Brain ConnectivityVol. 13, No. 3 EditorialFree AccessBrain Connectivity: A Journal of Clinical Neurology, Neuroscience, & Neuroimaging Advancing the Field of NeurologyPaul EdisonPaul EdisonPaul Edison, Editor-in-Chief, Imperial College LondonSearch for more papers by this authorPublished Online:4 Apr 2023https://doi.org/10.1089/brain.2023.29047.editorialAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Brain Connectivity is a leading print journal covering clinical neurology, neuroscience, and neuroimaging. The journal has recently expanded the remit with the aim to reach out to a much wider audience in the field of neurology and neuroscience, and this gives an opportunity for the journal audience to have a comprehensive knowledge of topics covered in Brain Connectivity.Following the expansion of the remit of Brain Connectivity, we are now inviting articles of a translational nature in the field of Clinical Neurology, Neuroscience, & Neuroimaging by focusing on■ Alzheimer's disease and other neurodegenerative diseases■ Parkinson's disease and other movement disorders■ Stroke and multiple sclerosisWe invite you to submit articles focusing on the aforementioned theme. Any of the following themes will be of huge interest: ■ Clinical and translational research■ Review articles in the field of clinical neurology, neuroscience, and neuroimaging■ Novel positron emission tomography (PET) and magnetic resonance imaging (MRI) markers in neurodegenerative diseases and stroke■ Influence of genetic and epigenetic factors on neurodegenerative diseases■ Structural and functional connectivity in brain disorders■ Multimodal imaging in brain disorders in both human subjects and animal models■ Experimental techniques combining MRI (connectivity), electroencephalography, magnetoencephalography, PET, single photon emission computed tomography, and other new and evolving methodsFor more information about the journal, including scope and instructions for authors, please visit our website (https://mc.manuscriptcentral.com/brainconnectivity).Feel free to contact Editor-in-Chief Dr. Paul Edison on paul.edison@imperial.ac.uk if you have any questions about the eligibility of your manuscript.In this issue, you will find several high-quality articles by experts in their fields.Relating Cognition to Both Brain Structure and Function: A Systematic Review of Methods (https://doi.org/10.1089/brain.2022.0036)Many studies in cognitive neuroscience have combined structural and functional neuroimaging techniques to uncover the complex relationship between them. In this first systematic review of this kind, Marta Litwińczuk and Anna Woollams along with their colleagues review how information from structural and functional neuroimaging methods can be integrated to investigate the brain substrates of cognition. They conclude that many studies consider either structural or functional neural correlates of cognition, and of those that consider both, they have rarely been integrated. They identified four emergent approaches to the characterization of the relationship between brain structure, function, and cognition: comparative, predictive, fusion, and complementary. They discuss the insights provided by each approach about the relationship between brain structure and function, and how it impacts cognitive performance. In addition, they provide insights into how authors can select approaches to suit their research questions.Upper-Limb Amputation Disrupts the Interhemispheric Structural Rather Than Functional Connectivity (https://doi.org/10.1089/brain.2022.0020)Recent neuroimaging studies on upper-limb amputation have revealed the reorganization of bilateral sensorimotor cortex after sensory deprivation, underpinning the assumption of changes in the interhemispheric connections. In this study, using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), Kexu Zhang and Shanbao Tong along with their colleagues explore the alterations in the interhemispheric functional and structural connectivity after upper-limb amputation.Upper-limb amputees and controls were recruited for MRI scanning. DTI metrics of corpus callosum (CC) subregions and resting-state functional connectivity between the bilateral sensorimotor cortex were measured for each participant. Linear mixed models were carried out to investigate the relationship of interhemispheric connectivity with the amputation, amputation side, and residual limb pain.Compared with healthy controls (HCs), upper-limb amputees showed lower axial diffusivity (AD) in CC subregions II and III. Subgroup analyses showed that the dominant hand amputation induced significant microstructural changes in CC subregion III. In addition, only amputees with residual limb pain showed decreased fractional anisotropy and AD in CC, which was also correlated with the intensity of residual limb pain. No significant changes in interhemispheric functional connectivity were found after upper-limb amputation. This study demonstrated that the interhemispheric structural connectivity rather than functional connectivity degenerated after upper-limb amputation, and the degeneration of interhemispheric structural connectivity was shown to be relevant to the amputation side and the intensity of residual limb pain.Hippocampal Neuronal Integrity and Functional Connectivity Within the Default Mode Network in Mild Cognitive Impairment: A Multimodal Investigation (https://doi.org/10.1089/brain.2022.0050)In mild cognitive impairment (MCI) subjects, the