Seminar – Benjamin de Leener


Speaker: Benjamin De Leener, Ph.D.
Title: The MRI anatomy of the spinal cord, Part I 
Where: CRIUGM Room E1910 (
When: Thursday June 7th,  13h-14h

*The seminar will be presented in English

Benjamin De Leener (PhD) is a HBHL Postdoctoral Fellow at Doyon Lab). He has a strong passion for medical imaging technologies and computer vision in general. Being able to understand and utilize the content of an image has the potential to revolutionize the way we interact with the world. His main contribution is the development of the Spinal Cord Toolbox (SCT), a comprehensive and open-source software for analyzing MRI images of the spinal cord. SCT includes tools for automatically detecting and segmenting spinal cord structures and extracting multi-parametric MRI data from white matter pathways and gray matter sub regions. His research interests are the development of new analysis and processing methods for medical data, with a particular interest in MRI and neurosciences.


Over the last decade, the neuroimaging community has developed various tools for processing and analyzing MRI data of the spinal cord. Particularly, recent advances in MRI templates of the spinal cord allows unbiased multicentric studies of large groups of patients, by providing a common referential space. However, the coordinate systems used to build these templates and atlases are based on anatomical structure (a.k.a. the vertebral bodies) and do not appropriately represent the functions of the spinal cord, therefore leading to potential errors when analyzing functional MRI data or the spinal cord internal structure (gray/white matter). This study presents a novel approach for approximating the position of the spinal roots along the spinal cord, and introduces the premise of a new coordinate system for template-based analysis, based on the functional structure of the spinal cord.

Seminar – Anisha Keshavan


Speaker: Dr Anisha Keshavan
Title: Leveraging Web Technology to address challenges with Big Data in Neuroscience. 
Where: CRIUGM Room E1910 (
When: Thursday May 31st,  13h-14h

*The seminar will be presented in English

Dr Anisha Keshavan works with Jason Yeatman in Speech and Hearing Sciences and Ariel Rokem at the eScience Institute. Her research focuses on big data methods in neuroimaging. Advances in MRI technology and image segmentation algorithms have enabled researchers to begin to understand the mechanisms of healthy brain development, psychiatric and neurological disorders. However, accurately measuring the brain at a scale large enough to accommodate genetic association and precision medicine studies is challenging; expert neuroanatomist tracings can take a long time, while automated algorithms are not accurate enough. Dr Keshavan aims to develop methods to combine the accuracy of an experts with the speed of computers by incorporating crowdsourced image segmentation with deep learning algorithms. She received a doctoral degree in Bioengineering from the UC Berkeley – UCSF Joint Graduate Program, and a Bachelor’s degree in Aerospace Engineering and Applied Mathematics from the University of California, Los Angeles.


Advances in technology have enabled neuroscientists to collect massive amounts of data to answer important scientific questions. But the drawback is that we are experiencing a “data deluge”, which has brought about new challenges that we must overcome in order to truly reap the benefits that Big Data promises. In this talk, I propose that web technology can help us overcome big data challenges, and present examples of how this is done in the field of neuroimaging. First, how web-based data visualization can address the challenges of high data dimensionality. Second, how web-based collaborative meta analyses can address the challenge of integrating the never-ending stream of new results in the research literature. Finally, how web-based citizen science platforms can address the problem that decisions made by neuroimaging experts cannot be reliably scaled to large datasets. Web technology has completely transformed our everyday lives, but we are only just beginning to unleash its full potential to accelerate scientific discovery.

Seminar – Erin W. Dickie


Speaker: Dr Erin W. Dickie
Title: Personalized Connectomics for the Study of Brain Health and Disease: Applications to Autism Spectrum Disorder and Schizophrenia Research.
Where: CRIUGM Room E1910 (
When: Thursday May 24th,  13h-14h

*The seminar will be presented in English

Dr. Erin Dickie (PhD, Neurological Sciences, McGill University) is a Project Scientist. Dr. Dickie’s research focus is personalized connectomics, or the ability to map brain organization at the level of the individual. Individual mapping of brain function may be a critical first step in the design of targets for stimulation therapy. Dr. Dickie recently submitted a manuscript describing her tool for mapping neurodiversity (PINT), and showed that the brains of those affected by autism and more variable in their organization that those of typically developing controls. This work suggests that personalized brain mapping might be a critical first step for future biomarker discovery. Dr. Dickie also assists with the lab’s data management and analysis system, and builds automated tools for data analysis. In the past year, she has developed a new tool for surface-based analyses (ciftify) that has been publicly available and adopted by international groups.


