Matthias Mittner
Job description
Matthias Mittner is a professor and leader of the research group for cognitive neuroscience at the University of Tromsø and a professor of quantitative research methods at the Norwegian University of Science and Technology in Norway. He has broad experience teaching university courses in statistics and research methods ranging from introductory to advanced topics both at the Bachelor, Master and PhD-level. His main research interests are centered on the neurobiology of cognitive functions and he is also interested in the development of methodological approaches and computational methods, cognitive modeling, machine-learning and Bayesian statistics. Matthias has studied psychology and computer science and completed his PhD in psychology at the University of Frankfurt (Germany). He has previously worked as a post-doc at the Max-Planck Institutes for Dynamics and Self-Organization as well as the MPI for experimental medicine and the University of Amsterdam (The Netherlands).
Personal website: http://ihrke.github.io
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Publications outside Cristin
Older publications that are not in the Cristin system
Boayue, N., Csifcsak, G., Aslaksen, P., Turi, Z., Antal, A., Groot, J., Hawkins, G., Forstmann, B., Opitz, A., Thielscher, A. and Mittner, M.(accepted). Increasing propensity of mind wandering by transcranial direct current stimulation? A registered report. European Journal of Neuroscience. [paper] [OSF repository] [registration]
Turi, Z., Bjørkedal, E., Gunkel, L., Antal, A., Paulus, W., & Mittner, M.(2018). Evidence for Cognitive Placebo and Nocebo Effects in Healthy Individuals. Scientific Reports, 8, 17443. [paper] [OSF repository]
Hetland A., Vittersø J., Wie S.O.B., Kjelstrup E., Mittner M. & Dahl T.I.(2018) Skiing and Thinking About It: Moment-to-Moment and Retrospective Analysis of Emotions in an Extreme Sport. Frontiers in Psychology. 9:971. doi:10.3389/fpsyg.2018.00971
Boayue N. M., Csifcsák G., Puonti O., Thielscher, A., & Mittner, M. (2018) Head models of healthy and depressed adults for simulating the effects of non-invasive brain stimulation [version 1; referees: 1 approved]. F1000Research., 7:704 doi:10.12688/f1000research.15125.1, preprint: [link].
Turi, Z., Schäfer, S. A., Antal, A., Paulus, W. and Mittner, M. (2018). Data from Placebo Enhances Reward Learning in Healthy Individuals. Journal of Open Psychology Data. [paper] [repository]
Csifcsák, G., Boayue, N. M., Puonti, O., Thielscher, A., & Mittner, M. (2018). Effects of transcranial direct current stimulation for treating depression: A modeling study. Journal of Affective Disorders. 234, 164 – 173. doi:10.1016/j.jad.2018.02.077. [preprint]
Csifcsák, G. & Mittner, M. (2017). Linking brain networks and behavioral variability to different types of mind-wandering. Proceedings of the National Academy of Sciences. 114 (30). doi: 10.1073/pnas.1705108114 [link]
Turi, Z. #, Mittner, M. #, Paulus, W. and Antal, A. (2017). Placebo Intervention Enhances Reward Learning in Healthy Individuals. Scientific Reports. 7, 41028. [link] [code and data]
# shared first authorship
Hawkins, G., Mittner, M., Forstmann, B. & Heathcote, A. (2016). On the efficiency of neurally-informed cognitive models to identify latent cognitive states. Journal of Mathematical Psychology. [link] [code]
Mittner, M., Hawkins, G., Boekel, W. & Forstmann, B. (2016). A neural model of mind wandering. Trends in Cognitive Sciences. DOI:10.1016/j.tics.2016.06.004. [link]
