Kahnt, Thorsten, PhD

Selected Publications

Selected Publications

Howard JD, Gottfried JA, Tobler PN, Kahnt T. 2015. Identity-specific coding of future rewards in the human orbitofrontal cortex. Proc Natl Acad Sci USA, 112(16):5195-200.
Kahnt T, Park SQ, Haynes JD, Tobler PN. 2014. Disentangling neural representations of value and salience in the human brain. Proc Natl Acad Sci USA, 111(13):5000-5.
Kahnt T, Park SQ, Burke CJ, Tobler PN. 2012. How glitter relates to gold: Similarity-dependent reward prediction errors in the human striatum. The Journal of Neuroscience, 32(46):16521–9.
Kahnt T, Chang LJ, Park SQ, Heinzle J, Haynes JD. 2012. Connectivity-based parcellation of the human orbitofrontal cortex. The Journal of Neuroscience, 32(18):6240-50.
Kahnt T, Grueschow M, Speck O, Haynes JD. 2011. Perceptual learning and decision making in human medial frontal cortex. Neuron, 70(3):549-59.
Kahnt T, Heinzle J, Park SQ, Haynes JD. 2010. The neural code of reward anticipation in human orbitofrontal cortex. Proc Natl Acad Sci USA, 107(13):6010-5.

Information

Name

Kahnt, Thorsten, PhD

Title

Assistant Professor

Email

thorsten.kahnt@northwestern.edu

Office Phone

312-503-2896

Department

Neurology

Office

Ward 13-006

Website

http://labs.feinberg.northwestern.edu/kahnt/

Areas of Research

Brain Imaging (FMRI etc.), Circuits and Behavior, Computational, Learning & Memory, Neurobiology of Disease

Training Grants

Training Program in the Neuroscience of Human Cognition

Recent Publications on PubMed

http://www.ncbi.nlm.nih.gov/pubmed/?term=Kahnt_t

Current Research

Current Research

Research in the lab examines the neural and computational principles of reward-guided behavior, with a focus on food choices. We study brain systems involved in reward processing, learning, generalization, and decision-making such as the striatum and the orbitofrontal cortex. For this, we use a combination of human olfactory psychophysics, computational modeling, fMRI and advanced multivariate analyses techniques borrowed from machine learning. This research may pave the way for understanding decision-making deficits in neurological diseases and addiction, and should ultimately lead to novel diagnostic markers and treatment strategies for these disorders.