Jan Zimmermann, PhD

Dr. Jan Zimmermann is an Assistant Professor in the Department of Neuroscience and the Center for Magnetic Resonance Research. His lab studies how the brain represents and constructs subjective value and how that signal is used to guide decision making. The lab is particularly interested in how the brain adaptively changes its coding strategy to encode statistical regularities within a changing environment. Using electrophysiology, ultra high field MRI and computational modeling the lab tries to understand how changes in reward encoding sensitivity could relate to a propensity for drug addiction.

The primary research goal of our laboratory is to better understand decision making. Making a choice, independent of it being a complex decision about your retirement allocations or which flavor of ice-cream to pick, is the normative consequence of any behavior that is observable.

To understand this process, we combine a multitude of tools that allow us to study neural function of non human primates associated to decision making. We combine single cell electrophysiology, computational modeling of neural responses as well as careful behavioral analysis and ultra high field functional magnetic resonance imaging to figure out how organisms adaptively use their finite neural coding capacity to make choices.

Steverson, K, Chung, H-K, Zimmermann, J, Louie, K & Glimcher, P 2019, 'Sensitivity of reaction time to the magnitude of rewards reveals the cost-structure of time', Scientific reports, vol. 9, no. 1, pp. 20053. https://doi.org/10.1038/s41598-019-56392-0

Eisenreich, BR, Hayden, BY & Zimmermann, J 2019, 'Macaques are risk-averse in a freely moving foraging task', Scientific reports, vol. 9, no. 1, 15091. https://doi.org/10.1038/s41598-019-51442-z

Zimmermann, J, Glimcher, PW & Louie, K 2018, 'Multiple timescales of normalized value coding underlie adaptive choice behavior', Nature communications, vol. 9, no. 1, 3206. https://doi.org/10.1038/s41467-018-05507-8

Sengupta, S, Roebroeck, A, Kemper, VG, Poser, BA, Zimmermann, J, Goebel, R & Adriany, G 2016, 'A specialized multi-transmit head coil for high resolution fMRI of the human visual cortex at 7T', PloS one, vol. 11, no. 12, e0165418. https://doi.org/10.1371/journal.pone.0165418

Zimmermann, J, Vazquez, Y, Glimcher, PW, Pesaran, B & Louie, K 2016, 'Oculomatic: High speed, reliable, and accurate open-source eye tracking for humans and non-human primates', Journal of Neuroscience Methods, vol. 270, pp. 138-146. https://doi.org/10.1016/j.jneumeth.2016.06.016

Emmerling, TC, Zimmermann, J, Sorger, B, Frost, M & Goebel, R 2016, 'Time-resolved searchlight analysis of imagined visual motion using 7 T ultra-high field fMRI: Data on interindividual differences', Data in Brief, vol. 7, pp. 468-471. https://doi.org/10.1016/j.dib.2016.02.071

Emmerling, TC, Zimmermann, J, Sorger, B, Frost, MA & Goebel, R 2016, 'Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI', NeuroImage, vol. 125, pp. 61-73. https://doi.org/10.1016/j.neuroimage.2015.10.022

Zilverstand, A, Sorger, B, Zimmermann, J, Kaas, A & Goebel, R 2014, 'Windowed correlation: A suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty', PloS one, vol. 9, no. 1, e85929. https://doi.org/10.1371/journal.pone.0085929

Gross, J, Woelbert, E, Zimmermann, J, Okamoto-Barth, S, Riedl, A & Goebel, R 2014, 'Value signals in the prefrontal cortex predict individual preferences across reward categories', Journal of Neuroscience, vol. 34, no. 22, pp. 7580-7586. https://doi.org/10.1523/JNEUROSCI.5082-13.2014

De Martino, F, Zimmermann, J, Muckli, L, Ugurbil, K, Yacoub, E & Goebel, R 2013, 'Cortical Depth Dependent Functional Responses in Humans at 7T: Improved Specificity with 3D GRASE', PloS one, vol. 8, no. 3, e60514. https://doi.org/10.1371/journal.pone.0060514