Halliday, D. W., Mulligan, B. P., Garrett, D. D., Schmidt, S., Hundza, S. R., Garcia-Barrera, M., Stawski, R. S., & MacDonald, S. W. S. (2018). Mean and variability in functional brain activations differentially predict executive function in older adults: An investigation employing functional near-infrared spectroscopy. Neurophotonics, 5(1), Article 011013. https://doi.org/10.1117/1.NPh.5.1.011013

Lövdén, M., Karalija, N., Andersson, M., Wåhlin, A., Axelsson, J., Köhncke, Y., Jonasson, L. S., Rieckman, A., Papenberg, G., Garrett, D. D., Guitart-Masip, M., Salami, A., Riklund, K., Bäckman, L., Nyberg, L., & Lindenberger, U. (2018). Latent-profile analysis reveals behavioral and brain correlates of dopamine-cognition associations. Cerebral Cortex, 28(11), 3894–3907. https://doi.org/10.1093/cercor/bhx253

Salami, A., Rieckmann, A., Karalija, N., Avelar-Pereira, B., Andersson, M., Wåhlin, A., Papenberg, G., Garrett, D. D., Riklund, K., Lövdén, M., Lindenberger, U., Bäckman, L., & Nyberg, L. (2018). Neurocognitive profiles of older adults with working-memory dysfunction. Cerebral Cortex, 28(7), 2525–2539. https://doi.org/10.1093/cercor/bhy062

Garrett, D. D., Lindenberger, U., Hoge, R. D., & Gauthier, C. J. (2017). Age differences in brain signal variability are robust to multiple vascular controls. Scientific Reports, 7(1), Article 10149. https://doi.org/10.1038/s41598-017-09752-7

Grandy, T. H., Garrett, D. D., Schmiedek, F., & Werkle-Bergner, M. (2016). On the estimation of brain signal entropy from sparse neuroimaging data. Scientific Reports, 6, Article 23073. https://doi.org/10.1038/srep23073

Guitart-Masip, M., Salami, A., Garrett, D. D., Rieckmann, A., Lindenberger, U., & Bäckman, L. (2016). BOLD variability is related to dopaminergic neurotransmission and cognitive aging. Cerebral Cortex, 26(5), 2074–2083. https://doi.org/10.1093/cercor/bhv029

Nyberg, L., Karalija, N., Salami, A., Andersson, M., Wåhlin, A., Kaboovand, N., Köhncke, Y., Axelsson, J., Rieckmann, A., Papenberg, G., Garrett, D. D., Riklund, K., Lövdén, M., Lindenberger, U., & Bäckman, L. (2016). Dopamine D2 receptor availability is linked to hippocampal-caudate functional connectivity and episodic memory. Proceedings of the National Academy of Sciences of the United States of America, 113(28), 7918–7923. https://doi.org/10.1073/pnas.1606309113

Garrett, D. D., Nagel, I. E., Preuschhof, C., Burzynska, A. Z., Marchner, J., Wiegert, S., Jungehülsing, G. J., Nyberg, L., Villringer, A., Li, S.-C., Heekeren, H. R., Bäckman, L., & Lindenberger, U. (2015). Amphetamine modulates brain signal variability and working memory in younger and older adults. Proceedings of the National Academy of Sciences of the United States of America, 112(24), 7593–7598. https://doi.org/10.1073/pnas.1504090112

Garrett, D. D., McIntosh, A. R., & Grady, C. L. (2014). Brain signal variability is parametrically modifiable. Cerebral Cortex, 24(11), 2931–2940. https://doi.org/10.1093/cercor/bht150

Grady, C. L., & Garrett, D. D. (2014). Understanding variability in the BOLD signal and why it matters for aging. Brain Imaging and Behavior, 8(2), 274–283. https://doi.org/10.1007/s11682-013-9253-0

Burzynska, A. Z., Garrett, D. D., Preuschhof, C., Nagel, I. E., Li, S.-C., Bäckman, L., Heekeren, H. R., & Lindenberger, U. (2013). A scaffold for efficiency in the human brain. The Journal of Neuroscience, 33(43), 17150–17159. https://doi.org/10.1523/JNEUROSCI.1426-13.2013

Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2013). The modulation of BOLD variability between cognitive states varies by age and processing speed. Cerebral Cortex, 23(3), 684–693. https://doi.org/10.1093/cercor/bhs055

Garrett, D. D., Samanez-Larkin, G. R., MacDonald, S. W. S., Lindenberger, U., McIntosh, A. R., & Grady, C. L. (2013). Moment-to-moment brain signal variability: A next frontier in human brain mapping? Neuroscience & Biobehavioral Reviews, 37, 610–624. https://doi.org/10.1016/j.neubiorev.2013.02.015

Garrett, D. D., MacDonald, S. W. S., & Craik, F. I. M. (2012). Intraindividual reaction time variability is malleable: Feedback- and education-related reductions in variability with age. Frontiers in Human Neuroscience, 6, Article 101. https://doi.org/10.3389/fnhum.2012.00101

Tochadse, M. (2019). Neural dynamics of scene viewing [Masterarbeit, Freie Universität Berlin].

Skowron, A., Kosciessa, J. Q., Lorenz, R., Hertwig, R., van den Bos, W., & Garrett, D. D. (2024). Neural variability compresses with increasing belief precision during Bayesian inference. BioRxiv, January 12, 2024. https://doi.org/10.1101/2024.01.11.575180

Kosciessa, J. Q., Mayr, U., Lindenberger, U., & Garrett, D. D. (2023). Broadscale dampening of uncertainty adjustment in the aging brain. BioRxiv, July 18, 2023. https://doi.org/10.1101/2023.07.14.549093

Waschke, L., Kamp, F., van den Elzen, E., Krishna, S., Lindenberger, U., Rutishauser, U., & Garrett, D. D. (2023). Single-neuron spiking variability in hippocampus dynamically tracks sensory content during memory formation in humans. BioRxiv, February 23, 2023. https://doi.org/10.1101/2023.02.23.529684

Garrett, D. D., Kloosterman, N. A., Epp, S. M., Chopurian, V., Kosciessa, J. Q., Waschke, L., Skowron, A., Shine, J. M., Perry, A., Salami, A., Rieckmann, A., Papenberg, G., Wåhlin, A., Karalija, N., Andersson, M., Riklund, K., Lövdén, M., Bäckman, L., Nyberg, L., & Lindenberger, U. (2022). Dynamic regulation of neural variability during working memory reflects dopamine, functional integration, and decision-making. BioRxiv, May 5, 2022. https://doi.org/10.1101/2022.05.05.490687

Lalwani, P., Polk, T. A., & Garrett, D. D. (2022). Modulation of neural variability: Age-related reduction, GABAergic basis, and behavioral implications. BioRxiv, September 17, 2022. https://doi.org/10.1101/2022.09.14.507785