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Li S, Xing X, Hua X, Zhang Y, Wu J, Shan C, Wang H, Zheng M, Xu J. Electroacupuncture modulates abnormal brain connectivity after ischemia reperfusion injury in rats: A graph theory-based approach. Brain Behav 2024; 14:e3504. [PMID: 38698583 PMCID: PMC11066419 DOI: 10.1002/brb3.3504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 03/29/2024] [Accepted: 04/06/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Electroacupuncture (EA) has been shown to facilitate brain plasticity-related functional recovery following ischemic stroke. The functional magnetic resonance imaging technique can be used to determine the range and mode of brain activation. After stroke, EA has been shown to alter brain connectivity, whereas EA's effect on brain network topology properties remains unclear. An evaluation of EA's effects on global and nodal topological properties in rats with ischemia reperfusion was conducted in this study. METHODS AND RESULTS There were three groups of adult male Sprague-Dawley rats: sham-operated group (sham group), middle cerebral artery occlusion/reperfusion (MCAO/R) group, and MCAO/R plus EA (MCAO/R + EA) group. The differences in global and nodal topological properties, including shortest path length, global efficiency, local efficiency, small-worldness index, betweenness centrality (BC), and degree centrality (DC) were estimated. Graphical network analyses revealed that, as compared with the sham group, the MCAO/R group demonstrated a decrease in BC value in the right ventral hippocampus and increased BC in the right substantia nigra, accompanied by increased DC in the left nucleus accumbens shell (AcbSh). The BC was increased in the right hippocampus ventral and decreased in the right substantia nigra after EA intervention, and MCAO/R + EA resulted in a decreased DC in left AcbSh compared to MCAO/R. CONCLUSION The results of this study provide a potential basis for EA to promote cognitive and motor function recovery after ischemic stroke.
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Affiliation(s)
- Si‐Si Li
- School of Rehabilitation ScienceShanghai University of Traditional Chinese MedicineShanghaiChina
- Department of Physical Medicine and RehabilitationThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouChina
| | - Xiang‐Xin Xing
- Center of Rehabilitation MedicineYueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina
| | - Xu‐Yun Hua
- Department of Traumatology and OrthopedicsYueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina
| | - Yu‐Wen Zhang
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
| | - Jia‐Jia Wu
- Center of Rehabilitation MedicineYueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina
| | - Chun‐Lei Shan
- School of Rehabilitation ScienceShanghai University of Traditional Chinese MedicineShanghaiChina
- Center of Rehabilitation MedicineYueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina
- Engineering Research Center of Traditional Chinese Medicine Intelligent RehabilitationMinistry of EducationShanghaiChina
| | - He Wang
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
| | - Mou‐Xiong Zheng
- Department of Traumatology and OrthopedicsYueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina
| | - Jian‐Guang Xu
- School of Rehabilitation ScienceShanghai University of Traditional Chinese MedicineShanghaiChina
- Engineering Research Center of Traditional Chinese Medicine Intelligent RehabilitationMinistry of EducationShanghaiChina
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Mecklenbrauck F, Gruber M, Siestrup S, Zahedi A, Grotegerd D, Mauritz M, Trempler I, Dannlowski U, Schubotz RI. The significance of structural rich club hubs for the processing of hierarchical stimuli. Hum Brain Mapp 2024; 45:e26543. [PMID: 38069537 PMCID: PMC10915744 DOI: 10.1002/hbm.26543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/17/2023] [Accepted: 11/09/2023] [Indexed: 03/07/2024] Open
Abstract
The brain's structural network follows a hierarchy that is described as rich club (RC) organization, with RC hubs forming the well-interconnected top of this hierarchy. In this study, we tested whether RC hubs are involved in the processing of hierarchically higher structures in stimulus sequences. Moreover, we explored the role of previously suggested cortical gradients along anterior-posterior and medial-lateral axes throughout the frontal cortex. To this end, we conducted a functional magnetic resonance imaging (fMRI) experiment and presented participants with blocks of digit sequences that were structured on different hierarchically nested levels. We additionally collected diffusion weighted imaging data of the same subjects to identify RC hubs. This classification then served as the basis for a region of interest analysis of the fMRI data. Moreover, we determined structural network centrality measures in areas that were found as activation clusters in the whole-brain fMRI analysis. Our findings support the previously found anterior and medial shift for processing hierarchically higher structures of stimuli. Additionally, we found that the processing of hierarchically higher structures of the stimulus structure engages RC hubs more than for lower levels. Areas involved in the functional processing of hierarchically higher structures were also more likely to be part of the structural RC and were furthermore more central to the structural network. In summary, our results highlight the potential role of the structural RC organization in shaping the cortical processing hierarchy.