relationship between early changes in functional connectivity and in vivo changes in key neurometabolites is not known. Two established correlates of MCI diagnosis are decreased in N-acetylaspartate (NAA) in the hippocampus, indicative of decreased neuronal integrity, and changes in the default mode network (DMN) functional network. If and how these measures inter-relate is yet to be established, and this understanding may provide insight into the processes underpinning observed cognitive decline. In this study, Marilena M. DeMayo and Fernando Calamante along with their colleagues evaluated the relationship between NAA levels in the left hippocampus and functional connectivity within the DMN in an aging cohort.In MCI participants and HCs, hippocampal NAA was determined using magnetic resonance spectroscopy, and DMN connectivity was quantified using resting-state functional MRI. The association between hippocampal NAA and the DMN functional connectivity was tested independently within the MCI and separately within the control group.In the DMN, they showed a significant inverse association between functional connectivity and hippocampal NAA in 20 specific brain connections for patients with MCI. This was despite no evidence of any associations in the HC group or group differences in either of these measures alone. This study suggests that decreased neuronal integrity in the hippocampus is associated with functional change within the DMN for those with MCI, in contrast to healthy older adults.A Novel Hidden Markov Approach to Studying Dynamic Functional Connectivity States in Human Neuroimaging (https://doi.org/10.1089/brain.2022.0031)Hidden Markov models are a popular choice to extract and examine recurring patterns of activity or functional connectivity in neuroimaging data, both in terms of spatial patterns and their temporal progression. Although many diverse hidden Markov models have been applied to neuroimaging data, most have defined states based on activity levels (intensity-based states) rather than patterns of functional connectivity between brain areas (connectivity-based states), which creates challenges when we want to understand connectivity dynamics: intensity-based states are unlikely to provide comprehensive information about dynamic connectivity patterns.Sana Hussain and Megan Peters along with their colleagues addressed this problem by introducing a new hidden Markov model that defines states based on full functional connectivity profiles among brain regions. They empirically explored the behavior of this new model in comparison with existing approaches based on intensity-based or summed functional connectivity states using the Human Connectome Project unrelated 100 fMRI “resting state” data set.Their “full functional connectivity” model discovered connectivity states with more distinguishable (i.e., unique and separable from each other) patterns than previous approaches, and recovered simulated connectivity-based states more faithfully than the other models tested. They conclude that their new model outperforms previous methods that miss information about the evolution of functional connectivity in the brain.Connectivity Between Salience and Default Mode Networks and Subcortical Nodes Distinguishes Between Two Classes of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (https://doi.org/10.1089/brain.2022.0049)Barnden, Leighton; Su, Jiasheng; Thapaliya, Kiran; Eaton-Fitch, Natalie; Marshall-Gradisnik, SonyaMyalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS) is a debilitating disease with unknown pathophysiology. fMRI studies in ME/CFS have reported disparate connectivities for the brain salience (SA) and default mode networks (DMN). In this study, Jiasheng Su and Leighton Barnden along with their colleagues acquired resting state and task fMRI with an advanced scanner for HCs and ME/CFS patients (a subgroup meeting International Consensus Criteria [ICC] and another subgroup meeting Fukuda criteria). They tested the hypothesis that ME/CFS connectivity differed from HC; and the ICC and Fukuda classes are distinguished by different connectivities with HC for different pairs of SA, DMN, or subcortical hubs.During resting state fMRI only two connections differed from HC, both for Fukuda ME/CFS and both with an SA hub. During task fMRI 10 ME/CFS connections differed from HC, 5 for ICC and 5 for Fukuda. None were common to both classes. Eight of the 10 different connections involved an SA hub, 6 of 10 were weaker in ME/CFS, whereas 4 were stronger. SA connections to the hippocampus and brainstem reticular activation system differed from and were stronger than HC. They conclude that different regulatory connections are consistent with the impaired cognitive performance and sleep–wake cycle of ME/CFS. Different neuropathology is involved in ICC and Fukuda classes.Finally, I would like to thank all the researchers and all the staff at Mary Ann Liebert, Inc., publishers, editors, and reviewers of Brain Connectivity who are dedicated to advancing research and improving our lives in every corner of the world.FiguresReferencesRelatedDetails Volume 13Issue 3Apr 2023 InformationCopyright 2023, Mary Ann Liebert, Inc., publishersTo cite this article:Paul Edison.Brain Connectivity: A Journal of Clinical Neurology, Neuroscience, & Neuroimaging Advancing the Field of Neurology.Brain Connectivity.Apr 2023.117-119.http://doi.org/10.1089/brain.2023.29047.editorialPublished in Volume: 13 Issue 3: April 4, 2023PDF download