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Brain Sciences
Special Issues
Neuromodulation for Neurological Disorders
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Neuromodulation for Neurological Disorders

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: closed (3 February 2023) | Viewed by 19610

Special Issue Editors

Dr. Kate Brown

E-Mail Website
Guest Editor
Department of Kinesiology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Interests: sensorimotor integration; neurophysiology; movement disorders; acute exercise; transcranial magnetic stimulation; electroencephalography
Dr. Jason Neva

E-Mail Website
Guest Editor
1. School of Kinesiology and Human Kinesiology, Faculty of Medicine, University of Mon-treal, Montreal, QC H3C 3J7, Canada
2. Research Center of the Montreal Geriatrics Institute, University of Montreal, Montreal, QC H3C 3J7, Canada
Interests: neurophysiology; motor learning; exercise; neuroplasticity; transcranial magnetic stimulation; stroke

Special Issue Information

Dear Colleagues,

Individuals with neuropathologies face a variety of deficits that can significantly impact their daily lives. Neuromodulatory techniques have often been proposed as a method to limit these deficits, enhance neuroplasticity, and/or to act as neurorehabilitative tools. Two components of neuromodulation that are important to understand are the underlying physiology of these techniques and how that might be impacted in neurological populations, as well as methods through which the physiological and behavioral response to neuromodulation in neurological disorders can be optimized.

The aim of the current Special Issue is to gather the latest high-quality research on the use of non-invasive brain stimulation and other neuromodulatory methods in neurological disorders, with specific interest in movement disorders and stroke. Authors are invited to submit original research articles, reviews, or protocol papers outlining new and promising techniques. We are keeping our outlook broad and welcome submissions on a wide variety of techniques in any neurological population. This will enable us to put together a collection of work that will provide insight into the potential wide-ranging applicability of neuromodulation.

Dr. Kate Brown
Dr. Jason Neva
Guest Editors

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. Brain Sciences 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 2200 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

  • neuromodulation
  • noninvasive brain stimulation
  • neuropathology
  • rehabilitation
  • neuroplasticity
  • TMS
  • tDCS

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Published Papers (5 papers)

