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Wang J, Turesky T, Loh M, Barber J, Hue V, Escalante E, Medina A, Zuk J, Gaab N. Lateralization of activation within the superior temporal gyrus during speech perception in sleeping infants is associated with subsequent language skills in kindergarten: A passive listening task-fMRI study. BRAIN AND LANGUAGE 2024; 257:105461. [PMID: 39278185 DOI: 10.1016/j.bandl.2024.105461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 06/30/2024] [Accepted: 08/29/2024] [Indexed: 09/18/2024]
Abstract
Brain asymmetries are hypothesized to reduce functional duplication and thus have evolutionary advantages. The goal of this study was to examine whether early brain lateralization contributes to skill development within the speech-language domain. To achieve this goal, 25 infants (2-13 months old) underwent behavioral language examination and fMRI during sleep while listening to forward and backward speech, and then were assessed on various language skills at 55-69 months old. We observed that infant functional lateralization of the superior temporal gyrus (STG) for forward > backward speech was associated with phonological, vocabulary, and expressive language skills 4 to 5 years later. However, we failed to observe that infant language skills or the anatomical lateralization of STG were related to subsequent language skills. Overall, our findings suggest that infant functional lateralization of STG for speech perception may scaffold subsequent language acquisition, supporting the hypothesis that functional hemisphere asymmetries are advantageous.
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Affiliation(s)
- Jin Wang
- School of Education and Information Studies, University of California, Los Angeles, CA, USA.
| | - Ted Turesky
- Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - Megan Loh
- Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - Ja'Kala Barber
- Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - Victoria Hue
- Graduate School of Education, Harvard University, Cambridge, MA, USA
| | | | - Adrian Medina
- Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - Jennifer Zuk
- Department of Speech, Language, & Hearing Sciences, Boston University, Boston, MA, USA
| | - Nadine Gaab
- Graduate School of Education, Harvard University, Cambridge, MA, USA
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Ekerdt C, Menks WM, Fernández G, McQueen JM, Takashima A, Janzen G. White matter connectivity linked to novel word learning in children. Brain Struct Funct 2024:10.1007/s00429-024-02857-6. [PMID: 39325144 DOI: 10.1007/s00429-024-02857-6] [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: 02/20/2024] [Accepted: 09/03/2024] [Indexed: 09/27/2024]
Abstract
Children and adults are excellent word learners. Increasing evidence suggests that the neural mechanisms that allow us to learn words change with age. In a recent fMRI study from our group, several brain regions exhibited age-related differences when accessing newly learned words in a second language (L2; Takashima et al. Dev Cogn Neurosci 37, 2019). Namely, while the Teen group (aged 14-16 years) activated more left frontal and parietal regions, the Young group (aged 8-10 years) activated right frontal and parietal regions. In the current study we analyzed the structural connectivity data from the aforementioned study, examining the white matter connectivity of the regions that showed age-related functional activation differences. Age group differences in streamline density as well as correlations with L2 word learning success and their interaction were examined. The Teen group showed stronger connectivity than the Young group in the right arcuate fasciculus (AF). Furthermore, white matter connectivity and memory for L2 words across the two age groups correlated in the left AF and the right anterior thalamic radiation (ATR) such that higher connectivity in the left AF and lower connectivity in the right ATR was related to better memory for L2 words. Additionally, connectivity in the area of the right AF that exhibited age-related differences predicted word learning success. The finding that across the two age groups, stronger connectivity is related to better memory for words lends further support to the hypothesis that the prolonged maturation of the prefrontal cortex, here in the form of structural connectivity, plays an important role in the development of memory.
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Affiliation(s)
- Clara Ekerdt
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands.
| | - Willeke M Menks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Guillén Fernández
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - James M McQueen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Atsuko Takashima
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Gabriele Janzen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands
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Zhang Y, Huang J, Huang L, Peng L, Wang X, Zhang Q, Zeng Y, Yang J, Li Z, Sun X, Liang S. Atypical characteristic changes of surface morphology and structural covariance network in developmental dyslexia. Neurol Sci 2024; 45:2261-2270. [PMID: 37996775 DOI: 10.1007/s10072-023-07193-x] [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: 08/24/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Developmental dyslexia (DD) is a neurodevelopmental disorder that is characterized by difficulties with all aspects of information acquisition in the written word, including slow and inaccurate word recognition. The neural basis behind DD has not been fully elucidated. METHOD The study included 22 typically developing (TD) children, 16 children with isolated spelling disorder (SpD), and 20 children with DD. The cortical thickness, folding index, and mean curvature of Broca's area, including the triangular part of the left inferior frontal gyrus (IFGtriang) and the opercular part of the left inferior frontal gyrus, were assessed to explore the differences of surface morphology among the TD, SpD, and DD groups. Furthermore, the structural covariance network (SCN) of the triangular part of the left inferior frontal gyrus was analyzed to explore the changes of structural connectivity in the SpD and DD groups. RESULTS The DD group showed higher curvature and cortical folding of the left IFGtriang than the TD group and SpD group. In addition, compared with the TD group and the SpD group, the structural connectivity between the left IFGtriang and the left middle-frontal gyrus and the right mid-orbital frontal gyrus was increased in the DD group, and the structural connectivity between the left IFGtriang and the right precuneus and anterior cingulate was decreased in the DD group. CONCLUSION DD had atypical structural connectivity in brain regions related to visual attention, memory and which might impact the information input and integration needed for reading and spelling.
