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• W3011206194 abstract "Brain ConnectivityVol. 10, No. 2 EditorialFree AccessBrain Connectivity: Neuronal Integrity and Its Relationship with Pathological SubstratesPaul EdisonPaul EdisonPaul Edison, Imperial College London Search for more papers by this authorPublished Online:18 Mar 2020https://doi.org/10.1089/brain.2020.29006.pedAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail The role of Brain Connectivity in evaluating neuronal integrity and its relationship with pathological substrates is going to be crucial and influential in the field of neuroscience and medicine over the coming years. As impairment of structural and functional connectivity, as either a primary or a secondary event, is implicated in neuronal damage in most brain disorders, Brain Connectivity plays a major role in research into normal brain function and a range of neurological disorders. As the field of neuroscience is constantly evolving, with multimodal imaging now considered as the preferable method of evaluating different diseases and interventions, we have now expanded the breadth of research published in Brain Connectivity to ensure that we are able to include articles of a translational nature in the field of neuroscience.With the view of expanding the scope of our journal, I would like to invite leaders in the field such as you to submit original articles and reviews describing: ▪ Advances in neuroimaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) in Alzheimer's disease, Parkinson's disease, and other neurodegenerative diseases;▪ Clinical translation of novel PET and MRI biomarkers in neurodegenerative diseases and stroke;▪ How different pathological substrates influence structural and functional connectivity in brain disorders;▪ Multimodal imaging in brain disorders in both human and animal models; and▪ Experimental techniques combining MRI (connectivity), electroencephalography, magnetoencephalography, PET, single photon emission computed tomography, and other new and evolving methods.For more information about the Journal, including scope and instructions for authors, please visit our website: https://mc.manuscriptcentral.com/brainconnectivityIn this current issue, you will find several high-quality articles by experts in their fields:A Checklist to Reduce Response Variability in Studies Using Transcranial Magnetic Stimulation for Assessment of Corticospinal Excitability: A Systematic Review of the Literature. In this review, Michael Pellegrini and Shapour Jaberzadeh along with their colleagues highlight the inter-individual variability and intra-individual variability in transcranial magnetic stimulation (TMS), raising questions about the validity of TMS to assess changes in corticospinal excitability in a predictable and reliable manner. They highlight that several participant-specific factors contribute to this observed response variability, with a current lack of consensus on the degree that each factor contributes, which highlights the need for consistency and structure in reporting study designs and methodologies. This systematic review was aimed to develop a checklist of methodological measures taken by previously published research to increase the homogeneity of participant selection criteria, preparation of participants prior to experimental testing, participant scheduling, and the instructions given to participants throughout experimental testing to minimize their effect on response variability. Eighty-four studies were included in this review. They summarize the methodological measures into a user-friendly checklist with considerations, suggestions, and rationale/justification for their inclusion, which provide the framework for further insights into ways to reduce response variability in TMS research.Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning. In this article, Wei Zhang and Tianming Liu along with their colleagues highlight that hierarchical organization of brain function has been an established concept in the neuroscience field for a long time. However, it has been rarely demonstrated how such hierarchical macroscale functional networks are actually organized in the human brain. In this study, to answer this question, they propose a novel methodology to provide evidence on hierarchical organization of functional brain networks. This paper introduces hybrid spatiotemporal deep learning by jointly using deep belief networks and deep LASSO to reveal the temporal hierarchical features and spatial hierarchical maps of brain networks based on the Human Connectome Project (HCP) 900 functional MRI (fMRI) data sets. They demonstrate that both spatial and temporal aspects of dozens of functional networks exhibit multiscale properties that can be well characterized and interpreted based on existing computational tools and neuroscience knowledge, giving an insightful opportunity to reveal the potential hierarchical organization of time series and functional brain networks using task-based fMRI signals of the human brain.Time-Delay Latency of Resting-State BOLD Signal Related to the Level of Consciousness in Patients with Severe Consciousness Impairment. In this article, Jorge Rudas and Francisco Gómez along with their colleagues describe how recent evidence on resting-state fMRI suggests that healthy human brains have a temporal organization represented in a widely complex time-delay structure. This structure seems to underlie brain communication flow, integration/propagation of brain activity, as well as information processing. Therefore, it probably links to the emergence of highly coordinated complex brain phenomena, such as consciousness. In this work, they hypothesized that due to a disruption in high-order functions and alterations of the brain communication flow, patients with disorders of consciousness (DOC) might exhibit changes in their time-delay structure of spontaneous brain activity. They explored this hypothesis by comparing the time-delay projections from fMRI resting-state data acquired from patients with DOC and healthy subjects (HC). Results suggest that time-delay structure modifies for patients with DOC conditions when compared to HC. Specifically, the average value and the directionality of latency inside the midcingulate cortex (mCC) shift with the level of consciousness. In particular, positive values of latency inside the mCC relate to preserved states of consciousness, while negative values change proportionally with the level of consciousness in patients with DOC, suggesting that the mCC may play a critical role as an integrator of brain activity in HC subjects, but this role vanishes in an altered state of consciousness.Graph Theoretic Analysis of Brain Connectomics in Multiple Sclerosis: Reliability and Relationship to Cognition. In this article, Thomas Welton and Robert Dineen along with their colleagues describe how research suggests that disruption of brain networks might explain cognitive deficits in multiple sclerosis (MS). The reliability and effectiveness of graph-theoretic network metrics as measures of cognitive performance were tested in people with MS and controls. Specifically, relationships to cognitive performance and one-month reliability (using the intra-class correlation coefficient [ICC]) of network metrics were measured using both resting-state functional and diffusion MRI data. Cognitive impairment was directly related to measures of brain network segregation and inversely related to network integration. Reliability of the measures over one month was mostly rated as good (ICC >0.6) for both controls and MS patients in both functional and diffusion data but was highly dependent on the chosen parcellation and graph density. This highlights that disrupted network organization predicts cognitive impairment in MS, and its measurement is reliable over a one-month period. This study support the hypothesis of network disruption as a major determinant of cognitive deficits in MS and the future possibility of the application of derived metrics as surrogate outcomes in trials of therapies for cognitive impairment.Finally, I would like to wish to thank all the staff at Mary Ann Liebert, Inc., publishers, editors, and reviewers of Brain Connectivity for their hard work. I hope that many of you will consider submitting your research papers to Brain Connectivity.FiguresReferencesRelatedDetails Volume 10Issue 2Mar 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Paul Edison.Brain Connectivity: Neuronal Integrity and Its Relationship with Pathological Substrates.Brain Connectivity.Mar 2020.51-52.http://doi.org/10.1089/brain.2020.29006.pedPublished in Volume: 10 Issue 2: March 18, 2020PDF download" @default.
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