On May 9, 2024, 12 trainees who were selected based on abstract submissions will each give a three-minute presentation on their research. There will be three flash talks for each of HBHL’s four research themes.
Theme 1: Neuroinformatics and Computational Modelling
Cameron Oram
Status: PhD candidate Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Jean-Francois Poulin Poster #108
Spatial characterization of midbrain dopamine neurons using multiplexed error-robust fluorescent in-situ hybridization (MERFISH)
Abstract
The midbrain Dopamine (DA) system contains a relatively small number of neurons yet has broad modulatory functions in the striatum and cortex. Despite their small number, DA neurons contain considerable heterogeneity in their transcriptomic identity, projection targets and ultimately function. How this heterogeneity is distributed spatially is not well understood. In this project we utilized Multiplexed Error-Robust Fluorescent In-Situ Hybridization (MERFISH) to create an atlas of mouse midbrain DA neurons. A 500 gene panel was generated spawning known DA markers and genes associated with neurotransmitter synthesis and transport. Mouse midbrain sections were imaged across 7 coronal planes and 4,563 DA neurons were identified. We integrated the data with single-nucleus RNA sequencing (sn-Seq) data of DAT enriched nuclei and found 2,297 cells that integrated with high confidence. Of the 22 distinct DA clusters found in the sn-Seq dataset we were able to resolve 17 with high DAergic characteristic. These 17 clusters were broken up into three major families: a Sox6 positive family (6 clusters), a Calb1 family (8 clusters) and a Gad2 family (3 clusters). Spatial mapping of each cluster showed distinct distributions for each family, with Sox6 clusters mapping to the substantia nigra pars compacta (SNc) and retrorubral field (RRF), Calb1 clusters mapping to the ventral tegmental area (VTA) and SNc and the Gad2 clusters mapping to the VTA, caudolinear nucleus. This atlas will be used to further explore the functional heterogeneity of DA neurons in the future.
Jiayue Yang
Status: Master’s student Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Justine Cléry Poster #115
A DeepLabCut-derived framework for precise quantification behavioural dynamics in common marmoset
Abstract
In systems neuroscience, movement is a fundamental behavioral feature, which is indicative of the animal’s well-being and a potential disease status. To track animal behaviors, the usage of automatic machine-learning tools has become increasingly popular, such as the pose estimation program DeepLabCut (DLC). However, there is a limited toolkits to analyze the complex DLC behavioral data in an easy, accessible manner. Thus, we present a Python-based pipeline to facilitate complex behavioral analysis in freely moving marmosets based on the DLC-derived coordinates. In this study, marmosets were housed in family units within home cages, with their behaviors recorded via a Webcam-based system. With user-defined points of interest, we therefore investigated the recorded marmoset videos using the DLC to capture the motion and coordinates of different body parts. We analyzed the DLC-derived coordinates using the pipeline to measure continuous speed, inter-individual distance, and head posture consistency. Our results show that this pipeline enables quantitative predictions of movement patterns with high accuracy, applicable for both single and multiple marmosets’ projects. Depending on their activity levels and social relationships, we found that marmosets exhibit various speed intensity (e.g. resting, jumping), types of social interaction (e.g. play-fighting, friendship), and head posture. Overall, this approach enhances objectivity, reduces human errors, and minimizes repetitive works for behavioral analysis. Moreover, by comparing these results with a marmoset synucleinopathy model (Parkinson’s disease, dementia), this pipeline will allow us to characterize potential behavioral deficits to better understand the impact of synucleinopathy.
