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Brain Sciences
Special Issues
Imaging Human Brain Connectivity in Health and Disease
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Imaging Human Brain Connectivity in Health and Disease

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

Deadline for manuscript submissions: closed (15 June 2021) | Viewed by 19453

Special Issue Editor

Prof. Dr. Carlo Cosimo Quattrocchi

E-Mail Website
Guest Editor
Imaging Center, Università Campus Bio-Medico di Roma, Rome, Italy
Interests: Neuroradiology, Magnetic Resonance Imaging, Contrast-Enhanced Imaging, Gadolinium, Contrast Agents

Special Issue Information

Dear Colleagues, 

Imaging human brain connectivity and its changes under the challenge of physiological and disease-related processes is a fascinating topic in brain sciences. Since Dr. Olaf Sporns and Dr. Patric Hagmann first mentioned the term “connectomics” in 2005, our understanding of brain structure and function has grown in depth and complexity, thanks to technological advancements in MRI hardware and software as well as in informatics and image analysis tools.

There is a need of a comprehensive and updated state-of-the-art description of brain imaging techniques and approaches to map the structural and functional connectivity of the living human brain. Diffusion MRI, perfusion MRI, and BOLD MRI have improved in the last years through new techniques (e.g., multiband and multishell techniques), with a great impact on spatial, temporal, and angular resolutions.

So far, research has largely focused on understanding spatial connections and temporal coupling of different brain regions to infer neural networks in health and disease. Neurovascular coupling using MRI techniques and its role in the dynamic changes occurring in the brain in healthy and pathological conditions have been poorly explored. We need to gain more knowledge on intra-subject changes in brain connectivity during physiological processes and disease-related processes. Cutting-edge research in this field will allow orienting and monitoring treatment efficacy in patients with brain diseases.

We will accept methodologically rigorous and original research papers on the topics mentioned, as well as systematic reviews, meta-analyses, and case studies (the latter only acceptable if normative data are used for reference).

Prof. Dr. Carlo Cosimo Quattrocchi
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. 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

  • diffusion 
  • perfusion 
  • arterial spin labeling 
  • blood oxygenation level-dependent 
  • functional magnetic resonance imaging 
  • brain connectivity 
  • neurovascular coupling 
  • brain disease 
  • brain mapping 
  • network analysis 
  • graph analysis 
  • resting state 
  • bioinformatics

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Published Papers (5 papers)

