2nd place for the best publication in psychiatry in 2025 by the French Congress for Psychiatry (CFP)
Award given by the International Society of Psychiatric Genetics (ISPG) to attend the World Congress of Psychiatric Genetics (WCPG)
ISIR: International Society for Intelligence Research. Grant provided by the Institute of Mental Chronometry
Undergraduate Award to conduct paid research over the summer at Concordia University, Montreal
Conduct transdisciplinary research on externalizing disorders and behaviors, psychiatric comorbidity, and cognitive development by leveraging genetic, neural, and environmental data from large-scale databases (e.g., UK Biobank, ABCD Study, MCS etc.).
I conducted transdisciplinary research on psychopathology and cognition by linking genetic and environmental factors to brain and behavioral measures using the UK Biobank and ABCD Study.
Lead data analyst on the Externalzing paper that excludes 23andMe data
Analysis of several datasets from private and public companies with work-related, psychological, socio-demographic, and other variables with regressions, and factor and latent class analyses. Aim: Understanding how working from home influences mental health.
Project 1: Understand how neuroanatomy mediates the effects that genes and the environment have on our cognition and behavior
Methods 1: So far: Big data analysis of the UK Biobank, creation of anatomical norms considering age, sex, and brain allometry. To come: linking norms to cognitive, behavioral, genetic, and environmental data
Goal 2: Examine somatic and mental health prevalence in high intelligence individuals in the UK Biobank
Methods 2: So far: Creating G factor score form available data and performing regression analyses on cognitive and somatic measures
Skills: R, data cleaning, regression analyses, factor analyses, structural equation modelling, clustering, network analyses, preregistration (open science practices), creating weights to generalize findings, supervised Master 1 & 2 Interns
Goal: Identify neuroanatomical (subcortical) correlates of Autism Spectrum Disorder.
Methods: Big data analysis of the Autism Brain Imaging Data Exchange (ABIDE I)
Results: No clear subcortical brain differences between individual with and without Autism Spectrum Disorder.
Skills: R, data cleaning, regression analyses, factor analyses, preregistration (open science practices)
Goal: Examine if contextual information and vocabulary production capacities help information maintenance
Methods: Analysis of variations in the N400 depending on high versus low information maintenance demands and high versus low vocabulary knowledge in 2-year-old children
Results: Preliminary. Information demands influenced frontal activity in in 2-year-old children.
Skills: Electroencephalography (EEG), R, Net Station, ANOVA, data cleaning, participant recruitment, preregistration (open science practices)
Goal: Create stimuli to understanding the occurrence of neuroenchantment (the attraction to neuroscientific information) and its effect on information belief
Skills: Literature review, stimuli creation, project management
Goal: Help with data collection and conduct an independent review on “Cognition as a ZeitGeber (Time Giver)”
Skills: Performed perfusions, brain slicing, and immunohistochemistry (Western Blot), Animal handling, feeding, cleaning, and injections (rat and mice)
Goal: Understand Bilingual Speech Perception by examining semantic context use in primary and secondary languages and take part in the Montreal Bilingual Brain Initiative (MOBI) Project
Methods: Analysis of variations in the N400 during a semantic context in speech perception in noise (SPIN) task in monolinguals and bilinguals
Results: Preliminary. Contextual advantage when perceiving speech in suboptimal listening conditions in bilinguals’ L1 compared to their L2.
Skills: Participant recruitment, Montreal Cognitive Assessment (MoCA), health questionnaire administration, EEG data collection and processing, project management and coordination
Awards: Concordia Undergraduate Research Award (4 months of research funding) | 04-07/15
"The 2022 Boulder Statistical Genetic Methods For Human Complex Traits workshop will be held virtually in June 2022. Topics will include: the biometrical model, structural equation modeling, path analysis, maximum likelihood, univariate twin models, sex limitation, GxE interaction, segregation variance, polygenic scores, assumptions in twin models and effects of violating those assumptions, genetic nurture and G-E covariance, multivariate genetic analyses, and longitudinal models. Software will include R, OpenMx, PLINK, and GCTA."
https://www.colorado.edu/ibg/international-workshop/2022-international-statistical-genetics-workshop
Instructor: Richard McElreath [https://xcelab.net/rm/] This is a 3-hour course on the foundations of causal inference.
Topical outline:
Intro: Foundations of causal inference
Part 1: Inadequacy of ordinary statistical procedures
Part 2: Causal design with structural causal models
Part 3: Bayesian causal inference
Slides, code examples, and exercises will be available at this repository: https://github.com/rmcelreath/causal_salad_2021
Held by the University of Amsterdam, Certificate
At the end of this course, you:
Understand and can interpret results from genetic studies of complex human behavioural traits.
Understand the current state of human genetics research in a historical perspective and can contribute to discussions about gene-environment interaction.
Can analyse genetically informative twin and family data.
Understand the assessment and diagnosis of traits and phenotypes.
Can work with multiple “-omics” data: genomics, epigenomics, transcriptomics (gene expression) and microbiomics.
Held by Alexandra de KAENEL
Held by Jean-Dominique Polack