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A study has been conducted to determine an alternative method of detecting sparse erroneous data points present within a given sample. A discrete random signal was first built with an imposed shape in the frequency domain to demonstrate the effectivity of the technique. Findings have indicated that the use of the fast wavelet transform have been successful in locating the points on a signal where occasional high frequency phenomena occur.

Background: The COVID-19 pandemic has accelerated the adoption of digital tools to support individuals struggling with their mental health. The use of a digital intervention plus human coaching ("dual" intervention) is gaining momentum in increasing overall engagement in digital cognitive behavioral interventions (dCBIs). However, there is limited insight into the methodologies and coaching models used by those deploying dual interventions. To achieve a deeper understanding, we need to identify and promote effective engagement that leads to clinical outcomes versus simply monitoring engagement metrics. Motivational interviewing (MI) is a collaborative, goal-oriented communication approach that pays particular attention to the language of change and is an effective engagement approach to help people manage mental health issues. However, this approach has been traditionally used for in-person or telephonic interventions, and less is known about the application of MI to digital interventions., Objective: We sought to provide a dual intervention approach and address multiple factors across two levels of engagement to operationalize a dCBI that combined cognitive behavioral therapy-based techniques and MI-based interactions between the digital health coach (DHC) and user., Methods: We reviewed hundreds of digital exchanges between DHCs and users to identify and improve training and quality assurance activities for digital interventions., Results: We tested five hypotheses and found that: (1) users of a dual digital behavioral health intervention had greater engagement levels than users of a noncoached intervention (P<.001); (2) DHCs with a demonstrated competency in applying MI to digital messages had more engaged users, as measured by the DHC-to-user message exchange ratio (P<.001); (3) the DHC-to-user message exchange ratio was correlated with more engagement in app activities (r=0.28, 95% CI 0.23-0.33); (4) DHCs with demonstrated MI proficiency elicited a greater amount of "change talk" from users than did DHCs without MI proficiency (H=25.12, P<.001); and (5) users who were engaged by DHCs with MI proficiency had better clinical outcomes compared to users engaged by DHCs without MI proficiency (P=.02)., Conclusions: To our knowledge, this pilot was the first of its kind to test the application of MI to digital coaching protocols, and it demonstrated the value of MI proficiency in digital health coaching for enhanced engagement and health improvement. Further research is needed to establish coaching models in dCBIs that incorporate MI to promote effective engagement and optimize positive behavioral outcomes., (©Catherine Serio, Amanda Gabarda, Fatma Uyar-Morency, Valerie Silfee, Justin Ludwig, Eva Szigethy, Susan Butterworth. Originally published in JMIR Formative Research (https://formative.jmir.org), 11.05.2022.)

