scholarly journals Investigating the Relationship between White Matter Connectivity and Motivational Circuits in Subjects with Deficit Schizophrenia: A Diffusion Tensor Imaging (DTI) Study

2021 ◽  
Vol 11 (1) ◽  
pp. 61
Author(s):  
Giulia M. Giordano ◽  
Pasquale Pezzella ◽  
Mario Quarantelli ◽  
Paola Bucci ◽  
Anna Prinster ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Negative Symptoms ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Insular Cortex ◽  
Deficit Syndrome ◽  
Deficit Schizophrenia ◽  
The Right ◽  
White Matter Connectivity ◽  
Diffusion Tensor Imaging Dti

Deficit schizophrenia is a subtype of schizophrenia presenting primary and enduring negative symptoms (NS). Although one of the most updated hypotheses indicates a relationship between NS and impaired motivation, only a few studies have investigated abnormalities of motivational circuits in subjects with deficit schizophrenia (DS). Our aim was to investigate structural connectivity within motivational circuits in DS. We analyzed diffusion tensor imaging (DTI) data from 46 subjects with schizophrenia (SCZ) and 35 healthy controls (HCs). SCZ were classified as DS (n = 9) and non-deficit (NDS) (n = 37) using the Schedule for Deficit Syndrome. The connectivity index (CI) and the Fractional Anisotropy (FA) of the connections between selected brain areas involved in motivational circuits were examined. DS, as compared with NDS and HCs, showed increased CI between the right amygdala and dorsal anterior insular cortex and increased FA of the pathway connecting the left nucleus accumbens with the posterior insular cortex. Our results support previous evidence of distinct neurobiological alterations underlying different clinical subtypes of schizophrenia. DS, as compared with NDS and HCs, may present an altered pruning process (consistent with the hyperconnectivity) in cerebral regions involved in updating the stimulus value to guide goal-directed behavior.

scholarly journals Reduction in White Matter Connectivity, Revealed by Diffusion Tensor Imaging, May Account for Age-related Changes in Face Perception

2008 ◽  
Vol 20 (2) ◽  
pp. 268-284 ◽  
Author(s):  
Cibu Thomas ◽  
Linda Moya ◽  
Galia Avidan ◽  
Kate Humphreys ◽  
Kwan Jin Jung ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Face Perception ◽  
Face Processing ◽  
Right Hemisphere ◽  
Diffusion Tensor ◽  
Temporal Cortex ◽  
Age Related ◽  
The Right ◽  
White Matter Connectivity

An age-related decline in face processing, even under conditions in which learning and memory are not implicated, has been well documented, but the mechanism underlying this perceptual alteration remains unknown. Here, we examine whether this behavioral change may be accounted for by a reduction in white matter connectivity with age. To this end, we acquired diffusion tensor imaging data from 28 individuals aged 18 to 86 years and quantified the number of fibers, voxels, and fractional anisotropy of the two major tracts that pass through the fusiform gyrus, the pre-eminent face processing region in the ventral temporal cortex. We also measured the ability of a subset of these individuals to make fine-grained discriminations between pairs of faces and between pairs of cars. There was a significant reduction in the structural integrity of the inferior fronto-occipital fasciculus (IFOF) in the right hemisphere as a function of age on all dependent measures and there were also some changes in the left hemisphere, albeit to a lesser extent. There was also a clear age-related decrement in accuracy of perceptual discrimination, especially for more challenging perceptual discriminations, and this held to a greater degree for faces than for cars. Of greatest relevance, there was a robust association between the reduction of IFOF integrity in the right hemisphere and the decline in face perception, suggesting that the alteration in structural connectivity between the right ventral temporal and frontal cortices may account for the age-related difficulties in face processing.

scholarly journals The white matter network in cognitive normal elderly predict the rate of cognitive decline

2020 ◽  
Author(s):  
Weijie Huang ◽  
Ni Shu
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Cognitive Decline ◽  
Parietal Lobe ◽  
Diffusion Tensor ◽  
Cognitive Changes ◽  
Cognitive Domains ◽  
Age Related ◽  
The Right ◽  
White Matter Connectivity