Youngeun Hwang
Status: PhD candidate Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Boris Bernhardt Poster #128
Multiparametric mapping of superficial white matter architecture using 7T quantitative MRI
Abstract
The superficial white matter (SWM), located underneath the cortex, contains subcortical U-fibers pivotal for brain plasticity and aging. Despite its significance, SWM research has been limited by technical challenges. Leveraging advancements in 7 Tesla MRI technology, this study aims to elucidate SWM microstructural properties using quantitative MRI (qMRI). Ten healthy participants underwent 7T MRI scans, including T1 relaxation time maps, diffusion-weighted imaging and magnetization transfer imaging. SWM surfaces were delineated at fifteen depths, revealing microstructural intensity profiles. Our study employed a novel conceptual and analytical approach to assess spatial gradients of microstructural differentiation between brain areas. By considering multiple modalities, we constructed a multi-modal microstructural profile covariance (mMPC) and evaluated correlations not only between qMRI feature maps but also across SWM depths. The first principal gradient was anchored on one end by pre-central and middle frontal areas and on the other end by occipito-temporal areas. Additionally, our in vivo findings were consistent with topographical SWM variation observed in a post-mortem histological dataset. These findings highlight the potential of 7T qMRI in unraveling SWM microstructure and advancing our understanding of brain connectivity and pathology detection.
Theme 2: Mechanistic Models of Neurodegenerative Disorders
Jonathan Gallego Rudolf
Status: PhD candidate Institution: McGill University Program: Integrated Program in Neuroscience Supervisors: Sylvain Baillet and Sylvia Villeneuve Poster #211
Neurophysiological markers for predicting MCI progression in asymptomatic older adults
Abstract
Alzheimer’s Disease (AD) is defined by the pathological accumulation of amyloid-beta (Aβ) and tau in the brain. Regional deposition of these proteins is associated with changes in frequency-defined neurophysiological activity, which can be detected using non-invasive magnetoencephalography (MEG). Here we examined the utility of neurophysiological activity features for predicting the progression of cognitively unimpaired individuals to mild cognitive impairment (MCI), as compared to other established AD biomarkers. We used Magnetic Resonance Imaging (MRI) to measure hippocampal volume, collected blood samples to assess AD plasma biomarkers, Positron Emission Tomography (PET) to measure Aβ ([18F]NAV4694) and tau ([18F] Flortaucipir) deposition and resting-state MEG to capture neurophysiological activity in a group of clinically unimpaired older adults with a family history of sporadic AD (PREVENT-AD cohort; n=95; 18 MCI progressors). We used logistic regression models that combined clinical and demographic information with each of these features, to assess the added value of different biomarkers for predicting MCI progression. Incorporating MRI hippocampal volume did not improve the accuracy of the clinical model. Including plasma biomarkers instead improved the accuracy but these models were outperformed by the model incorporating MEG spectral power features from temporal tau accumulating regions, which almost matched the accuracy provided by including Aβ and tau PET.Our results demonstrate that neurophysiological activity features improve the accuracy for predicting MCI progression, contributing information beyond demographic/clinical variables, structural MRI, and plasma biomarkers and representing a more accessible and less invasive alternative than PET imaging for screening participants in the preclinical stages of AD.
Julia Tourbina-Kolomiets
Status: Master’s student Institution: McGill University Program: Pharmacology and Therapeutics Supervisor: Anne McKinney Poster #212
Purkinje cell vulnerability depends on zebrin molecular identity and cerebellar location in a Christianson Syndrome mouse model
Abstract
Ataxia is a prominent symptom of the X-linked neurodevelopmental/neurodegenerative disorder Christianson Syndrome (CS). A hallmark of ataxia disorders is the death of Purkinje cells where Purkinje cell cerebellar location can influence their vulnerability. Purkinje cells express certain molecules in a highly patterned manner across the cerebellum, the most studied being aldolase C/zebrin-II (zebrin), expressed in parasagittal stripes across the cerebellum. We investigated if either type of Purkinje cell was more vulnerable in CS using immunohistochemistry, looking specifically at motor lobules, anterior lobule III and posterior lobule VIII. We found that zebrin patterning appears normal before disease onset in CS mice, followed by a narrow and aggressive window (10 days) of vulnerability in the anterior lobe of CS mice, arising at a similar time as the first firing alterations. The vulnerability affects only zebrin-negative Purkinje cells, with zebrin-positive Purkinje cells showing striking resilience. In contrast, all posterior Purkinje cells were equally susceptible to degeneration at later disease stages. As Purkinje cells are the only cerebellar cortex outputs and send their axons to the cerebellar nuclei (CN), we analyzed Purkinje cell input onto the CN. Similarly, we found decreased zebrin-negative input onto large neurons in anterior CN. In contrast, zebrin-negative inputs onto posterior CN neurons and zebrin-positive inputs onto both anterior and posterior CN neurons were resilient. Our results suggest that both cerebellar location and zebrin molecular identity play a role in Purkinje cell vulnerability in CS.
