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Massullo C, Panno A, Carbone GA, Della Marca G, Farina B, Imperatori C. Need for cognitive closure is associated with different intra-network functional connectivity patterns: A resting state EEG study. Soc Neurosci 2022; 17:143-153. [PMID: 35167428 DOI: 10.1080/17470919.2022.2043432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Need for Cognitive Closure (NCC) is a construct referring to the desire for predictability, unambiguity and firm answers to issues. Neuroscientific literature about NCC processes has mainly focused on task-related brain activity. According to the Triple Network model (TN), the main aim of the current study was to investigate resting state (RS) electroencephalographic (EEG) intra-network dynamics associated with NCC. Fifty-two young adults (39 females) were enrolled and underwent EEG recordings during RS. Functional connectivity analysis was computed through exact Low-Resolution Electromagnetic Tomography (eLORETA) software. Our results showed that higher levels of NCC were associated with both i) decreased alpha EEG connectivity within the Central Executive Network (CEN), and ii) increased delta connectivity within the Default Mode Network (DMN). No significant correlations were observed between NCC and functional connectivity in the Salience Network (SN). Our data would seem to suggest that high levels of NCC are characterized by a specific communication pattern within the CEN and the DMN during RS. These neurophysiological patterns might reflect several typical NCC-related cognitive characteristics (e.g., lower flexibility and preference for habitual and rigid response schemas).
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Affiliation(s)
| | - Angelo Panno
- Cognitive and Clinical Psychology Laboratory, Department of Human Sciences, European University of Rome, Rome, Italy
| | - Giuseppe Alessio Carbone
- Cognitive and Clinical Psychology Laboratory, Department of Human Sciences, European University of Rome, Rome, Italy
| | - Giacomo Della Marca
- Department of Neurosciences, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Benedetto Farina
- Cognitive and Clinical Psychology Laboratory, Department of Human Sciences, European University of Rome, Rome, Italy
| | - Claudio Imperatori
- Cognitive and Clinical Psychology Laboratory, Department of Human Sciences, European University of Rome, Rome, Italy
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Qu J, Pang Y, Liu X, Cao Y, Huang C, Mei L. Task modulates the orthographic and phonological representations in the bilateral ventral Occipitotemporal cortex. Brain Imaging Behav 2022; 16:1695-1707. [PMID: 35247162 DOI: 10.1007/s11682-022-00641-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2022] [Indexed: 11/25/2022]
Abstract
As a key area in word reading, the left ventral occipitotemporal cortex is proposed for abstract orthographic processing, and its middle part has even been labeled as the visual word form area. Because the definition of the VWFA largely varies and the reading task differs across studies, the function of the left ventral occipitotemporal cortex in word reading is continuingly debated on whether this region is specific for orthographic processing or be involved in an interactive framework. By using representational similarity analysis (RSA), this study examined information representation in the VWFA at the individual level and the modulatory effect of reading task. Twenty-four subjects were scanned while performing the explicit (i.e., the naming task) and implicit (i.e., the perceptual task) reading tasks. Activation analysis showed that the naming task elicited greater activation in regions related to phonological processing (e.g., the bilateral prefrontal cortex and temporoparietal cortex), while the perceptual task recruited greater activation in visual cortex and default mode network (e.g., the bilateral middle frontal gyrus, angular gyrus, and the right middle temporal gyrus). More importantly, RSA also showed that task modulated information representation in the bilateral anterior occipitotemporal cortex and VWFA. Specifically, ROI-based RSA revealed enhanced orthographic and phonological representations in the bilateral anterior fusiform cortex and VWFA in the naming task relative to the perceptual task. These results suggest that lexical representation in the VWFA is influenced by the demand of phonological processing, which supports the interactive account of the VWFA.
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Affiliation(s)
- Jing Qu
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Yingdan Pang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Xiaoyu Liu
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Ying Cao
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Chengmei Huang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Leilei Mei
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, China.
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Ge Y, Chen G, Waltz JA, Hong LE, Kochunov P, Chen S. An integrated cluster-wise significance measure for fMRI analysis. Hum Brain Mapp 2022; 43:2444-2459. [PMID: 35233859 PMCID: PMC9057103 DOI: 10.1002/hbm.25795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 12/31/2021] [Accepted: 01/17/2022] [Indexed: 11/07/2022] Open
Abstract
Cluster-wise inference is widely used in fMRI analysis. The cluster-level statistic is often obtained by counting the number of intra-cluster voxels which surpass a voxel-level statistical significance threshold. This measure can be sub-optimal regarding the power and false-positive error rate because the suprathreshold voxel count neglects the voxel-wise significance levels and ignores the dependence between voxels. This article aims to provide a new Integrated Cluster-wise significance Measure (ICM) for cluster-level significance determination in cluster-wise fMRI analysis by integrating cluster extent, voxel-level significance (e.g., p values), and activation dependence between within-cluster voxels. We develop a computationally efficient strategy for ICM based on probabilistic approximation theories. Consequently, the computational load for ICM-based cluster-wise inference (e.g., permutation tests) is affordable. We validate the proposed method via extensive simulations and then apply it to two fMRI data sets. The results demonstrate that ICM can improve the power with well-controlled family-wise error (FWE).
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Affiliation(s)
- Yunjiang Ge
- Department of Mathematics, University of Maryland-College Park, College Park, Maryland, USA
| | - Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institute of Health, Bethesda, Maryland, USA
| | - James A Waltz
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Catonsville, Maryland, USA
| | - Liyi Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Catonsville, Maryland, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Catonsville, Maryland, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Catonsville, Maryland, USA.,Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, USA
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54
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Kilpatrick LA, Alger JR, O’Neill J, Joshi SH, Narr KL, Levitt JG, O’Connor MJ. Impact of prenatal alcohol exposure on intracortical myelination and deep white matter in children with attention deficit hyperactivity disorder. NEUROIMAGE. REPORTS 2022; 2:100082. [PMID: 37284413 PMCID: PMC10243188 DOI: 10.1016/j.ynirp.2022.100082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
White matter alterations have been reported in children with prenatal alcohol exposure (PAE) and in children with attention deficit hyperactivity disorder (ADHD); however, as children with PAE often present with ADHD, covert PAE may have contributed to previous ADHD findings. Additionally, data regarding intracortical myelination in ADHD are lacking. Therefore, we evaluated intracortical myelination (assessed as the T1w/T2w ratio at 4 cortical ribbon levels) and myelin-related deep white matter features in children (aged 8-13 years) with ADHD with PAE (ADHD + PAE), children with familial ADHD without PAE (ADHD-PAE), and typically developing (TD) children. In widespread tracts, ADHD + PAE children showed higher mean and radial diffusivity than TD and ADHD-PAE children and lower fractional anisotropy than ADHD-PAE children; ADHD-PAE and TD children did not differ significantly. Compared to TD children, ADHD + PAE children had lower intracortical myelination only at the deepest cortical level (mainly in right insula and cingulate cortices), while ADHD-PAE children had lower intracortical myelination at multiple cortical levels (mainly in right insula, sensorimotor, and cingulate cortices); ADHD + PAE and ADHD-PAE children did not differ significantly in intracortical myelination. Considering the two ADHD groups jointly (via non-parametric combination) revealed common reductions in intracortical myelination, but no common deep white matter abnormalities. These results suggest the importance of considering PAE in ADHD studies of white matter pathology. ADHD + PAE may be associated with deeper, white matter abnormalities, while familial ADHD without PAE may be associated with more superficial, cortical abnormalities. This may be relevant to the different treatment response observed in these two ADHD etiologies.
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Affiliation(s)
- Lisa A. Kilpatrick
- G. Oppenheimer Family Center for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
| | - Jeffry R. Alger
- Department of Neurology, University of California, Los Angeles, CA, USA
- Neurospectroscopics, LLC., Sherman Oaks, CA, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Joseph O’Neill
- Division of Child & Adolescent Psychiatry, Jane & Terry Semel Institute for Neuroscience, University of California Los Angeles, CA, USA
| | - Shantanu H. Joshi
- Department of Neurology, University of California, Los Angeles, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
| | - Katherine L. Narr
- Department of Neurology, University of California, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Jennifer G. Levitt
- Division of Child & Adolescent Psychiatry, Jane & Terry Semel Institute for Neuroscience, University of California Los Angeles, CA, USA
| | - Mary J. O’Connor
- Division of Child & Adolescent Psychiatry, Jane & Terry Semel Institute for Neuroscience, University of California Los Angeles, CA, USA
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55
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Rothacher Y, Nguyen A, Efthymiou E, Werth E, Baumann CR, Lenggenhager B, Brugger P, Kunz A, Imbach LL. Dissociation of motor control from motor awareness in awake sleepwalkers: An EEG study in virtual reality. Cortex 2022; 149:165-172. [DOI: 10.1016/j.cortex.2021.12.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/20/2021] [Accepted: 12/22/2021] [Indexed: 12/31/2022]
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56
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Rosenkranz MA, Dean DC, Bendlin BB, Jarjour NN, Esnault S, Zetterberg H, Heslegrave A, Evans MD, Davidson RJ, Busse WW. Neuroimaging and biomarker evidence of neurodegeneration in asthma. J Allergy Clin Immunol 2022; 149:589-598.e6. [PMID: 34536414 PMCID: PMC8821112 DOI: 10.1016/j.jaci.2021.09.010] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 08/19/2021] [Accepted: 09/07/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND Epidemiologic studies have shown that Alzheimer's disease (AD) and related dementias (ADRD) are seen more frequently with asthma, especially with greater asthma severity or exacerbation frequency. OBJECTIVE To examine the changes in brain structure that may underlie this phenomenon, we examined diffusion-weighted magnetic resonance imaging (dMRI) and blood-based biomarkers of AD (phosphorylated tau 181, p-Tau181), neurodegeneration (neurofilament light chain, NfL), and glial activation (glial fibrillary acidic protein, GFAP). METHODS dMRI data were obtained in 111 individuals with asthma, ranging in disease severity from mild to severe, and 135 healthy controls. Regression analyses were used to test the relationships between asthma severity and neuroimaging measures, as well as AD pathology, neurodegeneration, and glial activation, indexed by plasma p-Tau181, NfL, and GFAP, respectively. Additional relationships were tested with cognitive function. RESULTS Asthma participants had widespread and large-magnitude differences in several dMRI metrics, which were indicative of neuroinflammation and neurodegeneration, and which were robustly associated with GFAP and, to a lesser extent, NfL. The AD biomarker p-Tau181 was only minimally associated with neuroimaging outcomes. Further, asthma severity was associated with deleterious changes in neuroimaging outcomes, which in turn were associated with slower processing speed, a test of cognitive performance. CONCLUSIONS Asthma, particularly when severe, is associated with characteristics of neuroinflammation and neurodegeneration, and may be a potential risk factor for neural injury and cognitive dysfunction. There is a need to determine how asthma may affect brain health and whether treatment directed toward characteristics of asthma associated with these risks can mitigate these effects.
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Affiliation(s)
- Melissa A Rosenkranz
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisc; Center for Healthy Minds, University of Wisconsin-Madison, Madison, Wisc.
| | - Douglas C Dean
- Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisc; Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisc; Waisman Center, University of Wisconsin-Madison, Madison, Wisc
| | - Barbara B Bendlin
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisc; Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, Madison, Wisc
| | - Nizar N Jarjour
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisc
| | - Stephane Esnault
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisc
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom; UK Dementia Research Institute at UCL, London, United Kingdom
| | | | - Michael D Evans
- Biostatistical Design and Analysis Center, Clinical and Translational Science Institute, University of Minnesota, Minneapolis, Minn
| | - Richard J Davidson
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisc; Center for Healthy Minds, University of Wisconsin-Madison, Madison, Wisc; Department of Psychology, University of Wisconsin-Madison, Madison, Wisc
| | - William W Busse
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisc
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57
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Individually unique dynamics of cortical connectivity reflect the ongoing intensity of chronic pain. Pain 2022; 163:1987-1998. [PMID: 35082250 DOI: 10.1097/j.pain.0000000000002594] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 12/17/2021] [Indexed: 11/27/2022]
Abstract
ABSTRACT Chronic pain diseases are characterised by an ongoing and fluctuating endogenous pain, yet it remains to be elucidated how this is reflected by the dynamics of ongoing functional cortical connections.Here, we investigated the cortical encoding of 20 chronic back pain patients and 20 chronic migraineurs in four repeated fMRI sessions. A brain parcellation approach subdivided the whole brain into 408 regions. Linear mixed effects models were fitted for each pair of brain regions to explore the relationship between the dynamic cortical connectivity and the observed trajectory of the patients' ratings of fluctuating endogenous pain.Overall, we found that periods of high and increasing pain were predominantly related to low cortical connectivity. The change of pain intensity in chronic back pain was subserved by connections in left parietal opercular regions, right insular regions, as well as large parts of the parietal, cingular and motor cortices. The change of pain intensity direction in chronic migraine was reflected by decreasing connectivity between the anterior insular cortex and orbitofrontal areas, as well as between the PCC and frontal and ACC regions.Interestingly, the group results were not mirrored by the individual patterns of pain-related connectivity, which is suggested to deny the idea of a common neuronal core problem for chronic pain diseases. The diversity of the individual cortical signatures of chronic pain encoding results adds to the understanding of chronic pain as a complex and multifaceted disease. The present findings support recent developments for more personalised medicine.
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58
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Lehmann N, Villringer A, Taubert M. Priming cardiovascular exercise improves complex motor skill learning by affecting the trajectory of learning-related brain plasticity. Sci Rep 2022; 12:1107. [PMID: 35064175 PMCID: PMC8783021 DOI: 10.1038/s41598-022-05145-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 12/31/2021] [Indexed: 11/24/2022] Open
Abstract
In recent years, mounting evidence from animal models and studies in humans has accumulated for the role of cardiovascular exercise (CE) in improving motor performance and learning. Both CE and motor learning may induce highly dynamic structural and functional brain changes, but how both processes interact to boost learning is presently unclear. Here, we hypothesized that subjects receiving CE would show a different pattern of learning-related brain plasticity compared to non-CE controls, which in turn associates with improved motor learning. To address this issue, we paired CE and motor learning sequentially in a randomized controlled trial with healthy human participants. Specifically, we compared the effects of a 2-week CE intervention against a non-CE control group on subsequent learning of a challenging dynamic balancing task (DBT) over 6 consecutive weeks. Structural and functional MRI measurements were conducted at regular 2-week time intervals to investigate dynamic brain changes during the experiment. The trajectory of learning-related changes in white matter microstructure beneath parieto-occipital and primary sensorimotor areas of the right hemisphere differed between the CE vs. non-CE groups, and these changes correlated with improved learning of the CE group. While group differences in sensorimotor white matter were already present immediately after CE and persisted during DBT learning, parieto-occipital effects gradually emerged during motor learning. Finally, we found that spontaneous neural activity at rest in gray matter spatially adjacent to white matter findings was also altered, therefore indicating a meaningful link between structural and functional plasticity. Collectively, these findings may lead to a better understanding of the neural mechanisms mediating the CE-learning link within the brain.
