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Results: 23
Number of items: 23
  • Open Access
    de Hollander, G. (2018). Understanding the human subcortex using ultra-high field MRI and computational cognitive models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Alkemade, A., de Hollander, G., Keuken, M. C., Schäfer, A., Ott, D. V. M., Schwarz, J., Weise, D., Kotz, S. A., & Forstmann, B. U. (2017). Comparison of T2∗-weighted and QSM contrasts in Parkinson's disease to visualize the STN with MRI. PLoS ONE, 12(4), Article e0176130. https://doi.org/10.1371/journal.pone.0176130
  • Open Access
    Salzer, Y., de Hollander, G., & Forstmann, B. U. (2017). Sensory neural pathways revisited to unravel the temporal dynamics of the Simon effect: A model-based cognitive neuroscience approach. Neuroscience and Biobehavioral Reviews, 77, 48-57. https://doi.org/10.1016/j.neubiorev.2017.02.023
  • Open Access
    de Hollander, G., Keuken, M. C., van der Zwaag, W., Forstmann, B. U., & Trampel, R. (2017). Comparing Functional MRI Protocols for Small, Iron-Rich Basal Ganglia Nuclei Such as the Subthalamic Nucleus at 7 T and 3 T. Human Brain Mapping, 38(6), 3226-3248. https://doi.org/10.1002/hbm.23586
  • Open Access
    Forstmann, B. U., de Hollander, G., van Maanen, L., Alkemade, A., & Keuken, M. C. (2017). Towards a mechanistic understanding of the human subcortex. Nature Reviews Neuroscience, 18(1), 57-65. https://doi.org/10.1038/nrn.2016.163
  • Open Access
    de Hollander, G., Labruna, L., Sellaro, R., Trutti, A., Colzato, L. S., Ratcliff, R., Ivry, R. B., & Forstmann, B. U. (2016). Transcranial direct current stimulation does not influence the speed-accuracy tradeoff in perceptual decision-making: Evidence from three independent studies. Journal of Cognitive Neuroscience, 28(9), 1283-1294. https://doi.org/10.1162/jocn_a_00967
  • Open Access
    de Hollander, G., Forstmann, B. U., & Brown, S. D. (2016). Different Ways of Linking Behavioral and Neural Data via Computational Cognitive Models. Biological psychiatry. Cognitive neuroscience and neuroimaging, 1(2), 101-109. https://doi.org/10.1016/j.bpsc.2015.11.004
  • Open Access
    de Hollander, G. (2016). Combining computational models of cognition and neural data to learn about mixed task strategies. The Journal of Neuroscience, 36(1), 1-3. https://doi.org/10.1523/JNEUROSCI.3690-15.2016
  • Open Access
    de Hollander, G., Keuken, M. C., & Forstmann, B. U. (2015). The subcortical cocktail problem; mixed signals from the subthalamic nucleus and substantia nigra. PLoS ONE, 10(3), Article e0120572. https://doi.org/10.1371/journal.pone.0120572
  • Open Access
    Karayanidis, F., Keuken, M. C., Wong, A., Rennie, J. L., de Hollander, G., Cooper, P. S., Fulham, W. R., Lenroot, R., Parsons, M., Philips, N., Michie, P. T., & Forstmann, B. U. (2015). The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository. NeuroImage, 124(B), 1137-1142. https://doi.org/10.1016/j.neuroimage.2015.04.047
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