scholarly journals Topographic diversity of structural connectivity in schizophrenia

2018 ◽  
Author(s):  
Hongtao Ruan ◽  
Qiang Luo ◽  
Lena Palaniyappan ◽  
Chu-Chung Huang ◽  
Chun-Yi Zac Lo ◽  
...  
Keyword(s):  
Classification Accuracy ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Common Pathway ◽  
Cross Sectional ◽  
Dsm Iv ◽  
High Degree ◽  
Pathophysiological Model ◽  
Diffusion Tensor Imaging Dti

AbstractThe neurobiological heterogeneity of schizophrenia is widely accepted, but it is unclear how mechanistic differences converge to produce the observed phenotype. Establishing a pathophysiological model that accounts for both heterogeneity and phenotypic similarity is essential to inform stratified treatment approaches. In this cross-sectional diffusion tensor imaging (DTI) study, we recruited 77 healthy controls (HC), and 71 patients with DSM-IV diagnosis of schizophrenia (SCZ), and reconstructed the structural connectivity of 90 brain regions covering entire cerebral cortex. We first confirmed the heterogeneity in structural connectivity by showing a reduced inter-individual similarity in SCZ compared with HC. Moreover, we found it was not possible to cluster patients into subgroups with shared patterns of dysconnectivity, indicating a high degree of mechanistic divergence in schizophrenia. Instead of the strength of connectivity between any particular brain regions, we investigated the diversity (or statistically, the variance) of the topographic distribution of the strength was reduced. HC had higher topographic diversity in whole brain structural connectivity compared to the patient group(P = 2 × 10−6, T = 4.96, Cohen′S d = 0.87). In 62 of the 90 brain regions, the topographic diversity was significantly reduced in patients compared to controls after FDR correction (<0.05). When topographic diversity was used as a discriminant feature for classification between patients and controls, we significantly (P = 4.29 × 10−24) improved the classification accuracy to 79.6% (sensitivity 78.3%, specificity 81.3%). This finding suggests highly individualized pattern of structural dysconnectivity underlying the heterogeneity of schizophrenia converges to a convergent common pathway as reduced topographic diversity for the clinical construct of the disease.

scholarly journals Structural connectivity-based segmentation of the human entorhinal cortex

2021 ◽  
Author(s):  
Ingrid Framås Syversen ◽  
Menno P. Witter ◽  
Asgeir Kobro-Flatmoen ◽  
Pål Erik Goa ◽  
Tobias Navarro Schröder ◽  
...  
Keyword(s):  
Entorhinal Cortex ◽  
Diffusion Tensor ◽  
Imaging Modality ◽  
Classical Model ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Retrosplenial Cortex ◽  
Strongly Connected ◽  
Posterior Anterior ◽  
Diffusion Tensor Imaging Dti

The medial (MEC) and lateral entorhinal cortex (LEC), widely studied in rodents, are well defined and characterized. In humans, however, the exact locations of their homologues remain uncertain. Previous functional magnetic resonance imaging (fMRI) studies have subdivided the human EC into posterior-medial (pmEC) and anterior-lateral (alEC) parts, but uncertainty remains about the choice of imaging modality and seed regions, in particular in light of a substantial revision of the classical model of EC connectivity based on novel insights from rodent anatomy. Here, we used structural, not functional imaging, namely diffusion tensor imaging (DTI) and probabilistic tractography to segment the human EC based on differential connectivity to other brain regions known to project selectively to MEC or LEC. We defined MEC as more strongly connected to presubiculum and retrosplenial cortex (RSC), and LEC as more strongly connected to distal CA1 and proximal subiculum (dCA1pSub) and orbitofrontal cortex (OFC). Although our DTI segmentation had a larger medial-lateral component than in previous fMRI studies, our results show that the human MEC and LEC homologues have a border oriented both towards the posterior-anterior and medial-lateral axes, supporting the differentiation between pmEC and alEC.

scholarly journals An architectonic type principle in the development of laminar patterns of cortico-cortical connections

2021 ◽  
Author(s):  
Sarah F. Beul ◽  
Alexandros Goulas ◽  
Claus C. Hilgetag
Keyword(s):  
Structural Connectivity ◽  
Macaque Monkey ◽  
Brain Regions ◽  
Adult Brain ◽  
Mammalian Brain ◽  
Cortical Connections ◽  
Cortical Projections ◽  
Structural Connections ◽  
High Degree ◽  
The Brain

