–WM networks. Through repeated measures ANOVA, decreased FC was observed between the GM–cerebellum network and the WM–superior temporal network, as well as the WM–sensorimotor network in the PS group under the cold condition, while this difference was not found in PIS group. Importantly, the changed FC was positively correlated with the state and trait anxiety scores, respectively. This study highlighted that the WM functional network might play an integral part in pain processing, and an altered FC may be related to the descending pain modulatory system. Full article
(This article belongs to the Special Issue Recent Technologies in Neuroimaging and Brain Intervention of PDs)
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12 pages, 2755 KiB  
Article
Diagnosis of Chronic Musculoskeletal Pain by Using Functional Near-Infrared Spectroscopy and Machine Learning
by Xinglin Zeng, Wen Tang, Jiajia Yang, Xiange Lin, Meng Du, Xueli Chen, Zhen Yuan, Zhou Zhang and Zhiyi Chen
Bioengineering 2023, 10(6), 669; https://doi.org/10.3390/bioengineering10060669 - 1 Jun 2023
Cited by 3 | Viewed by 2900
Abstract
Chronic pain (CP) has been found to cause significant alternations of the brain’s structure and function due to changes in pain processing and disrupted cognitive functions, including with respect to the prefrontal cortex (PFC). However, until now, no studies have used a wearable, [...] Read more.
Chronic pain (CP) has been found to cause significant alternations of the brain’s structure and function due to changes in pain processing and disrupted cognitive functions, including with respect to the prefrontal cortex (PFC). However, until now, no studies have used a wearable, low-cost neuroimaging tool capable of performing functional near-infrared spectroscopy (fNIRS) to explore the functional alternations of the PFC and thus automatically achieve a clinical diagnosis of CP. In this case-control study, the pain characteristics of 19 chronic pain patients and 32 healthy controls were measured using fNIRS. Functional connectivity (FC), FC in the PFC, and spontaneous brain activity of the PFC were examined in the CP patients and compared to those of healthy controls (HCs). Then, leave-one-out cross-validation and machine learning algorithms were used to automatically achieve a diagnosis corresponding to a CP patient or an HC. The current study found significantly weaker FC, notably higher small-worldness properties of FC, and increased spontaneous brain activity during resting state within the PFC. Additionally, the resting-state fNIRS measurements exhibited excellent performance in identifying the chronic pain patients via supervised machine learning, achieving F1 score of 0.8229 using only seven features. It is expected that potential FC features can be identified, which can thus serve as a neural marker for the detection of CP using machine learning algorithms. Therefore, the present study will open a new avenue for the diagnosis of chronic musculoskeletal pain by using fNIRS and machine learning techniques. Full article
(This article belongs to the Special Issue Recent Technologies in Neuroimaging and Brain Intervention of PDs)
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