Preprint (9)

2017
Preprint
Donnelly-Kehoe, P. A., Saenger, V. M., Lisofsky, N., Kühn, S., Kringelbach, M. L., Schwarzbach, J., & Deco, G. (2017). Consistent local dynamics in the brain across sessions are revealed by whole brain modeling of resting state activity. BioRxiv, 104232. https://doi.org/10.1101/104232
Preprint
Grandy, T., Lindenberger, U., & Werkle-Bergner, M. (2017). When group means fail: Can one size fit all? BioRxiv, 126490. https://doi.org/10.1101/126490
Preprint
Leuker, C., Pachur, T., Hertwig, R., & Pleskac, T. J. (2017, December 30). Exploiting risk-reward structures in decision making under uncertainty. Open Science Framework. https://doi.org/10.17605/OSF.IO/TMCND
Preprint
Motsch, S., Moussaïd, M., Guillot, E. G., Moreau, M., Pettré, J., Theraulaz, G., Appert-Rolland, C., & Degond, P. (2017). Forecasting crowd dynamics through coarse-grained data analysis. BioRxiv, 175760. https://doi.org/10.1101/175760
Preprint
Schuck, N. W., Wilson, R. C., & Niv, Y. (2017). A state representation for reinforcement learning and decision-making in the orbitofrontal cortex. BioRxiv, 210591. https://doi.org/10.1101/210591
Preprint
Wu, C. M., Schulz, E., Speekenbrink, M., Nelson, J. D., & Meder, B. (2017). Mapping the unknown: The spatially correlated multi-armed bandit. BioRxiv, 06286. https://doi.org/10.1101/106286

Software (5)

2017
Software
Arslan, R. C. (2017). formr survey framework utility package (Version v0.7.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.1041411
Software
Arslan, R. C. (2017). Cook codebooks from survey metadata encoded in attributes in R (Version v0.1.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.1041466
Software
Arslan, R. C., & Tata, C. S. (2017). rubenarslan/formr.org: v0.16.13 (Version v0.16.13) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.1000787
Software
Brandmaier, A. M. (2017). Recursive partitioning for Structural Equation Models [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.1116294
Software
Brandmaier, A. M. (2017). pdc: An R package for complexity-based clustering of time series [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.1116256
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