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Meet the team

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Jean-Philippe Thivierge
Role: Principal Investigator

Dr Thivierge received his Ph.D. from McGill University in 2006. He worked as a postdoctoral fellow at Indiana University before moving to the University of Ottawa where he is now a Full Professor of Psychology.

Our research focuses on computational and quantitative investigations of how the activity of synaptic circuits contributes to cognitive outcomes including perception, learning, memory, and decision making. Our lab uses a variety of techniques including large-scale simulations of neuronal dynamics and multi-electrode recordings in cortex and hippocampus.

There are currently two research axes in the lab: 1) Computer models of transcranial electric stimulation, and 2) Computer models of visual hallucinations induced by psychedelics. 

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Camille Godin
Role: Graduate Student, PhD Experimental Psychology

Camille earned a B.A. with Honors in Psychology from Université de Moncton, followed by an M.A. in Psychology. Currently, her focus lies in modeling brain activity in response to transcranial electric stimulation (TES), with the goal of optimizing stimulation parameters for effective control of brain oscillations. 

Camille is our current webmaster and is passionate about community involvement.

TES team: Kyla Schnitzler, Paitton-Lee Reese Hebert, Mara-Grace Xi Yu Ying Barrett, Lauren Lacelle, Isabelle Hetherington Bobby Penington.

 

Cynthia-Maria Kanaan
Role: Graduate Student, Master Experimental Psychology.

Cynthia earned a B.Sc. in Psychology with Honours from the University of Ottawa, where she is currently pursuing her M.A. in Experimental Psychology. Her research focuses on using advanced computational methods and AI tools to develop neural models that simulate brain activity and visual hallucinations induced by psychedelic substances. This work aims to advance our understanding of drug-brain interactions, with potential implications for clinical interventions and future research on altered states of consciousness in various contexts.

Psychedelic team: Colleen Matys, Catherine Laroche, Jessica Lambert, Aidan Mohamed, Brendan Saunders.

 

 

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Noura Elmawazini

Role: Undergraduate Honors Student

Noura is has been a lab volunteer for 3 years and is currently a BSc with Honors in Psychology student at University of Ottawa. Noura developed interest in convolutional neural networks and generative adversarial networks for epileptic seizures. Additionally, she is interested in investigating clinical intricacies of mental illness and psychopathology. 

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Barry Ngo

Role: Undergraduate volunteer

Barry is currently a lab volunteer and pursuing a BSc in Biomedical Science at University of Ottawa. His current research focuses broadly on developing biologically plausible neural networks with predictive coding learning rules. His models are motivated by the fundamental problems in neuroscience and artificial intelligence. 

GitHub: https://github.com/ngotdb0901

 

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Kyla Schnitzler

Role: Undergraduate volunteer

Kyla Schnitzler is currently a third-year undergraduate student pursuing a BA with Honors in Psychology. Her research interests lie in computational neuroscience and its applications in understanding neuroplasticity and cognitive function. Currently, she is focused on tuning and validating the Wilson-Cowan model to analyze neural responses to transcranial electric stimulation (TES).

 

 

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Mara-Grace Xi Yu Ying Barrett

Role: Undergraduate volunteer

Mara is currently a second year undergraduate student pursuing a BA with Honors in Psychology at University of Ottawa. She is interested in how research techniques can improved and change with the use of spiking neural networks and mean-field networks as alternatives to live animal labs. In addition, she aims to pursue a career in clinical pediatric neuropsychology, focusing on understanding and treating neurological and psychological disorders in children.

 

 

Graduation 2023 - Catheirne Laroche

Catherine Laroche

Role: Undergraduate volunteer

Catherine is currently in her second year at Teacher’s College at the University of Ottawa, where she is preparing to become a secondary-level biology teacher. She also holds an undergraduate degree in Health Sciences with a minor in Psychology, both completed at uOttawa. Presently, she is engaged in research on the neuroscience of psychedelics, exploring mathematical models related to this field. Additionally, she is conducting literature reviews on brain oscillations and their associated activity. She hopes this research could also open doors to potential outcomes in medical school.

 

 

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Paitton-Lei Reese Hebert

Role: Undergraduate volunteer

Paitton-Lei is a second-year BA Honours Psychology student at the University of Ottawa, with a strong interest in exploring how fMRI can be utilized as a diagnostic tool for neurodegenerative disorders. Her current research focuses on building and validating a Leaky Integrate-and-Fire model to investigate the effects of transcranial electric stimulation on brain activity.