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Affiliation(s)
- Yusi Zhang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- Fujian Key Laboratory of Cognitive Rehabilitation, Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, 350001, Fujian, China
| | - Jiayang Huang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Li Huang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Lixin Peng
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Xiuxiu Wang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Qingqing Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Yi Zeng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Junchao Yang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Zuanfang Li
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Xi Sun
- College of Information Engineering, Nanyang Institute of Technology, Nanyang, 473004, China
| | - Shengxiang Liang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China.
- Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China.
- Fujian Key Laboratory of Cognitive Rehabilitation, Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, 350001, Fujian, China.
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Symons GF, Gregg MC, Hicks AJ, Rowe CC, Shultz SR, Ponsford JL, Spitz G. Altered grey matter structural covariance in chronic moderate-severe traumatic brain injury. Sci Rep 2024; 14:1728. [PMID: 38242923 PMCID: PMC10799053 DOI: 10.1038/s41598-023-50396-7] [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: 08/29/2023] [Accepted: 12/19/2023] [Indexed: 01/21/2024] Open
Abstract
Traumatic brain injury (TBI) alters brain network connectivity. Structural covariance networks (SCNs) reflect morphological covariation between brain regions. SCNs may elucidate how altered brain network topology in TBI influences long-term outcomes. Here, we assessed whether SCN organisation is altered in individuals with chronic moderate-severe TBI (≥ 10 years post-injury) and associations with cognitive performance. This case-control study included fifty individuals with chronic moderate-severe TBI compared to 75 healthy controls recruited from an ongoing longitudinal head injury outcome study. SCNs were constructed using grey matter volume measurements from T1-weighted MRI images. Global and regional SCN organisation in relation to group membership and cognitive ability was examined using regression analyses. Globally, TBI participants had reduced small-worldness, longer characteristic path length, higher clustering, and higher modularity globally (p < 0.05). Regionally, TBI participants had greater betweenness centrality (p < 0.05) in frontal and central areas of the cortex. No significant associations were observed between global network measures and cognitive ability in participants with TBI (p > 0.05). Chronic moderate-severe TBI was associated with a shift towards a more segregated global network topology and altered organisation in frontal and central brain regions. There was no evidence that SCNs are associated with cognition.
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Affiliation(s)
- Georgia F Symons
- Department of Neuroscience, Monash University, 6th Floor, The Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia.
| | - Matthew C Gregg
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
| | - Amelia J Hicks
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Rd, Heidelberg, VIC, 3084, Australia
| | - Sandy R Shultz
- Department of Neuroscience, Monash University, 6th Floor, The Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Health Sciences, Vancouver Island University, 900 Fifth Street, Nanaimo, BC, V9R 5S5, Canada
| | - Jennie L Ponsford
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
| | - Gershon Spitz
- Department of Neuroscience, Monash University, 6th Floor, The Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
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De Benedictis A, Rossi-Espagnet MC, de Palma L, Sarubbo S, Marras CE. Structural networking of the developing brain: from maturation to neurosurgical implications. Front Neuroanat 2023; 17:1242757. [PMID: 38099209 PMCID: PMC10719860 DOI: 10.3389/fnana.2023.1242757] [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: 06/19/2023] [Accepted: 11/09/2023] [Indexed: 12/17/2023] Open
Abstract
Modern neuroscience agrees that neurological processing emerges from the multimodal interaction among multiple cortical and subcortical neuronal hubs, connected at short and long distance by white matter, to form a largely integrated and dynamic network, called the brain "connectome." The final architecture of these circuits results from a complex, continuous, and highly protracted development process of several axonal pathways that constitute the anatomical substrate of neuronal interactions. Awareness of the network organization of the central nervous system is crucial not only to understand the basis of children's neurological development, but also it may be of special interest to improve the quality of neurosurgical treatments of many pediatric diseases. Although there are a flourishing number of neuroimaging studies of the connectome, a comprehensive vision linking this research to neurosurgical practice is still lacking in the current pediatric literature. The goal of this review is to contribute to bridging this gap. In the first part, we summarize the main current knowledge concerning brain network maturation and its involvement in different aspects of normal neurocognitive development as well as in the pathophysiology of specific diseases. The final section is devoted to identifying possible implications of this knowledge in the neurosurgical field, especially in epilepsy and tumor surgery, and to discuss promising perspectives for future investigations.