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Affiliation(s)
- Nico Lehmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany. .,Faculty of Humanities, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104, Magdeburg, Germany.
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany.,Mind and Brain Institute, Charité and Humboldt University, Luisenstraße 56, 10117, Berlin, Germany
| | - Marco Taubert
- Faculty of Humanities, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104, Magdeburg, Germany.,Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106, Magdeburg, Germany
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59
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Deak B, Eggert T, Mayr A, Stankewitz A, Filippopulos F, Jahn P, Witkovsky V, Straube A, Schulz E. Intrinsic Network Activity Reflects the Fluctuating Experience of Tonic Pain. Cereb Cortex 2022; 32:4098-4109. [PMID: 35024821 DOI: 10.1093/cercor/bhab468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 11/16/2021] [Accepted: 11/18/2021] [Indexed: 11/14/2022] Open
Abstract
Although we know sensation is continuous, research on long-lasting and continuously changing stimuli is scarce and the dynamic nature of ongoing cortical processing is largely neglected. In a longitudinal study, 38 participants across four sessions were asked to continuously rate the intensity of an applied tonic heat pain for 20 min. Using group-independent component analysis and dual regression, we extracted the subjects' time courses of intrinsic network activity. The relationship between the dynamic fluctuation of network activity with the varying time courses of three pain processing entities was computed: pain intensity, the direction of pain intensity changes, and temperature. We were able to dissociate the spatio-temporal patterns of objective (temperature) and subjective (pain intensity/changes of pain intensity) aspects of pain processing in the human brain. We found two somatosensory networks with distinct functions: one network that encodes the small fluctuations in temperature and consists mainly of bilateral primary somatosensory cortex (SI), and a second right-lateralized network that encodes the intensity of the subjective experience of pain consisting of SI, secondary somatosensory cortex, the posterior cingulate cortex, and the thalamus. We revealed the somatosensory dynamics that build up toward a current subjective percept of pain. The timing suggests a cascade of subsequent processing steps toward the current pain percept.
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Affiliation(s)
- Bettina Deak
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Thomas Eggert
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Astrid Mayr
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany.,Department of Radiology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Anne Stankewitz
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Filipp Filippopulos
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Pauline Jahn
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Viktor Witkovsky
- Department of Theoretical Methods, Institute of Measurement Science, Slovak Academy of Sciences, 841 04 Bratislava, Slovak Republic
| | - Andreas Straube
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Enrico Schulz
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, 81377 Munich, Germany.,Department of Medical Psychology, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
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60
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Forodighasemabadi A, Baucher G, Soustelle L, Troalen T, Girard OM, Guye M, Grisoli JB, Ranjeva JP, Duhamel G, Callot V. Spinal cord and brain tissue impairments as long-term effects of rugby practice? An exploratory study based on T1 and ihMTsat measures. NEUROIMAGE: CLINICAL 2022; 35:103124. [PMID: 35905667 PMCID: PMC9421542 DOI: 10.1016/j.nicl.2022.103124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/14/2022] [Accepted: 07/20/2022] [Indexed: 12/03/2022] Open
Abstract
Diffuse degeneration of spinal cord (higher T1) is observed in retired rugby players. Demyelination of brain WM tracts (higher T1 / lower ihMTsat values) is present in rugby players. Early aging in both brain and spinal cord tissues may be linked to the rugby practice. The aforementioned effects may suggest cumulative effects of long-term impacts on the tissues.
Rugby players are subject to multiple impacts to their head and neck that could have adverse neurological effects and put them at increased risk of neurodegeneration. Previous studies demonstrated altered default mode network and diffusion metrics on brain, as well as more foraminal stenosis, disc protrusion and neck pain among players of contact sports as compared to healthy controls. However, the long-term effects of practice and repetitive impacts on brain and cervical spinal cord (cSC) of the rugby players have never been systematically investigated. In this study, 15 retired professional and amateur rugby players (R) and 15 age-matched healthy controls (HC) (all males; mean age R: 46.8 ± 7.6; and HC: 48.6 ± 9.5) were recruited both to investigate cord impairments and further characterize brain structure damage. Medical questionnaires including modified Japanese Orthopedic Association scale (mJOA) and Neck Disability Index (NDI) were filled by all participants. A 3 T multi-parametric MR protocol including conventional qualitative techniques such as T1-, T2-, and T2*-weighted sequences, as well as state-of-the art quantitative techniques including MP2RAGE T1 mapping and 3D ihMTRAGE, was used on both brain and cSC. Normalized brain WM and GM volumes, spine Overall Stenosis Score, cord cross-sectional area and regional T1 and ihMT metrics were derived from these acquisitions. Rugby players showed significantly higher NDI scores, as well as a faster decline of normalized brain GM volume with age as compared to HC. Moreover, higher T1 values on cSC suggestive of structural degeneration, together with higher T1 and lower ihMTsat on brain WM suggestive of demyelination, were observed in retired rugby players as compared to age-matched controls, which may suggest cumulative effects of long-term impacts on the tissues. Metrics also suggest early aging and different aging processes on brain tissue in the players. These preliminary observations provide new insights in the domain, which should now be further investigated on larger cohorts and multicentric longitudinal studies, and further correlated to the likelihood of neurodegenerative diseases and risk factors.
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61
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Alvand A, Kuruvilla-Mathew A, Kirk IJ, Roberts RP, Pedersen M, Purdy SC. Altered brain network topology in children with auditory processing disorder: A resting-state multi-echo fMRI study. NEUROIMAGE: CLINICAL 2022; 35:103139. [PMID: 36002970 PMCID: PMC9421544 DOI: 10.1016/j.nicl.2022.103139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 07/19/2022] [Accepted: 07/27/2022] [Indexed: 11/29/2022] Open
Abstract
A graph-theoretical approach was used to assess the functional topology in APD. Brain networks in APD are similarly integrated and segregated compared to HCs. Children with APD have different hub organization. Significant group differences were found in the PC measure in the bilateral STG. Regional differences observed within the DMN indicate multimodal roles in APD.
Children with auditory processing disorder (APD) experience hearing difficulties, particularly in the presence of competing sounds, despite having normal audiograms. There is considerable debate on whether APD symptoms originate from bottom-up (e.g., auditory sensory processing) and/or top-down processing (e.g., cognitive, language, memory). A related issue is that little is known about whether functional brain network topology is altered in APD. Therefore, we used resting-state functional magnetic resonance imaging data to investigate the functional brain network organization of 57 children from 8 to 14 years old, diagnosed with APD (n = 28) and without hearing difficulties (healthy control, HC; n = 29). We applied complex network analysis using graph theory to assess the whole-brain integration and segregation of functional networks and brain hub architecture. Our results showed children with APD and HC have similar global network properties –i.e., an average of all brain regions– and modular organization. Still, the APD group showed different hub architecture in default mode-ventral attention, somatomotor and frontoparietal-dorsal attention modules. At the nodal level –i.e., single-brain regions–, we observed decreased participation coefficient (PC – a measure quantifying the diversity of between-network connectivity) in auditory cortical regions in APD, including bilateral superior temporal gyrus and left middle temporal gyrus. Beyond auditory regions, PC was also decreased in APD in bilateral posterior temporo-occipital cortices, left intraparietal sulcus, and right posterior insular cortex. Correlation analysis suggested a positive association between PC in the left parahippocampal gyrus and the listening-in-spatialized-noise -sentences task where APD children were engaged in auditory perception. In conclusion, our findings provide evidence of altered brain network organization in children with APD, specific to auditory networks, and shed new light on the neural systems underlying children's listening difficulties.
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Affiliation(s)
- Ashkan Alvand
- School of Psychology, Faculty of Science, The University of Auckland, Auckland, New Zealand; Eisdell Moore Centre, Auckland, New Zealand.
| | - Abin Kuruvilla-Mathew
- School of Psychology, Faculty of Science, The University of Auckland, Auckland, New Zealand; Eisdell Moore Centre, Auckland, New Zealand.
| | - Ian J Kirk
- School of Psychology, Faculty of Science, The University of Auckland, Auckland, New Zealand; Eisdell Moore Centre, Auckland, New Zealand; Centre for Brain Research, The University of Auckland, Auckland, New Zealand.
| | - Reece P Roberts
- School of Psychology, Faculty of Science, The University of Auckland, Auckland, New Zealand; Centre for Brain Research, The University of Auckland, Auckland, New Zealand.
| | - Mangor Pedersen
- School of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand.
| | - Suzanne C Purdy
- School of Psychology, Faculty of Science, The University of Auckland, Auckland, New Zealand; Eisdell Moore Centre, Auckland, New Zealand; Centre for Brain Research, The University of Auckland, Auckland, New Zealand.
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62
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Chen YC, Arnatkevičiūtė A, McTavish E, Pang JC, Chopra S, Suo C, Fornito A, Aquino KM. The individuality of shape asymmetries of the human cerebral cortex. eLife 2022; 11:75056. [PMID: 36197720 PMCID: PMC9668337 DOI: 10.7554/elife.75056] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 10/04/2022] [Indexed: 01/05/2023] Open
Abstract
Asymmetries of the cerebral cortex are found across diverse phyla and are particularly pronounced in humans, with important implications for brain function and disease. However, many prior studies have confounded asymmetries due to size with those due to shape. Here, we introduce a novel approach to characterize asymmetries of the whole cortical shape, independent of size, across different spatial frequencies using magnetic resonance imaging data in three independent datasets. We find that cortical shape asymmetry is highly individualized and robust, akin to a cortical fingerprint, and identifies individuals more accurately than size-based descriptors, such as cortical thickness and surface area, or measures of inter-regional functional coupling of brain activity. Individual identifiability is optimal at coarse spatial scales (~37 mm wavelength), and shape asymmetries show scale-specific associations with sex and cognition, but not handedness. While unihemispheric cortical shape shows significant heritability at coarse scales (~65 mm wavelength), shape asymmetries are determined primarily by subject-specific environmental effects. Thus, coarse-scale shape asymmetries are highly personalized, sexually dimorphic, linked to individual differences in cognition, and are primarily driven by stochastic environmental influences.
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Affiliation(s)
- Yu-Chi Chen
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia,Monash Data Futures Institute, Monash UniversityMelbourneAustralia
| | - Aurina Arnatkevičiūtė
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia
| | - Eugene McTavish
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia,Healthy Brain and Mind Research Centre, Faculty of Health Sciences, Australian Catholic UniversityFitzroyAustralia
| | - James C Pang
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia
| | - Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia,Department of Psychology, Yale UniversityNew HavenUnited States
| | - Chao Suo
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia,BrainPark, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia
| | - Kevin M Aquino
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash UniversityMelbourneAustralia,Monash Biomedical Imaging, Monash UniversityMelbourneAustralia,School of Physics, University of SydneySydneyAustralia,Center of Excellence for Integrative Brain Function, University of SydneySydneyAustralia,BrainKey IncSan FranciscoUnited States
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63
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Haast RAM, De Coo IFM, Ivanov D, Khan AR, Jansen JFA, Smeets HJM, Uludağ K. OUP accepted manuscript. Brain Commun 2022; 4:fcac024. [PMID: 35187487 PMCID: PMC8853728 DOI: 10.1093/braincomms/fcac024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 11/26/2021] [Accepted: 02/01/2022] [Indexed: 11/14/2022] Open
Abstract
Mutations of the mitochondrial DNA are an important cause of inherited diseases that can severely affect the tissue’s homeostasis and integrity. The m.3243A > G mutation is the most commonly observed across mitochondrial disorders and is linked to multisystemic complications, including cognitive deficits. In line with in vitro experiments demonstrating the m.3243A > G’s negative impact on neuronal energy production and integrity, m.3243A > G patients show cerebral grey matter tissue changes. However, its impact on the most neuron dense, and therefore energy-consuming brain structure—the cerebellum—remains elusive. In this work, we used high-resolution structural and functional data acquired using 7 T MRI to characterize the neurodegenerative and functional signatures of the cerebellar cortex in m.3243A > G patients. Our results reveal altered tissue integrity within distinct clusters across the cerebellar cortex, apparent by their significantly reduced volume and longitudinal relaxation rate compared with healthy controls, indicating macroscopic atrophy and microstructural pathology. Spatial characterization reveals that these changes occur especially in regions related to the frontoparietal brain network that is involved in information processing and selective attention. In addition, based on resting-state functional MRI data, these clusters exhibit reduced functional connectivity to frontal and parietal cortical regions, especially in patients characterized by (i) a severe disease phenotype and (ii) reduced information-processing speed and attention control. Combined with our previous work, these results provide insight into the neuropathological changes and a solid base to guide longitudinal studies aimed to track disease progression.