Diffusion MRI tractography processing pipeline requires a large number of steps (typically 20+ steps). If parameters of these steps, number of threads, and random seed generators are not carefully controlled, the resulting tractography can easily be non-reproducible and non-replicable, even in test-test experiments. To handle these issues, we developed TractoFlow. TractoFlow is fully automatic from raw diffusion weighted images to tractography. The pipeline also outputs classical diffusion tensor imaging measures and several fiber orientation distribution function measures. TractoFlow supports the recent Brain Imaging Data Structure (BIDS) format as input and is based on two engines: Nextflow and Singularity. In this work, the TractoFlow pipeline is evaluated on three databases and shown to be efficient and reproducible from 98% to 100%, depending on parameter choices. Moreover, it is easy to use for non-technical users, with little to no installation requirements. TractoFlow is publicly available for academic research and is an important step forward for better structural brain connectivity mapping., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: To study if the thalamic lateral geniculate nucleus (LGN) is affected in multiple sclerosis (MS) due to anterograde degeneration from optic neuritis (ON) or retrograde degeneration from optic radiation (OR) pathology, and if this is relevant for visual function., Methods: In this cross-sectional study, LGN volume of 34 patients with relapsing-remitting MS and 33 matched healthy controls (HC) was assessed on MRI using atlas-based automated segmentation (MAGeT). ON history, thickness of the ganglion cell-inner plexiform layer (GC-IPL), OR lesion volume, and fractional anisotropy (FA) of normal-appearing OR (NAOR-FA) were assessed as measures of afferent visual pathway damage. Visual function was tested, including low-contrast letter acuity (LCLA) and Hardy-Rand-Rittler (HRR) plates for color vision., Results: LGN volume was reduced in patients vs HC (165.5 ± 45.5 vs 191.4 ± 47.7 mm 3 , B = -25.89, SE = 5.83, p < 0.001). It was associated with GC-IPL thickness (B = 0.95, SE = 0.33, p = 0.006) and correlated with OR lesion volume (Spearman ρ = -0.53, p = 0.001), and these relationships remained after adjustment for normalized brain volume. There was no association between NAOR-FA and LGN volume (B = -133.28, SE = 88.47, p = 0.137). LGN volume was not associated with LCLA (B = 5.5 × 10 -5 , SE = 0.03, p = 0.998), but it correlated with HRR color vision (ρ = 0.39, p = 0.032)., Conclusions: LGN volume loss in MS indicates structural damage with potential functional relevance. Our results suggest both anterograde degeneration from the retina and retrograde degeneration from the OR lesions as underlying causes. LGN volume is a promising marker reflecting damage of the visual pathway in MS, with the advantage of individual measurement per patient on conventional MRI., (© 2019 American Academy of Neurology.)

Background: In temporal lobe epilepsy (TLE), advanced neuroimaging techniques reveal anomalies extending beyond the temporal lobe such as thinning of fronto-central cortices. Operculo-insular epilepsy (OIE) is an under-recognized and poorly characterized condition with the potential of mimicking TLE. In this work, we investigated insular and extra-insular cortical thickness (CT) changes in OIE., Methods: All participants (14 patients with refractory OIE, 9 age- and sex-matched patients with refractory TLE and 26 healthy controls) underwent a T1-weighted acquisition on a 3 T MRI. Anatomical images were processed with Advanced Normalization Tools. Between-group analysis of CT was performed using a two-sided t -test (threshold of p < 0.05 after correction for multiple comparisons; cut-off threshold of 250 voxels) between (i) patients with OIE vs TLE, and (ii) patients with OIE vs healthy controls., Results: Significant widespread thinning was observed in OIE patients as compared with healthy controls mainly in the ipsilateral insula, peri-rolandic region, orbito-frontal area, mesiotemporal structures and lateral temporal neocortex. Contralateral cortical shrinkage followed a similar albeit milder and less diffuse pattern.The CT of OIE patients was equal or reduced relative to the TLE group for every cortical region analyzed. Thinning was observed diffusely in OIE patients, predominantly inboth insulae and the ipsilateral occipito-temporal area., Conclusion: Our results reveal structural anomalies extending beyond the operculo-insular area in OIE.

Interactions between nanoparticles (NP), humans and the environment are not fully understood yet. Moreover, frameworks aiming at protecting human health have not been adapted to NP but are nonetheless applied to NP-related activities. Consequently, business organizations currently have to deal with NP-related risks despite the lack of a proven effective method of risk-management. To respond to these concerns and fulfill the needs of populations and industries, ÉquiNanos was created as a largely interdisciplinary provincial research team in Canada. ÉquiNanos consists of eight platforms with different areas of action, from adaptive decision-aid tool to public and legal governance, while including biological monitoring. ÉquiNanos resources aim at responding to the concerns of the Quebec nanotechnology industry and public health authorities. Our mandate is to understand the impact of NP on human health in order to protect the population against all potential risks emerging from these high-priority and rapidly expanding innovative technologies., From the Clinical Editor: In this paper by Canadian authors an important framework is discussed with the goal of acquiring more detailed information and establishing an infrastructure to evaluate the interaction between nanoparticles and living organisms, with the ultimate goal of safety and risk management of the rapidly growing fields of nanotechnology-based biological applications., (Copyright © 2013 Elsevier Inc. All rights reserved.)