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Affiliation(s)
- Falko Mecklenbrauck
- Department of Psychology, Biological PsychologyUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral NeuroscienceUniversity of MünsterMünsterGermany
| | - Marius Gruber
- Institute for Translational PsychiatryUniversity of MünsterMünsterGermany
- Department for Psychiatry, Psychosomatic Medicine and PsychotherapyUniversity Hospital Frankfurt, Goethe UniversityFrankfurtGermany
| | - Sophie Siestrup
- Department of Psychology, Biological PsychologyUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral NeuroscienceUniversity of MünsterMünsterGermany
| | - Anoushiravan Zahedi
- Department of Psychology, Biological PsychologyUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral NeuroscienceUniversity of MünsterMünsterGermany
| | - Dominik Grotegerd
- Institute for Translational PsychiatryUniversity of MünsterMünsterGermany
| | - Marco Mauritz
- Institute for Translational PsychiatryUniversity of MünsterMünsterGermany
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
| | - Ima Trempler
- Department of Psychology, Biological PsychologyUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral NeuroscienceUniversity of MünsterMünsterGermany
| | - Udo Dannlowski
- Otto Creutzfeldt Center for Cognitive and Behavioral NeuroscienceUniversity of MünsterMünsterGermany
- Institute for Translational PsychiatryUniversity of MünsterMünsterGermany
| | - Ricarda I. Schubotz
- Department of Psychology, Biological PsychologyUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral NeuroscienceUniversity of MünsterMünsterGermany
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Schmitt A, Wollschläger R, Blanchette Sarrasin J, Masson S, Fischbach A, Schiltz C. Neuromyths and knowledge about intellectual giftedness in a highly educated multilingual country. Front Psychol 2023; 14:1252239. [PMID: 37928578 PMCID: PMC10623439 DOI: 10.3389/fpsyg.2023.1252239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 09/28/2023] [Indexed: 11/07/2023] Open
Abstract
Introduction Understanding brain functioning and intellectual giftedness can be challenging and give rise to various misconceptions. Nonetheless, there seems to be a widespread fascination and appetite for these subjects among the lay public and diverse professionals. The present study is the first to investigate general knowledge about the brain, neuromyths and knowledge about giftedness in a highly multilingual and educated country. Methods Starting from and extending two seminal studies on neuromyths, several novel statements on intellectual giftedness have been included in order to explore knowledge and misconceptions concerning giftedness. Our sample (N = 200) was composed of Luxembourgish education professionals, including students in educational science and cognitive psychology, thus allowing to analyze responses in general and according to training and professional profiles. Specifically, Group 1 consisted of teachers and futures teachers (n = 152). Group 2 consisted of other education professionals and psychology students (n = 48). Results Despite the size and the unbalanced distribution of the sample, our findings indicate a good level of general knowledge about the brain and learning (71.3% of correct responses in average) which does, however, not preclude the presence of the typically observed original neuromyths. Thus, we replicate the classical finding that misconceptions on Learning Styles (70% of error rate) and the Multiple Intelligence Theory (71.5% of error rate) are the most represented, both in (future and in-service) teachers and other education professionals. Moreover, the present sample also revealed a high presence of misconceptions on intellectual giftedness. Discussion Limitations and future directions are discussed.
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Affiliation(s)
- Anna Schmitt
- Department of Behavioral and Cognitive Sciences, Cognitive Science and Assessment Institute, Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- CRP-CPO, UR UPJV 7223, Université de Picardie Jules Verne, Amiens, France
| | - Rachel Wollschläger
- Luxembourg Centre for Educational Testing (LUCET), Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Jérémie Blanchette Sarrasin
- Département de Didactique, Laboratory for Research in Neuroeducation, Université du Québec à Montréal, Montréal, QC, Canada
| | - Steve Masson
- Département de Didactique, Laboratory for Research in Neuroeducation, Université du Québec à Montréal, Montréal, QC, Canada
| | - Antoine Fischbach
- Luxembourg Centre for Educational Testing (LUCET), Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Christine Schiltz
- Department of Behavioral and Cognitive Sciences, Cognitive Science and Assessment Institute, Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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Genç E, Metzen D, Fraenz C, Schlüter C, Voelkle MC, Arning L, Streit F, Nguyen HP, Güntürkün O, Ocklenburg S, Kumsta R. Structural architecture and brain network efficiency link polygenic scores to intelligence. Hum Brain Mapp 2023; 44:3359-3376. [PMID: 37013679 PMCID: PMC10171514 DOI: 10.1002/hbm.26286] [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] [Received: 07/27/2022] [Revised: 02/15/2023] [Accepted: 03/01/2023] [Indexed: 04/05/2023] Open
Abstract
Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.