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Affiliation(s)
| | | | - Luca de Palma
- Clinical and Experimental Neurology, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Silvio Sarubbo
- Department of Neurosurgery, Santa Chiara Hospital, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
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Sun X, Marks RA, Eggleston RL, Zhang K, Yu CL, Nickerson N, Caruso V, Chou TL, Hu XS, Tardif T, Booth JR, Beltz AM, Kovelman I. Sources of Heterogeneity in Functional Connectivity During English Word Processing in Bilingual and Monolingual Children. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2023; 4:198-220. [PMID: 37229508 PMCID: PMC10205148 DOI: 10.1162/nol_a_00092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 11/10/2022] [Indexed: 05/27/2023]
Abstract
Diversity and variation in language experiences, such as bilingualism, contribute to heterogeneity in children's neural organization for language and brain development. To uncover sources of such heterogeneity in children's neural language networks, the present study examined the effects of bilingual proficiency on children's neural organization for language function. To do so, we took an innovative person-specific analytical approach to investigate young Chinese-English and Spanish-English bilingual learners of structurally distinct languages. Bilingual and English monolingual children (N = 152, M(SD)age = 7.71(1.32)) completed an English word recognition task during functional near-infrared spectroscopy neuroimaging, along with language and literacy tasks in each of their languages. Two key findings emerged. First, bilinguals' heritage language proficiency (Chinese or Spanish) made a unique contribution to children's language network density. Second, the findings reveal common and unique patterns in children's patterns of task-related functional connectivity. Common across all participants were short-distance neural connections within left hemisphere regions associated with semantic processes (within middle temporal and frontal regions). Unique to more proficient language users were additional long-distance connections between frontal, temporal, and bilateral regions within the broader language network. The study informs neurodevelopmental theories of language by revealing the effects of heterogeneity in language proficiency and experiences on the structure and quality of emerging language neural networks in linguistically diverse learners.
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Affiliation(s)
- Xin Sun
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
- Department of Psychology, University of British Columbia, Vancouver, Canada
| | - Rebecca A. Marks
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Kehui Zhang
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Chi-Lin Yu
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Nia Nickerson
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Valeria Caruso
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Tai-Li Chou
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - Xiao-Su Hu
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Twila Tardif
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - James R. Booth
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - Adriene M. Beltz
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Ioulia Kovelman
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
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Zhang W, Zhao C, Sun L, Yang X, Yang L, Liang Y, Zhang X, Du X, Chen R, Li C. Articulation-Function-Associated Cortical Developmental Changes in Patients with Cleft Lip and Palate. Brain Sci 2023; 13:brainsci13040550. [PMID: 37190514 DOI: 10.3390/brainsci13040550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/17/2023] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
Cleft lip and palate (CLP) is one of the most common craniofacial malformations. Overall, 40–80% of CLP patients have varying degrees of articulation problems after palatoplasty. Previous studies revealed abnormal articulation-related brain function in CLP patients. However, the association between articulation disorders and cortical structure development in CLP patients remains unclear. Twenty-six CLP adolescents (aged 5–14 years; mean 8.88 years; female/male 8/18), twenty-three CLP adults (aged 18–35 years; mean 23.35 years; female/male 6/17), thirty-seven healthy adolescents (aged 5–16 years; mean 9.89 years; female/male 5/16), and twenty-two healthy adults (aged 19–37 years; mean 24.41 years; female/male 19/37) took part in the experiment. The current study aims to investigate developmental changes in cortical structures in CLP patients with articulation disorders using both structural and functional magnetic resonance imaging (MRI). Our results reveal the distinct distribution of abnormal cortical structures in adolescent and adult CLP patients. We also found that the developmental pattern of cortical structures in CLP patients differed from the pattern in healthy controls (delayed cortical development in the left lingual gyrus (t = 4.02, cluster-wise p < 0.05), inferior temporal cortex (z = −4.36, cluster-wise p < 0.05) and right precentral cortex (t = 4.19, cluster-wise p < 0.05)). Mediation analysis identified the cortical thickness of the left pericalcarine cortex as the mediator between age and articulation function (partial mediation effect (a*b = −0.48), 95% confident interval (−0.75, −0.26)). In conclusion, our results demonstrate an abnormal developmental pattern of cortical structures in CLP patients, which is directly related to their articulation disorders.