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Research

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10 pages, 1961 KiB  
Article
Development and Validation of a Prediction Model for Anxiety Improvement after Deep Brain Stimulation for Parkinson Disease
by Bowen Chang, Jiaming Mei, Chen Ni, Chi Xiong, Peng Chen, Manli Jiang and Chaoshi Niu
Brain Sci. 2023, 13(2), 219; https://doi.org/10.3390/brainsci13020219 - 28 Jan 2023
Cited by 4 | Viewed by 1602
Abstract
Background: Parkinson’s disease (PD) represents one of the most frequently seen neurodegenerative disorders, while anxiety accounts for its non-motor symptom (NMS), and it has greatly affected the life quality of PD cases. Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) can effectively treat PD. [...] Read more.
Background: Parkinson’s disease (PD) represents one of the most frequently seen neurodegenerative disorders, while anxiety accounts for its non-motor symptom (NMS), and it has greatly affected the life quality of PD cases. Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) can effectively treat PD. This study aimed to develop a clinical prediction model for the anxiety improvement rate achieved in PD patients receiving STN-DBS. Methods: The present work retrospectively enrolled 103 PD cases undergoing STN-DBS. Patients were followed up for 1 year after surgery to analyze the improvement in HAMA scores. Univariate and multivariate logistic regression were conducted to select factors affecting the Hamilton Anxiety Scale (HAMA) improvement. A nomogram was established to predict the likelihood of achieving anxiety improvement. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and calibration curve analysis were conducted to verify nomogram performance. Results: The mean improvement in HAMA score was 23.9% in 103 patients; among them, 68.9% had improved anxiety, 25.2% had worsened (Preop) anxiety, and 5.8% had no significant change in anxiety. Education years, UPDRS-III preoperative score, and HAMA preoperative score were independent risk factors for anxiety improvement. The nomogram-predicted values were consistent with real probabilities. Conclusions: Collectively, a nomogram is built in the present work for predicting anxiety improvement probability in PD patients 1 year after STN-DBS. The model is valuable for determining expected anxiety improvement in PD patients undergoing STN-DBS. Full article
(This article belongs to the Special Issue Neuromodulation for Neurological Disorders)
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10 pages, 2125 KiB  
Article
Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
by Bowen Chang, Chen Ni, Weiwen Zhang, Jiaming Mei, Chi Xiong, Peng Chen, Manli Jiang and Chaoshi Niu
Brain Sci. 2022, 12(6), 759; https://doi.org/10.3390/brainsci12060759 - 9 Jun 2022
Cited by 6 | Viewed by 2212
Abstract
Purpose: Parkinson’s disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement rate after STN-DBS [...] Read more.
Purpose: Parkinson’s disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement rate after STN-DBS in PD patients. Methods: We retrospectively analyzed 103 PD patients who underwent STN-DBS. Patients were followed up to measure improvement in MoCA scores one year after surgery. Univariate and multivariate logistic regression analyses were used to identify factors affecting improvement in cognitive status. A nomogram was developed to predict this factor. The discrimination and fitting performance were evaluated by receiver operating characteristics (ROC) analysis, calibration diagram, and decision curve analysis (DCA). Results: Among 103 patients, the mean improvement rate of the MoCA score was 37.3% and the median improvement rate was 27.3%, of which 64% improved cognition, 27% worsened cognition, and 8.7% remained unchanged. Logistic multivariate regression analysis showed that years of education, UPDRSIII drug use, MoCA Preop, and MMSE Preop scores were independent factors affecting the cognitive improvement rate. A nomogram model was subsequently developed. The C-index of the nomogram was 0.98 (95%CI, 0.97–1.00), and the area under the ROC was 0.98 (95%CI 0.97–1.00). The calibration plot and DCA demonstrated the goodness-of-fit between nomogram predictions and actual observations. Conclusion: Our nomogram could effectively predict the possibility of achieving good cognitive improvement one year after STN-DBS in patients with PD. This model has value in judging the expected cognitive improvement of patients with PD undergoing STN-DBS. Full article
(This article belongs to the Special Issue Neuromodulation for Neurological Disorders)
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12 pages, 1144 KiB  
Article
Characterization of Macular Structural and Microvascular Changes in Thalamic Infarction Patients: A Swept-Source Optical Coherence Tomography–Angiography Study
by Chen Ye, William Robert Kwapong, Wendan Tao, Kun Lu, Ruosu Pan, Anmo Wang, Junfeng Liu, Ming Liu and Bo Wu
Brain Sci. 2022, 12(5), 518; https://doi.org/10.3390/brainsci12050518 - 20 Apr 2022
Cited by 14 | Viewed by 3001
Abstract
Background: The retina and brain share similar neuronal and microvascular features. We aimed to investigate the retinal thickness and microvasculature in patients with thalamic infarcts compared with control participants. Material and methods: Swept-source optical coherence tomography (SS-OCT) was used to image the macular [...] Read more.
Background: The retina and brain share similar neuronal and microvascular features. We aimed to investigate the retinal thickness and microvasculature in patients with thalamic infarcts compared with control participants. Material and methods: Swept-source optical coherence tomography (SS-OCT) was used to image the macular thickness (retinal nerve fiber layer, RNFL; ganglion cell-inner plexiform layer, GCIP), while OCT angiography was used to image the microvasculature (superficial vascular plexus, SVP; intermediate capillary plexus, ICP; deep capillary plexus, DCP). Inbuilt software was used to measure the macular thickness (µm) and microvascular density (%). Lesion volumes were quantitively assessed based on structural magnetic resonance images. Results: A total of 35 patients with unilateral thalamic infarction and 31 age–sex-matched controls were enrolled. Compared with control participants, thalamic infarction patients showed a significantly thinner thickness of RNFL (p < 0.01) and GCIP (p = 0.02), and a lower density of SVP (p = 0.001) and ICP (p = 0.022). In the group of patients, ipsilateral eyes showed significant reductions in SVP (p = 0.033), RNFL (p = 0.01) and GCIP (p = 0.043). When divided into three groups based on disease duration (<1 month, 1–6 months, and >6 months), no significant differences were found among these groups. After adjusting for confounders, SVP, ICP, DCP, RNFL, and GCIP were significantly correlated with lesion volume in patients. Conclusions: Thalamic infarction patients showed significant macular structure and microvasculature changes. Lesion size was significantly correlated with these alterations. These findings may be useful for further research into the clinical utility of retinal imaging in stroke patients, especially those with damage to the visual pathway. Full article
(This article belongs to the Special Issue Neuromodulation for Neurological Disorders)
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Review