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Research

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9 pages, 838 KiB  
Article
Brain Structural Connectivity Differences in Patients with Normal Cognition and Cognitive Impairment
by Nauris Zdanovskis, Ardis Platkājis, Andrejs Kostiks, Guntis Karelis and Oļesja Grigorjeva
Brain Sci. 2021, 11(7), 943; https://doi.org/10.3390/brainsci11070943 - 18 Jul 2021
Cited by 7 | Viewed by 3496
Abstract
Advances in magnetic resonance imaging, particularly diffusion imaging, have allowed researchers to analyze brain connectivity. Identification of structural connectivity differences between patients with normal cognition, cognitive impairment, and dementia could lead to new biomarker discoveries that could improve dementia diagnostics. In our study, [...] Read more.
Advances in magnetic resonance imaging, particularly diffusion imaging, have allowed researchers to analyze brain connectivity. Identification of structural connectivity differences between patients with normal cognition, cognitive impairment, and dementia could lead to new biomarker discoveries that could improve dementia diagnostics. In our study, we analyzed 22 patients (11 control group patients, 11 dementia group patients) that underwent 3T MRI diffusion tensor imaging (DTI) scans and the Montreal Cognitive Assessment (MoCA) test. We reconstructed DTI images and used the Desikan–Killiany–Tourville cortical parcellation atlas. The connectivity matrix was calculated, and graph theoretical analysis was conducted using DSI Studio. We found statistically significant differences between groups in the graph density, network characteristic path length, small-worldness, global efficiency, and rich club organization. We did not find statistically significant differences between groups in the average clustering coefficient and the assortativity coefficient. These statistically significant graph theory measures could potentially be used as quantitative biomarkers in cognitive impairment and dementia diagnostics. Full article
(This article belongs to the Special Issue Imaging Human Brain Connectivity in Health and Disease)
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9 pages, 1682 KiB  
Article
Assessment of a Reliable Fractional Anisotropy Cutoff in Tractography of the Corticospinal Tract for Neurosurgical Patients
by Tim Wende, Johannes Kasper, Florian Wilhelmy, Eric Dietel, Gordian Hamerla, Cordula Scherlach, Jürgen Meixensberger and Michael Karl Fehrenbach
Brain Sci. 2021, 11(5), 650; https://doi.org/10.3390/brainsci11050650 - 16 May 2021
Cited by 9 | Viewed by 2784
Abstract
Background: Tractography has become a standard technique for planning neurosurgical operations in the past decades. This technique relies on diffusion magnetic resonance imaging. The cutoff value for the fractional anisotropy (FA) has an important role in avoiding false-positive and false-negative results. However, there [...] Read more.
Background: Tractography has become a standard technique for planning neurosurgical operations in the past decades. This technique relies on diffusion magnetic resonance imaging. The cutoff value for the fractional anisotropy (FA) has an important role in avoiding false-positive and false-negative results. However, there is a wide variation in FA cutoff values. Methods: We analyzed a prospective cohort of 14 patients (six males and eight females, 50.1 ± 4.0 years old) with intracerebral tumors that were mostly gliomas. Magnetic resonance imaging (MRI) was obtained within 7 days before and within 7 days after surgery with T1 and diffusion tensor image (DTI) sequences. We, then, reconstructed the corticospinal tract (CST) in all patients and extracted the FA values within the resulting volume. Results: The mean FA in all CSTs was 0.4406 ± 0.0003 with the fifth percentile at 0.1454. FA values in right-hemispheric CSTs were lower (p < 0.0001). Postoperatively, the FA values were more condensed around their mean (p < 0.0001). The analysis of infiltrated or compressed CSTs revealed a lower fifth percentile (0.1407 ± 0.0109 versus 0.1763 ± 0.0040, p = 0.0036). Conclusion: An FA cutoff value of 0.15 appears to be reasonable for neurosurgical patients and may shorten the tractography workflow. However, infiltrated fiber bundles must trigger vigilance and may require lower cutoffs. Full article
(This article belongs to the Special Issue Imaging Human Brain Connectivity in Health and Disease)
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17 pages, 7219 KiB  
Article
Spatiotemporal Characteristics of Neural Dynamics in Theta Oscillations Related to the Inhibition of Habitual Behavior
by Jae-Hwan Kang, Junsuk Kim, Yang Seok Cho and Sung-Phil Kim
Brain Sci. 2021, 11(3), 368; https://doi.org/10.3390/brainsci11030368 - 13 Mar 2021
Viewed by 2185
Abstract
The human brain carries out cognitive control for the inhibition of habitual behaviors by suppressing some familiar but inappropriate behaviors instead of engaging specific goal-directed behavior flexibly in a given situation. To examine the characteristics of neural dynamics related to such inhibition of [...] Read more.
The human brain carries out cognitive control for the inhibition of habitual behaviors by suppressing some familiar but inappropriate behaviors instead of engaging specific goal-directed behavior flexibly in a given situation. To examine the characteristics of neural dynamics related to such inhibition of habitual behaviors, we used a modified rock–paper–scissors (RPS) task that consisted of a basic, a lose-, and a win-conditioned game. Spectral and phase synchrony analyses were conducted to examine the acquired electroencephalogram signals across the entire brain during all RPS tasks. Temporal variations in frontal theta power activities were directly in line with the stream of RPS procedures in accordance with the task conditions. The lose-conditioned RPS task gave rise to increases in the local frontal power and global phase-synchronized pairs of theta oscillations. The activation of the global phase-synchronized network preceded the activation of frontal theta power. These results demonstrate that the frontal regions play a pivotal role in the inhibition of habitual behaviors—stereotyped and ingrained stimulus–response mappings that have been established over time. This study suggests that frontal theta oscillations may be engaged during the cognitive inhibition of habitual behaviors and that these oscillations characterize the degree of cognitive load required to inhibit habitual behaviors. Full article
(This article belongs to the Special Issue Imaging Human Brain Connectivity in Health and Disease)
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10 pages, 1278 KiB  
Article
Network Analysis of Induced Neural Plasticity Post-Acceptance and Commitment Therapy for Chronic Pain
by Sarah K. Meier, Kimberly L. Ray, Noah C. Waller, Barry C. Gendron, Semra A. Aytur and Donald A. Robin
Brain Sci. 2021, 11(1), 10; https://doi.org/10.3390/brainsci11010010 - 23 Dec 2020
Cited by 13 | Viewed by 5306
Abstract
Chronic musculoskeletal pain is a costly and prevalent condition that affects the lives of over 50 million individuals in the United States. Chronic pain leads to functional brain changes in those suffering from the condition. Not only does the primary pain network transform [...] Read more.
Chronic musculoskeletal pain is a costly and prevalent condition that affects the lives of over 50 million individuals in the United States. Chronic pain leads to functional brain changes in those suffering from the condition. Not only does the primary pain network transform as the condition changes from acute to persistent pain, a state of hyper-connectivity also exists between the default mode, frontoparietal, and salience networks. Graph theory analysis has recently been used to investigate treatment-driven brain network changes. For example, current research suggests that Acceptance and Commitment Therapy (ACT) may reduce the chronic pain associated hyper-connectivity between the default mode, frontoparietal, and salience networks, as well as within the salience network. This study extended previous work by examining the associations between the three networks above and a meta-analytically derived pain network. Results indicate decreased connectivity within the pain network (including left putamen, right insula, left insula, and right thalamus) in addition to triple network connectivity changes after the four-week Acceptance and Commitment Therapy intervention. Full article
(This article belongs to the Special Issue Imaging Human Brain Connectivity in Health and Disease)
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Review