AbstractStructural connections between cortical areas form an intricate network with a high degree of specificity. Many aspects of this complex network organization in the adult mammalian cortex are captured by an architectonic type principle, which relates structural connections to the architectonic differentiation of brain regions. In particular, the laminar patterns of projection origins are a prominent feature of structural connections that varies in a graded manner with the relative architectonic differentiation of connected areas in the adult brain. Here we show that the architectonic type principle is already apparent for the laminar origins of cortico-cortical projections in the immature cortex of the macaque monkey. We find that prenatal and neonatal laminar patterns correlate with cortical architectonic differentiation, and that the relation of laminar patterns to architectonic differences between connected areas is not substantially altered by the complete loss of visual input. Moreover, we find that the degree of change in laminar patterns that projections undergo during development varies in proportion to the relative architectonic differentiation of the connected areas. Hence, it appears that initial biases in laminar projection patterns become progressively strengthened by later developmental processes. These findings suggest that early neurogenetic processes during the formation of the brain are sufficient to establish the characteristic laminar projection patterns. This conclusion is in line with previously suggested mechanistic explanations underlying the emergence of the architectonic type principle and provides further constraints for exploring the fundamental factors that shape structural connectivity in the mammalian brain.

Diffusion tensor imaging (DTI) findings in schizophrenia: A review

2011 ◽  
Vol 26 (S2) ◽  
pp. 960-960
Author(s):  
J.L. Villegas Martínez ◽  
J.A. Blanco Garrote ◽  
F. Uribe Ladrón de Cegama ◽  
B. Arribas Simón ◽  
G. Cabús Piñol
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Cochrane Review ◽  
Brain Structures ◽  
Brain Regions ◽  
Parahippocampal Gyrus ◽  
First Episode ◽  
Chronic Patients ◽  
Brain White Matter ◽  
Diffusion Tensor Imaging Dti

IntroductionDiffusion tensor imaging (DTI) is a magnetic resonance imaging technique that have increasingly being used for the non-invasive evaluation of brain white matter (WM) abnormalities. Several studies suggest that the normal integration of cerebral function may be compromised in schizophrenia. Abnormalities in WM tracts may be directly relevant for the neuropathology of schizophrenia.ObjetivesThe purpose of this review was to discuss recent DTI findings in schizophrenia and a methodologic analysis.MethodsThe literature search was performed with the search engine PubMed of the U.S. National Library of Medicine. Search strategy used was based on the Cochrane review technique, limited to the period between 1998 (first report on DTI and schizophrenia) and May 2010. And limited to ‘Title/Abstract’. The reference lists of these studies were used to identify additional studies.ResultsThere is a striking amount of heterogeneity in findings, probably by methodologic problems. Brain regions such as the cingulate bundle, corpus callosum, and regions within frontal and temporal WM have a proportionally larger number of positive findings across the studies. In addition, WM tracts as The superior longitudinal fasciculus, fronto-occipital longitudinal fasciculi, uncinate fasciculi, frontal longitudinal fasciculus and the arcuate fasciculus have also positive findings in patients with schizophrenia. Other brain structures as the cerebellar peduncles, the fornix, the hippocampus and parahippocampal gyrus, the thalamic and optic radiations have been evaluated and shown positive findings. However, these findings are not present in all studies. DTI abnormalities in first-episode patients are less robust than in chronic patients.ConclusionsRecent DTI findings further support the hypothesis of structural dysconnectivity in schizophrenia.

scholarly journals Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Node Degree ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Structural Brain Network ◽  
Structural Networks

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

scholarly journals Structure supports function: informing directed and dynamic functional connectivity with anatomical priors

2021 ◽  
Author(s):  
David Pascucci ◽  
Maria Rubega ◽  
Joan Rue-Queralt ◽  
Sebastien Tourbier ◽  
Patric Hagmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Diffusion Tensor ◽  
Meta Analysis ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Noise Perturbation ◽  
Eeg Data ◽  
Functional Brain Networks ◽  
Anatomical Priors ◽  
And Diffusion

The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections: the lack of a direct structural link between two brain regions prevents direct functional interactions. Despite the intrinsic relationship between structural (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited, especially for electrophysiological data. In the present work, we propose a new linear adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors. We tested the filter in rat epicranial recordings and human event-related EEG data, using SC priors from a meta-analysis of tracer studies and diffusion tensor imaging metrics, respectively. Our results show that SC priors increase the resilience of FC estimates to noise perturbation while promoting sparser networks under biologically plausible constraints. The proposed filter provides intrinsic protection against SC-related false negatives, as well as robustness against false positives, representing a valuable new method for multimodal imaging and dynamic FC analysis.