Rodriguez-Aranda, C., Mittner, M. & Vasylenko, O. (2016). Association between Executive Functions, Working Memory, and Manual Dexterity in Young and Healthy Older Adults: An exploratory study. Perceptual & Motor Skills, 122 (1), 165-192. [link] [data]
Hawkins, G.E., Mittner, M., Boekel, W., Heathcote, A., and Forstmann, B.U.(2015). Towards a model-based cognitive neuroscience of mind wandering. Neuroscience, 310, 290-305. [link]
Høifødt R. S., Mittner M., Lillevoll K. R., Katla S. K., Kolstrup N., Eisemann M., Friborg O., Waterloo K. (2015). Predictors of response to Web-based cognitive behavioral therapy with face-toface therapist support for depression: A Bayesian analysis. Journal of Medical Internet Research, 17(9):e197. [link]
Mittner, M., Boekel, W., Tucker, A. M., Turner, B.M., Heathcote, A. and Forstmann, B.U.(2014). When the brain takes a break: A model-based analysis of mind wandering. Journal of Neuroscience, 34(49):16286-95. [link]
Turi, Z. [1], Mittner, M. [1], Opitz, A. [1], Popkes, M., Paulus, W., and Antal, A. (2014). Transcranial direct current stimulation over the left prefrontal cortex increases randomness of choice in instrumental learning.Cortex. 63: 145-154. [link]
[1]: these authors contributed equally
Mittner M., Behrendt J., Menge U., Titz C. M. and Hasselhorn M. (2014). Response-Retrieval in Identity Negative Priming is Modulated by Temporal Discriminability. Front. Psychol. 5:621. doi: 10.3389/fpsyg.2014.00621 [link]
Mittner, M. (2013). Functional Integration of Large-Scale Brain Networks. The Journal of Neuroscience, 33(48):18710-18711 [link]
Schrobsdorff H., Ihrke M., Behrendt J., Hasselhorn M., Herrmann J.M.(2012). Inhibition in the Dynamics of Selective Attention: An Integrative Model for Negative Priming. Frontiers in Psychology doi:10.3389/fpsyg.2012.00491 [link]
Ihrke M., Behrendt J., Schrobsdorff H., Visser I., Hasselhorn M. (2012). Negative Priming Persists in the Absence of Response-Retrieval. Experimental Psychology. 60 (1), pp. 12-21 [link]
Schrobsdorff H., Ihrke M., Behrendt J., Herrmann J. M., Hasselhorn M. (2012). Identity Negative Priming: A Phenomenon of Perception, Recognition or Selection? PLoS ONE 7 (3), doi:10.1371/journal.pone.0032946. [link]
Ihrke, M. & Behrendt, J. (2011). Automatic generation of randomized trial sequences for priming experiments.Frontiers in Psychology, 2 (255), doi:10.3389/fpsyg.2011.00225. [link] [home]
Ihrke, M. & Brennen, T. (2011). Sharing one biographical detail elicits priming between famous names: Empirical and computational approaches. Frontiers in Psychology, 2 (75), doi:10.3389/fpsyg.2011.00075. [link] [code]
Ihrke, M., Schrobsdorff, H. & Herrmann, J.M.(2011). Recurrence-Based Estimation of Time-Distortion Functions forERP Waveform Reconstruction. International Journal of Neural Systems, 21 (1), pp. 65-78. [link]
Ihrke, M., Behrendt, J., Schrobsdorff, H., Herrmann, J.M. & Hasselhorn, M. (2011). Response Retrieval and Negative Priming: Encoding and Retrieval Specific Effects. Experimental Psychology, 58 (2), pp. 154—161. [link]
Behrendt, J., Gibbons, H., Schrobsdorff, H., Ihrke, M., Herrmann, J.M. & Hasselhorn, M. (2010). Event-Related Brain Potential Correlates of Idendity Negative Priming From Overlapping Pictures. Psychophysiology, 47 (5), pp. 921—930. [link]
Ritschel, T., Ihrke, M., Frisvad, J.R., Coppens, J., Myszkowski, K. & Seidel, H.P.(2009). Temporal Glare: Real-Time Dynamic Simulation of the Scattering in the Human Eye. Computer Graphics Forum. 28 (2). pp. 183-192. [link] [home] [PDF]