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22 pages, 4689 KiB  
Review
Investigating Brain Microstructural Alterations in Type 1 and Type 2 Diabetes Using Diffusion Tensor Imaging: A Systematic Review
by Abdulmajeed Alotaibi, Christopher Tench, Rebecca Stevenson, Ghadah Felmban, Amjad Altokhis, Ali Aldhebaib, Rob A. Dineen and Cris S. Constantinescu
Brain Sci. 2021, 11(2), 140; https://doi.org/10.3390/brainsci11020140 - 22 Jan 2021
Cited by 22 | Viewed by 4746
Abstract
Type 1 and type 2 diabetes mellitus have an impact on the microstructural environment and cognitive functions of the brain due to its microvascular/macrovascular complications. Conventional Magnetic Resonance Imaging (MRI) techniques can allow detection of brain volume reduction in people with diabetes. However, [...] Read more.
Type 1 and type 2 diabetes mellitus have an impact on the microstructural environment and cognitive functions of the brain due to its microvascular/macrovascular complications. Conventional Magnetic Resonance Imaging (MRI) techniques can allow detection of brain volume reduction in people with diabetes. However, conventional MRI is insufficiently sensitive to quantify microstructural changes. Diffusion Tensor Imaging (DTI) has been used as a sensitive MRI-based technique for quantifying and assessing brain microstructural abnormalities in patients with diabetes. This systematic review aims to summarise the original research literature using DTI to quantify microstructural alterations in diabetes and the relation of such changes to cognitive status and metabolic profile. A total of thirty-eight published studies that demonstrate the impact of diabetes mellitus on brain microstructure using DTI are included, and these demonstrate that both type 1 diabetes mellitus and type 2 diabetes mellitus may affect cognitive abilities due to the alterations in brain microstructures. Full article
(This article belongs to the Special Issue Imaging Human Brain Connectivity in Health and Disease)
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