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Kallankari H, Taskila HL, Heikkinen M, Hallman M, Saunavaara V, Kaukola T. Microstructural alterations in association tracts and language abilities in schoolchildren born very preterm and with poor fetal growth. Pediatr Radiol 2023; 53:94-103. [PMID: 35773359 PMCID: PMC9816217 DOI: 10.1007/s00247-022-05418-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 05/07/2022] [Accepted: 06/02/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND Prematurity and perinatal risk factors may influence white matter microstructure. In turn, these maturational changes may influence language development in this high-risk population of children. OBJECTIVE To evaluate differences in the microstructure of association tracts between preterm and term children and between preterm children with appropriate growth and those with fetal growth restriction and to study whether the diffusion tensor metrics of these tracts correlate with language abilities in schoolchildren with no severe neurological impairment. MATERIALS AND METHODS This study prospectively followed 56 very preterm children (mean gestational age: 28.7 weeks) and 21 age- and gender-matched term children who underwent diffusion tensor imaging at a mean age of 9 years. We used automated probabilistic tractography and measured fractional anisotropy in seven bilateral association tracts known to belong to the white matter language network. Both groups participated in language assessment using five standardised tests at the same age. RESULTS Preterm children had lower fractional anisotropy in the right superior longitudinal fasciculus 1 compared to term children (P < 0.05). Preterm children with fetal growth restriction had lower fractional anisotropy in the left inferior longitudinal fasciculus compared to preterm children with appropriate fetal growth (P < 0.05). Fractional anisotropy in three dorsal tracts and in two dorsal and one ventral tract had a positive correlation with language assessments among preterm children and preterm children with fetal growth restriction, respectively (P < 0.05). CONCLUSION There were some microstructural differences in language-related tracts between preterm and term children and between preterm children with appropriate and those with restricted fetal growth. Children with better language abilities had a higher fractional anisotropy in distinct white matter tracts.
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Affiliation(s)
- Hanna Kallankari
- PEDEGO Research Unit and Medical Research Center Oulu, University of Oulu, Oulu, Finland. .,Department of Child Neurology, Oulu University Hospital, University of Oulu, P.O. Box 5000, FIN-90014, Oulu, Finland.
| | - Hanna-Leena Taskila
- PEDEGO Research Unit and Medical Research Center Oulu, University of Oulu, Oulu, Finland ,Department of Neonatology, Oulu University Hospital, Oulu, Finland
| | - Minna Heikkinen
- PEDEGO Research Unit and Medical Research Center Oulu, University of Oulu, Oulu, Finland ,Child Language Research Center, Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Mikko Hallman
- PEDEGO Research Unit and Medical Research Center Oulu, University of Oulu, Oulu, Finland
| | - Virva Saunavaara
- PET Center, Turku University Hospital, Turku, Finland ,Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Tuula Kaukola
- PEDEGO Research Unit and Medical Research Center Oulu, University of Oulu, Oulu, Finland ,Department of Neonatology, Oulu University Hospital, Oulu, Finland
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Zhang L, Hu X, Hu Y, Tang M, Qiu H, Zhu Z, Gao Y, Li H, Kuang W, Ji W. Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder. PSYCHORADIOLOGY 2022; 2:190-198. [PMID: 38665275 PMCID: PMC10917195 DOI: 10.1093/psyrad/kkac023] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/05/2022] [Accepted: 12/14/2022] [Indexed: 04/28/2024]
Abstract
Background The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD. Methods High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups. Results Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs. Conclusion Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.
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Affiliation(s)
- Lianqing Zhang
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Xinyue Hu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Yongbo Hu
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Mengyue Tang
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Hui Qiu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Ziyu Zhu
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Yingxue Gao
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Hailong Li
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Weidong Ji
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science and Affiliated Mental Health Center, East China Normal University, Shanghai 200335, China
- Child Psychiatry, Shanghai Changning Mental Health Center, Shanghai 200335, China
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Menks WM, Ekerdt C, Janzen G, Kidd E, Lemhöfer K, Fernández G, McQueen JM. Study protocol: a comprehensive multi-method neuroimaging approach to disentangle developmental effects and individual differences in second language learning. BMC Psychol 2022; 10:169. [PMID: 35804430 PMCID: PMC9270835 DOI: 10.1186/s40359-022-00873-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 06/23/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND While it is well established that second language (L2) learning success changes with age and across individuals, the underlying neural mechanisms responsible for this developmental shift and these individual differences are largely unknown. We will study the behavioral and neural factors that subserve new grammar and word learning in a large cross-sectional developmental sample. This study falls under the NWO (Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Dutch Research Council]) Language in Interaction consortium (website: https://www.languageininteraction.nl/ ). METHODS We will sample 360 healthy individuals across a broad age range between 8 and 25 years. In this paper, we describe the study design and protocol, which involves multiple study visits covering a comprehensive behavioral battery and extensive magnetic resonance imaging (MRI) protocols. On the basis of these measures, we will create behavioral and neural fingerprints that capture age-based and individual variability in new language learning. The behavioral fingerprint will be based on first and second language proficiency, memory systems, and executive functioning. We will map the neural fingerprint for each participant using the following MRI modalities: T1-weighted, diffusion-weighted, resting-state functional MRI, and multiple functional-MRI paradigms. With respect to the functional MRI measures, half of the sample will learn grammatical features and half will learn words of a new language. Combining all individual fingerprints allows us to explore the neural maturation effects on grammar and word learning. DISCUSSION This will be one of the largest neuroimaging studies to date that investigates the developmental shift in L2 learning covering preadolescence to adulthood. Our comprehensive approach of combining behavioral and neuroimaging data will contribute to the understanding of the mechanisms influencing this developmental shift and individual differences in new language learning. We aim to answer: (I) do these fingerprints differ according to age and can these explain the age-related differences observed in new language learning? And (II) which aspects of the behavioral and neural fingerprints explain individual differences (across and within ages) in grammar and word learning? The results of this study provide a unique opportunity to understand how the development of brain structure and function influence new language learning success.