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Affiliation(s)
- Roy A. M. Haast
- Correspondence to: Roy A. M. Haast Centre for Functional and Metabolic Mapping Robarts Research Institute Western University 1151 Richmond St N., London ON, Canada N6A 5B7 E-mail:
| | - Irenaeus F. M. De Coo
- Department of Toxicogenomics, Unit Clinical Genomics, Maastricht University, MHeNs School for Mental Health and Neuroscience, Maastricht, the Netherlands
| | - Dimo Ivanov
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, PO Box 616, 6200 MD, Maastricht, the Netherlands
| | - Ali R. Khan
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada, N6A 5B7
- Brain and Mind Institute, Western University, London, ON, Canada, N6A 3K7
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada, N6A 5B7
| | - Jacobus F. A. Jansen
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
- School for Mental Health & Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Hubert J. M. Smeets
- Department of Toxicogenomics, Unit Clinical Genomics, Maastricht University, MHeNs School for Mental Health and Neuroscience, Maastricht, the Netherlands
- School for Mental Health & Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Kâmil Uludağ
- IBS Center for Neuroscience Imaging Research, Sungkyunkwan University, Seobu-ro, 2066, Jangan-gu, Suwon, South Korea
- Department of Biomedical Engineering, N Center, Sungkyunkwan University, Seobu-ro, 2066, Jangan-gu, Suwon, South Korea
- Techna Institute and Koerner Scientist in MR Imaging, University Health Network, Toronto, ON, Canada, M5G 1L5
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64
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Zugman A, Harrewijn A, Cardinale EM, Zwiebel H, Freitag GF, Werwath KE, Bas‐Hoogendam JM, Groenewold NA, Aghajani M, Hilbert K, Cardoner N, Porta‐Casteràs D, Gosnell S, Salas R, Blair KS, Blair JR, Hammoud MZ, Milad M, Burkhouse K, Phan KL, Schroeder HK, Strawn JR, Beesdo‐Baum K, Thomopoulos SI, Grabe HJ, Van der Auwera S, Wittfeld K, Nielsen JA, Buckner R, Smoller JW, Mwangi B, Soares JC, Wu M, Zunta‐Soares GB, Jackowski AP, Pan PM, Salum GA, Assaf M, Diefenbach GJ, Brambilla P, Maggioni E, Hofmann D, Straube T, Andreescu C, Berta R, Tamburo E, Price R, Manfro GG, Critchley HD, Makovac E, Mancini M, Meeten F, Ottaviani C, Agosta F, Canu E, Cividini C, Filippi M, Kostić M, Munjiza A, Filippi CA, Leibenluft E, Alberton BAV, Balderston NL, Ernst M, Grillon C, Mujica‐Parodi LR, van Nieuwenhuizen H, Fonzo GA, Paulus MP, Stein MB, Gur RE, Gur RC, Kaczkurkin AN, Larsen B, Satterthwaite TD, Harper J, Myers M, Perino MT, Yu Q, Sylvester CM, Veltman DJ, Lueken U, Van der Wee NJA, Stein DJ, Jahanshad N, Thompson PM, Pine DS, Winkler AM. Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group. Hum Brain Mapp 2022; 43:255-277. [PMID: 32596977 PMCID: PMC8675407 DOI: 10.1002/hbm.25096] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 05/26/2020] [Accepted: 05/31/2020] [Indexed: 12/15/2022] Open
Abstract
The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.
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Affiliation(s)
- André Zugman
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Anita Harrewijn
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Elise M. Cardinale
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Hannah Zwiebel
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Gabrielle F. Freitag
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Katy E. Werwath
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Janna M. Bas‐Hoogendam
- Leiden University Medical Center, Department of PsychiatryLeidenThe Netherlands
- Leiden Institute for Brain and Cognition (LIBC)LeidenThe Netherlands
- Leiden University, Institute of Psychology, Developmental and Educational PsychologyLeidenThe Netherlands
| | - Nynke A. Groenewold
- Department of Psychiatry & Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Moji Aghajani
- Department. of PsychiatryAmsterdam UMC/VUMCAmsterdamThe Netherlands
- GGZ InGeestDepartment of Research & InnovationAmsterdamThe Netherlands
| | - Kevin Hilbert
- Department of PsychologyHumboldt‐Universität zu BerlinBerlinGermany
| | - Narcis Cardoner
- Department of Mental HealthUniversity Hospital Parc Taulí‐I3PTBarcelonaSpain
- Department of Psychiatry and Forensic MedicineUniversitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Salud MentalCarlos III Health InstituteMadridSpain
| | - Daniel Porta‐Casteràs
- Department of Mental HealthUniversity Hospital Parc Taulí‐I3PTBarcelonaSpain
- Department of Psychiatry and Forensic MedicineUniversitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Salud MentalCarlos III Health InstituteMadridSpain
| | - Savannah Gosnell
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | - Ramiro Salas
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | - Karina S. Blair
- Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
| | - James R. Blair
- Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
| | - Mira Z. Hammoud
- Department of PsychiatryNew York UniversityNew YorkNew YorkUSA
| | - Mohammed Milad
- Department of PsychiatryNew York UniversityNew YorkNew YorkUSA
| | - Katie Burkhouse
- Department of PsychiatryUniversity of Illinois at ChicagoChicagoIllinoisUSA
| | - K. Luan Phan
- Department of Psychiatry and Behavioral HealthThe Ohio State UniversityColumbusOhioUSA
| | - Heidi K. Schroeder
- Department of Psychiatry & Behavioral NeuroscienceUniversity of CincinnatiCincinnatiOhioUSA
| | - Jeffrey R. Strawn
- Department of Psychiatry & Behavioral NeuroscienceUniversity of CincinnatiCincinnatiOhioUSA
| | - Katja Beesdo‐Baum
- Behavioral EpidemiologyInstitute of Clinical Psychology and Psychotherapy, Technische Universität DresdenDresdenGermany
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Hans J. Grabe
- Department of Psychiatry and PsychotherapyUniversity Medicine GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Sandra Van der Auwera
- Department of Psychiatry and PsychotherapyUniversity Medicine GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Katharina Wittfeld
- Department of Psychiatry and PsychotherapyUniversity Medicine GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Jared A. Nielsen
- Department of PsychologyHarvard UniversityCambridgeMassachusettsUSA
- Center for Brain ScienceHarvard UniversityCambridgeMassachusettsUSA
| | - Randy Buckner
- Department of PsychologyHarvard UniversityCambridgeMassachusettsUSA
- Center for Brain ScienceHarvard UniversityCambridgeMassachusettsUSA
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Jordan W. Smoller
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Benson Mwangi
- Center Of Excellence On Mood Disorders, Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Jair C. Soares
- Center Of Excellence On Mood Disorders, Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Mon‐Ju Wu
- Center Of Excellence On Mood Disorders, Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Giovana B. Zunta‐Soares
- Center Of Excellence On Mood Disorders, Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Andrea P. Jackowski
- LiNC, Department of PsychiatryFederal University of São PauloSão PauloSão PauloBrazil
| | - Pedro M. Pan
- LiNC, Department of PsychiatryFederal University of São PauloSão PauloSão PauloBrazil
| | - Giovanni A. Salum
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do SulPorto AlegreRio Grande do SulBrazil
| | - Michal Assaf
- Olin Neuropsychiatry Research CenterInstitute of Living, Hartford HospitalHartfordConnecticutUSA
- Department of PsychiatryYale School of MedicineNew HavenConnecticutUSA
| | - Gretchen J. Diefenbach
- Anxiety Disorders CenterInstitute of Living, Hartford HospitalHartfordConnecticutUSA
- Yale School of MedicineNew HavenConnecticutUSA
| | - Paolo Brambilla
- Department of Neurosciences and Mental HealthFondazione IRCCS Ca' Granda Ospedale Maggiore PoliclinicoMilanItaly
| | - Eleonora Maggioni
- Department of Neurosciences and Mental HealthFondazione IRCCS Ca' Granda Ospedale Maggiore PoliclinicoMilanItaly
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of MuensterMuensterGermany
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of MuensterMuensterGermany
| | - Carmen Andreescu
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Rachel Berta
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Erica Tamburo
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Rebecca Price
- Department of Psychiatry & PsychologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Gisele G. Manfro
- Anxiety Disorder ProgramHospital de Clínicas de Porto AlegrePorto AlegreRio Grande do SulBrazil
- Department of PsychiatryFederal University of Rio Grande do SulPorto AlegreRio Grande do SulBrazil
| | - Hugo D. Critchley
- Department of NeuroscienceBrighton and Sussex Medical School, University of SussexBrightonUK
| | - Elena Makovac
- Centre for Neuroimaging ScienceKings College LondonLondonUK
| | - Matteo Mancini
- Department of NeuroscienceBrighton and Sussex Medical School, University of SussexBrightonUK
| | | | | | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Vita‐Salute San Raffaele UniversityMilanItaly
| | - Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Camilla Cividini
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Vita‐Salute San Raffaele UniversityMilanItaly
- Neurology and Neurophysiology UnitIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Milutin Kostić
- Institute of Mental Health, University of BelgradeBelgradeSerbia
- Department of Psychiatry, School of MedicineUniversity of BelgradeBelgradeSerbia
| | - Ana Munjiza
- Institute of Mental Health, University of BelgradeBelgradeSerbia
| | - Courtney A. Filippi
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Ellen Leibenluft
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Bianca A. V. Alberton
- Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal do ParanáCuritibaPuerto RicoBrazil
| | - Nicholas L. Balderston
- Center for Neuromodulation in Depression and StressUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Monique Ernst
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Christian Grillon
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | | | | | - Gregory A. Fonzo
- Department of PsychiatryThe University of Texas at Austin Dell Medical SchoolAustinTexasUSA
| | | | - Murray B. Stein
- Department of Psychiatry & Family Medicine and Public HealthUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Raquel E. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ruben C. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Bart Larsen
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Jennifer Harper
- Department of PsychiatryWashington UniversitySt. LouisMissouriUSA
| | - Michael Myers
- Department of PsychiatryWashington UniversitySt. LouisMissouriUSA
| | | | - Qiongru Yu
- Department of PsychiatryWashington UniversitySt. LouisMissouriUSA
| | | | - Dick J. Veltman
- Department. of PsychiatryAmsterdam UMC/VUMCAmsterdamThe Netherlands
| | - Ulrike Lueken
- Department of PsychologyHumboldt‐Universität zu BerlinBerlinGermany
| | - Nic J. A. Van der Wee
- Leiden University Medical Center, Department of PsychiatryLeidenThe Netherlands
- Leiden Institute for Brain and Cognition (LIBC)LeidenThe Netherlands
| | - Dan J. Stein
- Department of Psychiatry & Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
- SAMRC Unite on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Daniel S. Pine
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
| | - Anderson M. Winkler
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH)BethesdaMarylandUSA
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65
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Mayr A, Jahn P, Stankewitz A, Deak B, Winkler A, Witkovsky V, Eren O, Straube A, Schulz E. Patients with chronic pain exhibit individually unique cortical signatures of pain encoding. Hum Brain Mapp 2021; 43:1676-1693. [PMID: 34921467 PMCID: PMC8886665 DOI: 10.1002/hbm.25750] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/22/2021] [Accepted: 12/01/2021] [Indexed: 12/30/2022] Open
Abstract
Chronic pain is characterised by an ongoing and fluctuating intensity over time. Here, we investigated how the trajectory of the patients' endogenous pain is encoded in the brain. In repeated functional MRI (fMRI) sessions, 20 patients with chronic back pain and 20 patients with chronic migraine were asked to continuously rate the intensity of their endogenous pain. Linear mixed effects models were used to disentangle cortical processes related to pain intensity and to pain intensity changes. At group level, we found that the intensity of pain in patients with chronic back pain is encoded in the anterior insular cortex, the frontal operculum, and the pons; the change of pain in chronic back pain and chronic migraine patients is mainly encoded in the anterior insular cortex. At the individual level, we identified a more complex picture where each patient exhibited their own signature of endogenous pain encoding. The diversity of the individual cortical signatures of chronic pain encoding results bridge between clinical observations and neuroimaging; they add to the understanding of chronic pain as a complex and multifaceted disease.
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Affiliation(s)
- Astrid Mayr
- Department of Radiology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany.,Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Pauline Jahn
- Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anne Stankewitz
- Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Bettina Deak
- Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anderson Winkler
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Viktor Witkovsky
- Department of Theoretical Methods, Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovak Republic
| | - Ozan Eren
- Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Andreas Straube
- Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Enrico Schulz
- Department of Neurology, University Hospital LMU, Ludwig-Maximilians-Universität München, Munich, Germany.,Department of Medical Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
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66
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Task effects on functional connectivity measures after stroke. Exp Brain Res 2021; 240:575-590. [PMID: 34860257 DOI: 10.1007/s00221-021-06261-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 10/28/2021] [Indexed: 10/19/2022]
Abstract
Understanding the effect of task compared to rest on detecting stroke-related network abnormalities will inform efforts to optimize detection of such abnormalities. The goal of this work was to determine whether connectivity measures obtained during an overt task are more effective than connectivity obtained during a "resting" state for detecting stroke-related changes in network function of the brain. This study examined working memory, discrete pedaling, continuous pedaling and language tasks. Functional magnetic resonance imaging was used to examine regional and inter-regional brain network function in 14 stroke and 16 control participants. Independent component analysis was used to identify 149 regions of interest (ROI). Using the inter-regional connectivity measurements, the weighted sum was calculated across only regions associated with a given task. Both inter-regional connectivity and regional connectivity were greater during each of the tasks as compared to the resting state. The working memory and discrete pedaling tasks allowed for detection of stroke-related decreases in inter-regional connectivity, while the continuous pedaling and language tasks allowed for detection of stroke-related enhancements in regional connectivity. These observations illustrate that task-based functional connectivity allows for detection of stroke-related changes not seen during resting states. In addition, this work provides evidence that tasks emphasizing different cognitive domains reveal different aspects of stroke-related reorganization. We also illustrate that within the motor domain, different tasks can reveal inter-regional or regional stroke-related changes, in this case suggesting that discrete pedaling required more central drive than continuous pedaling.
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67
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Herman JD, Wang C, Loos C, Yoon H, Rivera J, Eugenia Dieterle M, Haslwanter D, Jangra RK, Bortz RH, Bar KJ, Julg B, Chandran K, Lauffenburger D, Pirofski LA, Alter G. Functional convalescent plasma antibodies and pre-infusion titers shape the early severe COVID-19 immune response. Nat Commun 2021; 12:6853. [PMID: 34824251 PMCID: PMC8617042 DOI: 10.1038/s41467-021-27201-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 10/28/2021] [Indexed: 01/10/2023] Open
Abstract
Transfer of convalescent plasma (CP) had been proposed early during the SARS-CoV-2 pandemic as an accessible therapy, yet trial results worldwide have been mixed, potentially due to the heterogeneous nature of CP. Here we perform deep profiling of SARS-CoV-2-specific antibody titer, Fc-receptor binding, and Fc-mediated functional assays in CP units, as well as in plasma from hospitalized COVID-19 patients before and after CP administration. The profiling results show that, although all recipients exhibit expanded SARS-CoV-2-specific humoral immune responses, CP units contain more functional antibodies than recipient plasma. Meanwhile, CP functional profiles influence the evolution of recipient humoral immunity in conjuncture with the recipient's pre-existing SARS-CoV2-specific antibody titers: CP-derived SARS-CoV-2 nucleocapsid-specific antibody functions are associated with muted humoral immune evolution in patients with high titer anti-spike IgG. Our data thus provide insights into the unexpected impact of CP-derived functional anti-spike and anti-nucleocapsid antibodies on the evolution of SARS-CoV-2-specific response following severe infection.
