Increased structural covariance in brain regions for number processing and memory in children with developmental dyscalculia

AbstractBackgroundIn patients with schizophrenia, distributed abnormalities are observed in grey matter volume. A recent hypothesis posits that these distributed changes are indicative of a plastic reorganisation process occurring in response to a functional defect in neuronal information transmission. We investigated the structural covariance across various brain regions in early-stage schizophrenia to determine if indeed the observed patterns of volumetric loss conform to a coordinated pattern of structural reorganisation.MethodsStructural magnetic resonance imaging scans were obtained from 40 healthy adults and 41 age, gender and parental socioeconomic status matched patients with schizophrenia. Volumes of grey matter tissue were estimated at the regional level across 90 atlas-based parcellations. Group-level structural covariance was studied using a graph theoretical framework.ResultsPatients had distributed reduction in grey matter volume, with high degree of localised covariance (clustering) compared with controls. Patients with schizophrenia had reduced centrality of anterior cingulate and insula but increased centrality of the fusiform cortex, compared with controls. Simulating targeted removal of highly central nodes resulted in significant loss of the overall covariance patterns in patients compared with controls.ConclusionRegional volumetric deficits in schizophrenia are not a result of random, mutually independent processes. Our observations support the occurrence of a spatially interconnected reorganisation with the systematic de-escalation of conventional ‘hub’ regions. This raises the question of whether the morphological architecture in schizophrenia is primed for compensatory functions, albeit with a high risk of inefficiency.

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Common and distinct brain regions in both parietal and frontal cortex support symbolic and nonsymbolic number processing in humans: A functional neuroimaging meta-analysis

NeuroImage ◽

10.1016/j.neuroimage.2016.10.028 ◽

2017 ◽

Vol 146 ◽

pp. 376-394 ◽

Cited By ~ 51

Author(s):

H. Moriah Sokolowski ◽

Wim Fias ◽

Ahmad Mousa ◽

Daniel Ansari

Keyword(s):

Frontal Cortex ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Brain Regions ◽

Number Processing

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Structural covariance networks across the lifespan, from 6-94 years of age

10.1101/090233 ◽

2016 ◽

Cited By ~ 2

Author(s):

Elizabeth DuPre ◽

R. Nathan Spreng

Keyword(s):

Grey Matter ◽

Age Groups ◽

Brain Regions ◽

Posterior Cingulate Cortex ◽

Structural Covariance ◽

Stable Pattern ◽

Combining Data ◽

Age Dependent ◽

Definition Of ◽

Access Data

AbstractStructural covariance examines covariation of grey matter morphology between brain regions and across individuals. Despite significant interest in the influence of age on structural covariance patterns, no study to date has provided a complete lifespan perspective—bridging childhood with early, middle, and late adulthood—on the development of structural covariance networks. Here, we investigate the lifespan trajectories of structural covariance in six canonical neurocognitive networks: default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual. By combining data from five open access data sources, we examine the structural covariance trajectories of these networks from 6-94 years of age in a sample of 1580 participants. Using partial least squares, we show that structural covariance patterns across the lifespan exhibit two significant, age-dependent trends. The first trend is a stable pattern whose integrity declines over the lifespan. The second trend is an inverted-U that differentiates young adulthood from other age groups. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, our results suggest that structural covariance provides a reliable definition of neurocognitive networks across the lifespan and reveal both shared and network-specific trajectories.

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Altered Topological Properties of Grey Matter Structural Covariance Networks in Complete Thoracic Spinal Cord Injury Patients: A Graph Theoretical Network Analysis

Neural Plasticity ◽

10.1155/2021/8815144 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Wen-Li Wang ◽

Yu-Lin Li ◽

Mou-Xiong Zheng ◽

Xu-Yun Hua ◽

Jia-Jia Wu ◽

...

Keyword(s):