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Affiliation(s)
- W M Menks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands.
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.
| | - C Ekerdt
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - G Janzen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands
| | - E Kidd
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
- ARC Centre of Excellence for the Dynamics of Language, Canberra, Australia
- Research School of Psychology, Australian National University, Canberra, Australia
| | - K Lemhöfer
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - G Fernández
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - J M McQueen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
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11
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Qi T, Schaadt G, Friederici AD. Associated functional network development and language abilities in children. Neuroimage 2021; 242:118452. [PMID: 34358655 PMCID: PMC8463838 DOI: 10.1016/j.neuroimage.2021.118452] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/14/2021] [Accepted: 08/03/2021] [Indexed: 11/26/2022] Open
Abstract
During childhood, the brain is gradually converging to the efficient functional architecture observed in adults. How the brain's functional architecture evolves with age, particularly in young children, is however, not well understood. We examined the functional connectivity of the core language regions, in association with cortical growth and language abilities, in 175 young children in the age range of 4 to 9 years. We analyzed the brain's developmental changes using resting-state functional and T1-weighted structural magnetic resonance imaging data. The results showed increased functional connectivity strength with age between the pars triangularis of the left inferior frontal gyrus and left temporoparietal regions (cohen's d = 0.54, CI: 0.24 - 0.84), associated with children's language abilities. Stronger functional connectivity between bilateral prefrontal and temporoparietal regions was associated with better language abilities regardless of age. In addition, the stronger functional connectivity between the left inferior frontal and temporoparietal regions was associated with larger surface area and thinner cortical thickness in these regions, which in turn was associated with superior language abilities. Thus, using functional and structural brain indices, coupled with behavioral measures, we elucidate the association of functional language network development, language ability, and cortical growth, thereby adding to our understanding of the neural basis of language acquisition in young children.
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Affiliation(s)
- Ting Qi
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Gesa Schaadt
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Education and Psychology, Free University of Berlin, Berlin, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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12
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Song J, Li J, Chen L, Lu X, Zheng S, Yang Y, Cao B, Weng Y, Chen Q, Ding J, Huang R. Altered gray matter structural covariance networks at both acute and chronic stages of mild traumatic brain injury. Brain Imaging Behav 2021; 15:1840-1854. [PMID: 32880075 DOI: 10.1007/s11682-020-00378-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Cognitive and emotional impairments observed in mild traumatic brain injury (mTBI) patients may reflect variances of brain connectivity within specific networks. Although previous studies found altered functional connectivity (FC) in mTBI patients, the alterations of brain structural properties remain unclear. In the present study, we analyzed structural covariance (SC) for the acute stages of mTBI (amTBI) patients, the chronic stages of mTBI (cmTBI) patients, and healthy controls. We first extracted the mean gray matter volume (GMV) of seed regions that are located in the default-mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), and the visual network (VN). Then we determined and compared the SC for each seed region among the amTBI, the cmTBI and the healthy controls. Compared with healthy controls, the amTBI patients showed lower SC for the ECN, and the cmTBI patients showed higher SC for the both DMN and SN but lower SC for the SMN. The results revealed disrupted ECN in the amTBI patients and disrupted DMN, SN and SMN in the cmTBI patients. These alterations suggest that early disruptions in SC between bilateral insula and the bilateral prefrontal cortices may appear in amTBI and persist into cmTBI, which might be potentially related to the cognitive and emotional impairments.