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Affiliation(s)
- Erhan Genç
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Dorothea Metzen
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Christoph Fraenz
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Caroline Schlüter
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Manuel C Voelkle
- Psychological Research Methods Department of Psychology, Humboldt University, Berlin, Germany
| | - Larissa Arning
- Department of Human Genetics, Faculty of Medicine, Ruhr University Bochum, Bochum, Germany
| | - Fabian Streit
- Department Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Huu Phuc Nguyen
- Department of Human Genetics, Faculty of Medicine, Ruhr University Bochum, Bochum, Germany
| | - Onur Güntürkün
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Sebastian Ocklenburg
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
- Department of Psychology, Medical School Hamburg, Hamburg, Germany
- ICAN Institute for Cognitive and Affective Neuroscience, Medical School Hamburg, Hamburg, Germany
| | - Robert Kumsta
- Genetic Psychology, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
- Department of Behavioural and Cognitive Sciences, Laboratory for Stress and Gene-Environment Interplay, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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Wu J, Peng J, Li Z, Deng H, Huang Z, He Y, Tu J, Cao L, Huang J. Multi-domain computerized cognitive training for children with intellectual developmental disorder: A randomized controlled trial. Front Psychol 2023; 13:1059889. [PMID: 36698581 PMCID: PMC9868813 DOI: 10.3389/fpsyg.2022.1059889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 12/08/2022] [Indexed: 01/12/2023] Open
Abstract
Purpose To verify the effects of multi-domain computerized cognitive training on intellectual function and adaptive functioning in children with intellectual developmental disorder (IDD). Methods Children with IDD were randomized to a multi-domain computerized cognitive training (CCT) group (n = 30) and control group (n = 30). Both groups received a 5-week training program. Intellectual function was assessed by Chinese-Wechsler Young Children scale (C-WYCSI) and adaptive functioning was assessed by the Chinese Vineland Adaptive Behavior Rating Scale (VABS-C), which were used at baseline, post-training, and 3-month follow-up. Results There were significant differences for intellectual function and adaptive functioning between the two groups. The CCT group showed significant improvements in total full-scale intelligence quotient (FSIQ) score the Wechsler Intelligence Scale (F[60] = 31.97, p < 0.01) and its subdomain VIQ score (F[60] = 33.83, p < 0.01). For adaptive functioning, CCT had a better adaptive developmental quotient (ADQ) score (F[60] = 28.05, p < 0.01), and subdomain communication (F[60] = 10.86, p < 0.01) and socialization scores (F[60] = 4.35, p < 0.015). Moreover, there was a positive correlation between FSIQ changes and ADQ changes in the CCT group (rs = 0.74, p < 0.01). A greater increase in VIQ score was associated with a greater increase in adaptive functioning (bootstrapping CI: [0.16, 3.30]) in the CCT group. Conclusion Multi-domain CCT improves the intellectual function and adaptive functioning of children with IDD.
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Chen X, Li B, Jia H, Feng F, Duan F, Sun Z, Caiafa CF, Solé-Casals J. Graph Empirical Mode Decomposition-Based Data Augmentation Applied to Gifted Children MRI Analysis. Front Neurosci 2022; 16:866735. [PMID: 35864986 PMCID: PMC9295389 DOI: 10.3389/fnins.2022.866735] [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: 01/31/2022] [Accepted: 05/27/2022] [Indexed: 12/05/2022] Open
Abstract
Gifted children and normal controls can be distinguished by analyzing the structural connectivity (SC) extracted from MRI data. Previous studies have improved classification accuracy by extracting several features of the brain regions. However, the limited size of the database may lead to degradation when training deep neural networks as classification models. To this end, we propose to use a data augmentation method by adding artificial samples generated using graph empirical mode decomposition (GEMD). We decompose the training samples by GEMD to obtain the intrinsic mode functions (IMFs). Then, the IMFs are randomly recombined to generate the new artificial samples. After that, we use the original training samples and the new artificial samples to enlarge the training set. To evaluate the proposed method, we use a deep neural network architecture called BrainNetCNN to classify the SCs of MRI data with and without data augmentation. The results show that the data augmentation with GEMD can improve the average classification performance from 55.7 to 78%, while we get a state-of-the-art classification accuracy of 93.3% by using GEMD in some cases. Our results demonstrate that the proposed GEMD augmentation method can effectively increase the limited number of samples in the gifted children dataset, improving the classification accuracy. We also found that the classification accuracy is improved when specific features extracted from brain regions are used, achieving 93.1% for some feature selection methods.