Grey Matter ◽

Brain Regions ◽

Healthy Controls ◽

Age And Gender ◽

Structural Covariance ◽

Clinical Variables ◽

Cord Injury ◽

Network Properties ◽

And Gender ◽

The Right

Purpose. This study is aimed at investigating brain structural changes and structural network properties in complete spinal cord injury (SCI) patients, as well as their relationship with clinical variables. Materials and Methods. Structural MRI of brain was acquired in 24 complete thoracic SCI patients ( 38.50 ± 11.19 years, 22 males) within the first postinjury year, while 26 age- and gender-matched healthy participants ( 38.38 ± 10.63 years, 24 males) were enrolled as control. The voxel-based morphometry (VBM) approach and graph theoretical network analysis based on cross-subject grey matter volume- (GMV-) based structural covariance networks (SCNs) were conducted to investigate the impact of SCI on brain structure. Partial correlation analysis was performed to explore the relationship between the GMV of structurally changed brain regions and SCI patients’ clinical variables, including injury duration, injury level, Visual Analog Scale (VAS), American Spinal Injury Association Impairment Scale (AIS), International Classification of Functioning, Disability and Health (ICF) scale, Self-rating Depression Scale (SDS), and Self-rating Anxiety Scale (SAS), after removing the effects of age and gender. Results. Compared with healthy controls, SCI patients showed higher SDS score ( t = 4.392 and p < 0.001 ). In the VBM analysis, significant GMV reduction was found in the left middle frontal cortex, right superior orbital frontal cortex (OFC), and left inferior OFC. No significant difference was found in global network properties between SCI patients and healthy controls. In the regional network properties, significantly higher betweenness centrality (BC) was noted in the right anterior cingulum cortex (ACC) and left inferior OFC and higher nodal degree and efficiency in bilateral middle OFCs, while decreased BC was noted in the right putamen in SCI patients. Only negative correlation was found between GMV of right middle OFC and SDS score in SCI patients ( r = − 0.503 and p = 0.017 ), while no significant correlation between other abnormal brain regions and any of the clinical variables (all p > 0.05 ). Conclusions. SCI patients would experience depressive and/or anxious feelings at the early stage. Their GMV reduction mainly involved psychology-cognition related rather than sensorimotor brain regions. The efficiency of regional information transmission in psychology-cognition regions increased. Greater GMV reduction in psychology region was related with more severe depressive feelings. Therefore, early neuropsychological intervention is suggested to prevent psychological and cognitive dysfunction as well as irreversible brain structure damage.

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Neural Correlates of Symbolic Number Comparison in Developmental Dyscalculia

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2009.21237 ◽

2010 ◽

Vol 22 (5) ◽

pp. 860-874 ◽

Cited By ~ 111

Author(s):

Christophe Mussolin ◽

Anne De Volder ◽

Cécile Grandin ◽

Xavier Schlögel ◽

Marie-Cécile Nassogne ◽

...

Keyword(s):

Number Processing ◽

Numerical Distance ◽

Comparison Task ◽

Developmental Dyscalculia ◽

Disability History ◽

Magnitude Processing ◽

Number Magnitude ◽

Number Comparison ◽

The Right ◽

Symbolic Number

Developmental dyscalculia (DD) is a deficit in number processing and arithmetic that affects 3–6% of schoolchildren. The goal of the present study was to analyze cerebral bases of DD related to symbolic number processing. Children with DD aged 9–11 years and matched children with no learning disability history were investigated using fMRI. The two groups of children were controlled for general cognitive factors, such as working memory, reading abilities, or IQ. Brain activations were measured during a number comparison task on pairs of Arabic numerals and a color comparison task on pairs of nonnumerical symbols. In each task, pairs of stimuli that were close or far on the relevant dimension were constituted. Brain activation in bilateral intraparietal sulcus (IPS) was modulated by numerical distance in controls but not in children with DD. Moreover, although the right IPS responded to numerical distance only, the left IPS was influenced by both numerical and color distances in control children. Our findings suggest that dyscalculia is associated with impairment in areas involved in number magnitude processing and, to a lesser extent, in areas dedicated to domain-general magnitude processing.

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Basic number processing deficits in developmental dyscalculia: Evidence from eye tracking

Cognitive Development ◽

10.1016/j.cogdev.2009.09.007 ◽

2009 ◽

Vol 24 (4) ◽

pp. 371-386 ◽

Cited By ~ 43

Author(s):

K. Moeller ◽

S. Neuburger ◽

L. Kaufmann ◽

K. Landerl ◽

H.-C. Nuerk

Keyword(s):

Eye Tracking ◽

Basic Number ◽

Number Processing ◽

Developmental Dyscalculia ◽

Processing Deficits

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Brain Structural Covariance Network in Asperger’s Syndrome Differs From Other Types of Autism and Healthy Controls

Basic and Clinical Neuroscience Journal ◽

10.32598/bcn.2021.2262.1 ◽

2021 ◽

Author(s):

Farnaz Faridi ◽

◽

Afrooz Seyedebrahimi ◽

Reza Khosrowabadi ◽

◽

...

Keyword(s):

Asperger's Syndrome ◽

Asperger’S Syndrome ◽

Neurodevelopmental Disorder ◽

Brain Regions ◽

Autism Spectrum ◽

Healthy Controls ◽

Structural Differentiation ◽

Structural Covariance ◽

Behavioral Impairments ◽

The Brain

Autism is a heterogeneous neurodevelopmental disorder associated with social, cognitive and behavioral impairments. These impairments are often reported along with alteration of the brain structure such as abnormal changes in the grey matter (GM) density. However, it is not yet clear whether these changes could be used to differentiate various subtypes of autism spectrum disorder (ASD). In this study, we compared the regional changes of GM density in ASD, Asperger's Syndrome (AS) individuals and a group of healthy controls (HC). In addition to regional changes itself, the amount of GM density changes in one region as compared to other brain regions was also calculated. We hypothesized that this structural covariance network could differentiate the AS individuals from the ASD and HC groups. Therefore, statistical analysis was performed on the MRI data of 70 male subjects including 26 ASD (age= 14-50, IQ= 92-132), 16 AS (age=7-58, IQ=93-133) and 28 HC (age=9-39, IQ=95-144). Results of one-way ANOVA on the GM density of 116 anatomically separated regions showed significant differences among the groups. The pattern of structural covariance network indicated that covariation of GM density between the brain regions is decreased in ASD. This attenuated structural differentiation could be considered as a reason for less efficient segregation and integration of information in the brain that could lead to cognitive dysfunctions in autism. We hope these findings could improve our understanding about the pathobiology of autism and may pave the way towards a more effective intervention paradigm.