 

 

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Isabelle Hetherington

Role: Undergraduate volunteer

Isabelle is currently in her second year at the University of Ottawa pursuing a BA in Psychology with Honours. She is interested in neuroplasticity, specifically how such a fascinating process can be involved in so many aspects of our day-to-day lives, from its role in learning to injury recovery. Currently, Isabelle is focused on tuning and validating a mean-field model of the Izhikevich SNN with the goal of finding a parameter combination that produces oscillations found within experimental data. In the future, Isabelle hopes to pursue graduate school and a career in research.

 

 

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Lauren Lacelle

Role: Undergraduate volunteer

Lauren is in her second year of an Honours BA in Psychology. Her research interest lies in experimental psychology, with a focus on multiple sclerosis. Specifically, the potential application of transcranial electrical stimulation (tES) to enhance neuroplasticity as a means of compensation for axonal damage associated with myelin loss


 

Colleen Matys

Role: Undergraduate volunteer

Colleen is a fourth-year undergraduate student in Honors Bachelor of Social Science in Conflict Studies and Human Rights with a minor in Psychology. Their current research interests are in the possible therapeutic benefits of psychedelics and the brain patterns of those with Obsessive Compulsive Disorder and the subsequent neural mechanisms connected to OCD. 

 

Brendan Saunders

Role: Undergraduate volunteer

Brendan is currently completing an Honours BA in psychology at the University of Ottawa. His research interests pertain to the areas of Cognitive Neuroscience, Ecopsychology, Artificial Intelligence, Machine Learning, Philosophy, and Addiction. Brendan intends on pursuing graduate studies at the end of his current degree.

 

Bobby Pennington

Role: Applied research program

Bobby is a grade 12 student in Lisgar Collegiate Institute's cooperative education program. He helps study and design machine learning algorithms that structurally mimic the processes of the human brain.

Jessica Lambert

Role: Undergraduate volunteer

Jessica is currently a fourth-year undergraduate pursuing a BA with Honors in Psychology at University of Ottawa. Her research interests include the study of psychopathology and community psychology.

 

Aidan Mohamed

Role: Applied research program

Aidan is a grade 12 student in the Applied Research program at Lisgar Collegiate Institute. They're interested in the applications of AI in psychedelic research, specifically in relation to patterns in visual hallucinations. 

 

Publications by year

2024
 

 Noura Elmawazini, Megan Boucher-Routhier, Gatete Queen Olea Umulinga, Jean-Philippe Thivierge. (2025). A Generative Adversarial Network for Data Augmentation of Ictal Waves from Multi-Electrode Brain Activity. Accepted to ICMLAS.

 Pilzak, A., Thivierge, J.P. (2024). Improving Generalization in Convolutional Neural Networks with a Dynamic Attention Layer. CSDE Conference.

 Boucher-Routhier, M., Szanto, J., Nair, V., Thivierge, JP. (2024). A high-density multi-electrode platform examining the effects of radiation on in vitro cortical networks. Scientific Reports.

 Pilzak, A., Thivierge, J.P. (2024). Top-down backpropagation in deep feedforward neural networks. ICONIP 2024.

 Asim Roy, Ali A Minai, Jean-Philippe Thivierge, Tsvi Achler, Juyang Weng. (2024). What AI and Neuroscience Can Learn from Each Other—Open Problems in Models and Theories. Cognitive Computation.

 Thivierge JP (2024). Augmenting data from epileptic brain seizures using deep generative networks. Book Chapter. Applications of Generative AI. DOI : 10.1007/978-3-031-46238-2.

2023

Thivierge JP (2023). Augmenting Data from Epileptic Brain Seizures Using Deep Generative Networks. Book Chapter. Applications of Generative AI. DOI : 10.1007/978-3-031-46238-2.

Boucher-Routhier, M., Thivierge, J.P. (2023) A deep generative adversarial network capturing spiral waves in disinhibited circuits of the cerebral cortex. BMC Neuroscience. [pdf]

J.P. Thivierge, Giraud, E., Lynn, M. (2023). Towards a brain-inspired theory of artificial learning. Cognitive Neurodynamics. [pdf]

2022

Thivierge, J.P. Giraud, E., Lynn, M. Theberge Charbonneau, A. (2022) Key role of neuronal diversity in structured reservoir computing. Chaos. [pdf]

Pilzak, A., Thivierge, J.P. Generating robust convolutional networks by injecting noise in the training data. (2022). IEEE Asia-Pacific Conference on Computer Science and Data Engineering.

