Publications

Human brain anatomy reflects separable genetic and environmental components of socioeconomic status
H. Kweon
Gökhan Aydogan
Alain Dagher
Danilo Bzdok
C. Ruff
Gideon Nave
Martha J Farah
Philipp Koellinger
Recent studies report that socioeconomic status (SES) correlates with brain structure. Yet, such findings are variable and little is known a… (see more)bout underlying causes. We present a well-powered voxel-based analysis of grey matter volume (GMV) across levels of SES, finding many small SES effects widely distributed across the brain, including cortical, subcortical and cerebellar regions. We also construct a polygenic index of SES to control for the additive effects of common genetic variation related to SES, which attenuates observed SES-GMV relations, to different degrees in different areas. Remaining variance, which may be attributable to environmental factors, is substantially accounted for by body mass index, a marker for lifestyle related to SES. In sum, SES affects multiple brain regions through measurable genetic and environmental effects. One-sentence Summary Socioeconomic status is linked with brain anatomy through a varying balance of genetic and environmental influences.
2021-07-29
bioRxiv (preprint)
doi.org
Local Structure Matters Most: Perturbation Study in NLU
Louis Clouâtre
Prasanna Parthasarathi
Amal Zouaq
Sarath Chandar
Recent research analyzing the sensitivity of natural language understanding models to word-order perturbations has shown that neural models … (see more)are surprisingly insensitive to the order of words.In this paper, we investigate this phenomenon by developing order-altering perturbations on the order of words, subwords, and characters to analyze their effect on neural models’ performance on language understanding tasks.We experiment with measuring the impact of perturbations to the local neighborhood of characters and global position of characters in the perturbed texts and observe that perturbation functions found in prior literature only affect the global ordering while the local ordering remains relatively unperturbed.We empirically show that neural models, invariant of their inductive biases, pretraining scheme, or the choice of tokenization, mostly rely on the local structure of text to build understanding and make limited use of the global structure.
2021-07-29
ArXiv (preprint)
doi.org
arxiv.org
Clones in deep learning code: what, where, and why?
Hadhemi Jebnoun
Md. Saidur Rahman
Foutse Khomh
Biruk Asmare Muse
2021-07-28
ArXiv (preprint)
doi.org
arxiv.org
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems
Ekaterina Kochmar
Dung D. Vu
Robert Belfer
Varun Gupta
Iulian V. Serban
Joelle Pineau
2021-07-27
International Journal of Artificial Intelligence in Education (published)
doi.org
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems
Ekaterina Kochmar
Dung D. Vu
Robert Belfer
Varun Gupta
Iulian V. Serban
Joelle Pineau
2021-07-27
International Journal of Artificial Intelligence in Education (published)
doi.org
Geographical concentration of COVID-19 cases by social determinants of health in 16 large metropolitan areas in Canada - a cross-sectional study
Yiqing Xia
Huiting Ma
Gary Moloney
Héctor A. Velásquez García
Monica Sirski
Naveed Janjua
David Vickers
Tyler Williamson
Alan Katz
Kristy Yu
Rafal Kustra
David Buckeridge
Marc Brisson
Stefan Baral
Sharmistha Mishra
Mathieu Maheu-Giroux
Background: There is a growing recognition that strategies to reduce SARS-CoV-2 transmission should be responsive to local transmission dyna… (see more)mics. Studies have revealed inequalities along social determinants of health, but little investigation was conducted surrounding geographic concentration within cities. We quantified social determinants of geographic concentration of COVID-19 cases across sixteen census metropolitan areas (CMA) in four Canadian provinces. Methods: We used surveillance data on confirmed COVID-19 cases at the level of dissemination area. Gini (co-Gini) coefficients were calculated by CMA based on the proportion of the population in ranks of diagnosed cases and each social determinant using census data (income, education, visible minority, recent immigration, suitable housing, and essential workers) and the corresponding share of cases. Heterogeneity was visualized using Lorenz (concentration) curves. Results: Geographic concentration was observed in all CMAs (half of the cumulative cases were concentrated among 21-35% of each city's population): with the greatest geographic heterogeneity in Ontario CMAs (Gini coefficients, 0.32-0.47), followed by British Columbia (0.23-0.36), Manitoba (0.32), and Quebec (0.28-0.37). Cases were disproportionately concentrated in areas with lower income, education attainment, and suitable housing; and higher proportion of visible minorities, recent immigrants, and essential workers. Although a consistent feature across CMAs was concentration by proportion visible minorities, the magnitude of concentration by social determinants varied across CMAs. Interpretation: The feature of geographical concentration of COVID-19 cases was consistent across CMAs, but the pattern by social determinants varied. Geographically-prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to SARS-CoV-2's resurgence.
