Zhaoping, L.: V1 serves as a motor cortex for visually guided saccades: Evidence from human and monkey behavioral and neural data. 29th Ocular Motor Research Meeting (MüTüZü 2020), Tübingen, Germany (2020)

Katliar, M.: Optimal control of motion simulators. Dissertation, 149 pp., Albert-Ludwigs-Universität, Freiburg i.Br., Germany (2020)

Nikulin, A.: Volume RF coils based on metamaterials for ultra-high field magnetic resonance imaging. Dissertation, 140 pp. (2020)

Foster, C.: The neural coding of properties shared by faces, bodies and objects. Dissertation, 194 pp., Eberhard-Karls-Universität, Tübingen, Germany (2020)

Chen, Y.: Mapping the local and brain-wide network effects by optogenetic activation with an MRI-guided robotic arm. Dissertation, 150 pp., Eberhard-Karls-Universität, Tübingen, Germany (2020)

He, Y.: High-Field Functional MRI from the Perspective of Single Vessels in Rats and Humans. Dissertation, Eberhard-Karls-Universität, Tübingen, Germany (2020)

Cleij, D.: Measuring, modelling and minimizing perceived motion incongruence: for vehicle motion simulation. Dissertation, 290 pp., Delft University of Technology, Delft, The Netherlands (2020)

Brielmann, A.: Understanding the Experience of Beauty. Dissertation, 216 pp., New York University, New York, NY, USA (2020)

Herz, K.: T1[rho]‐based dynamic glucose enhanced magnetic resonance imaging: from method development to clinical measurements in the human brain. Dissertation, 200 pp., Eberhard-Karls-Universität Tübingen, Tübingen, Germany (2020)

de Sardenberg Schmid, L.: Environmental prey density changes induce foraging strategy changes in larval zebrafish. Master, Eberhard-Karls-Universität Tübingen, Tübingen, Germany (2020)

Mahler, L.: Spatio-Temporal Feature Extraction for Action Recognition in Videos. Bachelor, Technische Hochschule Ulm, Ulm, Germany (2020)

Eckstein, M.; Master, S.; Dahl, R.; Wilbrecht, L.; Collins, A.: Understanding the Unique Advantage of Adolescents in Stochastic, Volatile Environments: Combining Reinforcement Learning and Bayesian Inference. (submitted)

Alon, N.; Meilijson, I.: Randomtime transformation analysis of Covid19 2020. (submitted)

Hinman, M.; Richardson, J.; Sockol, R.; Aronson, E.; Stednitz, S.; Murray, K.; Berglund, J.; Guillemin, K.: Zebrafish mbnl mutants model physical and molecular phenotypes of myotonic dystrophy. (submitted)

Bokharaie, V.: Iran and COVID-19: The Unfolding of a Humanitarian Disaster. (2020)

Zaiss, M.; Deshmane, A.; Scheffler, K.: Method And Apparatus For Processing Magnetic Resonance Data. (accepted)

Besserve, M.; Buchholz, S.; Schölkopf, B.: Assaying Large-scale Testing Models to InterpretCovid-19 Case Numbers: A Cross-country Study. (submitted)

Krockenberger, M.; Saleh, T.; Logothetis, N.; Evrard, H.: Connection “Stripes” in the Primate Insula. (submitted)

Vallier, M.; Mueller, M.; Bellucci, G.; Grange, M.; Lu, Y.; Duponchel, S.: Demographics and Employment of Max-Planck Society’s Postdocs. (submitted)

Chicharro, B.; Besserve, M.; Panzeri, S.: Causal learning with sufficient statistics: an information bottleneck approach. (submitted)