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Affiliation(s)
- Xuning Chen
- Department of Artificial Intelligence, Nankai University, Tianjin, China
| | - Binghua Li
- Department of Artificial Intelligence, Nankai University, Tianjin, China
| | - Hao Jia
- Department of Artificial Intelligence, Nankai University, Tianjin, China
| | - Fan Feng
- Department of Artificial Intelligence, Nankai University, Tianjin, China
| | - Feng Duan
- Department of Artificial Intelligence, Nankai University, Tianjin, China
- *Correspondence: Feng Duan
| | - Zhe Sun
- Computational Engineering Applications Unit, Head Office for Information Systems and Cybersecurity, RIKEN, Saitama, Japan
- Zhe Sun
| | - Cesar F. Caiafa
- Department of Artificial Intelligence, Nankai University, Tianjin, China
- Instituto Argentino de Radioastronomía, Consejo Nacional de Investigaciones Científicas y Técnicas – Centro Científico Tecnológico La Plata/Comisión de Investigaciones Científicas – Provincia de Buenos Aires/Universidad Nacional de La Plata, Villa Elisa, Argentina
| | - Jordi Solé-Casals
- Department of Artificial Intelligence, Nankai University, Tianjin, China
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Data and Signal Processing Research Group, University of Vic-Central University of Catalonia, Vic, Spain
- Jordi Solé-Casals
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Krupnik R, Yovel Y, Assaf Y. Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain. J Neurosci 2021; 41:8351-8361. [PMID: 34465598 PMCID: PMC8496194 DOI: 10.1523/jneurosci.1074-21.2021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 07/25/2021] [Accepted: 08/08/2021] [Indexed: 11/21/2022] Open
Abstract
The connectome of the brain has a great impact on the function of the brain as the structure of the connectome affects the speed and efficiency of information transfer. As a highly energy-consuming organ, an efficient network structure is essential. A previous study has shown consistent overall brain connectivity across a large variety of species. This connectivity conservation was explained by a balance between interhemispheric and intrahemispheric connections; that is, spices with highly connected hemispheres appear to have weaker interhemisphere connections. This study examines this connectivity trade-off in the human brain using diffusion-based tractography and network analysis in the Human Connectome Project (970 subjects, 527 female). We explore the biological origins of this phenomenon, heritability, and the effect on cognitive measures.The proportion of commissural fibers in the brain had a negative correlation to hemispheric efficiency, pointing to a trade-off between inner hemispheric and interhemispheric connectivity. Network hubs including anterior and middle cingulate cortex, superior frontal areas, medial occipital areas, the parahippocampal gyrus, post- and precentral gyri, and the precuneus had the strongest contribution to this phenomenon. Other results show a high heritability as well as a strong connection to crystalized intelligence. This work presents cohort-based network analysis research, spanning a large variety of samples and exploring the overall architecture of the human connectome. Our results show a connectivity conservation phenomenon at the base of the overall brain network architecture. This network structure may explain much of the functional, behavioral, and cognitive variability among different brains.SIGNIFICANCE STATEMENT The network structure of the brain is at the basis of every brain function as it dictates the characteristics of information transfer. Understanding the patterns and mechanisms that guide the connectome structure is crucial to understanding the brain itself. Here we unravel the mechanism at the base of the connectivity conservation phenomenon by exploring the interaction between hemispheric and commissural connectivity in a large-scale cohort-based connectivity study. We describe the trade-off between the two components and examine the origins of the trade-off and observe the effect on cognitive abilities and behavior.