Boucher-Routhier, M., Pilzak, A., Theberge Charbonneau, A., Thivierge, J.-P. (2022). Learning to stabilize extreme neural machines with metaplasticity. International Joint Conference on Neural Networks. [pdf]

Krause, M.R., Vieira, P.G., Thivierge, J.P., Pack, C.C. (2022). tACS competes with ongoing oscillations for control of spike-timing in the primate brain. PLoS Biology, 20(5): e3001650. [pdf]

Pilzak, A., Thivierge, J.P. (2022). Estimating null and potent modes of feedforward communication in a computational model of cortical activity. Scientific Reports, 12, 742. [pdf]

2021

Boucher-Routhier, M, Zheng, BLF, Thivierge, JP. (2021). Extreme neural machines. Neural Networks, 144, 639-647. [pdf]

Tauskela JS, Kuebler, ES, Thivierge, J-P, Aylsworth, A, Hewitt, M, Zhao, X, Mielke, JG, & Martina., M. (2021). Resilience of network activity in preconditioned neurons exposed to ‘stroke-in-a-dish’ insults. Neurochemistry International, 146, 105035.[pdf] 

Calderini, M., Thivierge, JP. (2021). Estimating Fisher discriminant error in a linear integrator model of neural population activity. Journal of Mathematical Neuroscience, 11:6. [pdf]

2020

Vincent-Lamarre, P., Calderini, M., Thivierge, J.P. (2020). Learning long temporal sequences in spiking networks by multiplexing neural oscillations. Frontiers in Computational Neuroscience, 24, 1-16. [pdf]

 Thivierge, J.P. (2020). Frequency-separated principal components analysis of cortical population activity. Journal of Neurophysiology, 124, 668-681. [pdf]
 
2019
 
Kuebler, E.S., Calderini, M., Lambert, P., Thivierge, J.P. (2019). Optimal Fisher decoding of neural activity near criticality. In: The Functional Role of Critical Dynamics in Neural Systems. Springer. [pdf]

2018

Calderini, M., Zhang, S., Berberian, N., Thivierge, J.P. (2018). Optimal readout of correlated neural activity in a decision making circuit. Neural Computation, 30, 1573-1611. [pdf]

Kuebler, E.S., Calderini, M., Longtin, A., Bent, N., Vincent-Lamarre, P., Thivierge, J.P. (2018). Non-monotonic accumulation of spike time variance during membrane potential oscillations. Biological Cybernetics, 112, 539-545. [pdf]
 
2017 
 
Berberian, N., MacPherson, A., Giraud, E., Richardson, L., Thivierge, J.P. (2017). Neuronal pattern separation of motion-relevant input in LIP. Journal of Neurophysiology, 117, 738-755. [pdf] 

Berberian, N., Ross, M., Chartier, S., Thivierge, J.P. (2017). Synergy between short-term and long-term plasticity explains direction-selectivity in visual cortex. Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI). [pdf]
 
2016

Lajoie, G., Lin, K.K., Thivierge, J.-P., Shea-Brown, E. (2016). Encoding in balanced networks: Revisiting spike patterns and chaos in stimulus-driven systems. PLoS Computational Biology, Dec 14;12(12):e1005258. [pdf]
 
Vincent-Lamarre, P., Lajoie, G., Thivierge, JP. (2016). Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic network. Journal of Computational Neuroscience, Dec;41(3):305-322. [pdf]
 
Snyder, M.A., McCann, K., Lalande, M.J., Thivierge, J.P., & Bergeron, R. (2016). Sigma receptor type 1-knockout mice show a mild deficit in plasticity but no significant change in synaptic transmission in the CA1 region of the hippocampus. Journal of Neurochemistry, Sep;138(5):700-9. [pdf] 

Shaukat, A., Thivierge, J.P. (2016). Statistical evaluation of waveform collapse reveals scale-free properties of neuronal avalanches. Frontiers in Computational Neuroscience, Apr 7;10:29. [pdf]

Lee, K.F.H., Soares, C., Thivierge, J.P., Beique, J.-C. (2016) Correlated synaptic inputs drive dendritic calcium amplification and cooperative plasticity during clustered synapse development. Neuron, 89, 4, 784-799. [pdf]

Cousineau, D., Thivierge, J.P., Harding, B., Lacouture. Y. (2016). Constructing a group distribution from individual distributions. Canadian Journal of Experimental Psychology, 70, 253-277. [pdf]

2015
 
Kuebler, E.S., Tauskela, J.S., Aylsworth, A., Zhao, X., Thivierge, J.P. (2015). Burst predicting neurons survive an in vitro glutamate injury model of cerebral ischemia. Nature Scientific Reports, 5, 17718. [pdf]