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23 pages, 663 KiB  
Review
Repetitive Transcranial Magnetic Stimulation of the Primary Motor Cortex beyond Motor Rehabilitation: A Review of the Current Evidence
by Abdulhameed Tomeh, Abdul Hanif Khan Yusof Khan, Liyana Najwa Inche Mat, Hamidon Basri and Wan Aliaa Wan Sulaiman
Brain Sci. 2022, 12(6), 761; https://doi.org/10.3390/brainsci12060761 - 10 Jun 2022
Cited by 8 | Viewed by 8836
Abstract
Transcranial magnetic stimulation (TMS) has emerged as a novel technique to stimulate the human brain through the scalp. Over the years, identifying the optimal brain region and stimulation parameters has been a subject of debate in the literature on therapeutic uses of repetitive [...] Read more.
Transcranial magnetic stimulation (TMS) has emerged as a novel technique to stimulate the human brain through the scalp. Over the years, identifying the optimal brain region and stimulation parameters has been a subject of debate in the literature on therapeutic uses of repetitive TMS (rTMS). Nevertheless, the primary motor cortex (M1) has been a conventional target for rTMS to treat motor symptoms, such as hemiplegia and spasticity, as it controls the voluntary movement of the body. However, with an expanding knowledge base of the M1 cortical and subcortical connections, M1-rTMS has shown a therapeutic efficacy that goes beyond the conventional motor rehabilitation to involve pain, headache, fatigue, dysphagia, speech and voice impairments, sleep disorders, cognitive dysfunction, disorders of consciousness, anxiety, depression, and bladder dysfunction. In this review, we summarize the latest evidence on using M1-rTMS to treat non-motor symptoms of diverse etiologies and discuss the potential mechanistic rationale behind the management of each of these symptoms. Full article
(This article belongs to the Special Issue Neuromodulation for Neurological Disorders)
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Other

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27 pages, 5648 KiB  
Perspective
Human-in-the-Loop Optimization of Transcranial Electrical Stimulation at the Point of Care: A Computational Perspective
by Yashika Arora and Anirban Dutta
Brain Sci. 2022, 12(10), 1294; https://doi.org/10.3390/brainsci12101294 - 26 Sep 2022
Cited by 6 | Viewed by 2674
Abstract
Individual differences in the responsiveness of the brain to transcranial electrical stimulation (tES) are increasingly demonstrated by the large variability in the effects of tES. Anatomically detailed computational brain models have been developed to address this variability; however, static brain models are not [...] Read more.
Individual differences in the responsiveness of the brain to transcranial electrical stimulation (tES) are increasingly demonstrated by the large variability in the effects of tES. Anatomically detailed computational brain models have been developed to address this variability; however, static brain models are not “realistic” in accounting for the dynamic state of the brain. Therefore, human-in-the-loop optimization at the point of care is proposed in this perspective article based on systems analysis of the neurovascular effects of tES. First, modal analysis was conducted using a physiologically detailed neurovascular model that found stable modes in the 0 Hz to 0.05 Hz range for the pathway for vessel response through the smooth muscle cells, measured with functional near-infrared spectroscopy (fNIRS). During tES, the transient sensations can have arousal effects on the hemodynamics, so we present a healthy case series for black-box modeling of fNIRS–pupillometry of short-duration tDCS effects. The block exogeneity test rejected the claim that tDCS is not a one-step Granger cause of the fNIRS total hemoglobin changes (HbT) and pupil dilation changes (p < 0.05). Moreover, grey-box modeling using fNIRS of the tDCS effects in chronic stroke showed the HbT response to be significantly different (paired-samples t-test, p < 0.05) between the ipsilesional and contralesional hemispheres for primary motor cortex tDCS and cerebellar tDCS, which was subserved by the smooth muscle cells. Here, our opinion is that various physiological pathways subserving the effects of tES can lead to state–trait variability, which can be challenging for clinical translation. Therefore, we conducted a case study on human-in-the-loop optimization using our reduced-dimensions model and a stochastic, derivative-free covariance matrix adaptation evolution strategy. We conclude from our computational analysis that human-in-the-loop optimization of the effects of tES at the point of care merits investigation in future studies for reducing inter-subject and intra-subject variability in neuromodulation. Full article
(This article belongs to the Special Issue Neuromodulation for Neurological Disorders)
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