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Recherche
Srdjan OSTOJIC
Researcher
Research Director
Cognitive Studies
Theoretical and Computational Neuroscience
ENS-PSL
Department of Cognitive Studies
Published on
28 September 2021
, updated on
9 December 2021
Laboratoire de neurosciences cognitives et computationnelles
2ème étage, bureau IEC
29, rue d'Ulm 75230 Paris cedex 05
01 44 322644
The overarching aim of research in my team is to understand how thousands of neurons in the brain work together to implement computations that underlie behavior. To this end, we develop mathematical models based on recurrent neural networks and perform population analyses of neural activity recorded in behaving animals.
Field of research
Recurrent interactions between neurons generate dynamic patterns of activity that serve as the physical substrate for performing behaviorally relevant computations. Understanding how collective dynamics and computations emerge from recurrent interactions is a key endeavor of research in my team. We investigate the interplay between collective dynamics and computations in recurrent neural networks by combining methods from machine learning with mathematical analyses inspired by statistical physics.
In a key development, my lab has developed a novel class of network models, low-rank recurrent networks, that allow us to directly understand how connectivity determines low-dimensional dynamics of neural activity that implement computations (Mastrogiuseppe and Ostojic 2018). This class of models provides a rich and tractable theoretical framework for unraveling how dynamics enable specific computations, and for interpreting neural recordings in behaving animals.
Publications
- Jazayeri M and Ostojic S (2021). Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity Current Opinions in Neurobiology, in press.
- Beiran M, Dubreuil A, Valente A, Mastrogiuseppe F and Ostojic S Shaping dynamics with multiple populations in low-rank recurrent networks, Neural Computation 33 (6), 1572-1615.
- Bondanelli. G., Deneux T., Bathellier B. & Ostojic, S. (2021). Network dynamics underlying OFF responses in the auditory cortex. eLife, 10, e53151.
- Bouchacourt, F., Palminteri, S., Koechlin, E. & Ostojic, S. (2020). Temporal Chunking as a Mechanism for Unsupervised Learning of Task-Sets. eLife, 9, e50469. doi:10.7554/eLife.50469
- Ladenbauer, J., McKenzie , S., English , D., Hagens , O. & Ostojic, S. (2019). Inferring and validating mechanistic models of neural microcircuits based on spike-train data. Nature Communications, 10(4933). doi:10.1038/s41467-019-12572-0
- Mastrogiuseppe, F. & Ostojic, S. (2018). Linking connectivity, dynamics and computations in low-rank recurrent neural networks. Neuron, 99(3), 609-623. doi:DOI:https://doi.org/10.1016/j.neuron.2018.07.003
- Bagur, S. , Averseng, M., Elgueda, D., David, S., Fritz, J., Yin, P., Shamma, S., Boubenec, Y. & Ostojic, S. (2018). Go/No-Go task engagement enhances population representation of target stimuli in primary auditory cortex. Nature Communications, 9, 2529 . doi:10.1038/s41467-018-04839-9
- Ostojic, S. (2014). Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons. Nature Neuroscience, 17(4), 594-600.