Ritschel, T., Smith, K., Ihrke, M., Grosch, T., Myszkowski, K., & Seidel, H. P.(2008). 3D Unsharp Masking for Scene Coherent Enhancement. ACM Transactions on Graphics (Proceedings SIGGRAPH 2008). 27 (3). [link] [home] [PDF]
Schrobsdorff, H., Ihrke, M., Kabisch, B., Behrendt, J., Hasselhorn, M., Herrmann, J. M.(2007). A Computational Approach to Negative Priming. Connection Science, 19 (3), 203-221. [link] [PDF]
Book Chapters
Ihrke, M., Schrobsdorff, H. & Herrmann, J. M.(2009). Denoising and Averaging Techniques for Electrophysiological Data. In Wennberg, R. & Perez-Velazquez, J. L.(Eds.), Coordinated Activity in the Brain: measurements and relevance to brain function and behaviour. Springer. [link] [PDF]
Peer-Reviewed Conference Proceedings
Schrobsdorff H., Ihrke M., Herrmann J.M.(2012). Modeling Structure and Dynamics of Selective Attention. Advances in Intelligent Systems and Computing (Biologically Inspired Cognitive Architectures 2012), 196, pp. 287—295. [link]
Ihrke, M., Schrobsdorff, H. & Herrmann, J. M.(2009). Recurrence-Based Synchronization of Single Trials for EEG-Data Analysis. Lecture Notes in Computer Science 5788, Intelligent Data Engineering and Automated Learning -IDEAL 2009. pp. 118-125. [link]
Ihrke M., Ritschel, T. , Smith, K., Grosch, T., Myszkowski, K., & Seidel, H. P.(2009). A Perceptual Evaluation of 3D Unsharp Masking. Proceedings Human Vision and Electronic Imaging XIII. [link] [PDF]
Ihrke, M., Schrobsdorff, H. & Herrmann, J. M.(2008). Compensation for Speed-of-Processing Effects in EEG-Data Analysis. Lecture Notes in Computer Science (Proceedings IDEAL 2008). 5326, pp. 354-361. [link] [PDF]
Yoshida, A., Ihrke, M., Mantiuk, R. & Seidel, H. P.(2008). Brightness of the Glare-Illusion. Proceedings of ACMSymposium on Applied Perception in Graphics and Visualization. pp. 83-90. [link] [PDF]
Research interests
Matthias' research interests include:
- Methods and statistics in psychology in neuroscience
- Bayesian statistics
- computational modeling and machine-learning
- non-invasive brain stimulation
- neuroimaging and electrophysiology
- attentional fluctuations and mind wandering
- value-based learning and decision making
Personal website: http://ihrke.github.io
Google scholar profile: https://scholar.google.com/citations?user=AFB4RYIAAAAJ
Lab-website: https://uit.no/research/cognitive-neuroscience
Short CV (full CV here)
Since 2022
Vice dean for research, Institute of Psychology, UiT - The arctic university of Norway
Since 2021
Professor II, Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
Since 2020
Full Professor, Institute of Psychology, UiT - The arctic university of Norway
2014-2020
Associate Professor, Institute of Psychology, UiT - The arctic university of Norway
2013-2014
Post-doc, Cognitive Science Center Amsterdam, University of Amsterdam, The Netherlands
2012-2013
Post-doc, Max-Planck Institute for Experimental Medicine, Göttingen, Germany
2008-2012
PhD, Max-Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
2005-2008
Diploma in Psychology (Göttingen)
BSc in Computer Science (Göttingen)
Member of research group
Member of project
Developing non-invasive brain stimulation methods for clinical and cognitive neuroscience
Modulating mind-wandering using non-invasive brain stimulation
The neural basis of off-task cognition
Understanding the neural basis of reinforcement learning