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Meet the team

JP 1-1
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.

Megan Boucher-Routhier
Role: Graduate Student, PhD Experimental Psychology

Megan obtained a B.A. with Honors in Psychology at University of Ottawa. Her research interest revolves around examining disinhibited/altered states of large-scale cortical networks using high-density multi-electrode array (HD-MEA) recordings. This includes radiation-induced changes in network dynamics as well as neural activity generated in pro-epileptiform networks.


Artem Pilzak
Role: Graduate Student, PhD Experimental Psychology

Artem earned a B.A. with Honors in Psychology at University of Ottawa. He also holds a position as an AI Scientist. His research focuses on multi-feature learning in Convolutional Neural Networks (CNNs). He is particularly interested in enhancing these models with dynamic attention mechanisms to improve their ability to generalize to out-of-distribution samples. This approach aims to significantly boost the models' robustness and performance, ensuring they perform well across wide range of challenging and diverse environments.

GitHub: https://github.com/DeepVisionary


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, where her research delved into the classification of phenotypes within an animal model of susceptibility to substance abuse. Currently, her focus lies in modeling brain activity in response to transcranial stimulation, with the goal of optimizing stimulation parameters for effective control of brain oscillations.

Camille is our current webmaster and is passionate about community involvement. She has successfully overseen two community projects that involved children from rural areas, integrating elements of 3D printing and urban art.


Tephnie Beau de Rochars

Role: Undergraduate student, Honors thesis

Tephnie is completing a B.Sc. in Psychology at University of Ottawa. Her Honors thesis focuses on investigating the potential benefits of combining supervised and top-down predictive learning in order to enhance network performance in artificial neural networks. 



Epueoghena Iluebbey

Role: Undergraduate Research Assistant

Epueoghena is currently a third year Honours student pursuing a B.Sc. in Psychology. As a research assistant, she is conducting a focused literature review on transcranial stimulation parameters. She actively seeks to blend theoretical knowledge with practical research experience.  
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Noura Elmawazini

Role: Undergraduate volunteer

Noura is currently a lab volunteer as she is pursuing a BSc with Honors in Psychology 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. 


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



Mia Tran

Role: Undergraduate volunteer

Mia is currently a third year undergraduate student pursuing a BSc with Honors in Psychology at University of Ottawa. Mia is interested in learning about computational neuroscience and programming with Matlab. She is currently working on a model of spiking neurons with heterogenous spiking thresholds. 


Gatete Queen Olea Umulinga

Role: Undergraduate volunteer

Queen is currently completing a Bachelor of Social Sciences with a Major in Psychology. She is interested in counseling psychology, particularly by the potential of AI as a valuable tool for advancing our understanding of the human mind and mental health. 

Publications by year


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]


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]


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]


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]
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]


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]
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]

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]

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]


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]


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]


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


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]


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]


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


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]


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]


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]


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]


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)

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

2018 (fall): Samy Djoudad, lab volunteer

2018 (spring) : directed research: Stephanie Norlock transferred to Honours thesis

2018 (Winter): directed research in psychology: Philippe Lambert

2017: M.A. Calderini, defended nov. 2019.

2017 Honours thesis (Biomed): Lea Caya-Bissonnette

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