Publications

The names of lab members are in bold.

Szczepanik, M., Wagner, A.S., Heunis, S., Waite, L. K., Eickhoff, S. B. & Hanke, M. (2024). Teaching research data management with DataLad: a multi-year, multi-domain effort. preprint, submitted to Neuroinformatics.

Moia, S., ..., Heunis, S., ..., Hanke, M., ..., Mönch, C., ..., Muller-Rodriguez, L., ..., Poldrack, P., ..., Szczepanik, M., ..., Wagner, A.S., Waite, L.K., Waite, A.Q., with 75 additional coauthors (2024) Proceedings of the OHBM Brainhack 2022. Aperture Neuro, 4.

Wagner, A.S. & Hanke, M. (2023) Datalad — An Introduction to Research Data Management. ISBN 979-8857037973

Zhao, C., Jarecka, D., Covitz, S., Chen, Y., Eickhoff, S. B., Fair, D. A., Franco, A. R., Halchenko, Y. O., Hendrickson, T. J., Hoffstaedter, F., Houghton, A., Kiar, G., Macdonald, A., Mehta, K., Milham, M. P., Salo, T., Hanke, M., Ghosh, S. S., Cieslak, M. & Satterthwaite T. D. (2024). A reproducible and generalizable software workflow for analysis of large-scale neuroimaging data collections using BIDS Apps. Imaging Neuroscience.

Kalantari, A., Szczepanik, M., Heunis, S., Mönch, C., Hanke, M., Wachtler, T. & Aswendt, M. (2023) How to establish and maintain a multimodal animal research dataset using DataLad. Scientific Data, 10, 357.

Klingner, C. M., Denker, M., Grün, S., Hanke, M., Oeltze-Jafra, S., Ohl, F. W., Radny, J., Rotter, S., Scherberger, H., Stein, A., Wachtler, T., Witte, O. W. & Ritter, P. (2023). Research Data Management and Data Sharing for Reproducible Research—Results of a Community Survey of the German National Research Data Infrastructure Initiative Neuroscience. eNeuro, 10.

Kaźmierowska, A. M., Szczepanik, M., Wypych, M., Droździel, D., Marchewka, A., Michałowski, J. M., Olsson, A., Knapska, E. (2022). Learning about threat from friends and strangers is equally effective: An fMRI study on observational fear conditioning. NeuroImage, 263, 119648.

Wu, J., Li, J., Eickhoff, S. B., Hoffstaedter, F., Hanke, M., Yeo, B. T. T. & Genon, S. (2022). Cross-cohort replicability and generalizability of connectivity-based psychometric prediction patterns. NeuroImage, 262:119569.

Häusler, C. O., Eickhoff, S. B. & Hanke, M. (2022). Processing of visual and non-visual naturalistic spatial information in the "parahippocampal place area". Scientific Data, 9, 147.

Wagner, A. S., Waite, L. K., Wierzba, M., Hoffstaedter, F. Waite, A. Q., Poldrack, B., Eickhoff, S. B. & Hanke, M. (2022) FAIRly big: A framework for computationally reproducible processing of large-scale data. Scientific Data, 9, 80.

Heunis, S., Breeuwer, M., Caballero-Gaudes, C., Hellrung, L., Huijbers, W., Jansen, J., Lamerichs, R., Zinger, S. & Aldenkamp, A. (2021). The effects of multi-echo fMRI combination and rapid T2*-mapping on offline and real-time BOLD sensitivity. NeuroImage, 238, 118244. [preprint]

Levitis, E., Gould van Praag, C.D., Gau, R., Heunis, S., [...] Wagner, A. S. S., [...] Camille Maumet. (2021) Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective. GigaScience, 10(8), giab051.

