About

I am a Postdoctoral Research Scientist in the Mathematics & Theoretical Computer Science Department at the IBM T.J. Watson Research Center in New York. I was previously a Swartz Fellow in Theoretical Neuroscience at Yale University working with John Murray. I completed my PhD in Neuroscience at Rutgers University with Michael Cole, and my BA in Mathematics at Washington University in St. Louis.

I am from NYC.

Research Interest

My research is in computational neuroscience and artificial intelligence. More recently, my interests lie in understanding how neural systems (e.g., artificial neural networks) learn to abstract and reason, as is required in compositional generalization. In the past, I have used neural data analysis and computational modeling to study the neural basis of flexible (e.g., multitask) cognition in humans and non-human primates.

Selected publications

Ito T, Campbell M, Horesh L, Klinger T, Ram P (2024). Quantifying artificial intelligence through algebraic generalization. arXiv. http://arxiv.org/abs/2411.05943

Ito T, Murray JD (2023). Multitask representations in the human cortex transform along a sensory-to-motor hierarchy. Nature Neuroscience. https://www.nature.com/articles/s41593-022-01224-0

Ito T, Klinger T, Schultz DH, Murray JD, Cole MW, Rigotti M (2022). Compositional generalization through abstract representations in human and artificial neural networks. Advances in Neural Information Processing Systems (NeurIPS, Oral). https://openreview.net/forum?id=177GzUAds8U

Ito T, Brincat SL, Siegel M, Mill RD, He BJ, Miller EK, Rotstein HG, Cole MW (2020). Task-evoked activity quenches neural correlations and variability across cortical areas. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1007983

Ito T, Kulkarni KR, Schultz DH, Mill RD, Chen RH, Solomyak LI, & Cole MW (2017). Cognitive task information is transferred between brain regions via resting-state network topology. Nature Communications. https://www.nature.com/articles/s41467-017-01000-w.

Publications

Preprint papers

28. Ito T, Campbell M, Horesh L, Klinger T, Ram P (2024). Quantifying artificial intelligence through algebraic generalization. arXiv. http://arxiv.org/abs/2411.05943

27. Robinson CN, Cocchi L, Ito T, Hearne LJ (2024). Temporally delayed representations in alpha and beta rhythms in higher-order cortical networks track increasing relational integration demands. bioRxiv. https://www.biorxiv.org/content/10.1101/2024.10.16.618779v1

26. Ito T, Cocchi L, Klinger T, Ram P, Campbell M, Hearne LJ (2024). Learning positional encodings in transformers depends on initialization. arXiv. https://arxiv.org/abs/2406.08272

Peer-reviewed papers

2024

25. Lei X, Ito T, Bashivan P (2024). Geometry of naturalistic object representations in recurrent neural network models of working memory. Advances in Neural Information Processing Systems (NeurIPS). https://arxiv.org/abs/2411.02685

24. Cocuzza CV, Sanchez-Romero R, Ito T, Mill RD, Keane BP, Cole MW (2024). Distributed network flows generate localized category selectivity in human visual cortex. PLOS Computational Biology. https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012507

23. Ito T, Dan S, Rigotti M, Kozloski J, Campbell M (2024). On the generalization capacity of neural networks during generic multimodal reasoning. International Conference on Learning Representations (ICLR). http://arxiv.org/abs/2401.15030.

22. Ito T, Murray JD (2024). The impact of functional correlations on task information coding. Network Neuroscience. https://doi.org/10.1162/netn_a_00402.

2023

21. Sanchez-Romero R, Ito T, Mill RD, Hanson SJ, Cole MW (2023). Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations. NeuroImage. https://doi.org/10.1016/j.neuroimage.2023.120300

20. Ito T, Murray JD (2023). Multitask representations in the human cortex transform along a sensory-to-motor hierarchy. Nature Neuroscience. https://www.nature.com/articles/s41593-022-01224-0

2022

19. Ito T, Klinger T, Schultz DH, Murray JD, Cole MW, Rigotti M (2022). Compositional generalization through abstract representations in human and artificial neural networks. Advances in Neural Information Processing Systems (NeurIPS, Oral). https://openreview.net/forum?id=177GzUAds8U

18. Ito T, Yang GR, Laurent P, Schultz DH, Cole MW (2022). Constructing neural network models from brain data reveals representational transformations underlying adaptive behavior. Nature Communications. https://doi.org/10.1038/s41467-022-28323-7

17. *McCormick EM, *Arnemann KL, Ito T, Hanson SJ, Cole MW (2022). Latent functional connectivity underlying multiple brain states. Network Neuroscience. https://doi.org/10.1162/netn_a_00234

16. Schultz DH, Ito T, Cole MW (2022). The human brain’s intrinsic network architecture is organized to represent diverse cognitive task information. Cerebral Cortex. https://doi.org/10.1093/cercor/bhab495

2021

15. Cole MW, Ito T, Cocuzza CV, Sanchez-Romero R (2020). The functional relevance of task-state functional connectivity. Journal of Neuroscience. https://doi.org/10.1523/JNEUROSCI.1713-20.2021

14. Spronk M, Keane BP, Ito T, Kulkarni K, Ji JL, Anticevic A, Cole MW (2021). A whole-brain and cross-diagnostic perspective on functional brain network dysfunction. Cerebral Cortex. https://doi.org/10.1093/cercor/bhaa242

2020

13. Ito T, Hearne LJ, Cole MW (2020). A cortical hierarchy of localized and distributed processes revealed via dissociation of task activations, connectivity changes, and intrinsic timescales. NeuroImage. https://doi.org/10.1016/j.neuroimage.2020.117141

12. Cocuzza CV, Ito T, Schultz DH, Bassett DS, Cole MW (2020). Flexible coordinator and switcher hubs for adaptive task control. Journal of Neuroscience. https://doi.org/10.1523/JNEUROSCI.2559-19.2020

11. Ito T, Brincat SL, Siegel M, Mill RD, He BJ, Miller EK, Rotstein HG, Cole MW (2020). Task-evoked activity quenches neural correlations and variability across cortical areas. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1007983

10. Kar K, Ito T, Cole MW, Krekelberg B (2020). Transcranial alternating current stimulation reduces BOLD adaptation and increases functional connectivity. Journal of Neurophysiology. https://doi.org/10.1152/jn.00376.2019

4. Mill RD, Ito T, Cole MW (2017). From connectome to cognition: The search for mechanism in human functional brain networks. NeuroImage. http://dx.doi.org/10.1016/j.neuroimage.2017.01.060

2016

3. Cole MW, Ito T, Bassett DS, & Schultz DH (2016). Activity flow over resting-state networks shapes cognitive task activations. Nature Neuroscience. doi:10.1038/nn.4406

2015

2. Cole MW, Ito T, & Braver TS (2015). Lateral prefrontal cortex contributes to fluid intelligence through multinetwork connectivity. Brain Connectivity, 5(8), 497–504. http://doi.org/10.1089/brain.2015.0357

1. Cole MW, Ito T, & Braver TS (2015). The behavioral relevance of task information in human prefrontal cortex. Cerebral Cortex (New York, N.Y. : 1991), bhv072–. http://doi.org/10.1093/cercor/bhv072