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Affiliation(s)
- Jie Song
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, 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
| | - Jie Li
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Lixiang Chen
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, 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
| | - Xingqi Lu
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Senning Zheng
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, 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 Yang
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Bolin Cao
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, 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
| | - Yihe Weng
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, 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
| | - Qinyuan Chen
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.,Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Jianping Ding
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China. .,School of Medicine, Hangzhou Normal University, Hangzhou, 310015, China.
| | - Ruiwang Huang
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, 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.
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13
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Reh R, Williams LJ, Todd RM, Ward LM. Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication. Behav Brain Res 2020; 399:113016. [PMID: 33212087 DOI: 10.1016/j.bbr.2020.113016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 12/27/2022]
Abstract
It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development.
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Affiliation(s)
- Rebecca Reh
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada
| | - Lynne J Williams
- BC Children's Hospital MRI Research Facility, 4480 Oak Street, Vancouver, BC V6H 0B3, Canada
| | - Rebecca M Todd
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada; University of British Columbia, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
| | - Lawrence M Ward
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada; University of British Columbia, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
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14
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Bellantuono L, Marzano L, La Rocca M, Duncan D, Lombardi A, Maggipinto T, Monaco A, Tangaro S, Amoroso N, Bellotti R. Predicting brain age with complex networks: From adolescence to adulthood. Neuroimage 2020; 225:117458. [PMID: 33099008 DOI: 10.1016/j.neuroimage.2020.117458] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 10/13/2020] [Indexed: 01/21/2023] Open
Abstract
In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brain scans (in the age range 7-64years). We introduce a structural connectivity model of the human brain: MRI scans are divided in rectangular boxes and Pearson's correlation is measured among them in order to obtain a complex network model. Brain connectivity is then characterized through few and easy-to-interpret centrality measures; finally, brain age is predicted by feeding a compact deep neural network. The proposed approach is accurate, robust and computationally efficient, despite the large and heterogeneous dataset used. Age prediction accuracy, in terms of correlation between predicted and actual age r=0.89and Mean Absolute Error MAE =2.19years, compares favorably with results from state-of-the-art approaches. On an independent test set including 262 subjects, whose scans were acquired with different scanners and protocols we found MAE =2.52. The only imaging analysis steps required in the proposed framework are brain extraction and linear registration, hence robust results are obtained with a low computational cost. In addition, the network model provides a novel insight on aging patterns within the brain and specific information about anatomical districts displaying relevant changes with aging.
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Affiliation(s)
- Loredana Bellantuono
- Dipartimento Interateneo di Fisica, Universitá degli Studi di Bari Aldo Moro, Bari, Italy
| | - Luca Marzano
- Dipartimento Interateneo di Fisica, Universitá degli Studi di Bari Aldo Moro, Bari, Italy
| | - Marianna La Rocca
- University of Southern California, Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Dominique Duncan
- University of Southern California, Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Angela Lombardi
- Istituto Nazionale di Fisica Nucleare, Sez. di Bari, Bari, Italy
| | - Tommaso Maggipinto
- Dipartimento Interateneo di Fisica, Universitá degli Studi di Bari Aldo Moro, Bari, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sez. di Bari, Bari, Italy.
| | - Sabina Tangaro
- Istituto Nazionale di Fisica Nucleare, Sez. di Bari, Bari, Italy; Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Universitá degli Studi di Bari Aldo Moro, Bari, Italy
| | - Nicola Amoroso
- Dipartimento di Farmacia - Scienze del Farmaco, Universitá degli Studi di Bari Aldo Moro, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sez. di Bari, Bari, Italy
| | - Roberto Bellotti
- Istituto Nazionale di Fisica Nucleare, Sez. di Bari, Bari, Italy; Dipartimento Interateneo di Fisica, Universitá degli Studi di Bari Aldo Moro, Bari, Italy
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15
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Gender-Related and Hemispheric Effects in Cortical Thickness-Based Hemispheric Brain Morphological Network. BIOMED RESEARCH INTERNATIONAL 2020; 2020:3560259. [PMID: 32851064 PMCID: PMC7439209 DOI: 10.1155/2020/3560259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/19/2020] [Accepted: 07/06/2020] [Indexed: 12/18/2022]
Abstract
Objective The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network. Methods Using the T1-weighted magnetic resonance imaging scans of 285 participants (150 females, 135 males) retrieved from the Human Connectome Project (HCP), hemispheric morphological networks were constructed per participant. In these hemispheric morphologic networks, the degree of similarity between two different brain regions in terms of the distributed patterns of cortical thickness values (the Jensen–Shannon divergence) was defined as weight of network edge that connects two different brain regions. After the calculation and summation of global and local graph metrics (across the network sparsity levels K = 0.10‐0.36), asymmetry indexes of these graph metrics were derived. Results Hemispheric morphological networks satisfied small-worldness and global efficiency for the network sparsity ranges of K = 0.10–0.36. Between-group comparisons (female versus male) of asymmetry indexes revealed opposite directionality of asymmetries (leftward versus rightward) for global metrics of normalized clustering coefficient, normalized characteristic path length, and global efficiency (all p < 0.05). For the local graph metrics, larger rightward asymmetries of cingulate-superior parietal gyri for nodal efficiency in male compared to female, larger leftward asymmetry of temporal pole for degree centrality in female compared to male, and opposite directionality of interhemispheric asymmetry of rectal gyrus for degree centrality between female (rightward) and male (leftward) were shown (all p < 0.05). Conclusion Patterns of interhemispheric asymmetries for cingulate, superior parietal gyrus, temporal pole, and rectal gyrus are different between male and female for the similarities of the cortical thickness distribution with other brain regions. Accordingly, possible effect of gender-by-hemispheric interaction has to be considered in future studies of brain morphology and brain structural covariance networks.
