An exploratory study on emotion regulation strategy use in individuals with Williams syndrome, autism spectrum disorder and intellectual disability

BACKGROUND: Individuals with neurodevelopmental disorders often have atypical emotion profiles, but little is known about how they regulate their emotions. While several studies have examined emotion regulation strategy use in autism spectrum disorder (ASD), only a few have included individuals with intellectual disability (ID) or focused on specific syndromes such as Williams syndrome (WS). METHODS: A parent-reported survey launched during the first months of the COVID-19 pandemic allowed to exploratorily study emotion regulation strategy use and its link to anxiety in individuals with ASD with (N=785) and without ID (N=596), WS (N=261), and Intellectual Disability not otherwise specified (N=649). RESULTS: Using multilevel analyses, besides revealing specific group differences in emotion regulation strategy use, a variety of strategies (e.g., rumination, avoiding information, repetitive behaviors) were found to be linked to elevated levels of anxiety, while focusing on the positive was linked to lower anxiety levels in all groups. Moreover, only autistic people without ID used humor more frequently while experiencing lower anxiety levels. CONCLUSION: This study sheds light on an underexplored area of emotion regulation strategy use in different neurodevelopmental disorders. It also paves the way to further examine emotion regulation in more rigorous ways to better understand emotion regulation in different neurodevelopmental disorders as well as the impact on outcome measures such as anxiety. This exploratory study may help to develop and validate adequate measures to study a broad array of ER strategies used by individuals with neurodevelopmental disorders

Meeting abstract: iMap 4: An Open Source Toolbox for the Statistical Fixation Mapping of Eye Movement data with Linear Mixed Modeling.

A major challenge in modern eye movement research is to statistically map where observers are looking at, as well as isolating statistical significant differences between groups and conditions. Compared to signals of contemporary neuroscience measures, such as M/EEG and fMRI, eye movement data are sparse with much larger variations across trials and participants. As a result, the implementation of a conventional Hierarchical Linear Model approach on two-dimensional fixation distributions often returns unstable estimations and underpowered results, leaving this statistical problem unresolved. Here, we tackled this issue by using the statistical framework implemented in diverse state-of-the-art neuroimaging data processing toolboxes: Statistical Parametric Mapping (SPM), Fieldtrip and LIMO EEG. We first estimated the mean individual fixation maps per condition by using trimmean to account for the sparseness and the high variations of fixation data. We then applied a univariate, pixel-wise linear mixed model (LMM) on the smoothed fixation data with each subject as a random effect, which offers the flexibility to code for multiple between- and within- subject comparisons. After this step, our approach allows to perform all the possible linear contrasts for the fixed effects (main effects, interactions, etc.). Importantly, we also introduced a novel spatial cluster test based on bootstrapping to assess the statistical significance of the linear contrasts. Finally, we validated this approach by using both experimental and computer simulation data with a Monte Carlo approach. iMap 4 is a freely available MATLAB open source toolbox for the statistical fixation mapping of eye movement data, with a user-friendly interface providing straightforward, easy to interpret statistical graphical outputs and matching the standards in robust statistical neuroimaging methods. iMap 4 represents a major step in the processing of eye movement fixation data, paving the way to a routine use of robust data-driven analyses in this important field of vision sciences. Meeting abstract presented at VSS 2015

iMap4: An Open Source Toolbox for the Statistical Fixation Mapping of Eye Movement data with Linear Mixed Modeling.

A major challenge in modern eye movement research is to statistically map where observers are looking, by isolating the significant differences between groups and conditions. Compared to signals of contemporary neuroscience measures, such as M/EEG and fMRI, eye movement data are sparser with much larger variations in space across trials and participants. As a result, the implementation of a conventional linear modeling approach on two-dimensional fixation distributions often returns unstable estimations and underpowered results, leaving this statistical problem unresolved (Liversedge, Gilchrist, & Everling. 2011). Here, we present a new version of the iMap toolbox (Caldara and Miellet, 2011) which tackles this issue by implementing a statistical framework comparable to those developped in state-of the- art neuroimaging data processing toolboxes. iMap4 uses univariate, pixel-wise Linear Mixed Models (LMM) on the smoothed fixation data, with the flexibility of coding for multiple between- and within- subject comparisons and performing all the possible linear contrasts for the fixed effects (main effects, interactions, etc.). Importantly, we also introduced novel nonparametric tests based on resampling to assess statistical significance. Finally, we validated this approach by using both experimental and Monte Carlo simulation data. iMap4 is a freely available MATLAB open source toolbox for the statistical fixation mapping of eye movement data, with a user-friendly interface providing straightforward, easy to interpret statistical graphical outputs. iMap4 matches the standards of robust statistical neuroimaging methods and represents an important step in the data-driven processing of eye movement fixation data, an important field of vision sciences

The Cathodic Breakdown Test to Assess Chromic Acid Anodized Aluminum Alloys Corrosion Protection Performance, in Correlation with Salt Spray (Fog) Testing

Chordless cycles are very natural structures in undirected graphs, with an important history and distinguished role in graph theory. Motivated also by previous work on the classical problem of listing cycles, we study how to list chordless cycles. The best known solution to list all the C chordless cycles contained in an undirected graph G\u2009=\u2009(V,E) takes O(|E|2\u2009+\u2009|E| \ub7C) time. In this paper we provide an algorithm taking O\u303 (|E|+|V| c5C) time. We also show how to obtain the same complexity for listing all the P chordless st-paths in G (where C is replaced by P)

A Benders Approach to the Minimum Chordal Completion Problem

This paper introduces an integer programming approach to the minimum chordal completion problem. This combinatorial optimization problem, although simple to pose, presents con-siderable computational difficulties and has been tackled mostly by heuristics. In this paper, an integer programming approach based on Benders decomposition is presented. Computa-tional results show that the improvement in solution times over a simple branch-and-bound algorithm is substantial. The results also indicate that the value of the solutions obtained by a state-of-the-art heuristic can be in some cases significantly far away from the previously unknown optimal solutions obtained via the Benders approach

Desmoplastic Fibroma of the Mandible: A Series of Three Cases and Review of Literature

The desmoplastic fibroma (DF) is a rare, fibroblastic lesion of bone that histologically resembles the desmoid tumor of soft tissue. Although classified as benign, it frequently demonstrates aggressive behavior, often causing tooth mobility, extensive bone destruction, and has a moderate to high recurrence rate. We present three cases of DF in the mandible: the first in a 13 year old female involving the mandibular body in the region of teeth #s 27–#28, the second in a 57 year old female with a lesion apical to tooth #30, and the third in a 20-year-old female involving the left posterior mandible. Clinical, histologic, immunohistochemical (IHC) and radiographic features of this rare neoplasm are discussed. The challenges encountered in establishing an accurate diagnosis due to significant microscopic overlap with other spindle cell lesions are also detailed. Additionally, the findings of IHC stains including vimentin, smooth muscle actin, S-100 protein, β-catenin, HHF-35 and proliferation marker, Ki-67 on 3 cases are reported. The potential for misdiagnosis is high, especially in early lesions, since immunohistochemistry has been reported in literature to be inconsistent when differentiating DFs from other spindle cell lesions. A comparative review of DF and similar entities in the jaws with current considerations in treatment and prognosis is presented