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Tseng, W.-Y. I.

Publications and source records attributed to Tseng, W.-Y. I..

5 recordsLinked to original sources
bioRxiv2021

DACO: Distortion/artefact correction for diffusion MRI data in an integrated framework

In this paper we propose a registration-based algorithm to correct various distortions or artefacts (DACO) commonly observed in diffusion weighted (DW) magnetic resonance images (MRI). The registration in DACO is proceeded on the basis of a pseudo b0 image, which is synthesized from the anatomical images such as T1-weighted image or T2-weighted image, and a pseudo diffusion MRI (dMRI) data, which is derived from the Gaussian model of diffusion tensor imaging (DTI) or the Hermite model of MAP-MRI. DACO corrects (1) the susceptibility-induced distortions, (2) the intensity inhomogeneity, and (3) the misalignment between the dMRI data and anatomical images by registering the real b0 image to the pseudo b0 image, and corrects (4) the eddy current (EC)-induced distortions and (5) the head motions by registering each of the DW images in the real dMRI data to the corresponding image in the pseudo dMRI data. As the above artefacts interact with each other, DACO models each type of artefact in an integrated framework and estimates these models in an interleaved and iterative manner. The mathematical formulation of the models and the comprehensive estimation procedures are detailed in this paper. The evaluation using the human connectome project data shows that DACO could estimate the model parameters accurately. Furthermore, the evaluation conducted on the real human data acquired from clinical MRI scanners reveals that the method could reduce the artefacts effectively. The DACO method leverages the anatomical image, which is routinely acquired in clinical practice, to correct the artefacts, minimizing the additional acquisitions needed to conduct the algorithm. Therefore, our method is beneficial to most dMRI data, particularly to those without acquiring the field map or blip-up and blip-down images.

neuroscience↗
bioRxiv2020

Multimodal Brain Age Gap as a Mediating Indicator in the Relation between Modifiable Dementia Risk Factors and Cognitive Functioning

IntroductionAs a structural proxy for evaluating brain health, neuroimaging-based brain age gap (BAG) is presumed to link the dementia risks to cognitive changes in the premorbid phase, but this remains unclear. MethodsBrain age prediction models were constructed and applied to a population-based cohort (N=371) to estimate their BAG. Further, structural equation modeling was employed to investigate the mediation effect of BAG between risk levels (assessed by 2 dementia-related risk scores) and cognitive changes (examined by 4 cognitive assessments). ResultsA higher burden of modifiable dementia risk factors was causally associated with a greater cognitive decline, and this was significantly mediated (P=0.017) by a larger multimodal BAG, which indicated an older brain. Moreover, a steeper slope (P=0.020) of association between cognitive decline and multimodal BAG was observed when individuals had higher dementia risks. DiscussionMultimodal BAG is a potential mediating indicator to reflect the changes in the pathophysiological mechanism of cognitive aging.

neuroscience↗
bioRxiv2019

Sustained modulation of emotion-related fibers after 8 weeks of mindfulness-based stress reduction training

An 8-week mindfulness-based stress reduction (MBSR) program enables novices to learn and practice mindfulness meditation. A longitudinal study design has been used in prior research to investigate the effect of short-term mindfulness meditation training on brain structures. Many studies have demonstrated microstructural changes in the white matter by comparing baseline measurements with measurements obtained immediately after short-term meditation training. However, these studies did not clarify the evolution of the modulated microstructures several months after mindfulness meditation practice is discontinued. Therefore, in this study, we recruited 13 novice practitioners and administered an 8-week MBSR training program. We extended the span of the longitudinal study by adding a third measurement taken approximately 6 months after the second time point. Diffusion indices derived from diffusion spectrum imaging were used to quantify the temporal changes in modulation across three time points. The analysis identified four tract bundles that were significantly modulated after the 8-week MBSR training program, namely the callosal fibers connecting the bilateral amygdalae and bilateral hippocampi, right thalamic radiation of the auditory nerve, and right uncinate fasciculus. At the third time point, at which the participants had discontinued practice for approximately 6 months, the diffusion indices of the four tract bundles still presented a significant difference compared with the baseline. Our results indicate that the modulation of microstructural properties of the white matter tract induced by the 8-week MBSR program was sustained after completion of the program and support that neuroplasticity in brain connection persists after the discontinuation of meditation training.

neuroscience↗
bioRxiv2019

ADHD symptoms map onto noise-driven structure-function decoupling between hub and peripheral brain regions

Adults with childhood-onset attention-deficit hyperactivity disorder (ADHD) show altered whole-brain connectivity. However, the relationship between structural and functional brain abnormalities, the implications for the development of life-long debilitating symptoms, and the underlying mechanisms remain uncharted. We recruited a unique sample of 80 medication-naive adults with a clinical diagnosis of childhood-onset ADHD without psychiatric comorbidities, and 123 age-, sex-, and intelligence-matched healthy controls. Structural and functional connectivity matrices were derived from diffusion spectrum imaging and multi-echo resting-state functional MRI data. Hub, feeder, and local connections were defined using diffusion data. Individual-level measures of structural connectivity and structure-function coupling were used to contrast groups and link behavior to brain abnormalities. Computational modeling was used to test possible neural mechanisms underpinning observed group differences in the structure-function coupling. Structural connectivity did not significantly differ between groups but, relative to controls, ADHD showed a reduction in structure-function coupling in feeder connections linking hubs with peripheral regions. This abnormality involved connections linking fronto-parietal control systems with sensory networks. Crucially, lower structure-function coupling was associated with higher ADHD symptoms. Results from our computational model further suggest that the observed structure-function decoupling in ADHD is driven by heterogeneity in neural noise variability across brain regions. By highlighting a neural cause of a clinically meaningful breakdown in the structure-function relationship, our work provides novel information on the nature of chronic ADHD. The current results encourage future work assessing the genetic and neurobiological underpinnings of neural noise in ADHD, particularly in brain regions encompassed by fronto-parietal systems.

neuroscience↗
bioRxiv2017

Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder

BackgroundChildhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD.\n\nMethodsWe first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naive adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype.\n\nResultsAdults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD.\n\nConclusionsOverall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.

neuroscience↗