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Affiliation(s)
- Jonathan D Herman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Division of Infectious Disease, Brigham and Women's Hospital, Boston, MA, USA
| | - Chuangqi Wang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Carolin Loos
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hyunah Yoon
- Division of Infectious Diseases, Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
| | - Johanna Rivera
- Division of Infectious Diseases, Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - M Eugenia Dieterle
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Denise Haslwanter
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Rohit K Jangra
- Department of Microbiology and Immunology, Louisiana State University Health Science Center-Shreveport, Shreveport, LA, USA
| | - Robert H Bortz
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Katharine J Bar
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Boris Julg
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Kartik Chandran
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Douglas Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Liise-Anne Pirofski
- Division of Infectious Diseases, Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA.
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA.
| | - Galit Alter
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA.
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68
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Lazari A, Salvan P, Cottaar M, Papp D, Jens van der Werf O, Johnstone A, Sanders ZB, Sampaio-Baptista C, Eichert N, Miyamoto K, Winkler A, Callaghan MF, Nichols TE, Stagg CJ, Rushworth MFS, Verhagen L, Johansen-Berg H. Reassessing associations between white matter and behaviour with multimodal microstructural imaging. Cortex 2021; 145:187-200. [PMID: 34742100 PMCID: PMC8940642 DOI: 10.1016/j.cortex.2021.08.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/21/2021] [Accepted: 08/27/2021] [Indexed: 12/15/2022]
Abstract
Several studies have established specific relationships between White Matter (WM) and behaviour. However, these studies have typically focussed on fractional anisotropy (FA), a neuroimaging metric that is sensitive to multiple tissue properties, making it difficult to identify what biological aspects of WM may drive such relationships. Here, we carry out a pre-registered assessment of WM-behaviour relationships in 50 healthy individuals across multiple behavioural and anatomical domains, and complementing FA with myelin-sensitive quantitative MR modalities (MT, R1, R2∗). Surprisingly, we only find support for predicted relationships between FA and behaviour in one of three pre-registered tests. For one behavioural domain, where we failed to detect an FA-behaviour correlation, we instead find evidence for a correlation between behaviour and R1. This hints that multimodal approaches are able to identify a wider range of WM-behaviour relationships than focusing on FA alone. To test whether a common biological substrate such as myelin underlies WM-behaviour relationships, we then ran joint multimodal analyses, combining across all MRI parameters considered. No significant multimodal signatures were found and power analyses suggested that sample sizes of 40–200 may be required to detect such joint multimodal effects, depending on the task being considered. These results demonstrate that FA-behaviour relationships from the literature can be replicated, but may not be easily generalisable across domains. Instead, multimodal microstructural imaging may be best placed to detect a wider range of WM-behaviour relationships, as different MRI modalities provide distinct biological sensitivities. Our findings highlight a broad heterogeneity in WM's relationship with behaviour, suggesting that variable biological effects may be shaping their interaction.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK.
| | - Piergiorgio Salvan
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Daniel Papp
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Olof Jens van der Werf
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, the Netherlands
| | - Ainslie Johnstone
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK; Department of Clinical and Movement Neuroscience, Institute of Neurology, University College London, UK
| | - Zeena-Britt Sanders
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Cassandra Sampaio-Baptista
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Kentaro Miyamoto
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, UK
| | - Anderson Winkler
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nu_eld Department of Population Health, University of Oxford, UK
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, UK
| | - Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK.
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69
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Filip P, Dufek M, Mangia S, Michaeli S, Bareš M, Schwarz D, Rektor I, Vojtíšek L. Alterations in Sensorimotor and Mesiotemporal Cortices and Diffuse White Matter Changes in Primary Progressive Multiple Sclerosis Detected by Adiabatic Relaxometry. Front Neurosci 2021; 15:711067. [PMID: 34594184 PMCID: PMC8476998 DOI: 10.3389/fnins.2021.711067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/12/2021] [Indexed: 11/17/2022] Open
Abstract
Background: The research of primary progressive multiple sclerosis (PPMS) has not been able to capitalize on recent progresses in advanced magnetic resonance imaging (MRI) protocols. Objective: The presented cross-sectional study evaluated the utility of four different MRI relaxation metrics and diffusion-weighted imaging in PPMS. Methods: Conventional free precession T1 and T2, and rotating frame adiabatic T1ρ and T2ρ in combination with diffusion-weighted parameters were acquired in 13 PPMS patients and 13 age- and sex-matched controls. Results: T1ρ, a marker of crucial relevance for PPMS due to its sensitivity to neuronal loss, revealed large-scale changes in mesiotemporal structures, the sensorimotor cortex, and the cingulate, in combination with diffuse alterations in the white matter and cerebellum. T2ρ, particularly sensitive to local tissue background gradients and thus an indicator of iron accumulation, concurred with similar topography of damage, but of lower extent. Moreover, these adiabatic protocols outperformed both conventional T1 and T2 maps and diffusion tensor/kurtosis approaches, methods previously used in the MRI research of PPMS. Conclusion: This study introduces adiabatic T1ρ and T2ρ as elegant markers confirming large-scale cortical gray matter, cerebellar, and white matter alterations in PPMS invisible to other in vivo biomarkers.
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Affiliation(s)
- Pavel Filip
- Department of Neurology, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czechia.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Michal Dufek
- First Department of Neurology, Faculty of Medicine, University Hospital of St. Anne, Masaryk University, Brno, Czechia
| | - Silvia Mangia
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Shalom Michaeli
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Martin Bareš
- First Department of Neurology, Faculty of Medicine, University Hospital of St. Anne, Masaryk University, Brno, Czechia.,Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, MN, United States
| | - Daniel Schwarz
- Faculty of Medicine, Institute of Biostatistics and Analyses, Masaryk University, Brno, Czechia.,Institute of Biostatistics and Analyses, Ltd., Masaryk University Spin-Off, Brno, Czechia
| | - Ivan Rektor
- Central European Institute of Technology, Masaryk University, Neuroscience Centre, Brno, Czechia
| | - Lubomír Vojtíšek
- Central European Institute of Technology, Masaryk University, Neuroscience Centre, Brno, Czechia
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70
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Harrewijn A, Cardinale EM, Groenewold NA, Bas-Hoogendam JM, Aghajani M, Hilbert K, Cardoner N, Porta-Casteràs D, Gosnell S, Salas R, Jackowski AP, Pan PM, Salum GA, Blair KS, Blair JR, Hammoud MZ, Milad MR, Burkhouse KL, Phan KL, Schroeder HK, Strawn JR, Beesdo-Baum K, Jahanshad N, Thomopoulos SI, Buckner R, Nielsen JA, Smoller JW, Soares JC, Mwangi B, Wu MJ, Zunta-Soares GB, Assaf M, Diefenbach GJ, Brambilla P, Maggioni E, Hofmann D, Straube T, Andreescu C, Berta R, Tamburo E, Price RB, Manfro GG, Agosta F, Canu E, Cividini C, Filippi M, Kostić M, Munjiza Jovanovic A, Alberton BAV, Benson B, Freitag GF, Filippi CA, Gold AL, Leibenluft E, Ringlein GV, Werwath KE, Zwiebel H, Zugman A, Grabe HJ, Van der Auwera S, Wittfeld K, Völzke H, Bülow R, Balderston NL, Ernst M, Grillon C, Mujica-Parodi LR, van Nieuwenhuizen H, Critchley HD, Makovac E, Mancini M, Meeten F, Ottaviani C, Ball TM, Fonzo GA, Paulus MP, Stein MB, Gur RE, Gur RC, Kaczkurkin AN, Larsen B, Satterthwaite TD, Harper J, Myers M, Perino MT, Sylvester CM, Yu Q, Lueken U, Veltman DJ, Thompson PM, Stein DJ, Van der Wee NJA, Winkler AM, Pine DS. Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group. Transl Psychiatry 2021; 11:502. [PMID: 34599145 PMCID: PMC8486763 DOI: 10.1038/s41398-021-01622-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 09/02/2021] [Accepted: 09/14/2021] [Indexed: 12/22/2022] Open
Abstract
The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.
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Affiliation(s)
- Anita Harrewijn
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA.
| | - Elise M Cardinale
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Nynke A Groenewold
- Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Janna Marie Bas-Hoogendam
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam, The Netherlands
- Department of Research & Innovation, GGZ InGeest, Amsterdam, The Netherlands
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Narcis Cardoner
- Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
| | - Daniel Porta-Casteràs
- Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
| | - Savannah Gosnell
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ramiro Salas
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Andrea P Jackowski
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil
| | - Pedro M Pan
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil
| | - Giovanni A Salum
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Karina S Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, USA
| | - James R Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Mira Z Hammoud
- Department of Psychiatry, NYU School of Medicine, New York University, New York, NY, USA
| | - Mohammed R Milad
- Department of Psychiatry, NYU School of Medicine, New York University, New York, NY, USA
| | - Katie L Burkhouse
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, USA
| | - Heidi K Schroeder
- Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jeffrey R Strawn
- Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Katja Beesdo-Baum
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Randy Buckner
- Center for Brain Science & Department of Psychology, Harvard University, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jared A Nielsen
- Center for Brain Science & Department of Psychology, Harvard University, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychology Department & Neuroscience Center, Brigham Young University, Provo, USA
| | - Jordan W Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jair C Soares
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Benson Mwangi
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mon-Ju Wu
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Giovana B Zunta-Soares
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Michal Assaf
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Gretchen J Diefenbach
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Anxiety Disorders Center, Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Eleonora Maggioni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rachel Berta
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Erica Tamburo
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rebecca B Price
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gisele G Manfro
- Anxiety Disorder Program, Hospital de Clínicas de Porto Alegre, Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Milutin Kostić
- Institute of Mental Health, University of Belgrade, Belgrade, Serbia
- Department of Psychiatry, School of Medicine, University of Belgrade, Belgrade, Serbia
| | | | - Bianca A V Alberton
- Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal do Paraná, Curitiba, Puerto Rico, Brazil
| | - Brenda Benson
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Gabrielle F Freitag
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Andrea L Gold
- Department of Psychiatry and Human Behavior, Brown University Warren Alpert Medical School, Providence, RI, USA
| | - Ellen Leibenluft
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Grace V Ringlein
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Kathryn E Werwath
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Hannah Zwiebel
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - André Zugman
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Nicholas L Balderston
- Center for Neuromodulation in Depression and Stress, University of Pennsylvania, Philadelphia, PA, USA
| | - Monique Ernst
- Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, Bethesda, MD, USA
| | - Christian Grillon
- Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, Bethesda, MD, USA
| | | | | | - Hugo D Critchley
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Elena Makovac
- Centre for Neuroimaging Science, Kings College London, London, UK
| | - Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Frances Meeten
- School of Psychology, University of Sussex, Brighton, UK
| | - Cristina Ottaviani
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- IRCCS Santa Lucia Foundation, Rome, Italy
| | - Tali M Ball
- Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Gregory A Fonzo
- Department of Psychiatry and Behavioral Sciences, The University of Texas at Austin Dell Medical School, Austin, TX, USA
| | | | - Murray B Stein
- Department of Psychiatry, School of Medicine and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Bart Larsen
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jennifer Harper
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Michael Myers
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Michael T Perino
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Qiongru Yu
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dan J Stein
- South African Medical Research Council Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Nic J A Van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Anderson M Winkler
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
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71
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Isen J, Perera-Ortega A, Vos SB, Rodionov R, Kanber B, Chowdhury FA, Duncan JS, Mousavi P, Winston GP. Non-parametric combination of multimodal MRI for lesion detection in focal epilepsy. NEUROIMAGE-CLINICAL 2021; 32:102837. [PMID: 34619650 PMCID: PMC8503566 DOI: 10.1016/j.nicl.2021.102837] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/10/2021] [Accepted: 09/20/2021] [Indexed: 12/21/2022]
Abstract
Multivariate voxel-based analysis useful for lesion detection in focal epilepsy. Non-parametric combination algorithm used to combine data from various MR sequences. Successful lesion detection demonstrated in MRI-positive and MRI-negative patients. Multimodal analysis detected abnormalities from diverse epileptogenic pathologies. Sensitivity of multivariate analysis notably higher than univariate analyses.
One third of patients with medically refractory focal epilepsy have normal-appearing MRI scans. This poses a problem as identification of the epileptogenic region is required for surgical treatment. This study performs a multimodal voxel-based analysis (VBA) to identify brain abnormalities in MRI-negative focal epilepsy. Data was collected from 69 focal epilepsy patients (42 with discrete lesions on MRI scans, 27 with no visible findings on scans), and 62 healthy controls. MR images comprised T1-weighted, fluid-attenuated inversion recovery (FLAIR), fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging, and neurite density index (NDI) from neurite orientation dispersion and density imaging. These multimodal images were coregistered to T1-weighted scans, normalized to a standard space, and smoothed with 8 mm FWHM. Initial analysis performed voxel-wise one-tailed t-tests separately on grey matter concentration (GMC), FLAIR, FA, MD, and NDI, comparing patients with epilepsy to controls. A multimodal non-parametric combination (NPC) analysis was also performed simultaneously on FLAIR, FA, MD, and NDI. Resulting p-maps were family-wise error rate corrected, threshold-free cluster enhanced, and thresholded at p < 0.05. Sensitivity was established through visual comparison of results to manually drawn lesion masks or seizure onset zone (SOZ) from stereoelectroencephalography. A leave-one-out cross-validation with the same analysis protocols was performed on controls to determine specificity. NDI was the best performing individual modality, detecting focal abnormalities in 38% of patients with normal MRI and conclusive SOZ. GMC demonstrated the lowest sensitivity at 19%. NPC provided superior performance to univariate analyses with 50% sensitivity. Specificity in controls ranged between 96 and 100% for all analyses. This study demonstrated the utility of a multimodal VBA utilizing NPC for detecting epileptogenic lesions in MRI-negative focal epilepsy. Future work will apply this approach to datasets from other centres and will experiment with different combinations of MR sequences.
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Affiliation(s)
- Jonah Isen
- School of Computing, Queen's University, Kingston, Canada
| | | | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London, London, UK; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK
| | - Baris Kanber
- Centre for Medical Image Computing, University College London, London, UK; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - Parvin Mousavi
- School of Computing, Queen's University, Kingston, Canada
| | - Gavin P Winston
- School of Computing, Queen's University, Kingston, Canada; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK; Department of Medicine, Division of Neurology & Centre for Neuroscience Studies, Queen's University, Kingston, Canada.