Emerging work from the neuroimaging community shows that everyone’s cerebral cortex has a unique functionally organisation and that this unique organisation can be mapped using neuroimaging data at the individual participant level. To do so, we start with an analytic approach, using the CIFTI file format, that allows for a more neuroanatomically-faithful representation of data. An open source set of tools ‘ciftify’ ( make this approach more accessible to the greater scientific community. We than introduce novel methods for incorporating resting-state fMRI data to map the spatial topography of the cortical surface in individual subjects and discuss the applications to the study of brain pathologies including Autism Spectrum Disorder and Schizophrenia. Using the ABIDEI dataset, we found greater spatial variability in resting state network location in individuals with ASD with a disrupted developmental trajectory. Accounting for this variability decreased the number of hypo-connected regions observed in individuals with ASD. This phenomenon could have far reaching implications for how clinical neuroimaging research is analysed and interpreted.

Seminar – Tal Yarkoni


Speaker: Dr Tal Yarkoni
Title: How to survive and thrive as an open scientist
Where: CRIUGM Amphithéâtre Le Groupe Maurice (
When: Thursday May 17th,  13h-14h

*The seminar will be presented in English

Dr Yarkoni is a Research Assistant Professor in the Department of Psychology at the University of Texas, where he directs the Psychoinformatics Lab. His research focuses on the development and application of new methods for acquiring, organizing, and synthesizing psychological data on a large scale. Tal’s work applies techniques from behavioral psychology, functional neuroimaging, and computer science to multiple domains within psychology, with a particular focus on personality and individual differences.


In principle, science is a cumulative, community-driven enterprise. To make new discoveries, researchers build directly on the products of other researchers’ efforts, and in turn, reciprocally share their own findings with the world. In practice, of course, things rarely proceed quite so idealistically. Researchers regularly hide their latest findings from one another as they compete for publication in rarified journals; data and protocols are hoarded to maintain competitive advantage; and “Questionable Research Practices” such as optional stopping and selective reporting are engaged in with alarming frequency, often under the justification that there is no other way for a modern scientist to succeed. In this talk I take issue with this philosophy, and argue that it is indeed possible for an open scientist to both survive and thrive in the modern environment. I review a series of open practices that can help advance one’s career while simultaneously maximizing the reproducibility, reliability, and accessibility of one’s scientific work. These include preprint deposition, open-access publication, preregistration, version control, and social media use, among others. I dispel a number of myths about these practices, and review empirical evidence suggesting that they are, if anything, beneficial to one’s reputation. I conclude by suggesting that early-career scientists are no longer faced with a hard choice between good science and good politics, and encouraging researchers to actively contribute to the rapid ongoing shift in structural incentives and cultural expectations.

Seminar – Daniel Margulies


Speaker: Dr Daniel Margulies
Title: Topographic principles of macroscale cortical connectivity
Where: CRIUGM Amphithéâtre Le Groupe Maurice (
When: Wednesday May 16th,  13h-14h

*The seminar will be presented in English

Dr Margulies investigates the organization of large-scale brain networks, primarily through the analysis of intrinsic activity as measured with functional magnetic resonance imaging (fMRI). He has developed approaches to define sub regions within complex cortical areas, conducted cross-species comparative neuroanatomical studies, and related variation in these networks to phenotypic differences across individuals. His current research addresses the emergence of network topography and its relationship to cortical structure.


What determines the spatial arrangement of distinct areas of the cerebral cortex? Insights into functional processing streams indicate that areas are arranged stepwise, such that adjacent spatial position along the cortical mantle represents functional gradients. Having been largely restricted to describing processing within specific sensory modalities, how do these principles generalize across modalities and extend to the surrounding association cortex? I will present recent work describing various features of a principal gradient in cortical connectivity that spans between primary sensory/motor areas and higher-order transmodal association regions that in humans are known as the default-mode network. This arrangement suggests developmental mechanisms giving rise to the spatial distribution of cortical functions, and provides an anatomical scaffolding for investigating the propagation of information at both local and distributed spatial scales.

