Publications by authors named "Boris C Bernhardt"

100 Publications

Anti-seizure medication correlated changes of cortical morphology in childhood epilepsy with centrotemporal spikes.

Epilepsy Res 2021 Mar 23;173:106621. Epub 2021 Mar 23.

Department of Medical Imaging, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, 210002, China; Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China; State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210093, China; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 Thirteenth Street, Suite 2301, Charlestown, MA, 02129, USA. Electronic address:

To investigate the morphological changes of cerebral cortex correlating with anti-seizure medication in Childhood Epilepsy with Centrotemporal Spikes (CECTS), and their relationships with seizure control. This study included a total of 188 children, including 62 patients with CECTS taking anti-seizure drugs, 56 patients with drug-naive, and 70 healthy controls. A portion of cases were also followed-up for longitudinal analysis. Cortical morphological parameters were quantitatively measured by applying surface-based morphometry analysis to high-resolution three-dimension T1 weighted images. Among the three groups, the morphological indices were compared to quantify any cortical changes affected by seizures and medication. The relationships among anti-seizure medication, seizure controls and cortical morphometry were investigated using causal mediator analysis. The Rolandic cortex of the drug-naive patients showed abnormal cortical thickness by comparing with that of healthy controls, and thinning by comparing with that of patients with medication. The cortical thickness in the Rolandic regions was negatively correlated with duration of medication and duration of seizure-free. Longitudinal analysis further demonstrated that the thickness of Rolandic cortex thinned in post-medication state relative to the pre-medication state. Mediation analysis revealed that morphological alteration of the Rolandic cortex might act as a mediator in the path of anti-seizure medication on seizure control. Our findings highlighted that anti-seizure medication was associated with regression of abnormal increment of cortical thickness in the Rolandic regions in CECTS. The neuroanatomical alteration might be a mediating factor in the process of seizure control by anti-seizure medication.
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http://dx.doi.org/10.1016/j.eplepsyres.2021.106621DOI Listing
March 2021

Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism.

Nat Commun 2021 04 13;12(1):2225. Epub 2021 Apr 13.

McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.

The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.
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http://dx.doi.org/10.1038/s41467-021-21732-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044226PMC
April 2021

An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization.

Elife 2021 Mar 31;10. Epub 2021 Mar 31.

McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

Adolescence is a critical time for the continued maturation of brain networks. Here, we assessed structural connectome development in a large longitudinal sample ranging from childhood to young adulthood. By projecting high-dimensional connectomes into compact manifold spaces, we identified a marked expansion of structural connectomes, with strongest effects in transmodal regions during adolescence. Findings reflected increased within-module connectivity together with increased segregation, indicating increasing differentiation of higher-order association networks from the rest of the brain. Projection of subcortico-cortical connectivity patterns into these manifolds showed parallel alterations in pathways centered on the caudate and thalamus. Connectome findings were contextualized via spatial transcriptome association analysis, highlighting genes enriched in cortex, thalamus, and striatum. Statistical learning of cortical and subcortical manifold features at baseline and their maturational change predicted measures of intelligence at follow-up. Our findings demonstrate that connectome manifold learning can bridge the conceptual and empirical gaps between macroscale network reconfigurations, microscale processes, and cognitive outcomes in adolescent development.
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http://dx.doi.org/10.7554/eLife.64694DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087442PMC
March 2021

Atypical neural topographies underpin dysfunctional pattern separation in temporal lobe epilepsy.

Brain 2021 Mar 17. Epub 2021 Mar 17.

Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

Episodic memory is the ability to accurately remember events from our past. The process of pattern separation is hypothesized to underpin this ability and is defined as the ability to orthogonalize memory traces, to maximize the features that make them unique. Contemporary cognitive neuroscience suggests that pattern separation entails complex interactions between the hippocampus and the neocortex, where specific hippocampal subregions shape neural reinstatement in the neocortex. To test this hypothesis, the current work studied both healthy controls and patients with temporal lobe epilepsy (TLE) who present with hippocampal structural anomalies. In all participants, we measured neural activity using functional magnetic resonance imaging (fMRI) while they retrieved memorized items compared to lure items which share features with the target. Behaviorally, TLE patients were less able to exclude lures than controls, and showed a reduction in pattern separation. To assess the hypothesized relationship between neural patterns in the hippocampus and the neocortex, we identified topographic gradients of intrinsic connectivity along neocortical and hippocampal subfield surfaces and identified the topographic profile of the neural activity accompanying pattern separation. In healthy controls, pattern separation followed a graded pattern of neural activity, both along the hippocampal long axis (and peaked in anterior segments that are more heavily engaged in transmodal processing) and along the neocortical hierarchy running from unimodal to transmodal regions (peaking in transmodal default mode regions). In TLE patients, however, this concordance between task-based functional activations and topographic gradients was markedly reduced. Furthermore, person specific measures of concordance between task-related activity and connectivity gradients in patients and controls related to inter-individual differences in behavioral measures of pattern separation and episodic memory, highlighting the functional relevance of the observed topographic motifs. Our work is consistent with an emerging understanding that successful discrimination between memories with similar features entails a shift in the locus of neural activity away from sensory systems, a pattern that is mirrored along the hippocampal long axis and with respect to neocortical hierarchies. More broadly, our study establishes topographic profiling using intrinsic connectivity gradients captures the functional underpinnings of episodic memory processes in manner that is sensitive to their reorganization in pathology.
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http://dx.doi.org/10.1093/brain/awab121DOI Listing
March 2021