Halchenko, Y. O., Meyer, K., Poldrack, B., Solanky, D. S., Wagner, A. S., Gors, J., MacFarlane, D., Pustina, D., Sochat, V., Ghosh, S. S., Mönch, C., Markiewicz, C. J., Waite, L., Shlyakhter, I., de la Vega, A., , Hayashi, S., Häusler, C. O., Poline, J.-B., Kadelka, T., Skytén, K., Jarecka, D., Kennedy, D., Strauss, T., Cieslak, M., Vavra, P., Ioanas, H.-I., Schneider, R., Pflüger, M., Haxby, J. V., Eickhoff, S. B. & Hanke, M. (2021). DataLad: distributed system for joint management of code, data, and their relationship. Journal of Open Source Software, 6(63), 3262.

Wachtler, T., Bauer, P., Denker, M., Grün, S., Hanke, M., Klein, J., Oeltze-Jafra, S., Ritter, P., Rotter, S., Scherberger, H., Stein, A. & Witte, O.W. (2021). NFDI-Neuro: Building a community for neuroscience research data management in Germany. Neuroforum, 27(1).

Hanke, M., Pestilli, F., Wagner, A. S., Markiewicz, C. J., Poline, J.-B., Halchenko, Y. O. (2021). In defense of decentralized research data management. Neuroforum, 27(1).

Häusler, C. O. & Hanke, M.. (2021) A studyforrest extension, an annotation of spoken language in the German dubbed movie “Forrest Gump” and its audio-description. F1000Research, 10:54.

Boos, M., Guntupalli, J. S., Rieger, J. W., Hanke, M. (2020). The role of auxiliary parameters in evaluating voxel-wise encoding models for 3T and 7T BOLD fMRI data. bioRxiv.

Dar, A. H., Wagner, A. S. & Hanke, M. (2020). REMoDNaV: Robust Eye-Movement Classification for Dynamic Stimulation. Behavior Research Methods, 53, 399–414. (first two authors contributed equally)

Porcu, E., Benz, K. M., Ball, F., Tempelmann, C., Hanke, M. & Noesselt, T. (2020). Macroscopic information-based taste representations in insular cortex are shaped by stimulus concentration. Proceedings of the National Academy of Sciences, 117, 7409-7417.

Wang, L., Baumgartner, F., Kaule, F. R., Hanke, M. & Pollmann, S. (2019). Individual face and house-related eye movement patterns distinctively activate FFA and PPA in the absence of faces and houses.. Nature Communications, 10, 5532.

DuPre, E., Hanke, M. & Poline, J.-B. (2019). Nature abhors a paywall: How open science can realize the potential of naturalistic stimuli. NeuroImage, 216, 116330. [preprint]

Wagner, A. S., Halchenko, Y. O. & Hanke, M. (2019). multimatch_gaze: The MultiMatch algorithm for gaze comparison in Python. The Journal of Open Source Software, 4(40), 1525.

Yarkoni, T., Markiewicz, C. J., de la Vega, A., Gorgolewski, K. J., Salo, T., Halchenko, Y. O., McNamara, Q., DeStasio, K., Poline, J.-B., Petrov, D., Hayot-Sasson, V., Nielson, D. M., Carlin, J., Kiar, G., Whitaker, K., DuPre, E., Wagner, A. S., Tirrell, L. S., Jas, M., Hanke, M., Poldrack, R. A., Esteban, O., Appelhoff, S., Holdgraf, C., Staden, I., Thirion, B., Kleinschmidt, D. F., Lee, J. A., Visconti di Oleggio Castello, M., Notter, M. P & Blair, R. (2019). PyBIDS: Python tools for BIDS datasets. The Journal of Open Source Software, 4(40), 1294.

Hanke, M., Mathôt, S., Ort, E., Peitek, N., Stadler, S. & Wagner, A. S. (2019). A practical guide to functional magnetic resonance imaging with simultaneous eye tracking for cognitive neuroimaging research. In Pollmann, S. (Ed.) Spatial learning and attention guidance. Springer.