Seminar – Cyril Pernet

Présentateur/ Speaker:              Dr Cyril Pernet
Titre/  Title:                                  On the simple relationships between brain and age: impact of methods and choices.
Endroit/ Where:                          CRIUGM (, room E1910
Date/ When:                                 Vendredi 4 mai, 13h-14h/ Friday May 4th 1pm-2pm

*La conférence sera présentée en anglais/The seminar will be present in English

Dr Pernet obtained a PhD in Cognitive Neuropsychology from the University of Toulouse in France in 2004. He joined the Brain Research Imaging Center, Edinburgh in 2007, as fMRI lead for SINPASE (Scottish Imaging Network A Platform for Scientific Excellence). He is now an Academic Fellow, teaching fMRI/EEG and researching in the areas of visual and auditory categorization and language with a focus on methods (statistics) and clinical applications (brain tumors, stroke). He is also the Edinburg Imaging scientific contact for functional MRI studies, a lead advocate for open science and the organizer of many courses on brain imaging.


Using a simple all brain volume and VBM approach to ageing, I will present various methods and analysis choices that can greatly impact results.

Brainhack Global 2018

The goal of the hackathon is to bring together researchers with disparate backgrounds to collaborate on open science projects in neuroimaging. Brainhack Montreal 2018 is part of the Brainhack Global 2018, with simultaneous hackathons running at more than 30 sites across the globe. Participants are encouraged to post project ideas on the website of brainhack Montreal.

Dates: April 26th-27th, 2018

Costs: $30 CAD, includes onsite breakfast and lunch for two days

Location: Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, Canada.


Brainhack Montreal is grateful for the support of the Québec BioImaging Network.

UNF seminars for 2018


Speaker Title Room Time
April 2018
April 25 Ella Gabitov Uncovering neural dynamics during continuous motor performance by modelling single events E-1910 13h00
May 2018
May 4 Cyril Pernet On the simple relationships between brain and age : impact of methods and choices E-1910 13h00
May 16 Daniel Margulies Topographic principles of macroscale cortical connectivity Amphithéâtre Le Groupe Maurice 13h00
May 17 Tal Yarkoni How to survive and thrive as an open scientist Amphithéâtre Le Groupe Maurice 13h00
May 24 Erin W. Dickie Personalized Connectomics for the Study of Brain Health and Disease: Applications to Autism Spectrum Disorder and Schizophrenia Research. E-1910 13h00
May 31 Anisha Keshavan Leveraging Web Technology to address challenges with Big Data in Neuroscience. E-1910 13h00
June 2018
June 7 Benjamin DeLeener The MRI anatomy of the spinal cord, Part I E-1910 13h00

UNF special seminar

False Discovery Rate Control Under Rounding of P-Values

Dr Hien Nguyen

Location : CRIUGM (, room M6804

Date: December 13th, 13h-14h

The seminar will be presented in English

Dr Hien Nguyen is going to give special seminar of Unité de Neuroimagerie Fonctionnelle (UNF) this coming Wednesday. Dr Nguyen is a Lecturer and Australia Research Council DECRA Research Fellow at La Trobe University in Melbourne Australia. His research currently focuses on the development of Big Data methodologies that are deployable on small-scale computing infrastructures, and deep learning and neural networks for applications in personalised medicine.


The mitigation of false positives is an important issue when conducting multiple hypothesis testing. The most popular paradigm for false positives mitigation is via the control of the false discovery rate (FDR). We present a method for FDR control that is applicable in cases where only p-values are available, and when those p-values are potentially equal to zero or one. Our method is based on an empirical-based paradigm where the Probit transformation of the p-values (called the z-scores) are modeled as a two-component mixture of normal distributions. Due to the rounding of the p-values, the usual approach for fitting mixture models cannot be applied. We instead use a binned data technique, which can be proved to consistently estimate the z-score distribution, even when the data are correlated. A simulation study shows that our methodology is competitive with popular alternatives, especially when data are correlated. We demonstrate the applicability of our methodology in practice via a brain imaging study of mice.