Altered communication dynamics reflect cognitive deficits in temporal lobe epilepsy.

Epilepsia 2021 Apr 11;62(4):1022-1033. Epub 2021 Mar 11.

Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.

Objective: Although temporal lobe epilepsy (TLE) is recognized as a system-level disorder, little work has investigated pathoconnectomics from a dynamic perspective. By leveraging computational simulations that quantify patterns of information flow across the connectome, we tested the hypothesis that network communication is abnormal in this condition, studied the interplay between hippocampal- and network-level disease effects, and assessed associations with cognition.

Methods: We simulated signal spreading via a linear threshold model that temporally evolves on a structural graph derived from diffusion-weighted magnetic resonance imaging (MRI), comparing a homogeneous group of 31 patients with histologically proven hippocampal sclerosis to 31 age- and sex-matched healthy controls. We evaluated the modulatory effects of structural alterations of the neocortex and hippocampus on network dynamics. Furthermore, multivariate statistics addressed the relationship with cognitive parameters.

Results: We observed a slowing of in- and out-spreading times across multiple areas bilaterally, indexing delayed information flow, with the strongest effects in ipsilateral frontotemporal regions, thalamus, and hippocampus. Effects were markedly reduced when controlling for hippocampal volume but not cortical thickness, underscoring the central role of the hippocampus in whole-brain disease expression. Multivariate analysis associated slower spreading time in frontoparietal, limbic, default mode, and subcortical networks with impairment across tasks tapping into sensorimotor, executive, memory, and verbal abilities.

Significance: Moving beyond descriptions of static topology toward the formulation of brain dynamics, our work provides novel insight into structurally mediated network dysfunction and demonstrates that altered whole-brain communication dynamics contribute to common cognitive difficulties in TLE.
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http://dx.doi.org/10.1111/epi.16864DOI Listing
April 2021

Cortico-striato-thalamo-cerebellar networks of structural covariance underlying different epilepsy syndromes associated with generalized tonic-clonic seizures.

Hum Brain Mapp 2021 Mar 29;42(4):1102-1115. Epub 2020 Dec 29.

Department of Medical Imaging, Jinling Hospital, Medical school of Nanjing University, Nanjing, China.

Generalized tonic-clonic seizures (GTCS) are the severest and most remarkable clinical expressions of human epilepsy. Cortical, subcortical, and cerebellar structures, organized with different network patterns, underlying the pathophysiological substrates of genetic associated epilepsy with GTCS (GE-GTCS) and focal epilepsy associated with focal to bilateral tonic-clonic seizure (FE-FBTS). Structural covariance analysis can delineate the features of epilepsy network related with long-term effects from seizure. Morphometric MRI data of 111 patients with GE-GTCS, 111 patients with FE-FBTS and 111 healthy controls were studied. Cortico-striato-thalao-cerebellar networks of structural covariance within the gray matter were constructed using a Winner-take-all strategy with five cortical parcellations. Comparisons of structural covariance networks were conducted using permutation tests, and module effects of disease duration on networks were conducted using GLM model. Both patient groups showed increased connectivity of structural covariance relative to controls, mainly within the striatum and thalamus, and mostly correlated with the frontal, motor, and somatosensory cortices. Connectivity changes increased as a function of epilepsy durations. FE-FBTS showed more intensive and extensive gray matter changes with volumetric loss and connectivity increment than GE-GTCS. Our findings implicated cortico-striato-thalamo-cerebellar network changes at a large temporal scale in GTCS, with FE-FBTS showing more severe network disruption. The study contributed novel imaging evidence for understanding the different epilepsy syndromes associated with generalized seizures.
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http://dx.doi.org/10.1002/hbm.25279DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7856655PMC
March 2021

Topographic gradients of intrinsic dynamics across neocortex.

Elife 2020 12 17;9. Epub 2020 Dec 17.

McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.