Abram, S., Hanke, M., Redish, A. D. & MacDonald, A. W. (2019). Neural signatures underlying deliberation in human foraging decisions. Cognitive, Affective, and Behavioral Neuroscience, 19, 1492–1508.

Kennedy, D. N., Abraham, S. A., Bates, J. F., Crowley, A., Ghosh, S., Gillespie, T., Goncalves, M., Grethe, J. S., Halchenko, Y. O., Hanke, M., Haselgrove, C., Hodge, S. M., Jarecka, D., Kaczmarzyk, J., Keator, D. B., Meyer, K., Martone, M. E., Padhy, S., Poline, J.-B., Preuss, N., Sincomb, T. & Travers, M. (2019). Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging. Frontiers in Neuroinformatics, 13:1.

Reeder, R. R., Olivers, C. N. L., Hanke, M. & Pollmann, S. (2018). No evidence for enhanced distractor template representation in early visual cortex. Cortex, 108:279-282.

Sengupta, A., Speck, O., Yakupov, R., Kanowski, M., Tempelmann, C., Pollmann, S. & Hanke, M. (2018) The effect of acquisition resolution on orientation decoding from V1: comparison of 3T and 7T. bioRxiv.

Sengupta, A., Pollmann, S. & Hanke, M. (2018). Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI. F1000Research, 7.

Notter, M., Hanke, M., Murray, M. & Geiser, E. (2018) Encoding of auditory temporal Gestalt in the human brain. Cerebral Cortex, 2, 475-484.

Derrfuss, J., Ekman, M., Hanke, M., Tittgemeyer, M. & Fiebach, C. (2017). Distractor-resistant short-term memory is supported by transient changes in neural stimulus representations. Journal of Cognitive Neuroscience, 29, 1547-1565.

Reeder, R. R., Hanke, M. & Pollmann, S. (2017). Task relevance modulates the representation of features and feature dimensions in the target template. Scientific Reports, 7, 4514.

Eglen, S., Marwick, B., Halchenko, Y. O, Hanke, M, Sufi, S., Gleeson, P., Silver. R. A., Davison, A., Lanyon, L., Abrams, M., Wachtler, T., Willshaw, D. J., Pouzat, C. & Poline, J. B. (2017). Towards standard practices for sharing computer code and programs in neuroscience. Nature Neuroscience, 20, 770-773.

Nichols, T. E., Das, S., Eickhoff, S. B., Evans, A. C., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M. P., Poldrack, R. A., Poline, J.-B., Proal, E., Thirion, B., Van Essen, D. C., White, T. & Yeo, B. T. T. (2017). Standards for Best Practices in Data Analysis and Sharing in Neuroimaging using MRI. Nature Neuroscience, 20, 299-303.

Nichols, T. E., Das, S., Eickhoff, S. B., Evans, A. C., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M. P., Poldrack, R. A., Poline, J.-B., Proal, E., Thirion, B., Van Essen, D. C., White, T., Yeo, B. T. T. (2016). Best Practices in Data Analysis and Sharing in Neuroimaging using MRI. Report of the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS). [bioRxiv doi:10.1101/054262]

Sengupta, A., Yakupov, R., Speck, O., Pollmann, S. & Hanke, M. (2017) The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7 Tesla. NeuroImage, 148, 64-76. [Description of associated dataset available in: Sengupta, A., Yakupov, R., Speck, O., Pollmann, S. & Hanke, M. (2017) Ultra high-field multi-resolution fMRI data for orientation decoding in visual cortex. Data in Brief, 13, 219-222.]

Hanke, M. & Ibe, P. (2016) Lies, irony, and contradiction — an annotation of semantic conflict in the movie "Forrest Gump". F1000Research, 5:2375.

Hanke, M., Adelhöfer, N., Kottke, D., Iacovella, V., Sengupta, A., Kaule, F. R., Nigbur, R., Waite, A. Q., Baumgartner, F. J. & Stadler, J. (2016). A studyforrest extension, simultaneous fMRI and eye gaze recordings during prolonged natural stimulation. Scientific Data, 3:160092.