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In-scanner head motion and structural covariance networks

10.1101/2021.04.28.441807 ◽

2021 ◽

Author(s):

Heath R. Pardoe ◽

Samantha P. Martin

Keyword(s):

Gray Matter ◽

Brain Mri ◽

Brain Regions ◽

Head Motion ◽

Voxel Based Morphometry ◽

Structural Covariance ◽

Graph Theoretic ◽

Network Analyses ◽

Gray Matter Volumes ◽

Source Of Error

AbstractIn-scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion-affected and motion-free whole brain T1-weighted MRI in 29 healthy adult subjects and estimated relative regional gray matter volumes using a voxel-based morphometry approach. Structural covariance network analyses were undertaken while systematically increasing the number of motion-affected scans included in the analysis. We demonstrate that the standard deviation in regional gray matter estimates increases as the number of motion-affected scans increases. This subsequently increases pair-wise correlations between regions, a key determinant for construction of structural covariance networks. We further demonstrate that head motion systematically alters graph theoretic metrics derived from these networks. Our findings suggest that in-scanner head motion is a source of error that violates the assumption that structural covariance networks reflect neuroanatomical connectivity between brain regions. Results of structural covariance studies should be interpreted with caution, particularly when subject groups are likely to move their heads in the scanner.

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Sex differences in Variability of Brain Structure Across the Lifespan

10.1101/842567 ◽

2019 ◽

Cited By ~ 1

Author(s):

Natalie J Forde ◽

Jerrold Jeyachandra ◽

Michael Joseph ◽

Grace R Jacobs ◽

Erin Dickie ◽

...

Keyword(s):

Sex Differences ◽

Early Life ◽

Disease Risk ◽

Late Life ◽

Brain Regions ◽

Variance Ratio ◽

Regional Variability ◽

Protective Mechanisms ◽

Structural Covariance ◽

Subcortical Volumes

AbstractSeveral brain disorders exhibit sex differences in onset, presentation, and prevalence. Increased understanding of the neurobiology of sex-based differences across the lifespan can provide insight into potential disease risk and protective mechanisms. We focused on sex-related differences in variability, which may be indicative of both disease vulnerability and resilience. In n=3,069 participants, from 8-95 years of age, we first analyzed the variance ratio in females vs. males of cortical surface area and global and subcortical volumes for discrete brain regions, and found widespread greater variability in males. In contrast, variance in cortical thickness was similar for males and females. Multivariate analysis that accounts for structural covariance supported variance ratio findings. Findings were present from early life and stable with age. We then examined variability among brain regions by sex. We found significant age-by-sex interactions across neuroimaging metrics, whereby in very early life males had reduced among-region variability compared to females, while in very late life this was reversed. Overall, our findings of greater regional variability but less among-region variability in males in early life may aid our understanding of sex-based risk for neurodevelopmental disorders. In contrast, our findings in late life may provide a potential sex-based risk mechanism for dementia.

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Developmental Dyscalculia

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000205 ◽

2015 ◽

Vol 223 (2) ◽

pp. 69-82 ◽

Cited By ~ 13

Author(s):

Jörg-Tobias Kuhn

Keyword(s):

Number Processing ◽

Cognitive Resources ◽

Cognitive Profiles ◽

Developmental Dyscalculia ◽

Hyperactivity Disorder ◽

Magnitude Processing ◽

Specific Learning Disorder ◽

Behavioral Evidence ◽

Fact Retrieval

Developmental dyscalculia (DD) is a specific learning disorder that affects the acquisition of arithmetic skills and number processing in children. A high comorbidity between DD and other neurodevelopmental disorders (e.g., dyslexia, attention-deficit/hyperactivity disorder [ADHD]) as well as substantial heterogeneity in cognitive profiles have been reported. Current studies indicate that DD is persistent, has a genetic component, and is related to functional and structural alterations of brain areas involved in magnitude representation. Recent neuronal and behavioral evidence is presented, showing that DD entails (a) impairments in two preverbal core systems of number, an approximate system for estimating larger magnitudes and an exact system for representing small magnitudes, (b) deficits in symbolic number processing, (c) aberrant and nonadaptive neuronal activation in basic magnitude processing and calculation, (d) dysfunctional arithmetic fact retrieval and persistent use of counting strategies in calculation, and (e) deficits in visuospatial working memory and the central executive. Finally, open research questions, including the role of domain-general cognitive resources in DD, causes and developmental consequences of comorbidity, as well as design and evaluation of interventions for DD, are briefly discussed.

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