scholarly journals Connectivity changes in major depressive disorder after rTMS: a review of functional and structural connectivity data

2021 ◽  
Vol 30 ◽  
Author(s):  
G. Schiena ◽  
G. Franco ◽  
A. Boscutti ◽  
G. Delvecchio ◽  
E. Maggioni ◽  
...  
Keyword(s):  
Diffusion Tensor ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Small Sample Size ◽  
Structural Connectivity ◽  
Unipolar Depression ◽  
Brain Regions ◽  
Small Sample ◽  
Anterior Cingulate ◽  
Antidepressant Effect ◽  
Dorsolateral Prefrontal

Abstract Aims In the search for effective therapeutic strategies for depression, repetitive transcranial magnetic stimulation (rTMS) emerged as a non-invasive, promising treatment. This is because the antidepressant effect of rTMS might be related to neuronal plasticity mechanisms possibly reverting connectivity alterations often observed in depression. Therefore, in this review, we aimed at providing an overview of the findings reported by studies investigating functional and structural connectivity changes after rTMS in depression. Methods A bibliographic search was conducted on PubMed, including studies that used unilateral, excitatory (⩾10 Hz) rTMS treatment targeted on the left dorsolateral prefrontal cortex (DLPFC) in unipolar depressed patients. Results The majority of the results showed significant TMS-induced changes in functional connectivity (FC) between areas important for emotion regulation, including the DLPFC and the subgenual anterior cingulate cortex, and among regions that are part of the major resting-state networks, such as the Default Mode Network, the Salience Networks and the Central Executive Network. Finally, in diffusion tensor imaging studies, it has been reported that rTMS appeared to increase fractional anisotropy in the frontal lobe. Limitations The small sample size, the heterogeneity of the rTMS stimulation parameters, the concomitant use of psychotropic drugs might have limited the generalisability of the results. Conclusions Overall, rTMS treatment induces structural and FC changes in brain regions and networks implicated in the pathogenesis of unipolar depression. However, whether these changes underlie the antidepressant effect of rTMS still needs to be clarified.

scholarly journals Scan–rescan and inter-vendor reproducibility of neurite orientation dispersion and density imaging metrics

2019 ◽  
Vol 62 (4) ◽  
pp. 483-494
Author(s):  
Christina Andica ◽  
Koji Kamagata ◽  
Takuya Hayashi ◽  
Akifumi Hagiwara ◽  
Wataru Uchida ◽  
...  
Keyword(s):  
Gray Matter ◽  
Healthy Subjects ◽  
Volume Fraction ◽  
Diffusion Tensor ◽  
Intraclass Correlation ◽  
Region Of Interest ◽  
Brain Regions ◽  
Automatic Extraction ◽  
Dispersion Index ◽  
Diffusion Tensor Imaging Dti

Abstract Purpose The reproducibility of neurite orientation dispersion and density imaging (NODDI) metrics in the human brain has not been explored across different magnetic resonance (MR) scanners from different vendors. This study aimed to evaluate the scan–rescan and inter-vendor reproducibility of NODDI metrics in white and gray matter of healthy subjects using two 3-T MR scanners from two vendors. Methods Ten healthy subjects (7 males; mean age 30 ± 7 years, range 23–37 years) were included in the study. Whole-brain diffusion-weighted imaging was performed with b-values of 1000 and 2000 s/mm2 using two 3-T MR scanners from two different vendors. Automatic extraction of the region of interest was performed to obtain NODDI metrics for whole and localized areas of white and gray matter. The coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated to assess the scan–rescan and inter-vendor reproducibilities of NODDI metrics. Results The scan–rescan and inter-vendor reproducibility of NODDI metrics (intracellular volume fraction and orientation dispersion index) were comparable with those of diffusion tensor imaging (DTI) metrics. However, the inter-vendor reproducibilities of NODDI (CoV = 2.3–14%) were lower than the scan–rescan reproducibility (CoV: scanner A = 0.8–3.8%; scanner B = 0.8–2.6%). Compared with the finding of DTI metrics, the reproducibility of NODDI metrics was lower in white matter and higher in gray matter. Conclusion The lower inter-vendor reproducibility of NODDI in some brain regions indicates that data acquired from different MRI scanners should be carefully interpreted.

scholarly journals Plasma neurofilament light and cerebrospinal fluid biomarkers are associated with white matter damage in Alzheimer's disease