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16
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Eichert N, Robinson EC, Bryant KL, Jbabdi S, Jenkinson M, Li L, Krug K, Watkins KE, Mars RB. Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe. eLife 2020; 9:e53232. [PMID: 32202497 PMCID: PMC7180052 DOI: 10.7554/elife.53232] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 03/19/2020] [Indexed: 01/03/2023] Open
Abstract
Evolutionary adaptations of temporo-parietal cortex are considered to be a critical specialization of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including local expansion of the cortical sheet or changes in connectivity between cortical areas. We distinguish different types of changes in brain architecture using a computational neuroanatomy approach. We investigate the extent to which between-species alignment, based on cortical myelin, can predict changes in connectivity patterns across macaque, chimpanzee, and human. We show that expansion and relocation of brain areas can predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the temporal lobe connectivity pattern. This approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization.
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Affiliation(s)
- Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Emma C Robinson
- Biomedical Engineering Department, King’s College LondonLondonUnited Kingdom
| | - Katherine L Bryant
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Longchuan Li
- Marcus Autism Center, Children's Healthcare of Atlanta, Emory UniversityAtlantaUnited States
| | - Kristine Krug
- Department of Physiology, Anatomy and Genetics, University of OxfordOxfordUnited Kingdom
- Institute of Biology, Otto-von-Guericke-Universität MagdeburgMagdeburgGermany
- Leibniz-Insitute for NeurobiologyMagdeburgGermany
| | - Kate E Watkins
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
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17
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Yun JY, Boedhoe PSW, Vriend C, Jahanshad N, Abe Y, Ameis SH, Anticevic A, Arnold PD, Batistuzzo MC, Benedetti F, Beucke JC, Bollettini I, Bose A, Brem S, Calvo A, Cheng Y, Cho KIK, Ciullo V, Dallaspezia S, Denys D, Feusner JD, Fouche JP, Giménez M, Gruner P, Hibar DP, Hoexter MQ, Hu H, Huyser C, Ikari K, Kathmann N, Kaufmann C, Koch K, Lazaro L, Lochner C, Marques P, Marsh R, Martínez-Zalacaín I, Mataix-Cols D, Menchón JM, Minuzzi L, Morgado P, Moreira P, Nakamae T, Nakao T, Narayanaswamy JC, Nurmi EL, O'Neill J, Piacentini J, Piras F, Piras F, Reddy YCJ, Sato JR, Simpson HB, Soreni N, Soriano-Mas C, Spalletta G, Stevens MC, Szeszko PR, Tolin DF, Venkatasubramanian G, Walitza S, Wang Z, van Wingen GA, Xu J, Xu X, Zhao Q, Thompson PM, Stein DJ, van den Heuvel OA, Kwon JS. Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium. Brain 2020; 143:684-700. [PMID: 32040561 PMCID: PMC7009583 DOI: 10.1093/brain/awaa001] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 11/24/2019] [Accepted: 11/26/2019] [Indexed: 12/13/2022] Open
Abstract
Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.