The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and macroscale connectome architecture. Here we comprehensively characterize the rich temporal patterns of neural activity throughout the human brain. Applying massive temporal feature extraction to regional haemodynamic activity, we systematically estimate over 6000 statistical properties of individual brain regions' time-series across the neocortex. We identify two robust spatial gradients of intrinsic dynamics, one spanning a ventromedial-dorsolateral axis and dominated by measures of signal autocorrelation, and the other spanning a unimodal-transmodal axis and dominated by measures of dynamic range. These gradients reflect spatial patterns of gene expression, intracortical myelin and cortical thickness, as well as structural and functional network embedding. Importantly, these gradients are correlated with patterns of meta-analytic functional activation, differentiating cognitive affective processing and sensory higher-order cognitive processing. Altogether, these findings demonstrate a link between microscale and macroscale architecture, intrinsic dynamics, and cognition.
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http://dx.doi.org/10.7554/eLife.62116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771969PMC
December 2020

The psychological correlates of distinct neural states occurring during wakeful rest.

Sci Rep 2020 12 3;10(1):21121. Epub 2020 Dec 3.

Department of Psychology, York Neuroimaging Centre, University of York, York, YO10 5DD, UK.

When unoccupied by an explicit external task, humans engage in a wide range of different types of self-generated thinking. These are often unrelated to the immediate environment and have unique psychological features. Although contemporary perspectives on ongoing thought recognise the heterogeneity of these self-generated states, we lack both a clear understanding of how to classify the specific states, and how they can be mapped empirically. In the current study, we capitalise on advances in machine learning that allow continuous neural data to be divided into a set of distinct temporally re-occurring patterns, or states. We applied this technique to a large set of resting state data in which we also acquired retrospective descriptions of the participants' experiences during the scan. We found that two of the identified states were predictive of patterns of thinking at rest. One state highlighted a pattern of neural activity commonly seen during demanding tasks, and the time individuals spent in this state was associated with descriptions of experience focused on problem solving in the future. A second state was associated with patterns of activity that are commonly seen under less demanding conditions, and the time spent in it was linked to reports of intrusive thoughts about the past. Finally, we found that these two neural states tended to fall at either end of a neural hierarchy that is thought to reflect the brain's response to cognitive demands. Together, these results demonstrate that approaches which take advantage of time-varying changes in neural function can play an important role in understanding the repertoire of self-generated states. Moreover, they establish that important features of self-generated ongoing experience are related to variation along a similar vein to those seen when the brain responds to cognitive task demands.
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http://dx.doi.org/10.1038/s41598-020-77336-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712889PMC
December 2020

A multi-scale cortical wiring space links cellular architecture and functional dynamics in the human brain.

PLoS Biol 2020 11 30;18(11):e3000979. Epub 2020 Nov 30.

Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.

The vast net of fibres within and underneath the cortex is optimised to support the convergence of different levels of brain organisation. Here, we propose a novel coordinate system of the human cortex based on an advanced model of its connectivity. Our approach is inspired by seminal, but so far largely neglected models of cortico-cortical wiring established by postmortem anatomical studies and capitalises on cutting-edge in vivo neuroimaging and machine learning. The new model expands the currently prevailing diffusion magnetic resonance imaging (MRI) tractography approach by incorporation of additional features of cortical microstructure and cortico-cortical proximity. Studying several datasets and different parcellation schemes, we could show that our coordinate system robustly recapitulates established sensory-limbic and anterior-posterior dimensions of brain organisation. A series of validation experiments showed that the new wiring space reflects cortical microcircuit features (including pyramidal neuron depth and glial expression) and allowed for competitive simulations of functional connectivity and dynamics based on resting-state functional magnetic resonance imaging (rs-fMRI) and human intracranial electroencephalography (EEG) coherence. Our results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. Our evaluations demonstrate the cortical wiring space bridges across scales of neural organisation and can be easily translated to single individuals.
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http://dx.doi.org/10.1371/journal.pbio.3000979DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728398PMC
November 2020

Connectome biomarkers of drug-resistant epilepsy.

Epilepsia 2021 01 25;62(1):6-24. Epub 2020 Nov 25.

Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.