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72
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Tackley G, Kong Y, Minne R, Messina S, Winkler A, Cavey A, Everett R, DeLuca GC, Weir A, Craner M, Tracey I, Palace J, Stagg CJ, Emir U. An In-vivo 1H-MRS short-echo time technique at 7T: Quantification of metabolites in chronic multiple sclerosis and neuromyelitis optica brain lesions and normal appearing brain tissue. Neuroimage 2021; 238:118225. [PMID: 34062267 PMCID: PMC7611458 DOI: 10.1016/j.neuroimage.2021.118225] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 03/09/2021] [Accepted: 05/29/2021] [Indexed: 11/05/2022] Open
Abstract
Magnetic Resonance Spectroscopy (MRS) allows for the non-invasive quantification of neurochemicals and has the potential to differentiate between the pathologically distinct diseases, multiple sclerosis (MS) and AQP4Ab-positive neuromyelitis optica spectrum disorder (AQP4Ab-NMOSD). In this study we characterised the metabolite profiles of brain lesions in 11 MS and 4 AQP4Ab-NMOSD patients using an optimised MRS methodology at ultra-high field strength (7T) incorporating correction for T2 water relaxation differences between lesioned and normal tissue. MS metabolite results were in keeping with the existing literature: total N-acetylaspartate (NAA) was lower in lesions compared to normal appearing brain white matter (NAWM) with reciprocal findings for myo-Inositol. An unexpected subtlety revealed by our technique was that total NAA differences were likely driven by NAA-glutamate (NAAG), a ubiquitous CNS molecule with functions quite distinct from NAA though commonly quantified together with NAA in MRS studies as total NAA. Surprisingly, AQP4Ab-NMOSD showed no significant differences for total NAA, NAA, NAAG or myo-Inositol between lesion and NAWM sites, nor were there any differences between MS and AQP4Ab-NMOSD for a priori hypotheses. Post-hoc testing revealed a significant correlation between NAWM Ins:NAA and disability (as measured by EDSS) for disease groups combined, driven by the AP4Ab-NMOSD group. Utilising an optimised MRS methodology, our study highlights some under-explored subtleties in MRS profiles, such as the absence of myo-Inositol concentration differences in AQP4Ab-NMOSD brain lesions versus NAWM and the potential influence of NAAG differences between lesions and normal appearing white matter in MS.
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Affiliation(s)
- George Tackley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, CF24 4HQ, United Kingdom.
| | - Yazhuo Kong
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; CAS Key Laboratory of Behavioural Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rachel Minne
- School of Health Sciences, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, (765) 494-1419, United States
| | - Silvia Messina
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Anderson Winkler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, United States
| | - Ana Cavey
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Rosie Everett
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Gabriele C DeLuca
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Andrew Weir
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Matthew Craner
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Irene Tracey
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Jacqueline Palace
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, OX1 3TH, United Kingdom
| | - Uzay Emir
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; School of Health Sciences, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, (765) 494-1419, United States; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
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73
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Song X, García-Saldivar P, Kindred N, Wang Y, Merchant H, Meguerditchian A, Yang Y, Stein EA, Bradberry CW, Ben Hamed S, Jedema HP, Poirier C. Strengths and challenges of longitudinal non-human primate neuroimaging. Neuroimage 2021; 236:118009. [PMID: 33794361 PMCID: PMC8270888 DOI: 10.1016/j.neuroimage.2021.118009] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 03/16/2021] [Accepted: 03/23/2021] [Indexed: 01/20/2023] Open
Abstract
Longitudinal non-human primate neuroimaging has the potential to greatly enhance our understanding of primate brain structure and function. Here we describe its specific strengths, compared to both cross-sectional non-human primate neuroimaging and longitudinal human neuroimaging, but also its associated challenges. We elaborate on factors guiding the use of different analytical tools, subject-specific versus age-specific templates for analyses, and issues related to statistical power.
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Affiliation(s)
- Xiaowei Song
- Preclinical Pharmacology Section, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Pamela García-Saldivar
- Instituto de Neurobiología, UNAM, Campus Juriquilla. Boulevard Juriquilla No. 3001 Querétaro, Qro. 76230, México
| | - Nathan Kindred
- Biosciences Institute & Centre for Behaviour and Evolution, Faculty of Medical Sciences, Newcastle University, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, United Kingdom
| | - Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla. Boulevard Juriquilla No. 3001 Querétaro, Qro. 76230, México
| | - Adrien Meguerditchian
- Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille/CNRS, Institut Language, Communication and the Brain 13331 Marseille, France
| | - Yihong Yang
- Neuroimaging Research Branch, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Elliot A Stein
- Neuroimaging Research Branch, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Charles W Bradberry
- Preclinical Pharmacology Section, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR 5229, Université de Lyon - CNRS, France
| | - Hank P Jedema
- Preclinical Pharmacology Section, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA.
| | - Colline Poirier
- Biosciences Institute & Centre for Behaviour and Evolution, Faculty of Medical Sciences, Newcastle University, United Kingdom.
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74
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Tu Y, Ta D, Lu ZL, Wang Y. Topology-preserving smoothing of retinotopic maps. PLoS Comput Biol 2021; 17:e1009216. [PMID: 34339414 PMCID: PMC8360528 DOI: 10.1371/journal.pcbi.1009216] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 08/12/2021] [Accepted: 06/27/2021] [Indexed: 11/18/2022] Open
Abstract
Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology that the mapping is topological (i.e., the topology of neighborhood connectivity is preserved) within each visual area, retinotopic maps derived from the state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The violation of topological condition is most severe in cortical regions corresponding to the neighborhood of the fovea (e.g., < 1 degree eccentricity in the Human Connectome Project (HCP) dataset), significantly impeding accurate analysis of retinotopic maps. This study aims to directly model the topological condition and generate topology-preserving and smooth retinotopic maps. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to define the topological condition, developed a mathematical model to quantify topological smoothing as a constrained optimization problem, and elaborated an efficient numerical method to solve the problem. The method was then applied to V1, V2, and V3 simultaneously in the HCP dataset. Experiments with both simulated and real retinotopy data demonstrated that the proposed method could generate topological and smooth retinotopic maps.
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Affiliation(s)
- Yanshuai Tu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Duyan Ta
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Zhong-Lin Lu
- Division of Arts and Sciences, New York University Shanghai, Shanghai, China
- Center for Neural Science and Department of Psychology, New York University, New York, United States of America
- NYU-ECNU Institute of Brain and Cognitive Science, NYU Shanghai, Shanghai, China
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
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75
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Ely BA, Nguyen TNB, Tobe RH, Walker AM, Gabbay V. Multimodal Investigations of Reward Circuitry and Anhedonia in Adolescent Depression. Front Psychiatry 2021; 12:678709. [PMID: 34366915 PMCID: PMC8345280 DOI: 10.3389/fpsyt.2021.678709] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 06/15/2021] [Indexed: 02/01/2023] Open
Abstract
Depression is a highly prevalent condition with devastating personal and public health consequences that often first manifests during adolescence. Though extensively studied, the pathogenesis of depression remains poorly understood, and efforts to stratify risks and identify optimal interventions have proceeded slowly. A major impediment has been the reliance on an all-or-nothing categorical diagnostic scheme based solely on whether a patient endorses an arbitrary number of common symptoms for a sufficiently long period. This approach masks the well-documented heterogeneity of depression, a disorder that is highly variable in presentation, severity, and course between individuals and is frequently comorbid with other psychiatric conditions. In this targeted review, we outline the limitations of traditional diagnosis-based research and instead advocate an alternative approach centered around symptoms as unique dimensions of clinical dysfunction that span across disorders and more closely reflect underlying neurobiological abnormalities. In particular, we highlight anhedonia-the reduced ability to anticipate and experience pleasure-as a specific, quantifiable index of reward dysfunction and an ideal candidate for dimensional investigation. Anhedonia is a core symptom of depression but also a salient feature of numerous other conditions, and its severity varies widely within clinical and even healthy populations. Similarly, reward dysfunction is a hallmark of depression but is evident across many psychiatric conditions. Reward function is especially relevant in adolescence, a period characterized by exaggerated reward-seeking behaviors and rapid maturation of neural reward circuitry. We detail extensive work by our research group and others to investigate the neural and systemic factors contributing to reward dysfunction in youth, including our cumulative findings using multiple neuroimaging and immunological measures to study depressed adolescents but also trans-diagnostic cohorts with diverse psychiatric symptoms. We describe convergent evidence that reward dysfunction: (a) predicts worse clinical outcomes, (b) is associated with functional and chemical abnormalities within and beyond the neural reward circuitry, (c) is linked to elevated peripheral levels of inflammatory biomarkers, and (d) manifests early in the course of illness. Emphasis is placed on high-resolution neuroimaging techniques, comprehensive immunological assays, and data-driven analyses to fully capture and characterize the complex, interconnected nature of these systems and their contributions to adolescent reward dysfunction.
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Affiliation(s)
- Benjamin A. Ely
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Tram N. B. Nguyen
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Russell H. Tobe
- Department of Clinical Research, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States
| | - Audrey M. Walker
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Vilma Gabbay
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Clinical Research, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States
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76
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Baxter L, Moultrie F, Fitzgibbon S, Aspbury M, Mansfield R, Bastiani M, Rogers R, Jbabdi S, Duff E, Slater R. Functional and diffusion MRI reveal the neurophysiological basis of neonates' noxious-stimulus evoked brain activity. Nat Commun 2021; 12:2744. [PMID: 33980860 PMCID: PMC8115252 DOI: 10.1038/s41467-021-22960-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 04/05/2021] [Indexed: 11/20/2022] Open
Abstract
Understanding the neurophysiology underlying neonatal responses to noxious stimulation is central to improving early life pain management. In this neonatal multimodal MRI study, we use resting-state and diffusion MRI to investigate inter-individual variability in noxious-stimulus evoked brain activity. We observe that cerebral haemodynamic responses to experimental noxious stimulation can be predicted from separately acquired resting-state brain activity (n = 18). Applying this prediction model to independent Developing Human Connectome Project data (n = 215), we identify negative associations between predicted noxious-stimulus evoked responses and white matter mean diffusivity. These associations are subsequently confirmed in the original noxious stimulation paradigm dataset, validating the prediction model. Here, we observe that noxious-stimulus evoked brain activity in healthy neonates is coupled to resting-state activity and white matter microstructure, that neural features can be used to predict responses to noxious stimulation, and that the dHCP dataset could be utilised for future exploratory research of early life pain system neurophysiology.
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Affiliation(s)
- Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Fiona Moultrie
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Sean Fitzgibbon
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | | | - Matteo Bastiani
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Richard Rogers
- Nuffield Department of Anaesthetics, John Radcliffe Hospital, Oxford, UK
| | - Saad Jbabdi
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Eugene Duff
- Department of Paediatrics, University of Oxford, Oxford, UK
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK.
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77
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Warren DE, Rangel AJ, Christopher-Hayes NJ, Eastman JA, Frenzel MR, Stephen JM, Calhoun VD, Wang YP, Wilson TW. Resting-state functional connectivity of the human hippocampus in periadolescent children: Associations with age and memory performance. Hum Brain Mapp 2021; 42:3620-3642. [PMID: 33978276 PMCID: PMC8249892 DOI: 10.1002/hbm.25458] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 12/12/2022] Open
Abstract
The hippocampus is necessary for declarative (relational) memory, and the ability to form hippocampal‐dependent memories develops through late adolescence. This developmental trajectory of hippocampal‐dependent memory could reflect maturation of intrinsic functional brain networks, but resting‐state functional connectivity (rs‐FC) of the human hippocampus is not well‐characterized for periadolescent children. Measuring hippocampal rs‐FC in periadolescence would thus fill a gap, and testing covariance of hippocampal rs‐FC with age and memory could inform theories of cognitive development. Here, we studied hippocampal rs‐FC in a cross‐sectional sample of healthy children (N = 96; 59 F; age 9–15 years) using a seed‐based approach, and linked these data with NIH Toolbox measures, the Picture‐Sequence Memory Test (PSMT) and the List Sorting Working Memory Test (LSWMT). The PSMT was expected to rely more on hippocampal‐dependent memory than the LSWMT. We observed hippocampal rs‐FC with an extensive brain network including temporal, parietal, and frontal regions. This pattern was consistent with prior work measuring hippocampal rs‐FC in younger and older samples. We also observed novel, regionally specific variation in hippocampal rs‐FC with age and hippocampal‐dependent memory but not working memory. Evidence consistent with these findings was observed in a second, validation dataset of similar‐age healthy children drawn from the Philadelphia Neurodevelopment Cohort. Further, a cross‐dataset analysis suggested generalizable properties of hippocampal rs‐FC and covariance with age and memory. Our findings connect prior work by describing hippocampal rs‐FC and covariance with age and memory in typically developing periadolescent children, and our observations suggest a developmental trajectory for brain networks that support hippocampal‐dependent memory.
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Affiliation(s)
- David E Warren
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Anthony J Rangel
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | | | - Jacob A Eastman
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Michaela R Frenzel
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | | | - Vince D Calhoun
- The Mind Research Network, Albuquerque, New Mexico, USA.,Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | | | - Tony W Wilson
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA.,Boys Town National Research Hospital, Boys Town, Nebraska, USA
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78
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Ely BA, Liu Q, DeWitt SJ, Mehra LM, Alonso CM, Gabbay V. Data-driven parcellation and graph theory analyses to study adolescent mood and anxiety symptoms. Transl Psychiatry 2021; 11:266. [PMID: 33941762 PMCID: PMC8093238 DOI: 10.1038/s41398-021-01321-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 12/31/2020] [Accepted: 02/01/2021] [Indexed: 02/03/2023] Open
Abstract
Adolescence is a period of rapid brain development when psychiatric symptoms often first emerge. Studying adolescents may therefore facilitate the identification of neural alterations early in the course of psychiatric conditions. Here, we sought to utilize new, high-quality brain parcellations and data-driven graph theory approaches to characterize associations between resting-state networks and the severity of depression, anxiety, and anhedonia symptoms-salient features across psychiatric conditions. As reward circuitry matures considerably during adolescence, we examined both Whole Brain and three task-derived reward networks. Subjects were 87 psychotropic-medication-free adolescents (age = 12-20) with diverse psychiatric conditions (n = 68) and healthy controls (n = 19). All completed diagnostic interviews, dimensional clinical assessments, and 3T resting-state fMRI (10 min/2.3 mm/TR = 1 s). Following high-quality Human Connectome Project-style preprocessing, multimodal surface matching (MSMAll) alignment, and parcellation via the Cole-Anticevic Brain-wide Network Partition, weighted graph theoretical metrics (Strength Centrality = CStr; Eigenvector Centrality = CEig; Local Efficiency = ELoc) were estimated within each network. Associations with symptom severity and clinical status were assessed non-parametrically (two-tailed pFWE < 0.05). Across subjects, depression scores correlated with ventral striatum CStr within the Reward Attainment network, while anticipatory anhedonia correlated with CStr and ELoc in the subgenual anterior cingulate, dorsal anterior cingulate, orbitofrontal cortex, caudate, and ventral striatum across multiple networks. Group differences and associations with anxiety were not detected. Using detailed functional and clinical measures, we found that adolescent depression and anhedonia involve increased influence and communication efficiency in prefrontal and limbic reward areas. Resting-state network properties thus reflect positive valence system anomalies related to discrete reward sub-systems and processing phases early in the course of illness.
