scholarly journals Structural Neuroplastic Responses Preserve Functional Connectivity and Neurobehavioural Outcomes in Children Born Without Corpus Callosum

2020 ◽  
Author(s):  
Vanessa Siffredi ◽  
Maria G Preti ◽  
Valeria Kebets ◽  
Silvia Obertino ◽  
Richard J Leventer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Corpus Callosum ◽  
Developmental Disorders ◽  
Structural Connectivity ◽  
Axonal Guidance ◽  
Typically Developing ◽  
Interhemispheric Connectivity ◽  
Data Driven Approach ◽  
Neurobehavioral Outcomes ◽  
The Brain

Abstract The corpus callosum is the largest white matter pathway in the brain connecting the two hemispheres. In the context of developmental absence (agenesis) of the corpus callosum (AgCC), a proposed candidate for neuroplastic response is strengthening of intrahemispheric pathways. To test this hypothesis, we assessed structural and functional connectivity in a uniquely large cohort of children with AgCC (n = 20) compared with typically developing controls (TDC, n = 29), and then examined associations with neurobehavioral outcomes using a multivariate data-driven approach (partial least squares correlation, PLSC). For structural connectivity, children with AgCC showed a significant increase in intrahemispheric connectivity in addition to a significant decrease in interhemispheric connectivity compared with TDC, in line with the aforementioned hypothesis. In contrast, for functional connectivity, children with AgCC and TDC showed a similar pattern of intrahemispheric and interhemispheric connectivity. In conclusion, we observed structural strengthening of intrahemispheric pathways in children born without corpus callosum, which seems to allow for functional connectivity comparable to a typically developing brain, and were relevant to explain neurobehavioral outcomes in this population. This neuroplasticity might be relevant to other disorders of axonal guidance, and developmental disorders in which corpus callosum alteration is observed.

scholarly journals Structural neuroplastic responses preserve functional connectivity and neurobehavioural outcomes in children born without corpus callosum

2020 ◽  
Author(s):  
Vanessa Siffredi ◽  
Maria G. Preti ◽  
Valeria Kebets ◽  
Silvia Obertino ◽  
Richard J. Leventer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Corpus Callosum ◽  
Developmental Disorders ◽  
Verbal Learning ◽  
Structural Connectivity ◽  
Axonal Guidance ◽  
Typically Developing ◽  
Data Driven Approach ◽  
The Right ◽  
And Function

AbstractBackgroundThe corpus callosum is the largest white matter pathway in the brain connecting the left and the right hemispheres. Developmental absence of the corpus callosum is a model disease for exploring disrupted connectivity and in turn understanding plasticity of the human brain, with atypically developing structure and function resulting in a highly heterogeneous clinical and cognitive profile. A proposed candidate for neuroplastic response in the context of this brain malformation is strengthening of intra-hemispheric pathways.MethodsTo test this hypothesis, we assessed structural and functional connectivity at the whole-brain and regional level in a uniquely large cohort of children with agenesis of the corpus callosum (AgCC, n = 20) compared with typically developing controls (TDC, n = 29), and then examined associations with neurobehavioural outcomes using a multivariate data-driven approach.ResultsFor structural connectivity, children with AgCC showed a significant increase in intrahemispheric connectivity in addition to a significant decrease in inter-hemispheric connectivity compared with TDC. In contrast, for functional connectivity, children with AgCC and TDC showed a similar pattern of intra-hemispheric and inter-hemispheric connectivity. In AgCC, structural strengthening of the intra-hemispheric pathway was uniquely associated with verbal learning and memory, attention and executive measures.ConclusionsWe observed structural strengthening of intra-hemispheric pathways in children born without corpus callosum, which seems to allow for functional connectivity comparable to a typically developing brain, and were relevant to explain neurobehavioural outcomes in this population. This neuroplasticity might be relevant to other disorders of axonal guidance, and developmental disorders in which corpus callosum alteration is observed.

Functional Connectivity: Application to Developmental Disorders

2013 ◽  
pp. 995-1009
Author(s):  
Luke Bloy ◽  
Ragini Verma ◽  
Timothy P.L. Roberts
Keyword(s):  
Functional Connectivity ◽  
Developmental Disorders ◽  
Brain Activity ◽  
Structural Connectivity ◽  
Autism Spectrum ◽  
Great Success ◽  
Experimental Conditions ◽  
Neuronal Ensembles ◽  
The Brain

Noninvasive imaging and electrophysiological methods have been developed to facilitate the in vivo investigation of brain function and dysfunction. Such methods have been employed, with great success, to the functional mapping of the brain, as well as the characterization of the temporal activity of these regions during a variety of tasks and experimental conditions. These methods are however inadequate to fully capture our current understanding of brain activity, as the complex interplay of structurally and functionally connected networks of neuronal ensembles. Here we offer an overview of the methodological advancements that have been made to better facilitate the investigation of connectivity in the brain and its relationship to development and pathology. We have focused primarily on in vivo modalities that have been most widely adopted, namely fMRI and electro/magneto encephalography for the investigation of functional connectivity and diffusion MRI for structural connectivity. Finally, the application of these methodologies to the study of neurodevelopmental disorders, such as the autism spectrum disorders, schizophrenia and attention deficit hyperactivity disorder, is presented.