Amitha Muraleedharan
Status: Postdoctoral researcher Institution: Université du Québec à Montréal (UQAM) Program: Département des sciences biologiques Supervisor: Benoît Vanderperre Poster #213
A genome-wide CRISPR/Cas9 screen identifies genes that regulate the cellular uptake of α-synuclein fibrils by modulating heparan sulfate proteoglycans
Abstract
Synucleinopathies are characterized by the accumulation and propagation of α-synuclein (α-syn) aggregates throughout the brain, leading to neuronal dysfunction and death. Understanding how these aggregates propagate from cell to cell in a prion-like fashion thus holds great therapeutic promises. Here, we focused on understanding the cellular processes involved in the entry and accumulation of pathological α-syn aggregates. We used an unbiased FACS-based genome-wide CRISPR/Cas9 knockout (KO) screening to identify genes that regulate the accumulation of α-syn preformed fibrils (PFFs) in cells. We identified key genes and pathways specifically implicated in α-syn PFFs intracellular accumulation, including heparan sulfate proteoglycans (HSPG) biosynthesis and Golgi trafficking. We show that all confirmed hits affect heparan sulfate (HS), a post-translational modification known to act as a receptor for proteinaceous aggregates including α-syn and tau. Intriguingly, KO of SLC39A9 and C3orf58 genes, encoding respectively a Golgi-localized exporter of Zn2+, and the Golgi-localized putative kinase DIPK2A, specifically impaired the uptake of α-syn PFFs uptake but not of tau oligomers, by preventing the binding of PFFs to the cell surface. Mass spectrometry-based analysis of HS chains indicated major defects in HS maturation in SLC39A9 and C3orf58 KO cells, explaining the cell surface binding deficit. Our findings establish these two genes as HSPG-modulating factors. Interestingly, C3orf58 KO human iPSC-derived microglia exhibited a strong reduction in their ability to internalize α-syn PFFs. Altogether, our data establish HSPGs as major receptors for α-syn PFFs binding on the cell surface and identifies new players in α-syn PFF binding and uptake.
Theme 3: Applied Cognitive Neuroscience of Brain Plasticity
Christy Au-Yeng
Status: PhD candidate Institution: McGill University Program: Psychology Supervisor: Martin Lepage Poster #304
Hippocampal subfield trajectories in persistent negative symptoms following a first episode of psychosis
Abstract
Persistent negative symptoms (e.g., avolition, anhedonia, alogia) impact up to 30% of individuals diagnosed with a first episode of psychosis (FEP) and greatly impact social and occupational functioning. Primary (PNS) and secondary PNS (sPNS: concomitant with positive, depressive, or extrapyramidal symptoms) are thought to indicate distinct pathophysiologies, particularly involving the hippocampus. Our previous work has showed that the hippocampus is central to the development of schizophrenia, and that specific hippocampal subfields have distinct roles and are differently affected by illness progression. However, the specific influence of hippocampal subfields on PNS remains unexplored. We investigated longitudinal volumetric trajectories within nine bilateral hippocampal subfields in 59 patients with FEP and 59 healthy controls over 1.5 years. Generalized estimating equations were used to examine main effects of time and group (control, non-PNS, primary PNS, secondary PNS), and their interaction. The model controlled for age, sex, years of education, medication (product of dosage and adherence) and total brain volume and multiple comparison corrections were applied using the Benjamini-Hochberg Procedure. Left mamillary body showed a significant Group*Time interaction (χ2=26.69 , df=9, p corrected=0.036). There were significant increases in the left mamillary body between 1 and 1.5 years within sPNS. These findings underscore the involvement of the mamillary body in the development of negative symptoms in specific negative symptom profiles. The implications of these results for our understanding of schizophrenia and the role of the hippocampus in the disorder will be discussed.