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Affiliation(s)
- Benjamin A. Ely
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY USA
| | - Qi Liu
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY USA
| | - Samuel J. DeWitt
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Lushna M. Mehra
- Department of Psychology, Florida State University, Tallahassee, FL USA
| | - Carmen M. Alonso
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY USA
| | - Vilma Gabbay
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA. .,Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
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79
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Multimodal assessment of white matter microstructure in antipsychotic-naïve schizophrenia patients and confounding effects of recreational drug use. Brain Imaging Behav 2021; 15:36-48. [PMID: 31909444 DOI: 10.1007/s11682-019-00230-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Cerebral white matter (WM) aberrations in schizophrenia have been linked to multiple neurobiological substrates but the underlying mechanisms remain unknown. Moreover, antipsychotic treatment and substance use constitute potential confounders. Multimodal studies using diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) may provide deeper insight into the whole brain WM pathophysiology in schizophrenia. We combined DTI and MTI to investigate WM integrity in 51 antipsychotic-naïve, first-episode schizophrenia patients and 55 matched healthy controls, using 3 T magnetic resonance imaging (MRI). Psychopathology was assessed with the positive and negative syndrome scale (PANSS). A whole brain partial least squares correlation (PLSC) method was used to conjointly analyze DTI-derived measures (fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mode of anisotropy (MO)) and the magnetization transfer ratio (MTR) to identify group differences, and associations with psychopathology. In secondary analyses, we excluded recreational substance users from both groups resulting in 34 patients and 51 healthy controls. The primary PLSC group difference analysis identified a significant pattern of lower FA, AD, MO and higher RD in patients (p = 0.04). This pattern suggests disorganized WM microstructure in patients. The secondary PLSC group difference analysis without recreational substance users revealed a significant pattern of lower FA and higher AD, RD, MO, MTR in patients (p = 0.04). This pattern in the substance free patients is consistent with higher extracellular free-water concentrations, which may reflect neuroinflammation. No significant associations with psychopathology were observed. Recreational substance use appears to be a confounding issue, which calls for attention in future WM studies.
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80
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Lazari A, Lipp I. Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology. Neuroimage 2021; 230:117744. [PMID: 33524576 PMCID: PMC8063174 DOI: 10.1016/j.neuroimage.2021.117744] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/05/2021] [Accepted: 01/09/2021] [Indexed: 12/16/2022] Open
Abstract
Recent years have seen an increased understanding of the importance of myelination in healthy brain function and neuropsychiatric diseases. Non-invasive microstructural magnetic resonance imaging (MRI) holds the potential to expand and translate these insights to basic and clinical human research, but the sensitivity and specificity of different MR markers to myelination is a subject of debate. To consolidate current knowledge on the topic, we perform a systematic review and meta-analysis of studies that validate microstructural imaging by combining it with myelin histology. We find meta-analytic evidence for correlations between various myelin histology metrics and markers from different MRI modalities, including fractional anisotropy, radial diffusivity, macromolecular pool, magnetization transfer ratio, susceptibility and longitudinal relaxation rate, but not mean diffusivity. Meta-analytic correlation effect sizes range widely, between R2 = 0.26 and R2 = 0.82. However, formal comparisons between MRI-based myelin markers are limited by methodological variability, inconsistent reporting and potential for publication bias, thus preventing the establishment of a single most sensitive strategy to measure myelin with MRI. To facilitate further progress, we provide a detailed characterisation of the evaluated studies as an online resource. We also share a set of 12 recommendations for future studies validating putative MR-based myelin markers and deploying them in vivo in humans.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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81
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Berry SC, Wise RG, Lawrence AD, Lancaster TM. Extended-amygdala intrinsic functional connectivity networks: A population study. Hum Brain Mapp 2021; 42:1594-1616. [PMID: 33314443 PMCID: PMC7978137 DOI: 10.1002/hbm.25314] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 11/12/2020] [Accepted: 11/30/2020] [Indexed: 12/17/2022] Open
Abstract
Pre-clinical and human neuroimaging research implicates the extended-amygdala (ExtA) (including the bed nucleus of the stria terminalis [BST] and central nucleus of the amygdala [CeA]) in networks mediating negative emotional states associated with stress and substance-use behaviours. The extent to which individual ExtA structures form a functionally integrated unit is controversial. We utilised a large sample (n > 1,000 healthy young adult humans) to compare the intrinsic functional connectivity networks (ICNs) of the BST and CeA using task-free functional magnetic resonance imaging (fMRI) data from the Human Connectome Project. We assessed whether inter-individual differences within these ICNs were related to two principal components representing negative disposition and alcohol use. Building on recent primate evidence, we tested whether within BST-CeA intrinsic functional connectivity (iFC) was heritable and further examined co-heritability with our principal components. We demonstrate the BST and CeA to have discrete, but largely overlapping ICNs similar to previous findings. We found no evidence that within BST-CeA iFC was heritable; however, post hoc analyses found significant BST iFC heritability with the broader superficial and centromedial amygdala regions. There were no significant correlations or co-heritability associations with our principal components either across the ICNs or for specific BST-Amygdala iFC. Possible differences in phenotype associations across task-free, task-based, and clinical fMRI are discussed, along with suggestions for more causal investigative paradigms that make use of the now well-established ExtA ICNs.
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Affiliation(s)
- Samuel C. Berry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Richard G. Wise
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences"G. D'Annunzio University" of Chieti‐PescaraChietiItaly
| | - Andrew D. Lawrence
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
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Zitser J, Anatürk M, Zsoldos E, Mahmood A, Filippini N, Suri S, Leng Y, Yaffe K, Singh-Manoux A, Kivimaki M, Ebmeier K, Sexton C. Sleep duration over 28 years, cognition, gray matter volume, and white matter microstructure: a prospective cohort study. Sleep 2021; 43:5697049. [PMID: 31904084 PMCID: PMC7215267 DOI: 10.1093/sleep/zsz290] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 10/28/2019] [Indexed: 11/24/2022] Open
Abstract
Study Objectives To examine the association between sleep duration trajectories over 28 years and measures of cognition, gray matter volume, and white matter microstructure. We hypothesize that consistently meeting sleep guidelines that recommend at least 7 hours of sleep per night will be associated with better cognition, greater gray matter volumes, higher fractional anisotropy, and lower radial diffusivity values. Methods We studied 613 participants (age 42.3 ± 5.03 years at baseline) who self-reported sleep duration at five time points between 1985 and 2013, and who had cognitive testing and magnetic resonance imaging administered at a single timepoint between 2012 and 2016. We applied latent class growth analysis to estimate membership into trajectory groups based on self-reported sleep duration over time. Analysis of gray matter volumes was carried out using FSL Voxel-Based-Morphometry and white matter microstructure using Tract Based Spatial Statistics. We assessed group differences in cognitive and MRI outcomes using nonparametric permutation testing. Results Latent class growth analysis identified four trajectory groups, with an average sleep duration of 5.4 ± 0.2 hours (5%, N = 29), 6.2 ± 0.3 hours (37%, N = 228), 7.0 ± 0.2 hours (45%, N = 278), and 7.9 ± 0.3 hours (13%, N = 78). No differences in cognition, gray matter, and white matter measures were detected between groups. Conclusions Our null findings suggest that current sleep guidelines that recommend at least 7 hours of sleep per night may not be supported in relation to an association between sleep patterns and cognitive function or brain structure.
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Affiliation(s)
- Jennifer Zitser
- Department of Neurology, Global Brain Health Institute, Memory and Aging Center, University of California, San Francisco, CA.,Department of Neurology, Movement Disorders Unit, Tel Aviv Sourazky Medical Center, Affiliated to the Sackler Faculty of Medicine, Tel-Aviv University, Israel
| | - Melis Anatürk
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.,FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Nicola Filippini
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Sana Suri
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Yue Leng
- Department of Neurology, Global Brain Health Institute, Memory and Aging Center, University of California, San Francisco, CA.,Department of Psychiatry, University of California, San Francisco, CA
| | - Kristine Yaffe
- Department of Psychiatry, Neurology and Epidemiology, University of California, San Francisco, CA
| | - Archana Singh-Manoux
- Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Paris, France.,Department of Epidemiology and Public Health, University College London, London, UK
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Klaus Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Claire Sexton
- Department of Neurology, Global Brain Health Institute, Memory and Aging Center, University of California, San Francisco, CA.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
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83
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Deep brain stimulation response in obsessive-compulsive disorder is associated with preoperative nucleus accumbens volume. NEUROIMAGE-CLINICAL 2021; 30:102640. [PMID: 33799272 PMCID: PMC8044711 DOI: 10.1016/j.nicl.2021.102640] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/16/2021] [Accepted: 03/17/2021] [Indexed: 12/11/2022]
Abstract
Preoperative MRI was associated with 12-months DBS treatment outcome in OCD patients. Larger nucleus accumbens volume was associated with larger clinical improvement. Machine learning analysis was not successful in predicting clinical improvement.
Background Deep brain stimulation (DBS) is a new treatment option for patients with therapy-resistant obsessive–compulsive disorder (OCD). Approximately 60% of patients benefit from DBS, which might be improved if a biomarker could identify patients who are likely to respond. Therefore, we evaluated the use of preoperative structural magnetic resonance imaging (MRI) in predicting treatment outcome for OCD patients on the group- and individual-level. Methods In this retrospective study, we analyzed preoperative MRI data of a large cohort of patients who received DBS for OCD (n = 57). We used voxel-based morphometry to investigate whether grey matter (GM) or white matter (WM) volume surrounding the DBS electrode (nucleus accumbens (NAc), anterior thalamic radiation), and whole-brain GM/WM volume were associated with OCD severity and response status at 12-month follow-up. In addition, we performed machine learning analyses to predict treatment outcome at an individual-level and evaluated its performance using cross-validation. Results Larger preoperative left NAc volume was associated with lower OCD severity at 12-month follow-up (pFWE < 0.05). None of the individual-level regression/classification analyses exceeded chance-level performance. Conclusions These results provide evidence that patients with larger NAc volumes show a better response to DBS, indicating that DBS success is partly determined by individual differences in brain anatomy. However, the results also indicate that structural MRI data alone does not provide sufficient information to guide clinical decision making at an individual level yet.
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84
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Geerligs L, Maris E. Improving the sensitivity of cluster-based statistics for functional magnetic resonance imaging data. Hum Brain Mapp 2021; 42:2746-2765. [PMID: 33724597 PMCID: PMC8127161 DOI: 10.1002/hbm.25399] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/20/2021] [Accepted: 02/21/2021] [Indexed: 12/11/2022] Open
Abstract
Because of the high dimensionality of neuroimaging data, identifying a statistical test that is both valid and maximally sensitive is an important challenge. Here, we present a combination of two approaches for functional magnetic resonance imaging (fMRI) data analysis that together result in substantial improvements of the sensitivity of cluster‐based statistics. The first approach is to create novel cluster definitions that optimize sensitivity to plausible effect patterns. The second is to adopt a new approach to combine test statistics with different sensitivity profiles, which we call the min(p) method. These innovations are made possible by using the randomization inference framework. In this article, we report on a set of simulations and analyses of real task fMRI data that demonstrate (a) that the proposed methods control the false‐alarm rate, (b) that the sensitivity profiles of cluster‐based test statistics vary depending on the cluster defining thresholds and cluster definitions, and (c) that the min(p) method for combining these test statistics results in a drastic increase of sensitivity (up to fivefold), compared to existing fMRI analysis methods. This increase in sensitivity is not at the expense of the spatial specificity of the inference.
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Affiliation(s)
- Linda Geerligs
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Eric Maris
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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85
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Herman JD, Wang C, Loos C, Yoon H, Rivera J, Dieterle ME, Haslwanter D, Jangra RK, Bortz RH, Bar KJ, Julg B, Chandran K, Lauffenburger D, Pirofski LA, Alter G. Functional Antibodies in COVID-19 Convalescent Plasma. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.03.08.21253157. [PMID: 33758875 PMCID: PMC7987034 DOI: 10.1101/2021.03.08.21253157] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Abstract
In the absence of an effective vaccine or monoclonal therapeutic, transfer of convalescent plasma (CCP) was proposed early in the SARS-CoV-2 pandemic as an easily accessible therapy. However, despite the global excitement around this historically valuable therapeutic approach, results from CCP trials have been mixed and highly debated. Unlike other therapeutic interventions, CCP represents a heterogeneous drug. Each CCP unit is unique and collected from an individual recovered COVID-19 patient, making the interpretation of therapeutic benefit more complicated. While the prevailing view in the field would suggest that it is administration of neutralizing antibodies via CCP that centrally provides therapeutic benefit to newly infected COVID-19 patients, many hospitalized COVID-19 patients already possess neutralizing antibodies. Importantly, the therapeutic benefit of antibodies can extend far beyond their simple ability to bind and block infection, especially related to their ability to interact with the innate immune system. In our work we deeply profiled the SARS-CoV-2-specific Fc-response in CCP donors, along with the recipients prior to and after CCP transfer, revealing striking SARS-CoV-2 specific Fc-heterogeneity across CCP units and their recipients. However, CCP units possessed more functional antibodies than acute COVID-19 patients, that shaped the evolution of COVID-19 patient humoral profiles via distinct immunomodulatory effects that varied by pre-existing SARS-CoV-2 Spike (S)-specific IgG titers in the patients. Our analysis identified surprising influence of both S and Nucleocapsid (N) specific antibody functions not only in direct antiviral activity but also in anti-inflammatory effects. These findings offer insights for more comprehensive interpretation of correlates of immunity in ongoing large scale CCP trials and for the design of next generation therapeutic design.