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Affiliation(s)
- Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
- Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Premika S W Boedhoe
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Chris Vriend
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Yoshinari Abe
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Stephanie H Ameis
- The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Campbell Family Mental Health Research Institute, The Centre for Addiction and Mental Health, Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Canada
- Centre for Brain and Mental Health, The Hospital for Sick Children, Toronto, Canada
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Paul D Arnold
- Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Marcelo C Batistuzzo
- Departamento e Instituto de Psiquiatria do Hospital das Clinicas, IPQ HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, SP, Brazil
| | - Francesco Benedetti
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, Scientific Institute Ospedale San Raffaele, Milano, Italy
| | - Jan C Beucke
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Irene Bollettini
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, Scientific Institute Ospedale San Raffaele, Milano, Italy
| | - Anushree Bose
- Obsessive-Compulsive Disorder (OCD) Clinic Department of Psychiatry National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Anna Calvo
- Magnetic Resonance Image Core Facility, IDIBAPS (Institut d'Investigacions Biomèdiques August Pi i Sunyer), Barcelona, Spain
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Kang Ik K Cho
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea
| | - Valentina Ciullo
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Sara Dallaspezia
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, Scientific Institute Ospedale San Raffaele, Milano, Italy
| | - Damiaan Denys
- Amsterdam UMC, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Jamie D Feusner
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Jean-Paul Fouche
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Mònica Giménez
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Carlos III Health Institute, Barcelona, Spain
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Patricia Gruner
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Derrek P Hibar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Marcelo Q Hoexter
- Departamento e Instituto de Psiquiatria do Hospital das Clinicas, IPQ HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, SP, Brazil
| | - Hao Hu
- Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine, PR China
| | - Chaim Huyser
- De Bascule, Academic Center for Child and Adolescent Psychiatry, Amsterdam, The Netherlands
- Amsterdam UMC, Department of Child and Adolescent Psychiatry, Amsterdam, The Netherlands
| | - Keisuke Ikari
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi Higashi-ku, Fukuoka, Japan
| | - Norbert Kathmann
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Christian Kaufmann
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Kathrin Koch
- Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Germany
- TUM-Neuroimaging Center (TUM-NIC) of Klinikum rechts der Isar, Technische Universität München, Germany
| | - Luisa Lazaro
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clínic Universitari, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomèdica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Christine Lochner
- SAMRC Unit on Anxiety and Stress Disorders, Department of Psychiatry, University of Stellenbosch, South Africa
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
| | - Rachel Marsh
- Columbia University Medical College, Columbia University, New York, NY, USA
- The New York State Psychiatric Institute, New York, NY, USA
| | - Ignacio Martínez-Zalacaín
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, University of Barcelona, Spain
| | - David Mataix-Cols
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - José M Menchón
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Centro de Investigación Biomèdica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
- Department of Clinical Sciences, University of Barcelona, Spain
| | - Luciano Minuzzi
- McMaster University, Department of Psychiatry and Behavioural Neurosciences, Hamilton, Ontario, Canada
| | - Pedro Morgado
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Clinical Academic Center-Braga, Braga, Portugal
- ICVS-3Bs PT Government Associate Laboratory, Braga, Portugal
| | - Pedro Moreira
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Clinical Academic Center-Braga, Braga, Portugal
- ICVS-3Bs PT Government Associate Laboratory, Braga, Portugal
| | - Takashi Nakamae
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Tomohiro Nakao
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Janardhanan C Narayanaswamy
- Obsessive-Compulsive Disorder (OCD) Clinic Department of Psychiatry National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Erika L Nurmi
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Joseph O'Neill
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Division of Child and Adolescent Psychiatry, University of California, Los Angeles, CA, USA
| | - John Piacentini
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Division of Child and Adolescent Psychiatry, University of California, Los Angeles, CA, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Y C Janardhan Reddy
- Obsessive-Compulsive Disorder (OCD) Clinic Department of Psychiatry National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Joao R Sato
- Center for Mathematics, Computing and Cognition, Universidade Federal do ABC, Santo Andre, Brazil
| | - H Blair Simpson
- Columbia University Medical College, Columbia University, New York, NY, USA
- Center for OCD and Related Disorders, New York State Psychiatric Institute, New York, NY, USA
| | - Noam Soreni
- Pediatric OCD Consultation Service, Anxiety Treatment and Research Center, St. Joseph's HealthCare, Hamilton, Ontario, Canada
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Centro de Investigación Biomèdica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
- Department of Psychobiology and Methodology of Health Sciences, Universitat Autònoma de Barcelona, Spain
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
- Beth K. and Stuart C. Yudofsky Division of Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Michael C Stevens
- Yale University School of Medicine, New Haven, Connecticut, USA
- Clinical Neuroscience and Development Laboratory, Olin Neuropsychiatry Research Center, Hartford, Connecticut, USA
| | - Philip R Szeszko
- Icahn School of Medicine at Mount Sinai, New York, USA
- James J. Peters VA Medical Center, Bronx, New York, USA
| | - David F Tolin
- Yale University School of Medicine, New Haven, Connecticut, USA
- Institute of Living/Hartford Hospital, Hartford, Connecticut, USA
| | - Ganesan Venkatasubramanian
- Obsessive-Compulsive Disorder (OCD) Clinic Department of Psychiatry National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Zhen Wang
- Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine, PR China
- Shanghai Key Laboratory of Psychotic Disorders, PR China
| | - Guido A van Wingen
- Amsterdam UMC, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jian Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, PR China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, PR China
| | - Qing Zhao
- Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine, PR China
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
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