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Affiliation(s)
- Ronnie Krupnik
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yossi Yovel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
- School of Zoology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
- Steinhardt Museum of Natural History, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yaniv Assaf
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
- School of Neurobiology, Biochemistry and Biophysics, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
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Li D, Liu T, Shi J. Fluid intelligence and neural mechanisms of emotional conflict adaptation. Int J Psychophysiol 2020; 152:1-14. [DOI: 10.1016/j.ijpsycho.2020.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 03/11/2020] [Accepted: 03/18/2020] [Indexed: 12/21/2022]
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Drenthen GS, Fonseca Wald ELA, Backes WH, Aldenkamp AP, Vermeulen RJ, Debeij-van Hall MHJA, Klinkenberg S, Jansen JFA. Constructing an Axonal-Specific Myelin Developmental Graph and its Application to Childhood Absence Epilepsy. J Neuroimaging 2020; 30:308-314. [PMID: 32255537 PMCID: PMC7317939 DOI: 10.1111/jon.12707] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 03/18/2020] [Accepted: 03/20/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND AND PURPOSE The process of myelination starts in utero around 20 weeks of gestation and continues through adulthood. We first set out to characterize the maturation of the tract-specific myelin content in healthy subjects from childhood (7-12 years) into adulthood (18-32 years). Second, we apply the resulting development graph to children with childhood absence epilepsy (CAE), a pediatric epilepsy that was previously characterized by changes in myelin content. METHODS In a prospective cross-sectional study, 15 healthy children (7-12 years), 14 healthy adult participants (18-32 years) and 17 children with a clinical diagnosis of CAE (6-12 years) were included. For each participant, diffusion weighted images were acquired to reconstruct bundles of white matter tracts and multi-echo multi-slice GRASE images were acquired for myelin-water estimation. Subsequently, a tract-specific myelin development graph was constructed using the percentual difference in myelin-water content from childhood (12 year) to adulthood (25 year). RESULTS The graph revealed myelination patterns, where tracts in the central regions myelinate prior to peripheral tracts and intra-hemispheric tracts as well as tracts in the left hemisphere myelinate prior to inter-hemispheric tracts and tracts in the right hemisphere, respectively. No significant differences were found in myelin-water content between children with CAE and healthy children for neither the early developing tracts, nor the tracts that develop in a later stage. However, the difference between the myelin-water of late and early developing tracts is significantly smaller in the children with CAE. CONCLUSION These results indicate that CAE is associated with widespread neurodevelopmental myelin differences.
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Affiliation(s)
- Gerhard S Drenthen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, The Netherlands
| | - Eric L A Fonseca Wald
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Behavioral Sciences, Epilepsy Center Kempenhaeghe, Sterkselseweg 65, Heeze, The Netherlands
| | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands
| | - Albert P Aldenkamp
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, The Netherlands.,Department of Behavioral Sciences, Epilepsy Center Kempenhaeghe, Sterkselseweg 65, Heeze, The Netherlands
| | - R Jeroen Vermeulen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands
| | | | - Sylvia Klinkenberg
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Neurology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands
| | - Jacobus F A Jansen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, The Netherlands
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Neuroanatomical Dysconnectivity Underlying Cognitive Deficits in Bipolar Disorder. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 5:152-162. [PMID: 31806486 DOI: 10.1016/j.bpsc.2019.09.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 09/06/2019] [Accepted: 09/07/2019] [Indexed: 12/25/2022]
Abstract
BACKGROUND Graph theory applied to brain networks is an emerging approach to understanding the brain's topological associations with human cognitive ability. Despite well-documented cognitive impairments in bipolar disorder (BD) and recent reports of altered anatomical network organization, the association between connectivity and cognitive impairments in BD remains unclear. METHODS We examined the role of anatomical network connectivity derived from T1- and diffusion-weighted magnetic resonance imaging in impaired cognitive performance in individuals with BD (n = 32) compared with healthy control individuals (n = 38). Fractional anisotropy- and number of streamlines-weighted anatomical brain networks were generated by mapping constrained spherical deconvolution-reconstructed white matter among 86 cortical/subcortical bilateral brain regions delineated in the individual's own coordinate space. Intelligence and executive function were investigated as distributed functions using measures of global, rich-club, and interhemispheric connectivity, while memory and social cognition were examined in relation to subnetwork connectivity. RESULTS Lower executive functioning related to higher global clustering coefficient in participants with BD, and lower IQ performance may present with a differential relationship between global and interhemispheric efficiency in individuals with BD relative to control individuals. Spatial recognition memory accuracy and response times were similar between diagnostic groups and associated with basal ganglia and thalamus interconnectivity and connectivity within extended anatomical subnetworks in all participants. No anatomical subnetworks related to episodic memory, short-term memory, or social cognition generally or differently in BD. CONCLUSIONS Results demonstrate selective influence of subnetwork patterns of connectivity in underlying cognitive performance generally and abnormal global topology underlying discrete cognitive impairments in BD.
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