GitHub

Citations

The paper for IntrinsicTimescales.jl is currently in review in Journal of Open Source Software. Once it is published, I'll add the reference here for citation.

For specific methods, you can cite the following papers:

  • :acw50:

    • Honey, C. J., Thesen, T., Donner, T. H., Silbert, L. J., Carlson, C. E., Devinsky, O., Doyle, W. K., Rubin, N., Heeger, D. J., & Hasson, U. (2012). Slow Cortical Dynamics and the Accumulation of Information over Long Timescales. Neuron, 76(2), 423–434. https://doi.org/10.1016/j.neuron.2012.08.011
    • Wolman, A., Çatal, Y., Wolff, A., Wainio-Theberge, S., Scalabrini, A., Ahmadi, A. E., & Northoff, G. (2023). Intrinsic neural timescales mediate the cognitive bias of self—Temporal integration as key mechanism. NeuroImage, 268, 119896. https://doi.org/10.1016/j.neuroimage.2023.119896
    • Çatal, Y., Wolman, A., Buccellato, A., Keskin, K., & Northoff, G. (2025). How Intrinsic Neural Timescales Relate To Event-Related Activity - Key Role For Intracolumnar Connections (p. 2025.01.10.632350). bioRxiv. https://doi.org/10.1101/2025.01.10.632350

  • :acw0:

    • Golesorkhi, M., Gomez-Pilar, J., Tumati, S., Fraser, M., & Northoff, G. (2021). Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization. Communications Biology, 4(1), Article 1. https://doi.org/10.1038/s42003-021-01785-z
    • Wolman, A., Çatal, Y., Wolff, A., Wainio-Theberge, S., Scalabrini, A., Ahmadi, A. E., & Northoff, G. (2023). Intrinsic neural timescales mediate the cognitive bias of self—Temporal integration as key mechanism. NeuroImage, 268, 119896. https://doi.org/10.1016/j.neuroimage.2023.119896
    • Tang, X., Wang, S., Xu, X., Luo, W., & Zhang, M. (n.d.). Test–retest reliability of resting-state EEG intrinsic neural timescales. Cerebral Cortex. Retrieved June 3, 2025, from https://dx.doi.org/10.1093/cercor/bhaf034

  • :acweuler:

    • Cusinato, R., Alnes, S. L., Maren, E. van, Boccalaro, I., Ledergerber, D., Adamantidis, A., Imbach, L. L., Schindler, K., Baud, M. O., & Tzovara, A. (2023). Intrinsic Neural Timescales in the Temporal Lobe Support an Auditory Processing Hierarchy. Journal of Neuroscience, 43(20), 3696–3707. https://doi.org/10.1523/JNEUROSCI.1941-22.2023

  • :auc:

    • Manea, A. M. G., Maisson, D. J.-N., Voloh, B., Zilverstand, A., Hayden, B., & Zimmermann, J. (2024). Neural timescales reflect behavioral demands in freely moving rhesus macaques. Nature Communications, 15(1), 2151. https://doi.org/10.1038/s41467-024-46488-1
    • Raut, R. V., Mitra, A., Marek, S., Ortega, M., Snyder, A. Z., Tanenbaum, A., Laumann, T. O., Dosenbach, N. U. F., & Raichle, M. E. (2020). Organization of Propagated Intrinsic Brain Activity in Individual Humans. Cerebral Cortex, 30(3), 1716–1734. https://doi.org/10.1093/cercor/bhz198

    -Watanabe, T., Rees, G., & Masuda, N. (2019). Atypical intrinsic neural timescale in autism. eLife, 8, e42256. https://doi.org/10.7554/eLife.42256

    • Wu, K., & Gollo, L. L. (2025). Mapping and modeling age-related changes in intrinsic neural timescales. Communications Biology, 8(1), 1–16. https://doi.org/10.1038/s42003-025-07517-x

  • :tau:

    • Murray, J. D., Bernacchia, A., Freedman, D. J., Romo, R., Wallis, J. D., Cai, X., Padoa-Schioppa, C., Pasternak, T., Seo, H., Lee, D., & Wang, X.-J. (2014). A hierarchy of intrinsic timescales across primate cortex. Nature Neuroscience, 17(12), Article 12. https://doi.org/10.1038/nn.3862
    • Ito, T., Hearne, L. J., & Cole, M. W. (2020). A cortical hierarchy of localized and distributed processes revealed via dissociation of task activations, connectivity changes, and intrinsic timescales. NeuroImage, 221, 117141. https://doi.org/10.1016/j.neuroimage.2020.117141
    • Çatal, Y., Keskin, K., Wolman, A., Klar, P., Smith, D., & Northoff, G. (2024). Flexibility of intrinsic neural timescales during distinct behavioral states. Communications Biology, 7(1), 1667. https://doi.org/10.1038/s42003-024-07349-1

  • :knee:

    • Gao, R., van den Brink, R. L., Pfeffer, T., & Voytek, B. (2020). Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture. eLife, 9, e61277. https://doi.org/10.7554/eLife.61277
    • Manea, A. M. G., Maisson, D. J.-N., Voloh, B., Zilverstand, A., Hayden, B., & Zimmermann, J. (2024). Neural timescales reflect behavioral demands in freely moving rhesus macaques. Nature Communications, 15(1), 2151. https://doi.org/10.1038/s41467-024-46488-1

  • If you are using Bayesian methods, cite

    • Zeraati, R., Engel, T. A., & Levina, A. (2022). A flexible Bayesian framework for unbiased estimation of timescales. Nature Computational Science, 2(3), 193–204. https://doi.org/10.1038/s43588-022-00214-3
    • Zeraati, R., Shi, Y.-L., Steinmetz, N. A., Gieselmann, M. A., Thiele, A., Moore, T., Levina, A., & Engel, T. A. (2023). Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity. Nature Communications, 14(1), Article 1. https://doi.org/10.1038/s41467-023-37613-7

  • If you are using :abc as fitting method in Bayesian methods, cite:

    • Beaumont, M. A., Cornuet, J.-M., Marin, J.-M., & Robert, C. P. (2009). Adaptive approximate Bayesian computation. Biometrika, 96(4), 983–990.

  • If you are using :advi,

    • Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., & Blei, D. M. (2017). Automatic Differentiation Variational Inference. Journal of Machine Learning Research, 18(14), 1–45.