Zac Yeap
Status: PhD candidate Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Rachel Rabin Poster #311
Cannabis and tobacco co-use and its association with striatal brain morphometry: Leveraging data from the ENIGMA Addiction Working Group
Abstract
Cannabis and tobacco are frequently used addictive substances and daily co-use is common. Cannabis use is associated with greater striatal gray matter volume (GMV), while tobacco use is associated with lower striatal GMV. However, the effects associated with their combined use on striatal GMV remain unclear. Therefore, we investigated whether daily cannabis and tobacco co-use was associated with different patterns of striatal GMV compared to either substance alone or no substance use. Pooling T1-weighted MRI scans from 10 ENIGMA Addiction sites yielded a sample of N=273. Four groups were examined: individuals with co-use (CT, n=45), cannabis-only use (CAN, n=28), tobacco-only use (TOB, n=60), and no use (controls, n=140). Cannabis groups used ≥0.5 joints/day and tobacco groups used ≥5 cigarettes/day. Using Freesurfer, GMV in the nucleus accumbens, caudate nucleus, and putamen were extracted. We employed 2×2 ANCOVAs controlling for age, sex, site, and alcoholic drinks/day. Since years of cannabis use differed between CT and CAN, and years of tobacco and daily tobacco use differed between CT and TO, these were controlled for in the analyses. False-discovery-rate correction was applied to control for multiple comparisons. In the right nucleus accumbens, there was a significant interaction between cannabis and tobacco use (p=0.042). Main effects for cannabis (p=0.06) and tobacco (p=0.39) were not significant. Post-hoc comparisons revealed higher GMV in CAN than CT (p=0.045), TOB (p=0.028), and controls (p=0.001); no other group differences emerged. Among individuals with cannabis use, tobacco co-use may suppress cannabis-induced GMV increases in the nucleus accumbens.
Leanne Young
Status: Master’s student Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Aparna Suvrathan Poster #312
Precise measurement of motor learning in a mouse model of Fragile X Syndrome
Abstract
The ability to learn motor skills is essential for survival, yet how different parameters of learning change during skill acquisition and the underlying neural circuit mechanisms remain incompletely understood. To understand this problem, we trained C57BL/6 wild-type (WT) mice to perform a skilled forelimb reaching task and tracked their movements using DeepLabCut to measure paw trajectory and kinematics. Our results revealed a significant reduction in both the vertical spread of reach trajectories and average distance per reach by the end of training, indicating markers of learning that align with a significant increase in success rate across all WT mice. To examine the neurological substrates of motor learning dysfunction, we also utilize a mouse model (Fmr1 KO) of Fragile X Syndrome (FXS), a severe intellectual disability that causes an array of deficits including impaired motor learning and coordination. Remarkably, we found that overall, Fmr1 KO mice significantly learn and achieve success rates similar to WT mice in the paw reach task when utilizing an automated apparatus with a physical and visual cue, but did not show a significant decrease in vertical spread of reach trajectories or average distance per reach by the end of training. This suggests the possibility that the Fmr1 KO mice developed alternate learning strategies to achieve success. Preliminary data using the same setup and protocol in the absence of cues showed poorer performance in Fmr1 KO mice of the same age, suggesting adequate support and structure could alleviate the learning deficit.
Theme 4: Population Neuroscience and Brain Health
Enzo Cipriani
Status: PhD candidate Institution: Université de Montréal Program: Département de Psychiatrie et d’addictologie Supervisor: Robert-Paul Juster Poster #407
Using Bourdieu’s framework as social determinants in schizophrenia: The influence of economic and social capitals on symptoms severity
Abstract
Schizophrenia is a severe disorder drastically impairing patient’s social integration and quality of life. Social determinants of health (SDoH; e.g., migrant status, race/ethnicity, socioeconomic status) have a major influence on schizophrenia’s severity and course. There are a wide array of identified social factors related to schizophrenia; however, their inclusion is very challenging in quantitative approaches with limited sample sizes. To address this challenge, we decided to use French sociologist Pierre Bourdieu’s theory of social space as a framework to include multiple social dimensions. The theory of social space defines one’s position in society through four capitals: social, economic, cultural, and symbolic. To investigate the role of SDoH in psychotic symptom severity, we included 16 sociodemographic variables in a composite score representing Bourdieu’s four capitals mentioned above. Our sample comes from the Signature Biobank and is composed of 317 patients diagnosed with schizophrenia visiting the emergency room of the Institut universitaire en santé mentale de Montréal between 2012 and 2020 and 149 healthy controls. Preliminary results show significantly lower social and economic capitals among patients as compared with controls. Among patients, social capital is negatively correlated to depressive and anxious symptoms, indicating a potential protective effect. Economic capital, on the other end, is negatively correlated to delusions severity, indicating that a lower economic capital is related to more severe and distressing delusions. Results show a promising avenue for this sociological approach and underlines the essential social underpinnings of mental health.