Häusler, C. O. & Hanke, M.. (2016) An annotation of cuts, depicted locations, and temporal progression in the motion picture "Forrest Gump". F1000Research, 5:2273.

Güçlü, U., Thielen, J., Hanke, M., van Gerven, M. A. J. (2016). Brains on Beats. In Advances in Neural Information Processing Systems (NIPS), 29, 2101-2109. [ArXiv].

Sengupta, A., Kaule, F. R., Guntupalli, J. S., Hoffmann, M. B., Häusler, C., Stadler, J. & Hanke, M. (2016). A studyforrest extension, retinotopic mapping and localization of higher visual areas. Scientific Data, 3:160093.

Gorgolewski, K. J., Auer, T., Calhoun, V. D., Craddock, R. C., Duff, E. P., Flandin, G., Ghosh, S. S., Halchenko, Y. O., Handwerker, D. A., Hanke, M., Keator, D., Li, X., Maumet, M., Michael, Z., Nichols, N. N., Nichols, T. E., Poline, J. B., Rokem, A., Schaefer, G., Sochat, V., Turner, J. A., Varoquaux, G. & Poldrack, R. A. (2016). The Brain Imaging Data Structure: a protocol for standardizing and describing outputs of neuroimaging experiments. Scientific Data, 3:160044.

Guntupalli, J. S., Hanke, M., Halchenko, Y. O., Connolly, A. C., Ramadge, P. J. & Haxby, J. V. (2016). A Model of Representational Spaces in Human Cortex. Cerebral Cortex, 26, 2919-2934.

Hanke, M. & Halchenko, Y. O. (2015). A communication hub for a decentralized collaboration on studying real-life cognition. F1000Research, 4:62.

Halchenko, Y. O. & Hanke, M. (2015). Four aspects to make science open "by design" and not as an after-thought. GigaScience, 4:31.

Hanke, M., Dinga, R., Häusler, C., Guntupalli, J. S., Casey, M., Kaule, F. R. & Stadler, S. (2015). High-resolution 7-Tesla fMRI data on the perception of musical genres – an extension to the studyforrest dataset. F1000Research, 4:174.

Labs, A., Reich, T., Schulenburg, H., Boennen, M., Gehrke, M., Golz, M., Hartings, B., Hoffmann, N., Keil, S., Perlow, M., Peukmann, A. K., Rabe, L. N., von Sobbe, F.-R. & Hanke, M. (2015). Portrayed emotions in the movie "Forrest Gump". F1000Research, 4:92.

Pollmann, S., Zinke, W., Baumgartner, F., Geringswald, F. & Hanke, M. (2014). The right temporo-parietal junction contributes to visual feature binding. NeuroImage, 101, 289-297.

Hanke, M., Baumgartner, F. J., Ibe, P., Kaule, F. R., Pollmann, S., Speck, O., Zinke, W. & Stadler, J. (2014). A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Scientific Data, 1:140003.

Halchenko, Y.O., Hanke, M., Haxby, J.V., Hanson, S.J. & Herrmann, C.S. (2013). Transmodal Analysis of Neural Signals. arXiv:1307.215.

Kohler, P. J., Fogelson, S. V., Reavis, E. A., Meng, M., Guntupalli, J. S., Hanke, M., Halchenko, Y. O., Connolly, A. C., Haxby, J. V. & Tse, P. U. (2013). Pattern classification precedes region-average hemodynamic response in early visual cortex. NeuroImage, 78, 249-260.

Baumgartner, F., Hanke, M., Geringswald, F., Zinke, W., Speck, O. & Pollmann, S. (2013). Evidence for feature binding in the superior parietal lobule. NeuroImage, 68, 173-180.

Halchenko, Y. O. & Hanke, M. (2012). