JUMPS 2025
The rebirth.
Featured Article Abstracts
Optimizing Pupil Tracking in Mice during an Attentional Task
Alexa Labrecque1, Arjun Krishnaswamy1, Erik Cook1
1Department of Physiology, McGill University, Montreal, QC, Canada
Visual attention, as seen in mice, is essential for guiding their behaviors and analyzing the environment. Behavioral signals that may be identified as attentional signals include changes in the pupil size of the mice. To quantify these changes, the framework, Facemap, was used on mouse eye videos recorded during an attentional task. In this study, we assessed the accuracy of pupil detection and measurement by recording the eyes of head-fixed mice. The raw pupil data was then verified using a MATLAB code and a mock mouse skull was made to serve as a reference when improving the experimental setup. Videos were uploaded to Facemap and parameters such as color contrast were adjusted to optimize pupil recognition. The pupil data output by Facemap was then plotted over the video using the MATLAB code. Due to a sizable distance between the camera and the mouse eye, the resolution of the pupil was found to be suboptimal. This resulted in errors in the pupil data for a fraction of the video frames, such as rapid increases in pupil area and inaccurate identification of the pupil periphery. Our findings show that Facemap can accurately identify and measure the pupil, although improving the experimental setup is required to reduce error in the pupil data.
Subclinical Schizotypy-based Quantification of the Practice Effects of Social Role Acceptance
Jiani Zhang1, J. Bruno Debruille2
1Department of Cognitive Science, McGill University, Montreal, QC, Canada
2Department of Psychiatry, McGill University, Montreal, QC, Canada2
The “effects of practice” phenomenon refers to the tendency of individuals to improve their performance on cognitive ability tests with repeated testing. It is able to provide insights into the potential for cognitive rehabilitation or intervention programs. By understanding how practice can improve cognitive function, we can better develop targeted interventions and select suitable medications to address populations with cognitive defects like schizophrenia. In addition, it is well established that individuals with delusional disorders or high levels of schizotypy are more likely to form implausible beliefs based on information gained from observing the behavior of others. These beliefs can influence their personal motivation to adopt corresponding social roles. To develop a pre-treatment test, our study split 39 healthy participants into low- and high-SPQ groups according to their Schizotypal Personality Questionnaire (SPQ) and asked them to perform a social role acceptance task twice, with a 1.5-hour gap between sessions. We explored the change in reaction times (RTs) and event-related brain potentials (ERPs) of both groups due to the effects of practice. While RTs were found to be reduced in both groups, the increased amplitude of the N400 ERPs was only found in the low-schizotypy subgroup. These might indicate that practice leads participants with low-SPQ scores to have improved cognitive processing and enhanced self-concept clarity. Furthermore, both RTs and N400 amplitudes demonstrated strong test-retest reliability across the two sessions, confirming the task as a reliable and valuable tool. Further research should investigate practice effects through clinical trials or placebo-controlled studies to aid psychiatrists in identifying the most effective treatments for patients with schizophrenia traits.
Designing a Low-Cost Incubator Microscope Powered by a 3D Printer for Live Cell Imaging
Ioana Ilie1, Geneviève Marceau2, Fedgi Gaspard3, Gil Bub3
1Department of Physiology and Pharmacology, Western University, London, ON, Canada
2Department of Medicine, McGill University, Montreal, QC, Canada
3Department of Physiology, McGill University, Montreal, QC, Canada
Live-cell imaging has emerged as a critical technique for observing cellular processes and physiological conditions. Commercial solutions, despite their effectiveness, are often prohibitively expensive for many laboratories. Open-source alternatives have sought to reduce costs but are hindered by complex assembly requirements and sterility, making their use complex for the average researcher. In response to these challenges, we designed an automated, low-cost microscope that utilizes both 3D printed components and 3D printer-based motion control. The microscope system reuses readily available laboratory materials, such as syringes and tubing, alongside custom 3D-printed parts, to create versatile and easily disposable pieces in the event of contamination. The analysis revealed mechanical and fluid dynamic limitations. Discrepancies in stage motion– caused by motor constraints, pressure transmission inefficiencies, and gaps in articulated components– affected precision and reliability. Additionally, the hydraulic system introduced challenges such as air pocket formation and reduced force efficiency. The design highlights critical areas for improvement, including enhanced motion systems and live-cell imaging capabilities, to offer a more affordable alternative to commercial instruments. This work lays the foundation for future iterations to democratize live-cell imaging technologies for resource-constrained laboratories worldwide.
JUMPS 2025
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Our journal authors
Alexa Labrecque
Alexa is a U2 student in the Joint Physiology and Mathematics program. She is passionate about using computational and analytical tools to decode physiological signals. She is curious about how recent technological advancements provide new tools to decipher signals in Neuroscience. She is particularly interested in how attention to visual features is allocated in mice and how their behaviour can provide insight into their attentional state. Her research focuses on finding the best tool to track the behaviour of mice as they undergo an attentional task. By understanding under which experimental conditions this tool works best, she aims to reduce the error in the data obtained from tracking behaviour. Outside of academics, she enjoys reading, hiking and baking.
Elva Zhang
Elva is a U3 Cognitive Science student concentrating in Neuroscience, with a minor in Interdisciplinary Life Sciences. She has a deep interest in neurodegenerative and neurodevelopmental diseases. She is also passionate about understanding the neural mechanisms underlying cognitive and social behaviors. Her research investigates the practice effects in social role acceptance, particularly in healthy individuals with varying levels of schizotypy. By examining reaction times and event-related brain potentials, as behavioral and neural measures respectively, she aims to investigate cognitive processes underlying this novel task that combines both social cognition and self-referential processing elements. Elva is deeply interested in bridging neuroscience with cognitive rehabilitation, hoping to contribute to the early detection of neurodegenerative disease-related traits and the development of targeted interventions. Outside of research, she enjoys baking, swimming, and collecting photocards in her spare time
Fedgi Gaspard
Fedgi is a U3 physiology student at McGill university. He is an aspiring researcher who thrives on solving complex problems, especially at the intersection of physiology and physics. He is driven by a strong desire to make scientific advancements more accessible, focusing on creating innovative solutions that are both effective and low-cost. For Fedgi, research is not just about recognition—it’s about finding solutions that improve people’s quality of life, simplify challenging tasks, and provide the necessary tools to tackle life’s obstacles. In his free time, Fedgi enjoys football and politics, drawing connections between the strategic thinking required on the field and the analytical skills needed to navigate political landscapes. Whether analyzing game tactics or political dynamics, Fedgi finds inspiration in how both areas involve careful planning and decision-making, which influences his approach to scientific challenges.
Geneviève Marceau
Geneviève is a first-year medical student at McGill University with a strong passion for bridging the gap between fundamental scientific research and healthcare. She is particularly dedicated to developing innovative, accessible technologies, with a focus on improving access to high-quality live-cell imaging for research labs. Her specific interest lies in understanding the intrinsic mechanisms of cardiac cells and the electrophysiological processes that govern their function. Gaining a deeper insight into these mechanisms will pave the way for the development of new technologies and treatment approaches for cardiac diseases. Before entering medical school, Geneviève completed a double DEC in science and music, as well as the Med-P program at McGill’s Montreal campus. Outside of her academic pursuits, she enjoys classical and jazz music, baking, and outdoor sports.
Ioana Ilie
Ioana is a 4th-year physiology student at Western University, passionate about developing accessible tools to advance scientific research. She is particularly interested in leveraging engineering and computational approaches to overcome financial barriers in discovery, ensuring that high-quality imaging is available to more labs. Precise imaging is crucial for studying cellular mechanisms, especially in cardiovascular physiology, where such techniques play a vital role in understanding and treating conditions like myocardial infarctions and atrial fibrillation. Ioana believes that improving research tools is key to accelerating discoveries, allowing for better cellular analysis and the development of novel therapeutics for rising chronic diseases. By integrating technology and physiology, she aims to bridge gaps in biomedical research, making advancements more accessible and impactful. Outside of research, she enjoys baking, painting, and rock climbing.