No abstract

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organisation. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "fixel-based analysis" (FBA) framework that implements bespoke solutions to this end, and has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to fixel-based analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of current fixel-based analysis studies (until August 2020), categorised across a broad range of neuroscientific domains, listing key design choices and summarising their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the fixel-based analysis framework, and outline some directions and future opportunities.

No abstract

Fixel-based analysis was used to probe age-related changes in white matter micro- and macrostructure of the corpus callosum between participants with (N = 54) and without (N = 50) autism spectrum disorder (ASD). Data were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Compared to age-matched controls, young adolescents with ASD (11.19 ± 7.54 years) showed reduced macroscopic fiber cross-section (logFC) and combined fiber-density and cross-section (FDC). Reduced fiber-density (FD) and FDC was noted in a marginally older (13.87 ± 3.15 years) ASD cohort. Among the oldest ASD cohort (17.07 ± 3.56 years), a non-significant trend indicative of reduced FD was noted. White matter aberration appears greatest and most widespread among younger ASD cohorts. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.

In recent years, there has been an increasing quest in improving our understanding of the neurocognitive deficits underlying adult attention-deficit/hyperactivity disorder (ADHD). Current statistical manuals of psychiatric disorders emphasize inattention and hyperactivity-impulsivity symptoms, but empirical studies have also shown consistent alterations in inhibitory control. To date, there is no established neuropsychological test to assess inhibitory control deficits in adult ADHD. A common paradigm for assessing response inhibition is the stop-signal task (SST). Following PRISMA-selection criteria, our systematic review and meta-analysis integrated the findings of 26 publications with 27 studies examining the SST in adult ADHD. The meta-analysis, which included 883 patients with adult ADHD and 916 control participants, revealed reliable inhibitory control deficits, as expressed in prolonged SST response times, with a moderate effect size $$g$$ g = 0.51 (95% CI: 0.376–0.644,$$p$$ p < 0.0001). The deficits were not moderated by study quality, sample characteristics or clinical parameters, suggesting that they may be a phenotype in this disorder. The analyses of secondary outcome measures revealed greater SST omission errors and reduced go accuracy in patients, indicative of altered sustained attention. However, only few (N < 10) studies were available for these measures. Our meta-analysis suggests that the SST, in conjunction with other tests and questionnaires, could become a valuable tool for assessing inhibitory control deficits in adult ADHD.

Corpus callosum anomalies are commonly noted in autism spectrum disorder (ASD). Given the complexity of its microstructural architecture, with crossing fibers projecting throughout, we applied fixel-based analysis to probe white matter micro- and macrostructure within this region. As ASD is a neurodevelopmental condition with noted abnormalities in brain growth, age was also investigated. Methods: Data for participants with (N=54) and without (N=50) ASD, aged 5-34 years, were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Within each site, indices of fiber density (FD), fiber cross-section (FC), and combined fiber density and cross-section (FDC) were compared between those groups. Results: Young adolescents with ASD (age = 11.19 +/- 7.54) showed reduced macroscopic FC and FDC compared to age-matched neurotypical controls (age = 10.04 +/- 4.40). Reduced FD and FDC was noted in a marginally older ASD (age 13.87 +/- 3.15) cohort compared to matched controls (age = 13.85 +/- 2.90). Among the oldest cohorts, a non-significant trend indicated reduced FD in older adolescents/young adults with ASD (age = 17.07 +/- 3.56) compared to controls (age = 16.55 +/- 2.95). There was a positive correlation between age and callosal mean FC and FDC in the youngest cohort. When stratified by diagnosis, this finding remained only for the ASD sample. Conclusion: White matter aberration appears greatest among younger ASD cohorts. In older adolescents and young adults, less of the corpus callosum seems affected. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.

No abstract

Background: In recent years, there has been an increasing quest in improving our understanding of neurocognitive deficits underlying adult attention-deficit/hyperactivity disorder (ADHD). Current statistical manuals of psychiatric disorders emphasize inattention and hyperactivity-impulsivity symptoms, but empirical studies have also shown consistent alterations in inhibitory control. Thus far, there is no established neuropsychological test to assess inhibitory control deficits in adult ADHD. A common paradigm for assessing response inhibition is the stop-signal task (SST). Methods: Following PRISMA-selection criteria, our systematic review and meta-analysis integrated the findings of 26 publications with 27 studies examining the SST in adult ADHD. Results: The meta-analysis, which included 883 patients with adult ADHD and 916 control participants, revealed reliable inhibitory control deficits, as expressed in prolonged SST response times, with a moderate effect size g = 0.51. The deficits were not moderated by study quality, sample characteristics or clinical parameters, suggesting that they may be a phenotype in this disorder. The analyses of secondary outcome measures revealed greater SST omission errors and reduced go accuracy in patients, indicative of altered sustained attention. However, only few (N<10) studies were available for these measures. Discussion: Our meta-analysis suggests that the SST could, in conjunction with other tests and questionnaires, become a valuable tool for the assessment of inhibitory control deficits in adult ADHD.