University of Ottawa

School of Psychology

136 Jean Jacques Lussier, Ottawa, ON  K1N 6N5 Canada


Research interests

My 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.

Publications By Year

2024


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]

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