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Affiliation(s)
- Jonathan D. Herman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Division of Infectious Disease, Brigham and Women’s Hospital, Boston, MA, USA
| | - Chuangqi Wang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Carolin Loos
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hyunah Yoon
- Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY,USA
| | - Johanna Rivera
- Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY,USA
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - M. Eugenia Dieterle
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Denise Haslwanter
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Rohit K. Jangra
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Robert H. Bortz
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Katharine J. Bar
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Boris Julg
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Kartik Chandran
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Douglas Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Liise-anne Pirofski
- Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY,USA
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Galit Alter
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
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86
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Grill F, Nyberg L, Rieckmann A. Neural correlates of reward processing: Functional dissociation of two components within the ventral striatum. Brain Behav 2021; 11:e01987. [PMID: 33300306 PMCID: PMC7882172 DOI: 10.1002/brb3.1987] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 10/29/2020] [Accepted: 11/18/2020] [Indexed: 12/29/2022] Open
Abstract
INTRODUCTION Rewarding and punishing stimuli elicit BOLD responses in the affective division of the striatum. The responses typically traverse from the affective to the associative division of the striatum, suggesting an involvement of associative processes during the modulation of stimuli valance. In this study, we hypothesized that fMRI responses to rewards versus punishments in a guessing card game can be disassociated into two functional component processes that reflect the convergence of limbic and associative functional networks in the ventral striatum. METHODS We used fMRI data of 175 (92 female) subjects from the human connectome project´s gambling task, working memory task, and resting-state scans. A reward > punish contrast identified a ventral striatum cluster from which voxelwise GLM parameter estimates were entered into a k-means clustering algorithm. The k-means analysis supported separating the cluster into two spatially distinct components. These components were used as seeds to investigate their functional connectivity profile. GLM parameter estimates were extracted and compared from the task contrasts reward > punish and 2-back > 0-back from two ROIs in the ventral striatum and one ROI in hippocampus. RESULTS The analyses converged to show that a superior striatal component, coupled with the ventral attention and frontal control networks, was responsive to both a modulation of cognitive control in working memory and to rewards, whereas the most inferior part of the ventral striatum, coupled with the limbic and default mode networks including the hippocampus, was selectively responsive to rewards. CONCLUSION We show that the fMRI response to rewards in the ventral striatum reflects a mixture of component processes of reward. An inferior ventral striatal component and hippocampus are part of an intrinsically coupled network that responds to reward-based processing during gambling. The more superior ventral striatal component is intrinsically coupled to networks involved with executive functioning and responded to both reward and cognitive control demands.
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Affiliation(s)
- Filip Grill
- Department of Radiation Sciences, Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Lars Nyberg
- Department of Radiation Sciences, Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Anna Rieckmann
- Department of Radiation Sciences, Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
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87
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Lehmann N, Aye N, Kaufmann J, Heinze HJ, Düzel E, Ziegler G, Taubert M. Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter. Neuroscience 2021; 457:165-185. [PMID: 33465411 DOI: 10.1016/j.neuroscience.2021.01.005] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 02/06/2023]
Abstract
Diffusion-weighted magnetic resonance imaging (DWI) is undergoing constant evolution with the ambitious goal of developing in-vivo histology of the brain. A recent methodological advancement is Neurite Orientation Dispersion and Density Imaging (NODDI), a histologically validated multi-compartment model to yield microstructural features of brain tissue such as geometric complexity and neurite packing density, which are especially useful in imaging the white matter. Since NODDI is increasingly popular in clinical research and fields such as developmental neuroscience and neuroplasticity, it is of vast importance to characterize its reproducibility (or reliability). We acquired multi-shell DWI data in 29 healthy young subjects twice over a rescan interval of 4 weeks to assess the within-subject coefficient of variation (CVWS), between-subject coefficient of variation (CVBS) and the intraclass correlation coefficient (ICC), respectively. Using these metrics, we compared regional and voxel-by-voxel reproducibility of the most common image analysis approaches (tract-based spatial statistics [TBSS], voxel-based analysis with different extents of smoothing ["VBM-style"], ROI-based analysis). We observed high test-retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). Our findings also suggest that the choice of analysis approach might have significant consequences for the results of a study. Collectively, the voxel-based approach with Gaussian smoothing kernels of ≥4 mm FWHM and ROI-averaging yielded the highest reproducibility across NDI and ODI maps (CVWS mostly ≤3%, ICC mostly ≥0.8), respectively, whilst smaller kernels and TBSS performed consistently worse. Furthermore, we demonstrate that image quality (signal-to-noise ratio [SNR]) is an important determinant of NODDI metric reproducibility. We discuss the implications of these results for longitudinal and cross-sectional research designs commonly employed in the neuroimaging field.
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Affiliation(s)
- Nico Lehmann
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany.
| | - Norman Aye
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany
| | - Jörn Kaufmann
- Department of Neurology, Otto von Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Hans-Jochen Heinze
- Department of Neurology, Otto von Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany; Germany German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, 39120 Magdeburg, Germany; Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany; Leibniz-Institute for Neurobiology (LIN), Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Emrah Düzel
- Germany German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, 39120 Magdeburg, Germany; Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, Alexandra House, 17-19 Queen Square, Bloomsbury, London, WC1N 3AZ, UK
| | - Gabriel Ziegler
- Germany German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, 39120 Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Marco Taubert
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany; Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany
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88
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High-resolution connectomic fingerprints: Mapping neural identity and behavior. Neuroimage 2021; 229:117695. [PMID: 33422711 DOI: 10.1016/j.neuroimage.2020.117695] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 12/16/2020] [Accepted: 12/23/2020] [Indexed: 01/30/2023] Open
Abstract
Connectomes are typically mapped at low resolution based on a specific brain parcellation atlas. Here, we investigate high-resolution connectomes independent of any atlas, propose new methodologies to facilitate their mapping and demonstrate their utility in predicting behavior and identifying individuals. Using structural, functional and diffusion-weighted MRI acquired in 1000 healthy adults, we aimed to map the cortical correlates of identity and behavior at ultra-high spatial resolution. Using methods based on sparse matrix representations, we propose a computationally feasible high-resolution connectomic approach that improves neural fingerprinting and behavior prediction. Using this high-resolution approach, we find that the multimodal cortical gradients of individual uniqueness reside in the association cortices. Furthermore, our analyses identified a striking dichotomy between the facets of a person's neural identity that best predict their behavior and cognition, compared to those that best differentiate them from other individuals. Functional connectivity was one of the most accurate predictors of behavior, yet resided among the weakest differentiators of identity; whereas the converse was found for morphological properties, such as cortical curvature. This study provides new insights into the neural basis of personal identity and new tools to facilitate ultra-high-resolution connectomics.
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89
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Brown SSG, Mak E, Zaman S. Multi-Modal Imaging in Down's Syndrome: Maximizing Utility Through Innovative Neuroimaging Approaches. Front Neurol 2021; 11:629463. [PMID: 33488507 PMCID: PMC7817620 DOI: 10.3389/fneur.2020.629463] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 12/08/2020] [Indexed: 11/13/2022] Open
Abstract
In recent decades, the field of neuroimaging has experienced a surge of popularity and innovation which has led to significant advancements in the understanding of neurological disease, if not immediate clinical translation. In the case of Down's syndrome, a complex interplay of neurodevelopmental and neurodegenerative processes occur as a result of the trisomy of chromosome 21. The substantial potential impact of improved clinical intervention and the limited research under-taken to date make it a prime candidate for longitudinal neuroimaging-based study. However, as with a multitude of other multifaceted brain-based disorders, singular utilization of lone modality imaging has limited interpretability and applicability. Indeed, a present challenge facing the neuroimaging community as a whole is the methodological integration of multi-modal imaging to enhance clinical understanding. This review therefore aims to assess the current literature in Down's syndrome utilizing a multi-modal approach with regards to improvement upon consideration of a single modality. Additionally, we discuss potential avenues of future research that may effectively combine structural, functional and molecular-based imaging techniques for the significant benefit of the understanding of Down's syndrome pathology.
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Affiliation(s)
- Stephanie S. G. Brown
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Elijah Mak
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Shahid Zaman
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
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90
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Trauma-focused psychotherapy response in youth with posttraumatic stress disorder is associated with changes in insula volume. J Psychiatr Res 2021; 132:207-214. [PMID: 33189355 DOI: 10.1016/j.jpsychires.2020.10.037] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 10/04/2020] [Accepted: 10/26/2020] [Indexed: 02/04/2023]
Abstract
Randomized controlled trials have shown efficacy of trauma-focused psychotherapies in youth with posttraumatic stress disorder (PTSD), but little is known about the relationship between treatment response and alternations in brain structures associated with PTSD. In this study, we longitudinally examined the association between treatment response and pre-to posttreatment changes in structural magnetic resonance imaging (MRI) scans using a voxel-based morphometry approach. We analyzed MRI scans of 35 patients (ages 8-18 years, 21 female) with PTSD (80%) or partial PTSD (20%) before and after eight weekly sessions of trauma-focused psychotherapy. PTSD severity was assessed longitudinally using the Clinician-Administered PTSD scale for Children and Adolescents to divide participants into responders and non-responders. Group by time interaction analysis showed significant differences in grey-matter volume in the bilateral insula due to volume reductions over time in non-responders compared to responders. Despite the significant group by time interaction, there were no significant group differences at baseline or follow-up. As typical development is associated with insula volume increase, these longitudinal MRI findings suggest that treatment non-response is associated with atypical neurodevelopment of the insula, which may underlie persistence of PTSD in youth. The absence of structural MRI changes in treatment responders, while in need of replication, suggest that successful trauma-focused psychotherapy may not directly normalize brain abnormalities associated with PTSD.
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91
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Myrvang AD, Vangberg TR, Stedal K, Rø Ø, Endestad T, Rosenvinge JH, Aslaksen PM. Cerebral cortical thickness and surface area in adolescent anorexia nervosa: Separate and joint analyses with a permutation-based nonparametric method. Int J Eat Disord 2020; 54:561-568. [PMID: 33350512 DOI: 10.1002/eat.23448] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 11/12/2020] [Accepted: 12/07/2020] [Indexed: 12/29/2022]
Abstract
OBJECTIVE Reduction in cerebral volume is often found in underweight patients with anorexia nervosa (AN), but few studies have investigated other morphological measures. Cortical thickness (CTh) and surface area (CSA), often used to produce the measure of cortical volume, are developmentally distinct measures that may be differentially affected in AN, particularly in the developing brain. In the present study, we investigated CTh and CSA both separately and jointly to gain further insight into structural alterations in adolescent AN patients. METHOD Thirty female AN inpatients 12-18 years of age, and 27 age-matched healthy controls (HC) underwent structural magnetic resonance imaging. Group differences in CTh and CSA were investigated separately and jointly with a permutation-based nonparametric combination method (NPC) which may be more sensitive in detecting group differences compared to traditional volumetric methods. RESULTS Results showed significant reduction in in both CTh and CSA in several cortical regions in AN compared to HC and the reduction was related to BMI. Different results for the two morphological measures were found in a small number of cortical regions. The joint NPC analyses showed significant group differences across most of the cortical mantle. DISCUSSION Results from this study give novel insight to areal reduction in adolescent AN patients and indicate that both CTh and CSA reduction is related to BMI. The study is the first to use the NPC method to reveal large structural alterations covering most of the brain in adolescent AN.
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Affiliation(s)
- Anna D Myrvang
- Department of psychology, Faculty of Health Sciences, UiT The Artic University of Norway, Tromsø, Norway
| | - Torgil R Vangberg
- Department of Clinical Medicine, University Hospital of North Norway, Tromsø, Norway
- PET Center, University Hospital of North Norway, Tromsø, Norway
| | - Kristin Stedal
- Regional Department for Eating Disorders, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Øyvind Rø
- Regional Department for Eating Disorders, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Tor Endestad
- Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway
| | - Jan H Rosenvinge
- Department of psychology, Faculty of Health Sciences, UiT The Artic University of Norway, Tromsø, Norway
| | - Per M Aslaksen
- Department of psychology, Faculty of Health Sciences, UiT The Artic University of Norway, Tromsø, Norway
- Regional Center for Eating Disorders, University Hospital of North Norway, Tromsø, Norway
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Zohar T, Loos C, Fischinger S, Atyeo C, Wang C, Slein MD, Burke J, Yu J, Feldman J, Hauser BM, Caradonna T, Schmidt AG, Cai Y, Streeck H, Ryan ET, Barouch DH, Charles RC, Lauffenburger DA, Alter G. Compromised Humoral Functional Evolution Tracks with SARS-CoV-2 Mortality. Cell 2020; 183:1508-1519.e12. [PMID: 33207184 PMCID: PMC7608014 DOI: 10.1016/j.cell.2020.10.052] [Citation(s) in RCA: 224] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 09/15/2020] [Accepted: 10/29/2020] [Indexed: 12/19/2022]
Abstract
The urgent need for an effective SARS-CoV-2 vaccine has forced development to progress in the absence of well-defined correlates of immunity. While neutralization has been linked to protection against other pathogens, whether neutralization alone will be sufficient to drive protection against SARS-CoV-2 in the broader population remains unclear. Therefore, to fully define protective humoral immunity, we dissected the early evolution of the humoral response in 193 hospitalized individuals ranging from moderate to severe. Although robust IgM and IgA responses evolved in both survivors and non-survivors with severe disease, non-survivors showed attenuated IgG responses, accompanied by compromised Fcɣ receptor binding and Fc effector activity, pointing to deficient humoral development rather than disease-enhancing humoral immunity. In contrast, individuals with moderate disease exhibited delayed responses that ultimately matured. These data highlight distinct humoral trajectories associated with resolution of SARS-CoV-2 infection and the need for early functional humoral immunity.
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Affiliation(s)
- Tomer Zohar
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Carolin Loos
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stephanie Fischinger
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA,PhD Program in Immunology and Virology, University of Duisburg-Essen, Essen, Germany
| | - Caroline Atyeo
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA,PhD Program in Virology, Division of Medical Sciences, Harvard University, Boston, MA, USA
| | - Chuangqi Wang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - John Burke
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Jingyou Yu
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard, Medical School, Boston, MA 02215, USA
| | - Jared Feldman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | | | - Tim Caradonna
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | | | - Yongfei Cai
- Division of Molecular Medicine, Boston Children’s Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Hendrik Streeck
- Institute of Virology, University Hospital, University of Bonn and German Center for Infection Research (DZIF), Bonn-Cologne, Bonn, Germany
| | - Edward T. Ryan
- Infectious Disease Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Dan H. Barouch
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard, Medical School, Boston, MA 02215, USA
| | - Richelle C. Charles
- Infectious Disease Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA,Corresponding author
| | - Douglas A. Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA,Corresponding author
| | - Galit Alter
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA.
