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Results: 205
Number of items: 205
  • Open Access
    Turi, Z., Csifcsák, G., Boayue, N. M., Aslaksen, P., Antal, A., Paulus, W., Groot, J., Hawkins, G. E., Forstmann, B., Opitz, A., Thielscher, A., & Mittner, M. (2019). Blinding is compromised for transcranial direct current stimulation at 1 mA for 20 min in young healthy adults. European Journal of Neuroscience, 50(8), 3261-3268. https://doi.org/10.1111/ejn.14403
  • Open Access
    Alkemade, A., de Hollander, G., Miletic, S., Keuken, M. C., Balesar, R., de Boer, O., Swaab, D. F., & Forstmann, B. U. (2019). The functional microscopic neuroanatomy of the human subthalamic nucleus. Brain Structure and Function, 224(9), 3212-3227. https://doi.org/10.1007/s00429-019-01960-3
  • Open Access
    Mulder, M. J., Keuken, M. C., Bazin, P.-L., Alkemade, A., & Forstmann, B. U. (2019). Size and shape matter: The impact of voxel geometry on the identification of small nuclei. PLoS ONE, 14(4), Article e0215382. https://doi.org/10.1371/journal.pone.0215382
  • Open Access
    Trutti, A. C., Mulder, M. J., Hommel, B., & Forstmann, B. U. (2019). Functional neuroanatomical review of the ventral tegmental area. NeuroImage, 191, 258-268. https://doi.org/10.1016/j.neuroimage.2019.01.062
  • Open Access
    Wisniewski, D., Forstmann, B., & Brass, M. (2019). Outcome contingency selectively affects the neural coding of outcomes but not of tasks. Scientific Reports, 9, Article 19395. https://doi.org/10.1038/s41598-019-55887-0
  • Open Access
    Bazin, P.-L., Alkemade, A., van der Zwaag, W., Caan, M., Mulder, M., & Forstmann, B. U. (2019). Denoising High-Field Multi-Dimensional MRI With Local Complex PCA. Frontiers in Neuroscience, 13, Article 1066. https://doi.org/10.3389/fnins.2019.01066
  • Open Access
    Hawkins, G. E., Mittner, M., Forstmann, B. U., & Heathcote, A. (2019). Modeling distracted performance. Cognitive Psychology, 112, 48-80. https://doi.org/10.1016/j.cogpsych.2019.05.002
  • Turner, B. M., Miletić, S., & Forstmann, B. U. (2018). Outlook on deep neural networks in computational cognitive neuroscience. NeuroImage, 180(A), 117-118. https://doi.org/10.1016/j.neuroimage.2017.12.078
  • Alkemade, A., Kotz, S. A., Ott, D. V., Keuken, M. C., Schwarz, J., Weise, D., Schäfer, A., Forstmann, B. U., & de Hollander, G. (2018). Data from: Comparison of T2*-weighted and QSM contrasts in Parkinson's disease to visualize the STN with MRI [Data set]. DRYAD. https://doi.org/10.5061/dryad.t7kp7
  • Ly, A., Böhm, U., Heathcote, A., Turner, B. M., Forstmann, B., Marsman, M., & Matzke, D. (2018). A flexible and efficient hierarchical Bayesian approach to the exploration of individual differences in cognitive-model-based neuroscience. In A. A. Moustafa (Ed.), Computational Models of Brain and Behavior (pp. 467-480). Wiley Blackwell. https://doi.org/10.1002/9781119159193.ch34
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