2021-07-26
medRxiv (preprint)
doi.org
Modelling Latent Translations for Cross-Lingual Transfer
Edoardo Ponti
Julia Kreutzer
Ivan Vulic
Siva Reddy
2021-07-23
ArXiv (preprint)
arxiv.org
arxiv.org
Dynamic shimming in the cervical spinal cord for multi-echo gradient-echo imaging at 3 T
Eva Alonso‐Ortiz
Daniel Papp
Alain D’astous
Julien Cohen-Adad
2021-07-21
ArXiv (preprint)
doi.org
arxiv.org
Parametric Scattering Networks
Shanel Gauthier
Benjamin Th'erien
Laurent Alséne-Racicot
Irina Rish
Eugene Belilovsky
Michael Eickenberg
Guy Wolf
The wavelet scattering transform creates geometric in-variants and deformation stability. In multiple signal do-mains, it has been shown to … (see more)yield more discriminative rep-resentations compared to other non-learned representations and to outperform learned representations in certain tasks, particularly on limited labeled data and highly structured signals. The wavelet filters used in the scattering trans-form are typically selected to create a tight frame via a pa-rameterized mother wavelet. In this work, we investigate whether this standard wavelet filterbank construction is op-timal. Focusing on Morlet wavelets, we propose to learn the scales, orientations, and aspect ratios of the filters to produce problem-specific parameterizations of the scattering transform. We show that our learned versions of the scattering transform yield significant performance gains in small-sample classification settings over the standard scat-tering transform. Moreover, our empirical results suggest that traditional filterbank constructions may not always be necessary for scattering transforms to extract effective rep-resentations.
2021-07-20
ArXiv (preprint)
doi.org
arxiv.org
Symptom network analysis of the sleep disorders diagnostic criteria based on the clinical text of the ICSD‐3
Christophe Gauld
Régis Lopez
C. Morin
Pierre A. GEOFFROY
Julien Maquet
Pierre Desvergnes
Aileen McGonigal
Yves A. Dauvilliers
Pierre Philip
Guillaume Dumas
J-a Micoulaud-franchi
The third edition of the International Classification of Sleep Disorders (ICSD‐3) is the authoritative clinical text for the diagnosis of … (see more)sleep disorders. An important issue of sleep nosology is to better understand the relationship between symptoms found in conventional diagnostic manuals and to compare classifications. Nevertheless, to our knowledge, there is no specific exhaustive work on the general structure of the networks of symptoms of sleep disorders as described in diagnostic manuals. The general aim of the present study was to use symptom network analysis to explore the diagnostic criteria in the ICSD‐3 manual. The ICSD‐3 diagnostic criteria related to clinical manifestations were systematically identified, and the units of analysis (symptoms) were labelled from these clinical manifestation diagnostic criteria using three rules (“Conservation”, “Splitting”, “Lumping”). A total of 37 of the 43 main sleep disorders with 160 units of analysis from 114 clinical manifestations in the ICSD‐3 were analysed. A symptom network representing all individual ICSD‐3 criteria and connections between them was constructed graphically (network estimation), quantified with classical metrics (network inference with global and local measures) and tested for robustness. The global measure of the sleep symptoms network shows that it can be considered as a small world, suggesting a strong interconnection between symptoms in the ICSD‐3. Local measures show the central role of three kinds of bridge sleep symptoms: daytime sleepiness, insomnia, and behaviour during sleep symptoms. Such a symptom network analysis of the ICSD‐3 structure could provide a framework for better systematising and organising symptomatology in sleep medicine.
2021-07-16
Journal of Sleep Research (published)
doi.org
Symptom network analysis of the sleep disorders diagnostic criteria based on the clinical text of the ICSD‐3
Christophe Gauld
Régis Lopez
Charles Morin
Pierre A. GEOFFROY
Julien Maquet
Pierre Desvergnes
Aileen McGonigal
Yves Dauvilliers
Pierre Philip
Guillaume Dumas
Jean‐Arthur Micoulaud‐Franchi
2021-07-16
Journal of Sleep Research (published)
doi.org
Design of Hesitation Gestures for Nonverbal Human-Robot Negotiation of Conflicts
AJung Moon
Maneezhay Hashmi
H. F. Machiel Van Der Loos
Elizabeth A. Croft
Aude Billard
When the question of who should get access to a communal resource first is uncertain, people often negotiate via nonverbal communication to … (see more)resolve the conflict. What should a robot be programmed to do when such conflicts arise in Human-Robot Interaction? The answer to this question varies depending on the context of the situation. Learning from how humans use hesitation gestures to negotiate a solution in such conflict situations, we present a human-inspired design of nonverbal hesitation gestures that can be used for Human-Robot Negotiation. We extracted characteristic features of such negotiative hesitations humans use, and subsequently designed a trajectory generator (Negotiative Hesitation Generator) that can re-create the features in robot responses to conflicts. Our human-subjects experiment demonstrates the efficacy of the designed robot behaviour against non-negotiative stopping behaviour of a robot. With positive results from our human-robot interaction experiment, we provide a validated trajectory generator with which one can explore the dynamics of human-robot nonverbal negotiation of resource conflicts.
2021-07-11
ACM Transactions on Human-Robot Interaction (published)
doi.org