Citations

If you are using this package, please cite:

• Çatal Y., Northoff G. (2025). IntrinsicTimescales.jl: A Julia package to estimate intrinsic (neural) timescales (INTs) from time-series data. Journal of Open Source Software, 10(114), 8261, https://doi.org/10.21105/joss.08261

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.