scholarly journals Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

2019 ◽  
Author(s):  
Milou Straathof ◽  
Michel R.T. Sinke ◽  
Theresia J.M. Roelofs ◽  
Erwin L.A. Blezer ◽  
R. Angela Sarabdjitsingh ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Rat Brain ◽  
Resting State ◽  
Structural Connectivity ◽  
Distinct Structure ◽  
Macro Scale ◽  
Function Relationship ◽  
The Brain ◽  
Meso Scale

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in many disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional connectivity and macro-scale diffusion-based structural connectivity, but no correspondence between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Locally, strong functional connectivity was found in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Distinct structure-function relationships across the brain can explain the organization of networks and may underlie variations in the impact of structural damage on functional networks and behavior.

Developmental disorders of the brain

2019 ◽  
pp. 971-982
Author(s):  
Colin Ferrie ◽  
Daniel Warren ◽  
Atul Tyagi
Keyword(s):  
Clinical Practice ◽  
Corpus Callosum ◽  
Developmental Disorders ◽  
Clinical Implications ◽  
Brain Malformations ◽  
Genetic Abnormalities ◽  
Genetic Mechanisms ◽  
Posterior Fossa Malformations ◽  
And Migration ◽  
The Brain

Prenatal and postnatal development of the brain is controlled by a multiplicity of genetic mechanisms. Genetic abnormalities and environmental insults are responsible for a bewildering array of developmental disorders associated with brain malformations. Classic embryology remains key to understanding these, and an appreciation of the processes of gastrulation, dorsal and ventral induction, neuronal differentiation, proliferation, histogenesis, and migration and myelination will help the neurosurgeon understand the conditions likely to be encountered in clinical practice. In this chapter the more common and many less common brain malformations are reviewed. These include anencephaly, holoprosencephaly, septo-optic dysplasia, schizencephaly, grey matter heterotopias, lissencephaly/pachygyria, polymicrogyria, porencephaly, developmental anomalies of the corpus callosum, microcephaly, hemimegalencephaly, and posterior fossa malformations. The emphasis is on promoting an understanding of concepts and on clinical implications, rather than on imparting detail.

scholarly journals Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Milou Straathof ◽  
Michel R. T. Sinke ◽  
Theresia J. M. Roelofs ◽  
Erwin L. A. Blezer ◽  
R. Angela Sarabdjitsingh ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Rat Brain ◽  
Resting State ◽  
Structural Connectivity ◽  
Distinct Structure ◽  
Macro Scale ◽  
Function Relationship ◽  
The Brain ◽  
Meso Scale

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional and macro-scale diffusion-based structural connectivity, but no significant correlation between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Zooming in on individual connections, we found strong functional connectivity in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Although characteristics of the applied techniques may affect where structural and functional networks (dis)agree, distinct structure-function relationships across the brain could also have a biological basis.

scholarly journals A-GHN: Attention-based Fusion of Multiple GraphHeat Networks for Structural to Functional Brain Mapping

2021 ◽  
Author(s):  
SUBBA REDDY OOTA ◽  
Archi Yadav ◽  
Arpita Dash ◽  
Surampudi Bapi Raju ◽  
Avinash Sharma
Keyword(s):  
Deep Learning ◽  
Functional Connectivity ◽  
Complex Dynamics ◽  
Brain Activity ◽  
Structural Connectivity ◽  
Reaction Diffusion ◽  
Complex Nature ◽  
Relational Structures ◽  
Human Connectome Project ◽  
The Brain

Over the last decade, there has been growing interest in learning the mapping from structural connectivity (SC) to functional connectivity (FC) of the brain. The spontaneous fluctuations of the brain activity during the resting-state as captured by functional MRI (rsfMRI) contain rich non-stationary dynamics over a relatively fixed structural connectome. Among the modeling approaches, graph diffusion-based methods with single and multiple diffusion kernels approximating static or dynamic functional connectivity have shown promise in predicting the FC given the SC. However, these methods are computationally expensive, not scalable, and fail to capture the complex dynamics underlying the whole process. Recently, deep learning methods such as GraphHeat networks along with graph diffusion have been shown to handle complex relational structures while preserving global information. In this paper, we propose a novel attention-based fusion of multiple GraphHeat networks (A-GHN) for mapping SC-FC. A-GHN enables us to model multiple heat kernel diffusion over the brain graph for approximating the complex Reaction Diffusion phenomenon. We argue that the proposed deep learning method overcomes the scalability and computational inefficiency issues but can still learn the SC-FC mapping successfully. Training and testing were done using the rsfMRI data of 100 participants from the human connectome project (HCP), and the results establish the viability of the proposed model. Furthermore, experiments demonstrate that A-GHN outperforms the existing methods in learning the complex nature of human brain function.

scholarly journals A functional-structural connectivity metric detects ipsilateral connections with distinct functional specialisation in each hemisphere