2020 ◽  
Author(s):  
Fardin Nabizadeh ◽  
Mohammad Balabandian ◽  
Mohammad Reza Rostami ◽  
Samuel Berchi Kankam
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Csf Biomarkers ◽  
Cross Sectional ◽  
Neurofilament Light ◽  
Microstructural Changes ◽  
Cerebrospinal Fluid Biomarkers

Abstract The most replicated blood biomarker for monitoring Alzheimer’s disease is neurofilament light (NFL). Recent evidence revealed that the plasma level of the NFL has a strong predictive value in cognitive decline and is elevated in AD patients. The Diffusion Tensor Imaging (DTI) is understood to reflect white matter disruption, neurodegeneration largely, and synaptic damage in AD. However, there is no investigation of the association between plasma NFL and white matter microstructure integrity. we have investigated the cross-sectional associations of plasma NFL, CSF tau, p tau, and Aβ with white matter microstructural changes as measured by DTI in 92 mild cognitive impairment (MCI) participants. We investigated potential correlations of the DTI values of each region of the MNI atlas, with plasma NFL, CSF total tau, CSF p tau, and as well as CSF Aβ, separately using a partial correlation model controlled for the effect of age, sex and APOE ε4 genotype. Our findings revealed a significant correlation between plasma and CSF biomarkers with altered white matter microstructural changes in widespread brain regions. Plasma NFL has a negative correlation with FA and positive correlation with RD, AD, and MD values in different regions. Plasma NFL promises to be an early biomarker of microstructural changes in MCI and for MCI progression to AD.

Single Cortical Microinfarcts Lead to Widespread Microglia/Macrophage Migration Along the White Matter

2020 ◽  
Vol 31 (1) ◽  
pp. 248-266
Author(s):  
Alisa Lubart ◽  
Amit Benbenishty ◽  
Hagai Har-Gil ◽  
Hadas Laufer ◽  
Amos Gdalyahu ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Subcortical White Matter ◽  
Dependent Manner ◽  
Longitudinal Diffusion ◽  
Distant Tissue ◽  
Migratory Path ◽  
Tissue Reorganization ◽  
Diffusion Tensor Imaging Dti

Abstract Loss of cognitive function with aging is a complex and poorly understood process. Recently, clinical research has linked the occurrence of cortical microinfarcts to cognitive decline. Cortical microinfarcts form following the occlusion of penetrating vessels and are considered to be restricted to the proximity of the occluded vessel. Whether and how such local events propagate and affect remote brain regions remain unknown. To this end, we combined histological analysis and longitudinal diffusion tensor imaging (DTI), following the targeted-photothrombotic occlusion of single cortical penetrating vessels. Occlusions resulted in distant tissue reorganization across the mouse brain. This remodeling co-occurred with the formation of a microglia/macrophage migratory path along subcortical white matter tracts, reaching the contralateral hemisphere through the corpus callosum and leaving a microstructural signature detected by DTI-tractography. CX3CR1-deficient mice exhibited shorter trail lengths, differential remodeling, and only ipsilateral white matter tract changes. We concluded that microinfarcts lead to brain-wide remodeling in a microglial CX3CR1-dependent manner.

Diffusion tensor imaging in schizophrenia

2008 ◽  
Vol 23 (4) ◽  
pp. 255-273 ◽  
Author(s):  
Marinos Kyriakopoulos ◽  
Theodoros Bargiotas ◽  
Gareth J. Barker ◽  
Sophia Frangou
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Basic Principles ◽  
Future Directions ◽  
White Matter Abnormalities ◽  
Non Invasive ◽  
Brain White Matter ◽  
Diffusion Tensor Imaging Dti

AbstractDiffusion tensor imaging (DTI) is a magnetic resonance imaging technique that is increasingly being used for the non-invasive evaluation of brain white matter abnormalities. In this review, we discuss the basic principles of DTI, its roots and the contribution of European centres in its development, and we review the findings from DTI studies in schizophrenia. We searched EMBASE, PubMed, PsychInfo, and Medline from February 1998 to December 2006 using as keywords ‘schizophrenia’, ‘diffusion’, ‘tensor’, and ‘DTI’. Forty studies fulfilling the inclusion criteria of this review were included and systematically reviewed. White matter abnormalities in many diverse brain regions were identified in schizophrenia. Although the findings are not completely consistent, frontal and temporal white matter seems to be more commonly affected. Limitations and future directions of this method are discussed.

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