Jessica Ahrens
Status: PhD candidate Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Lena Palaniyappan Poster #409
Neuromelanin-sensitive MRI in cannabis use disorder and first episode schizophrenia
Abstract
Adolescent cannabis use has been associated with increased risk of schizophrenia. Although the mechanism linking cannabis use disorder with schizophrenia remains elusive, aberrations in dopamine turnover is suspected to play a role, but findings to date have been contradictory. We investigated this relationship using neuromelanin-sensitive MRI (neuromelanin-MRI), a putative proxy measure of dopamine system function that has previously shown alterations in schizophrenia and substance use disorders. Twenty-five participants with cannabis use disorder (CUD) and 36 participants without CUD (nCUD) participated in the study. 28 of these participants had been diagnosed with first episode schizophrenia (FES). We collected a neuromelanin-MRI scan from the substantia nigra (SN) and tested the association of CUD and FES diagnoses with neuromelanin-MRI signal using robust linear regression analysis. CUD was associated with elevated neuromelanin-MRI signal in a cluster of ventral SN voxels (353 of 2060 SN voxels, pcorrected=0.023, permutation test). FES diagnosis was not associated with a significant alteration in SN NM-MRI signal. Within a SN subregion previously shown to be associated with severity of untreated schizophrenia, CUD participants showed elevated signal compared to nCUD participants (t56=2.01, p=0.049). This indicates an increased dopamine turnover in subregions relevant to schizophrenia risk in individuals with cannabis use disorder. Cannabis-associated elevation of dopamine turnover may contribute to the risk of schizophrenia in long-term users of cannabis. The relationship between neuromelanin-MRI signal in the SN and dopamine turnover in other brain regions critical for schizophrenia requires further clarification.
Qizhou Xia
Status: Master’s student Institution: McGill University Program: Integrated Program in Neuroscience Supervisor: Patricia Pelufo Silveira Poster #416
Sex-specific causal dynamic between Insulin resistance and MDD, a bidirectional Mendelian randomization study
Abstract
Evidence from various studies has shown a bidirectional association between major depressive disorder (MDD), Insulin resistance (IR), and related diseases, which varies between sexes and ancestries. There has also been evidence suggesting that IR influences response to antidepressant treatment. We conducted a sex-specific two-sample bidirectional Mendelian randomization (MR) study to assess the causal associations of MDD with Insulin resistance measured through the TG: HDL-C ratio and vice versa. Furthermore, we also performed another two-sample Mendelian analysis to assess the causal influence of IR on anti-depressant response. We obtained summary-level statistics for MDD, antidepressant response, and insulin resistance from corresponding published large genome-wide association studies of individuals mainly of European ancestry and partially replicated the analyses using available summary data from studies of individuals of East Asian descent. The random-effects inverse-variance weighted method was used for the main analyses. Genetic liability to MDD was significantly associated with Insulin resistance both generally and sex-specifically, while the causal effect of Insulin resistance on MDD is only significant in females. We found limited evidence supporting the causal effects of insulin resistance on antidepressant response. None of the previous associations were found using summary data with East Asian subjects. The present study consolidated MDD as a potential risk factor for insulin resistance and that insulin resistance plays a sex—and ancestry-specific role in MDD pathology. Together, these findings could contribute to further our understanding of the comorbidity between MDD and IR-related diseases, allowing for more individualized treatment and diagnosis.
HBHL Symposium 