2014

Lajoie, G., Thivierge, J.P., Shea-Brown, E. (2014). Structured chaos shapes joint spike-response noise entropy in temporally driven balanced networks. Frontiers in Computational Neuroscience 8. [pdf]

Thivierge, J.P. (2014). Scale-free and economical features of functional connectivity in neuronal networks. Physical Review E 90, 022721. [pdf]

Kuebler, E.S., Thivierge, J.P. (2014). Spiking variability: Theory, measures, and implementation in MATLAB. Quantitative Methods for Psychology 10, 131-142. [pdf]

Thivierge, J.P., Comas, R., & Longtin, A. (2014). Attractor dynamics in local neuronal networks. Frontiers in Neural Circuits 8, 22. [pdf]

Langlois, D., Cousineau, D., Thivierge, J.P. (2014) Maximum likelihood estimators for truncated and censored power law distributions show how neuronal avalanches may be misevaluated. Physical Review E 89, 012709. [pdf]

2013 

Zunini, R.A.L., Thivierge, J.P., Kousaie, S., Sheppard, C., Taler, V. (2013). Alterations in Resting-State Activity Relate to Performance in a Verbal Recall Task. PLoS ONE, 8, e65608. [pdf] 

Vincent, K., Tauskela, J.S., Mealing, G.M., Thivierge, J.P. (2013). Altered network communication following a neuroprotective drug treatment. PLoS ONE, 8, e54478. [pdf]

Kuebler, E.S., Bonnema, E., McCorriston, J., Thivierge, J.P. (2013). Stimulus Discrimination in Networks of Spiking Neurons. Proceedings of the IEEE International Joint Conference on Neural Networks. 1-8. [pdf]

2012

Vincent, K., Tauskela, J.S., Thivierge, J.P. (2012). Extracting functionally feedforward networks from a population of spiking neurons. Frontiers in Comput Neurosci, 6, 1-12. [pdf]

Thivierge, J.P., Minai, A., Siegelmann, H., Alippi, C., Geourgiopoulos, M. (2012). A year of neural network research. Neural Networks, 32, 1-2. [pdf]

Thivierge, J.P., Dandurand, F., Cousineau, D. (2012). A multi-state model of cortical memory. Proceedings of the IEEE International Joint Conference on Neural Networks, pp.133-138. [pdf] 

2011

Rubinov, M., Sporns, O., Thivierge, J.P., Breakspear, M. (2011). Neurobiologically realistic determinants of self-organized criticality in large networks of spiking neurons. Public Library of Science: Computational Biology, 7, e1002038. [pdf]

Thivierge, J.P., & Cisek, P. (2011). Spiking neurons that keep the rhythm. Journal of Computational Neuroscience, 30, 589-605. [pdf]

2010

Arnall, S., Cheam, L.Y., Smart, C., Rengel, Fitzgerald, L., Thivierge, J.P., Rodger, J. (2010). Abnormal strategies during visual discrimination reversal learning in ephrin-A2-/- mice. Behavioral Brain Research, 209, 109-113. [pdf]

Honey, C.J., Thivierge, J.P., & Sporns, O. (2010). Can structure predict function in the human brain? Neuroimage, 52, 766-776. [pdf]

Thivierge, J.P. (2010). Computational developmental neuroscience: Capturing developmental trajectories from genes to cognition. IEEE Transactions on Autonomous Mental Development, 2, 51-58.[pdf]

2009 

Thivierge, J.P. (2009). How does non-random spontaneous activity contribute to brain development? Neural Networks, 22, 901-912. [pdf] Covered in New Scientist.

2008

Thivierge, J.P. (2008). Neural diversity creates a rich repertoire of brain activity. Communicative & Integrative Biology, 1. [pdf]

Shultz, T.R., Thivierge, J.P., & Laurin, K. (2008). Modeling the Characteristic-to-defining Features Shift in Concept Acquisition. Proceedings of the Annual Meeting of the Cognitive Science Society. 531-536. [pdf]

Tauskela, J.S., Fang, H., Hewitt, M., Brunette, E., Ahuja, T., Thivierge, J.P., Comas, T., & Mealing, G.A. (2008). Elevated synaptic activity preconditions neurons against an in vitro model of ischemia. Journal of Biological Chemistry, 283, 34667-34676. [pdf]

Thivierge, J.P., & Cisek, P. (2008). Non-periodic synchronization in heterogeneous networks of spiking neurons. Journal of Neuroscience, 28, 7968-7978. With cover illustration. [pdf]