AbstractWhite matter degradation has been proposed as one possible explanation for age-related cognitive decline. The human brain is, however, a network and it may be more appropriate to relate cognitive functions to properties of the network rather than specific brain regions. Cognitive domains were measured annually (mean follow-up = 1.25 ± 0.61 years), including processing speed, memory, language, visuospatial, and executive functions. Diffusion tensor imaging was performed at baseline in 90 clinically normal older adults (aged 54–86). We report on graph theory-based analyses of diffusion tensor imaging tract-derived connectivity. The machine learning approach was used to predict the rate of cognitive decline from white matter connectivity data. The reduced efficacy of white matter networks could predict the performance of these cognitive domains except memory. The predicted scores were significantly correlated with the real scores. For the local regions for predicting the cognitive changes, the right precuneus, left inferior parietal lobe and cuneus are the most important regions for predicting monthly change of executive function; some left partial and occipital regions are the most important for the changed of attention; the right frontal and temporal regions are the most important for the changed of language. Our findings suggested that the global white matter connectivity characteristics are the valuable predictive index for the longitudinal cognitive decline. For the first time, topological efficiency of white matter connectivity maps which related to special domains of cognitive decline in the elderly are identified.

Intraspinal Tumors: The Value of Diffusion Tensor Imaging (DTI) and Tractography: A Preliminary Study

2018 ◽  
Author(s):  
F. Cartes-Zumelzu ◽  
S. Ingorokva ◽  
H. Kostron ◽  
G. Feuchtner ◽  
C. Kremser ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Preliminary Study ◽  
Diffusion Tensor Imaging Dti

White Matter Alteration Following SWAT Explosive Breaching Training and the Moderating Effect of a Neck Collar Device: A DTI and NODDI Study

2021 ◽  
Author(s):  
Weihong Yuan ◽  
Jonathan Dudley ◽  
Alexis B Slutsky-Ganesh ◽  
James Leach ◽  
Pete Scheifele ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Moderating Effect ◽  
Significant Group ◽  
Blast Exposure ◽  
Diffusion Weighted ◽  
Weighted Data ◽  
The Right ◽  
The Impact

ABSTRACT Introduction Special Weapons and Tactics (SWAT) personnel who practice breaching with blast exposure are at risk for blast-related head trauma. We aimed to investigate the impact of low-level blast exposure on underlying white matter (WM) microstructure based on diffusion tensor imaging (DTI) and neurite orientation and density imaging (NODDI) in SWAT personnel before and after breacher training. Diffusion tensor imaging is an advanced MRI technique sensitive to underlying WM alterations. NODDI is a novel MRI technique emerged recently that acquires diffusion weighted data from multiple shells modeling for different compartments in the microstructural environment in the brain. We also aimed to evaluate the effect of a jugular vein compression collar device in mitigating the alteration of the diffusion properties in the WM as well as its role as a moderator on the association between the diffusion property changes and the blast exposure. Materials and Methods Twenty-one SWAT personnel (10 non-collar and 11 collar) completed the breacher training and underwent MRI at both baseline and after blast exposure. Diffusion weighted data were acquired with two shells (b = 1,000, 2,000 s/mm2) on 3T Phillips scanners. Diffusion tensor imaging metrices, including fractional anisotropy, mean, axial, and radial diffusivity, and NODDI metrics, including neurite density index (NDI), isotropic volume fraction (fiso), and orientation dispersion index, were calculated. Tract-based spatial statistics was used in the voxel-wise statistical analysis. Post hoc analyses were performed for the quantification of the pre- to post-blast exposure diffusion percentage change in the WM regions with significant group difference and for the assessment of the interaction of the relationship between blast exposure and diffusion alteration. Results The non-collar group exhibited significant pre- to post-blast increase in NDI (corrected P < .05) in the WM involving the right internal capsule, the right posterior corona radiation, the right posterior thalamic radiation, and the right sagittal stratum. A subset of these regions showed significantly greater alteration in NDI and fiso in the non-collar group when compared with those in the collar group (corrected P < .05). In addition, collar wearing exhibited a significant moderating effect for the alteration of fiso for its association with average peak pulse pressure. Conclusions Our data provided initial evidence of the impact of blast exposure on WM diffusion alteration based on both DTI and NODDI. The mitigating effect of WM diffusivity changes and the moderating effect of collar wearing suggest that the device may serve as a promising solution to protect WM against blast exposure.

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