2020 ◽  
Author(s):  
Oren Civier ◽  
Marion Sourty ◽  
Fernando Calamante
Keyword(s):  
Functional Connectivity ◽  
Functional Mri ◽  
Measurement Errors ◽  
Diffusion Mri ◽  
Right Hemisphere ◽  
Structural Connectivity ◽  
Joint Analysis ◽  
Fibre Bundles ◽  
Human Connectome Project ◽  
The Brain

AbstractWe introduce a connectomics metric that integrates information on structural connectivity (SC) from diffusion MRI tractography and functional connectivity (FC) from resting-state functional MRI, at individual subject level. The metric is based on the ability of SC to broadly predict FC using a simple linear predictive model; for each connection in the brain, the metric quantifies the deviation from that model. For the metric to capture underlying physiological properties, we minimise systematic measurement errors and processing biases in both SC and FC, and address several challenges with the joint analysis. This also includes a data-driven normalisation approach. The combined metric may provide new information by indirectly assessing white matter structural properties that cannot be inferred from diffusion MRI alone, and/or complex interregional neural interactions that cannot be inferred from functional MRI alone. To demonstrate the utility of the metric, we used young adult data from the Human Connectome Project to examine all bilateral pairs of ipsilateral connections, i.e. each left-hemisphere connection in the brain was paired with its right-hemisphere homologue. We detected a minority of bilateral pairs where the metric value is significantly different across hemispheres, which we suggest reflects cases of ipsilateral connections that have distinct functional specialisation in each hemisphere. The pairs with significant effects spanned all cortical lobes, and also included several cortico-subcortical connections. Our findings highlight the potential in a joint analysis of structural and functional measures of connectivity, both for clinical applications and to help in the interpretation of results from standard functional connectivity analysis.Significance StatementBased on the notion that structure predicts function, the scientific community sought to demonstrate that structural information on fibre bundles that connect brain regions is sufficient to estimate the strength of interregional interactions. However, an accurate prediction using MRI has proved elusive. This paper posits that the failure to predict function from structure originates from limitations in measurement or interpretation of either diffusion MRI (to assess fibre bundles), fMRI (to assess functional interactions), or both. We show that these limitations can be nevertheless beneficial, as the extent of divergence between the two modalities may reflect hard-to-measure properties of interregional connections, such as their functional role in the brain. This provides many insights, including into the division of labour between hemispheres.

scholarly journals Subject specificity of the correlation between large-scale structural and functional connectivity

2019 ◽  
Vol 3 (1) ◽  
pp. 90-106 ◽  
Author(s):  
J. Zimmermann ◽  
J. Griffiths ◽  
M. Schirner ◽  
P. Ritter ◽  
A. R. McIntosh
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Structural Connectivity ◽  
Subject Specificity ◽  
Human Connectome Project ◽  
Subject Specific ◽  
The Brain ◽  
Human Neuroimaging

Structural connectivity (SC), the physical pathways connecting regions in the brain, and functional connectivity (FC), the temporal coactivations, are known to be tightly linked. However, the nature of this relationship is still not understood. In the present study, we examined this relation more closely in six separate human neuroimaging datasets with different acquisition and preprocessing methods. We show that using simple linear associations, the relation between an individual’s SC and FC is not subject specific for five of the datasets. Subject specificity of SC-FC fit is achieved only for one of the six datasets, the multimodal Glasser Human Connectome Project (HCP) parcellated dataset. We show that subject specificity of SC-FC correspondence is limited across datasets due to relatively small variability between subjects in SC compared with the larger variability in FC.

scholarly journals Enhanced structural connectivity within the motor loop in professional boxers prior to a match

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuichi Ogino ◽  
Hiroaki Kawamichi ◽  
Daisuke Takizawa ◽  
Sho K. Sugawara ◽  
Yuki H. Hamano ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Body Mass ◽  
Primary Motor Cortex ◽  
Skill Training ◽  
Gray Matter Volume ◽  
Structural Connectivity ◽  
Matter Volume ◽  
Essential Region ◽  
Motor Loop ◽  
The Brain

AbstractProfessional boxers train to reduce their body mass before a match to refine their body movements. To test the hypothesis that the well-defined movements of boxers are represented within the motor loop (cortico-striatal circuit), we first elucidated the brain structure and functional connectivity specific to boxers and then investigated plasticity in relation to boxing matches. We recruited 21 male boxers 1 month before a match (Time1) and compared them to 22 age-, sex-, and body mass index (BMI)-matched controls. Boxers were longitudinally followed up within 1 week prior to the match (Time2) and 1 month after the match (Time3). The BMIs of boxers significantly decreased at Time2 compared with those at Time1 and Time3. Compared to controls, boxers presented significantly higher gray matter volume in the left putamen, a critical region representing motor skill training. Boxers presented significantly higher functional connectivity than controls between the left primary motor cortex (M1) and left putamen, which is an essential region for establishing well-defined movements. Boxers also showed significantly higher structural connectivity in the same region within the motor loop from Time1 to Time2 than during other periods, which may represent the refined movements of their body induced by training for the match.

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