Thivierge, J.P. (2008). Higher derivatives of ERP responses to cross-modality processing. Neuroinformatics, 6, 35-46. [pdf]

2007

Thivierge, J.P. (2007). Functional Data Analysis of Cognitive Events in EEG. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 2473-2478. [pdf]

Thivierge, J.P., & Balaban, E. (2007). Getting into shape: Optimal ligand gradients for axonal guidance. BioSystems, 90, 61-77. [pdf]

Shultz, T.R., Rivest, R., Egri, L., Thivierge, J.P., & Dandurand, F. Could knowledge-based neural learning be useful in developmental robotics? The case of KBCC. (2007). International Journal of Humanoid Robotics, 4, 245-279. [pdf]

Thivierge, J.P., & Marcus, G.F. (2007). The Topographic Brain: From Neural Connectivity to Cognition. Trends in Neurosciences, 30, 251-259. [pdf] With cover illustration.

Thivierge, J.P., Rivest, F., & Monchi, O. (2007). Spiking neurons, dopamine, and plasticity: Timing is everything, but concentration also matters. Synapse, 61, 375-390. [pdf]

2006

Shultz, T. R., Rivest, F., Egri, L., & Thivierge, J. P. (2006). Knowledge-based learning with KBCC. Proceedings of the International Conference on Development and Learning. Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN. [pdf]

Thivierge, J.P., & Marcus, G.F. (2006). Computational Developmental Neuroscience: Exploring the Interactions Between Genetics and Neural Activity. Proceedings of the IEEE International Joint Conference on Neural Networks, 9380-9388. [pdf]

2005

Thivierge, J.P., Titone, D., & Shultz, T.R. (2005). Simulating frontotemporal pathways involved in lexical ambiguity resolution. In B.G. Bara, L. Barsalou, & Bucciarelli, M. (Eds). Proceedings of the Annual Meeting of the Cognitive Science Society. (pp.2178-2183). [pdf]

Thivierge, J.P., & Balaban, E., (2005). Faithful retinotopic maps with local optimum rules, axonal competition, and hebbian learning. Proceedings of the IEEE International Joint Conference on Neural Networks, 2760-2765. [pdf]

Thivierge, J.P., Shultz, T.R., & Balaban, E. (2005, conference proceedings). A unified model of thalamocortical axon guidance. Proceedings of the AAAI Annual Conference. (pp.3-14). [pdf]

2000-2004

Thivierge, J.P., Dandurand, F., & Shultz, T.R. (2004). Transferring domain rules in a constructive network: Introducing RBCC. Proceedings of the IEEE International Joint Conference on Neural Networks. 1403-1409. [pdf]

Thivierge, J.P., & Shultz, T.R. (2003). Information networks with modular experts. M.H. Hamza (Ed.) Proceedings of the IASTED Conference on Artificial Intelligence and Applications. (pp. 753-758). Zurich. [pdf]

Thivierge, J.P., Rivest, F., & Shultz, T.R. (2003). A dual-phase technique for pruning constructive networks. Proceedings of the IEEE International Joint Conference on Neural Networks. (pp. 559-564). [pdf]

Thivierge, J.P., & Shultz, T.R. (2002). Finding relevant knowledge: KBCC applied to DNA splice-junction determination. Proceedings of the IEEE International Joint Conference on Neural Networks, pp. 1401-1405. [pdf]

Thivierge, J.P., Plowright, C.M.S., & Chan, T. (2002). Visual recognition of half-patterns by bumblebees. Journal of Behavioral Processes, 59, 185-191. [pdf]

Plowright, C.M.S., Landry, F., Church, D., Heyding, J., Dupuis-Roy, N., Thivierge, J.P., & Simonds, V. (2000). A change in orientation: Recognition of rotated patterns by bumblebees. Journal of Insect Behavior, 14, 113-127. [pdf]

Lab alumni

A list of past lab members (previous 5 years)

2024 - Artem Pilzak, PhD experimental psychology (defended December 2023).

2024- Megan Boucher-Routhier, PhD experimental psychology (defended July 2023).

2024 - Tephnie Beau de Rochars, Honors thesis student

2024 - Epueoghena Iluebber, Undergraduate research assistant

2023 – Quifeng Zhu, visiting scientist, Department of Information Engineering, Suzhou City University

2022 - Judy Chékiée, undergrad lab volunteer

2021- Anny Samake, undergrad directed research, summer term

2020- UROP student: Habib Najjar

2020- Honours student: Bill Ling Feng Zhang

 

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