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93
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Alfred KL, Hillis ME, Kraemer DJM. Individual Differences in the Neural Localization of Relational Networks of Semantic Concepts. J Cogn Neurosci 2020; 33:390-401. [PMID: 33284078 DOI: 10.1162/jocn_a_01657] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Semantic concepts relate to each other to varying degrees to form a network of zero-order relations, and these zero-order relations serve as input into networks of general relation types as well as higher order relations. Previous work has studied the neural mapping of semantic concepts across domains, although much work remains to be done to understand how the localization and structure of those architectures differ depending on various individual differences in attentional bias toward different content presentation formats. Using an item-wise model of semantic distance of zero-order relations (Word2vec) between stimuli (presented both in word and picture forms), we used representational similarity analysis to identify individual differences in the neural localization of semantic concepts and how those localization differences can be predicted by individual variance in the degree to which individuals attend to word information instead of pictures. Importantly, there were no reliable representations of this zero-order semantic relational network when looking at the full group, and it was only through considering individual differences that a stable localization difference became evident. These results indicate that individual differences in the degree to which a person habitually attends to word information instead of picture information substantially affects the neural localization of zero-order semantic representations.
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94
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Aslan K, Gunbey HP, Cortcu S, Ozyurt O, Avci U, Incesu L. Diffusion tensor imaging in hyperthyroidism: assessment of microstructural white matter abnormality with a tract-based spatial statistical analysis. Acta Radiol 2020; 61:1677-1683. [PMID: 32202136 DOI: 10.1177/0284185120909960] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Metabolic, morphological, and functional brain changes associated with a neurological deficit in hyperthyroidism have been observed. However, changes in microstructural white matter (WM), which can explain the underlying pathophysiology of brain dysfunctions, have not been researched. PURPOSE To assess microstructural WM abnormality in patients with untreated or newly diagnosed hyperthyroidism using tract-based spatial statistics (TBSS). MATERIAL AND METHODS Eighteen patients with hyperthyroidism and 14 age- and sex-matched healthy controls were included in this study. TBSS were used in this diffusion tensor imaging study for a whole-brain voxel-wise analysis of fractional anisotropy, mean diffusivity, axial diffusivity (AD), and radial diffusivity (RD) of WM. RESULTS When compared to the control group, TBSS showed a significant increase in the RD of the corpus callosum, anterior and posterior corona radiata, posterior thalamic radiation, cingulum, superior longitudinal fasciculus, and the retrolenticular region of the internal capsule in patients with hyperthyroidism (P < 0.05), as well as a significant decrease in AD in the anterior corona radiata and the genu of corpus callosum (P < 0.05). CONCLUSION This study showed that more regions are affected by the RD increase than the AD decrease in the WM tracts of patients with hyperthyroidism. These preliminary results suggest that demyelination is the main mechanism of microstructural alterations in the WM of hyperthyroid patients.
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Affiliation(s)
- Kerim Aslan
- Department of Radiology, Ondokuz Mayis University Faculty of Medicine, Samsun, Turkey
| | - Hediye Pinar Gunbey
- Department of Radiology, Health Sciences University Kartal Lütfi Kırdar Training and Research Hospital, Istanbul, Turkey
| | - Sumeyra Cortcu
- Department of Radiology, Kastamonu State Hospital, Kastamonu, Turkey
| | - Onur Ozyurt
- Telemed Solutions Teknopark, Bogazici University, İstanbul, Turkey
| | - Ugur Avci
- Department of Endocrinology and Metabolism, Recep Tayyip Erdogan University Faculty of Medicine, Rize, Turkey
| | - Lutfi Incesu
- Department of Radiology, Ondokuz Mayis University Faculty of Medicine, Samsun, Turkey
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95
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Filip P, Vojtíšek L, Baláž M, Mangia S, Michaeli S, Šumec R, Bareš M. Differential diagnosis of tremor syndromes using MRI relaxometry. Parkinsonism Relat Disord 2020; 81:190-193. [PMID: 33186797 DOI: 10.1016/j.parkreldis.2020.10.048] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 10/21/2020] [Accepted: 10/31/2020] [Indexed: 01/08/2023]
Abstract
Differential diagnosis of the most common tremor syndromes - essential tremor (ET) and Parkinson's disease (PD) is burdened with high error rate. However, diagnostic MRI biomarkers applicable in this clinically highly relevant scenario remain an unfulfilled objective. The presented study was designed in search for possible candidate MRI protocols relevant for differential diagnostic process in tremor syndromes.10 non-advanced tremor-dominant PD patients meeting diagnostic criteria for clinically established PD, 12 isolated ET patients and 16 healthy controls were enrolled into this study. The study focused on relaxation MRI protocols - T1, T2, adiabatic T1ρ and adiabatic T2ρ due to their relatively low post-processing requirements enabling implementation into routine clinical practice. Compared to ET, PD patients had significantly longer T2 relaxation times in striata with dominant findings in the putamen contralateral to the clinically more affected body side. This difference was driven by alterations in the PD group as confirmed in the complementary comparison with healthy controls. According to the receiver operating characteristic analysis, this region provided a reasonable sensitivity of 0.91 and specificity of 0.89 in the differential diagnosis of PD and ET. In PD patients, we further found prolonged T1ρ in the substantia nigra compared to ET and healthy controls, and shorter T2 and T2ρ in the cerebellum compared to healthy controls. T2 relaxation time in the putamen contralateral to the clinically more affected body side is a plausible candidate diagnostic marker for the differentiation of PD and ET.
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Affiliation(s)
- Pavel Filip
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic; First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic; International Clinical Research Center (ICRC), University Hospital of St. Anne, Brno, Czech Republic; Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.
| | - Lubomír Vojtíšek
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
| | - Marek Baláž
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic
| | - Silvia Mangia
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
| | - Shalom Michaeli
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
| | - Rastislav Šumec
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic; International Clinical Research Center (ICRC), University Hospital of St. Anne, Brno, Czech Republic; Department of Psychology and Psychosomatics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Martin Bareš
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic; Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, MN, USA
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96
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Bevan RLT, Budyn N, Zhang J, Croxford AJ, Kitazawa S, Wilcox PD. Data Fusion of Multiview Ultrasonic Imaging for Characterization of Large Defects. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2020; 67:2387-2401. [PMID: 32746190 DOI: 10.1109/tuffc.2020.3004982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The multiview total focusing method (TFM) enables a region of interest within a specimen to be imaged using different ray paths and wave-mode combinations. For defects larger than the ultrasonic wavelength, different portions of the same defect may manifest in a number of views. For a crack, the tip diffraction response may be evident in certain views and the specular reflection in others. Accurate characterization of large defects requires the information in multiple views to be combined. In this work, three data fusion methodologies are presented: a simple sum over all views, a sum weighted according to the inverse of the noise in each view, and a matched filter approach. Four large defects are examined; one stress corrosion crack (SCC), two weld cracks, and a pair of slagline defects in a weld. The matched filter (matched to a small circular void) provided significant improvement over the best individual view. The data fusion process incorporates artifact removal, where nondefect artifact signals within each image view are identified and masked, using a single defect-free data set for training. The matched filter was able to accurately visualize the full 3-D extent of the four defects, allowing characterization via the decibel drop method. When compared to X-ray computed tomography and micrograph data in the case of the SCC, the matched filter fusion provided excellent agreement. Its performance was also superior to any individual view while providing a single fused image that is easier for an operator to interpret than a set of multiview images.
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97
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Lehmann N, Villringer A, Taubert M. Intrinsic Connectivity Changes Mediate the Beneficial Effect of Cardiovascular Exercise on Sustained Visual Attention. Cereb Cortex Commun 2020; 1:tgaa075. [PMID: 34296135 PMCID: PMC8152900 DOI: 10.1093/texcom/tgaa075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 10/05/2020] [Accepted: 10/06/2020] [Indexed: 01/21/2023] Open
Abstract
Cardiovascular exercise (CE) is an evidence-based healthy lifestyle strategy. Yet, little is known about its effects on brain and cognition in young adults. Furthermore, evidence supporting a causal path linking CE to human cognitive performance via neuroplasticity is currently lacking. To understand the brain networks that mediate the CE-cognition relationship, we conducted a longitudinal, controlled trial with healthy human participants to compare the effects of a 2-week CE intervention against a non-CE control group on cognitive performance. Concomitantly, we used structural and functional magnetic resonance imaging to investigate the neural mechanisms mediating between CE and cognition. On the behavioral level, we found that CE improved sustained attention, but not processing speed or short-term memory. Using graph theoretical measures and statistical mediation analysis, we found that a localized increase in eigenvector centrality in the left middle frontal gyrus, probably reflecting changes within an attention-related network, conveyed the effect of CE on cognition. Finally, we found CE-induced changes in white matter microstructure that correlated with intrinsic connectivity changes (intermodal correlation). These results suggest that CE is a promising intervention strategy to improve sustained attention via brain plasticity in young, healthy adults.
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Affiliation(s)
- Nico Lehmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
- Department of Sport Science, Faculty of Human Sciences, Institute III, Otto von Guericke University, Magdeburg 39104, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
- Mind and Brain Institute, Charité and Humboldt University, Berlin 10117, Germany
| | - Marco Taubert
- Department of Sport Science, Faculty of Human Sciences, Institute III, Otto von Guericke University, Magdeburg 39104, Germany
- Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Magdeburg 39106, Germany
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98
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Mantel T, Altenmüller E, Li Y, Lee A, Meindl T, Jochim A, Zimmer C, Haslinger B. Structure-function abnormalities in cortical sensory projections in embouchure dystonia. NEUROIMAGE-CLINICAL 2020; 28:102410. [PMID: 32932052 PMCID: PMC7495104 DOI: 10.1016/j.nicl.2020.102410] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/29/2020] [Accepted: 08/30/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND Embouchure dystonia (ED) is a task-specific focal dystonia in professional brass players leading to abnormal orofacial muscle posturing/spasms during performance. Previous studies have outlined abnormal cortical sensorimotor function during sensory/motor tasks and in the resting state as well as abnormal cortical sensorimotor structure. Yet, potentially underlying white-matter tract abnormalities in this network disease are unknown. OBJECTIVE To delineate structure-function abnormalities within cerebral sensorimotor trajectories in ED. METHOD Probabilistic tractography and seed-based functional connectivity analysis were performed in 16/16 ED patients/healthy brass players within a simple literature-informed network model of cortical sensorimotor processing encompassing supplementary motor, superior parietal, primary somatosensory and motor cortex as well as the putamen. Post-hoc grey matter volumetry was performed within cortices of abnormal trajectories. RESULTS ED patients showed average axial diffusivity reduction within projections between the primary somatosensory cortex and putamen, with converse increases within projections between supplementary motor and superior parietal cortex in both hemispheres. Increase in the mode of anisotropy in patients was accompanying the latter left-hemispheric projection, as well as in the supplementary motor area's projection to the left primary motor cortex. Patient's left primary somatosensory functional connectivity with the putamen was abnormally reduced and significantly associated with the axial diffusivity reduction. Left primary somatosensory grey matter volume was increased in patients. CONCLUSION Correlates of abnormal tract integrity within primary somatosensory cortico-subcortical projections and higher-order sensorimotor projections support the key role of dysfunctional sensory information propagation in ED pathophysiology. Differential directionality of cortico-cortical and cortico-subcortical abnormalities hints at non-uniform sensory system changes.
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Affiliation(s)
- Tobias Mantel
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany
| | - Eckart Altenmüller
- Hochschule für Musik, Theater und Medien Hannover, Emmichplatz 1, Hanover, Germany
| | - Yong Li
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany
| | - André Lee
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany; Hochschule für Musik, Theater und Medien Hannover, Emmichplatz 1, Hanover, Germany
| | - Tobias Meindl
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany
| | - Angela Jochim
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany
| | - Bernhard Haslinger
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, Munich, Germany.
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Low A, Mak E, Malpetti M, Passamonti L, Nicastro N, Stefaniak JD, Savulich G, Chouliaras L, Su L, Rowe JB, Markus HS, O'Brien JT. In vivo neuroinflammation and cerebral small vessel disease in mild cognitive impairment and Alzheimer's disease. J Neurol Neurosurg Psychiatry 2020; 92:jnnp-2020-323894. [PMID: 32917821 PMCID: PMC7803899 DOI: 10.1136/jnnp-2020-323894] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 07/06/2020] [Accepted: 08/05/2020] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Associations between cerebral small vessel disease (SVD) and inflammation have been largely examined using peripheral blood markers of inflammation, with few studies measuring inflammation within the brain. We investigated the cross-sectional relationship between SVD and in vivo neuroinflammation using [11C]PK11195 positron emission tomography (PET) imaging. METHODS Forty-two participants were recruited (according to NIA-AA guidelines, 14 healthy controls, 14 mild Alzheimer's disease, 14 amyloid-positive mild cognitive impairment). Neuroinflammation was assessed using [11C]PK11195 PET imaging, a marker of microglial activation. To quantify SVD, we assessed white matter hyperintensities (WMH), enlarged perivascular spaces, cerebral microbleeds and lacunes. Composite scores were calculated for global SVD burden, and SVD subtypes of hypertensive arteriopathy and cerebral amyloid angiopathy (CAA). General linear models examined associations between SVD and [11C]PK11195, adjusting for sex, age, education, cognition, scan interval, and corrected for multiple comparisons via false discovery rate (FDR). Dominance analysis directly compared the relative importance of hypertensive arteriopathy and CAA scores as predictors of [11C]PK11195. RESULTS Global [11C]PK11195 binding was associated with SVD markers, particularly in regions typical of hypertensive arteriopathy: deep microbleeds (β=0.63, F(1,35)=35.24, p<0.001), deep WMH (β=0.59, t=4.91, p<0.001). In dominance analysis, hypertensive arteriopathy score outperformed CAA in predicting [11C]PK11195 binding globally and in 28 out of 37 regions of interest, especially the medial temporal lobe (β=0.66-0.76, t=3.90-5.58, FDR-corrected p (pFDR)=<0.001-0.002) and orbitofrontal cortex (β=0.51-0.57, t=3.53-4.30, pFDR=0.001-0.004). CONCLUSION Microglial activation is associated with SVD, particularly with the hypertensive arteriopathy subtype of SVD. Although further research is needed to determine causality, our study suggests that targeting neuroinflammation might represent a novel therapeutic strategy for SVD.
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Affiliation(s)
- Audrey Low
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Maura Malpetti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Nicolas Nicastro
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals, Geneva, Switzerland
| | - James D Stefaniak
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - George Savulich
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Hugh S Markus
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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