Drug-resistant epilepsy (DRE) considerably affects patient health, cognition, and well-being, and disproportionally contributes to the overall burden of epilepsy. The most common DRE syndromes are temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal epilepsy related to cortical malformations. Both syndromes have been traditionally considered as "focal," and most patients benefit from brain surgery for long-term seizure control. However, increasing evidence indicates that many DRE patients also present with widespread structural and functional network disruptions. These anomalies have been suggested to relate to cognitive impairment and prognosis, highlighting their importance for patient management. The advent of multimodal neuroimaging and formal methods to quantify complex systems has offered unprecedented ability to profile structural and functional brain networks in DRE patients. Here, we performed a systematic review on existing DRE network biomarker candidates and their contribution to three key application areas: (1) modeling of cognitive impairments, (2) localization of the surgical target, and (3) prediction of clinical and cognitive outcomes after surgery. Although network biomarkers hold promise for a range of clinical applications, translation of neuroimaging biomarkers to the patient's bedside has been challenged by a lack of clinical and prospective studies. We therefore close by highlighting conceptual and methodological strategies to improve the evaluation and accessibility of network biomarkers, and ultimately guide clinically actionable decisions.
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http://dx.doi.org/10.1111/epi.16753DOI Listing
January 2021

Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study.

Sci Adv 2020 Nov 18;6(47). Epub 2020 Nov 18.

Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia.

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.
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http://dx.doi.org/10.1126/sciadv.abc6457DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673818PMC
November 2020

Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation.

Neuroimage 2021 02 11;226:117547. Epub 2020 Nov 11.

PERFORM Centre, Concordia University, Montreal, Canada; Center for Studies in Behavioral Neurobiology, Department of Health, Kinesiology and Applied Physiology, Concordia University, Montreal, Canada; Institut Universitaire de Gériatrie de Montréal and CRIUGM, CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montreal, Canada. Electronic address:

Sleep deprivation leads to significant impairments in cognitive performance and changes to the interactions between large scale cortical networks, yet the hierarchical organization of cortical activity across states is still being explored. We used functional magnetic resonance imaging to assess activations and connectivity during cognitive tasks in 20 healthy young adults, during three states: (i) following a normal night of sleep, (ii) following 24hr of total sleep deprivation, and (iii) after a morning recovery nap. Situating cortical activity during cognitive tasks along hierarchical organizing gradients based upon similarity of functional connectivity patterns, we found that regional variations in task-activations were captured by an axis differentiating areas involved in executive control from default mode regions and paralimbic cortex. After global signal regression, the range of functional differentiation along this axis at baseline was significantly related to decline in working memory performance (2-back task) following sleep deprivation, as well as the extent of recovery in performance following a nap. The relative positions of cortical regions within gradients did not significantly change across states, except for a lesser differentiation of the visual system and increased coupling of the posterior cingulate cortex with executive control areas after sleep deprivation. This was despite a widespread increase in the magnitude of functional connectivity across the cortex following sleep deprivation. Cortical gradients of functional differentiation thus appear relatively insensitive to state-dependent changes following sleep deprivation and recovery, suggesting that there are no large-scale changes in cortical functional organization across vigilance states. Certain features of particular gradient axes may be informative for the extent of decline in performance on more complex tasks following sleep deprivation, and could be beneficial over traditional voxel- or parcel-based approaches in identifying realtionships between state-dependent brain activity and behavior.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117547DOI Listing
February 2021

Convergence of cortical types and functional motifs in the human mesiotemporal lobe.

Elife 2020 11 4;9. Epub 2020 Nov 4.

Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

The mesiotemporal lobe (MTL) is implicated in many cognitive processes, is compromised in numerous brain disorders, and exhibits a gradual cytoarchitectural transition from six-layered parahippocampal isocortex to three-layered hippocampal allocortex. Leveraging an ultra-high-resolution histological reconstruction of a human brain, our study showed that the dominant axis of MTL cytoarchitectural differentiation follows the iso-to-allocortical transition and depth-specific variations in neuronal density. Projecting the histology-derived MTL model to in-vivo functional MRI, we furthermore determined how its cytoarchitecture underpins its intrinsic effective connectivity and association to large-scale networks. Here, the cytoarchitectural gradient was found to underpin intrinsic effective connectivity of the MTL, but patterns differed along the anterior-posterior axis. Moreover, while the iso-to-allocortical gradient parametrically represented the multiple-demand relative to task-negative networks, anterior-posterior gradients represented transmodal versus unimodal networks. Our findings establish that the combination of micro- and macrostructural features allow the MTL to represent dominant motifs of whole-brain functional organisation.
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http://dx.doi.org/10.7554/eLife.60673DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671688PMC
November 2020

Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function.

Neuroimage 2021 01 7;224:117429. Epub 2020 Oct 7.

Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. Electronic address:

Human cognition is dynamic, alternating over time between externally-focused states and more abstract, often self-generated, patterns of thought. Although cognitive neuroscience has documented how networks anchor particular modes of brain function, mechanisms that describe transitions between distinct functional states remain poorly understood. Here, we examined how time-varying changes in brain function emerge within the constraints imposed by macroscale structural network organization. Studying a large cohort of healthy adults (n = 326), we capitalized on manifold learning techniques that identify low dimensional representations of structural connectome organization and we decomposed neurophysiological activity into distinct functional states and their transition patterns using Hidden Markov Models. Structural connectome organization predicted dynamic transitions anchored in sensorimotor systems and those between sensorimotor and transmodal states. Connectome topology analyses revealed that transitions involving sensorimotor states traversed short and intermediary distances and adhered strongly to communication mechanisms of network diffusion. Conversely, transitions between transmodal states involved spatially distributed hubs and increasingly engaged long-range routing. These findings establish that the structure of the cortex is optimized to allow neural states the freedom to vary between distinct modes of processing, and so provides a key insight into the neural mechanisms that give rise to the flexibility of human cognition.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117429DOI Listing
January 2021

Shaping brain structure: Genetic and phylogenetic axes of macroscale organization of cortical thickness.

Sci Adv 2020 Sep 25;6(39). Epub 2020 Sep 25.

Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.

The topology of the cerebral cortex has been proposed to provide an important source of constraint for the organization of cognition. In a sample of twins ( = 1113), we determined structural covariance of thickness to be organized along both a posterior-to-anterior and an inferior-to-superior axis. Both organizational axes were present when investigating the genetic correlation of cortical thickness, suggesting a strong genetic component in humans, and had a comparable organization in macaques, demonstrating they are phylogenetically conserved in primates. In both species, the inferior-superior dimension of cortical organization aligned with the predictions of dual-origin theory, and in humans, we found that the posterior-to-anterior axis related to a functional topography describing a continuum of functions from basic processes involved in perception and action to more abstract features of human cognition. Together, our study provides important insights into how functional and evolutionary patterns converge at the level of macroscale cortical structural organization.
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http://dx.doi.org/10.1126/sciadv.abb3417DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518868PMC
September 2020

Latent Clinical-Anatomical Dimensions of Schizophrenia.

Schizophr Bull 2020 12;46(6):1426-1438

McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada.

Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.
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http://dx.doi.org/10.1093/schbul/sbaa097DOI Listing
December 2020

Neurocognitive patterns dissociating semantic processing from executive control are linked to more detailed off-task mental time travel.

Sci Rep 2020 07 17;10(1):11904. Epub 2020 Jul 17.

Department of Psychology, University of York, York, UK.

Features of ongoing experience are common across individuals and cultures. However, certain people express specific patterns of thought to a greater extent than others. Contemporary psychological theory assumes that individual differences in thought patterns occur because different types of experience depend on the expression of different neurocognitive processes. Consequently, individual variation in the underlying neurocognitive architecture is hypothesised to determine the ease with which certain thought patterns are generated or maintained. Our study (N = 178) tested this hypothesis using multivariate pattern analysis to infer shared variance among measures of cognitive function and neural organisation and examined whether these latent variables explained reports of the patterns of on-going thoughts people experienced in the lab. We found that relatively better performance on tasks relying primarily on semantic knowledge, rather than executive control, was linked to a neural functional organisation associated, via meta-analysis, with task labels related to semantic associations (sentence processing, reading and verbal semantics). Variability of this functional mode predicted significant individual variation in the types of thoughts that individuals experienced in the laboratory: neurocognitive patterns linked to better performance at tasks that required guidance from semantic representation, rather than those dependent on executive control, were associated with patterns of thought characterised by greater subjective detail and a focus on time periods other than the here and now. These relationships were consistent across different days and did not vary with level of task demands, indicating they are relatively stable features of an individual's cognitive profile. Together these data confirm that individual variation in aspects of ongoing experience can be inferred from hidden neurocognitive architecture and demonstrate that performance trade-offs between executive control and long-term semantic knowledge are linked to a person's tendency to imagine situations that transcend the here and now.
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http://dx.doi.org/10.1038/s41598-020-67605-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7368037PMC
July 2020

Reductions in task positive neural systems occur with the passage of time and are associated with changes in ongoing thought.

Sci Rep 2020 06 18;10(1):9912. Epub 2020 Jun 18.

Department of Psychology, University of York, York, UK.

Cognition is dynamic and involves both the maintenance of and transitions between neurocognitive states. While recent research has identified some of the neural systems involved in sustaining task states, it is less well understood how intrinsic influences on cognition emerge over time. The current study uses fMRI and Multi-Dimensional Experience Sampling (MDES) to chart how cognition changes over time from moments in time when external attention was established. We found that the passage of time was associated with brain regions associated with external attention decreasing in activity over time. Comparing this pattern of activity to defined functional hierarchies of brain organization, we found that it could be best understood as movement away from systems involved in task performance. Moments where the participants described their thoughts as off-task showed a significant similarity to the task-negative end of the same hierarchy. Finally, the greater the similarity of a participant's neural dynamics to this hierarchy the faster their rate of increasing off-task thought over time. These findings suggest topographical changes in neural processing that emerge over time and those seen during off-task thought can both be understood as a common shift away from neural motifs seen during complex task performance.
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http://dx.doi.org/10.1038/s41598-020-66698-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303126PMC
June 2020

Toward Neurosubtypes in Autism.

Biol Psychiatry 2020 07 22;88(1):111-128. Epub 2020 Apr 22.

Autism Center, Child Mind Institute, New York. Electronic address:

There is a consensus that substantial heterogeneity underlies the neurobiology of autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular, cellular, and brain network domains is a prerequisite for identifying biomarkers. Neuroimaging has been widely used to characterize atypical brain patterns in ASD, although findings have varied across studies. This is due, at least in part, to a failure to account for neurobiological heterogeneity. Here, we summarize emerging data-driven efforts to delineate more homogeneous ASD subgroups at the level of brain structure and function-that is, neurosubtyping. We break this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithms, and validation approaches. Although preliminary and methodologically diverse, current studies generally agree that at least 2 to 4 distinct ASD neurosubtypes may exist. Their identification improved symptom prediction and diagnostic label accuracy above and beyond group average comparisons. Yet, this nascent literature has shed light onto challenges and gaps. These include 1) the need for wider and more deeply transdiagnostic samples collected while minimizing artifacts (e.g., head motion), 2) quantitative and unbiased methods for feature selection and multimodal fusion, 3) greater emphasis on algorithms' ability to capture hybrid dimensional and categorical models of ASD, and 4) systematic independent replications and validations that integrate different units of analyses across multiple scales. Solutions aimed to address these challenges and gaps are discussed for future avenues leading toward a comprehensive understanding of the mechanisms underlying ASD heterogeneity.
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http://dx.doi.org/10.1016/j.biopsych.2020.03.022DOI Listing
July 2020

Resting state signal latency assesses the propagation of intrinsic activations and estimates anti-epileptic effect of levetiracetam in Rolandic epilepsy.

Brain Res Bull 2020 09 11;162:125-131. Epub 2020 Jun 11.

Department of Medical Imaging, Jinling Hospital, Medical school of Nanjing University, Nanjing, China; College Of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China; State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China. Electronic address:

Purpose: We assessed the potential of resting-state fMRI lag analysis (RSLA) in detecting epileptic activation and in estimating anti-epileptic effects of Levetiracetam (LEV) in Rolandic epilepsy.

Methods: Forty-three children with Rolandic epilepsy underwent simultaneous EEG-fMRI. They were grouped into LEV vs drug-naïve groups according to their medication, and into patients who showed or did not show central-temporal spike (CTS) discharges during scans. We calculated the lag structure of rs-fMRI for all patients and assessed interactions with drug (LEV vs. drug-naïve) and CTS status (CTS vs. no-CTS). We furthermore assessed correlations between lag values and number of CTS and medication conditions.

Results: RSLA analysis indicated earlier intrinsic activations in bilateral Rolandic areas when CTS occurred. More frequent epileptic discharges were correlated with earlier intrinsic activations (r=-0.46, p = 0.03 left Rolandic). Patients with LEV therapy, on the other hand, displayed delayed intrinsic activity in Rolandic areas compared to drug-naïve patients CONCLUSION: Our RSLA analysis indicated an association between centro-temporal spikes and earlier hemodynamic activations in epileptogenic regions in Rolandic epilepsy, which were counteracted by LEV treatment. As it allows for the mapping of propagation features of intrinsic activity and drug-effects, our findings suggest potential of lag based analyses in detecting focus localization and estimating treatment effects.
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http://dx.doi.org/10.1016/j.brainresbull.2020.05.016DOI Listing
September 2020

Population variability in social brain morphology for social support, household size and friendship satisfaction.

Soc Cogn Affect Neurosci 2020 07;15(6):635-647

Department of Biomedical Engineering, McConnell Brain Imaging Centre, Montreal Neurological Institute, Faculty of Medicine, McGill University, H3A 0G4 Montreal, Canada.

The social brain hypothesis proposes that the complexity of human brains has coevolved with increasing complexity of social interactions in primate societies. The present study explored the possible relationships between brain morphology and the richness of more intimate 'inner' and wider 'outer' social circles by integrating Bayesian hierarchical modeling with a large cohort sample from the UK Biobank resource (n = 10 000). In this way, we examined population volume effects in 36 regions of the 'social brain', ranging from lower sensory to higher associative cortices. We observed strong volume effects in the visual sensory network for the group of individuals with satisfying friendships. Further, the limbic network displayed several brain regions with substantial volume variations in individuals with a lack of social support. Our population neuroscience approach thus showed that distinct networks of the social brain show different patterns of volume variations linked to the examined social indices.
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http://dx.doi.org/10.1093/scan/nsaa075DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393310PMC
July 2020

Functional connectome contractions in temporal lobe epilepsy: Microstructural underpinnings and predictors of surgical outcome.

Epilepsia 2020 06 26;61(6):1221-1233. Epub 2020 May 26.

Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.

Objective: Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Although it is commonly related to hippocampal pathology, increasing evidence suggests structural changes beyond the mesiotemporal lobe. Functional anomalies and their link to underlying structural alterations, however, remain incompletely understood.

Methods: We studied 30 drug-resistant TLE patients and 57 healthy controls using multimodal magnetic resonance imaging (MRI) analyses. All patients had histologically verified hippocampal sclerosis and underwent postoperative imaging to outline the extent of their surgical resection. Our analysis leveraged a novel resting-state functional MRI framework that parameterizes functional connectivity distance, consolidating topological and physical properties of macroscale brain networks. Functional findings were integrated with morphological and microstructural metrics, and utility for surgical outcome prediction was assessed using machine learning techniques.

Results: Compared to controls, TLE patients showed connectivity distance reductions in temporoinsular and prefrontal networks, indicating topological segregation of functional networks. Testing for morphological and microstructural associations, we observed that functional connectivity contractions occurred independently from TLE-related cortical atrophy but were mediated by microstructural changes in the underlying white matter. Following our imaging study, all patients underwent an anterior temporal lobectomy as a treatment of their seizures, and postsurgical seizure outcome was determined at a follow-up at least 1 year after surgery. Using a regularized supervised machine learning paradigm with fivefold cross-validation, we demonstrated that patient-specific functional anomalies predicted postsurgical seizure outcome with 76 ± 4% accuracy, outperforming classifiers operating on clinical and structural imaging features.

Significance: Our findings suggest connectivity distance contractions as a macroscale substrate of TLE. Functional topological isolation may represent a microstructurally mediated network mechanism that tilts the balance toward epileptogenesis in affected networks and that may assist in patient-specific surgical prognostication.
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http://dx.doi.org/10.1111/epi.16540DOI Listing
June 2020

Macroscale and microcircuit dissociation of focal and generalized human epilepsies.

Commun Biol 2020 05 18;3(1):244. Epub 2020 May 18.

McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A2B4, Canada.

Thalamo-cortical pathology plays key roles in both generalized and focal epilepsies, but there is little work directly comparing these syndromes at the level of whole-brain mechanisms. Using multimodal imaging, connectomics, and computational simulations, we examined thalamo-cortical and cortico-cortical signatures and underlying microcircuits in 96 genetic generalized (GE) and 107 temporal lobe epilepsy (TLE) patients, along with 65 healthy controls. Structural and functional network profiling highlighted extensive atrophy, microstructural disruptions and decreased thalamo-cortical connectivity in TLE, while GE showed only subtle structural anomalies paralleled by enhanced thalamo-cortical connectivity. Connectome-informed biophysical simulations indicated modest increases in subcortical drive contributing to cortical dynamics in GE, while TLE presented with reduced subcortical drive and imbalanced excitation-inhibition within limbic and somatomotor microcircuits. Multiple sensitivity analyses supported robustness. Our multiscale analyses differentiate human focal and generalized epilepsy at the systems-level, showing paradoxically more severe microcircuit and macroscale imbalances in the former.
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http://dx.doi.org/10.1038/s42003-020-0958-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234993PMC
May 2020

Word up - Experiential and neurocognitive evidence for associations between autistic symptomology and a preference for thinking in the form of words.

Cortex 2020 07 27;128:88-106. Epub 2020 Mar 27.

Department of Psychology, University of York, York, United Kingdom.

Autism symptomology has a profound impact on cognitive and affective functioning, yet we know relatively little about how it shapes patterns of ongoing thought. In an exploratory study in a large population of neurotypical individuals, we used experience sampling to characterise the relationship between ongoing cognition and self-reported autistic traits. We found that with increasing autistic symptom score, cognition was characterised by thinking more in words than images. Analysis of structural neuroimaging data found that autistic traits linked to social interaction were associated with greater cortical thickness in a region of lingual gyrus (LG) within the occipital cortex. Analysis of resting state functional neuroimaging data found autistic traits were associated with stronger connectivity between the LG and a region of motor cortex. Importantly, the strength of connectivity between the LG and motor cortex moderated the link between autistic symptoms and thinking in words: individuals showing higher connectivity showed a stronger association between autistic traits and thinking in words. Together we provide behavioural and neural evidence linking autistic traits to the tendency to think in words which may be rooted in underlying cortical organisation. These observations lay the groundwork for research into the form and content of self-generated thoughts in individuals with the established diagnosis of autism.
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http://dx.doi.org/10.1016/j.cortex.2020.02.019DOI Listing
July 2020

Myeloarchitecture gradients in the human insula: Histological underpinnings and association to intrinsic functional connectivity.

Neuroimage 2020 08 20;216:116859. Epub 2020 Apr 20.

Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada. Electronic address:

Insular cortex is a core hub involved in multiple cognitive and socio-affective processes. Yet, the anatomical mechanisms that explain how it is involved in such a diverse array of functions remain incompletely understood. Here, we tested the hypothesis that changes in myeloarchitecture across the insular cortex explain how it can be involved in many different facets of cognitive function. Detailed intracortical profiling, performed across hundreds of insular locations on the basis of myelin-sensitive magnetic resonance imaging (MRI), was compressed into a lower-dimensional space uncovering principal axes of myeloarchitectonic variation. Leveraging two datasets with different high-resolution MRI contrasts, we obtained robust support for two principal dimensions of insular myeloarchitectonic differentiation in vivo, one running from ventral anterior to posterior banks and one radiating from dorsal anterior towards both ventral anterior and posterior subregions. Analyses of post mortem 3D histological data showed that the antero-posterior axis was mirrored in cytoarchitectural markers, even when controlling for sulco-gyral folding. Resting-state functional connectomics in the same individuals and ad hoc meta-analyses showed that myelin gradients in the insula relate to diverse affiliation to macroscale intrinsic functional systems, showing differential shifts in functional network embedding across each myelin-derived gradient. Collectively, our findings offer a novel approach to capture structure-function interactions of a key node of the limbic system, and suggest a multidimensional structural basis underlying the diverse functional roles of the insula.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116859DOI Listing
August 2020

Multidimensional associations between cognition and connectome organization in temporal lobe epilepsy.

Neuroimage 2020 06 6;213:116706. Epub 2020 Mar 6.

Universidad Nacional Autónoma de México, Instituto de Neurobiología, Querétaro, Querétaro, Mexico. Electronic address:

Objective: Temporal lobe epilepsy (TLE) is known to affect large-scale structural networks and cognitive function in multiple domains. The study of complex relations between structural network organization and cognition requires comprehensive analytical methods and a shift towards multivariate techniques. Here, we sought to identify multidimensional associations between cognitive performance and structural network topology in TLE.

Methods: We studied 34 drug-resistant adult TLE patients and 24 age- and sex-matched healthy controls. Participants underwent a comprehensive neurocognitive battery and multimodal MRI, allowing for large-scale connectomics, and morphological evaluation of subcortical and neocortical regions. Using canonical correlation analysis, we identified a multivariate mode that links cognitive performance to a brain structural network. Our approach was complemented by bootstrap-based hierarchical clustering to derive cognitive subtypes and associated patterns of macroscale connectome anomalies.

Results: Both methodologies provided converging evidence for a close coupling between cognitive impairments across multiple domains and large-scale structural network compromise. Cognitive classes presented with an increasing gradient of abnormalities (increasing cortical and subcortical atrophy and less efficient white matter connectome organization in patients with increasing degrees of cognitive impairments). Notably, network topology characterized cognitive performance better than morphometric measures did.

Conclusions: Our multivariate approach emphasized a close coupling of cognitive dysfunction and large-scale network anomalies in TLE. Our findings contribute to understand the complexity of structural connectivity regulating the heterogeneous cognitive deficits found in epilepsy.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116706DOI Listing
June 2020

Microstructural imaging in temporal lobe epilepsy: Diffusion imaging changes relate to reduced neurite density.

Neuroimage Clin 2020 28;26:102231. Epub 2020 Feb 28.

Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, UK.

Purpose: Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics.

Methods: 20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured.

Results: In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF.

Conclusions: Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study.
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http://dx.doi.org/10.1016/j.nicl.2020.102231DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063236PMC
February 2021

BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Commun Biol 2020 03 5;3(1):103. Epub 2020 Mar 5.

McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be described in a compact manner with multivariate machine learning approaches that identify manifolds often described as cortical gradients. By quantifying topographic principles of macroscale organization, cortical gradients lend an analytical framework to study structural and functional brain organization across species, throughout development and aging, and its perturbations in disease. Here, we present BrainSpace, a Python/Matlab toolbox for (i) the identification of gradients, (ii) their alignment, and (iii) their visualization. Our toolbox furthermore allows for controlled association studies between gradients with other brain-level features, adjusted with respect to null models that account for spatial autocorrelation. Validation experiments demonstrate the usage and consistency of our tools for the analysis of functional and microstructural gradients across different spatial scales.
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http://dx.doi.org/10.1038/s42003-020-0794-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058611PMC
March 2020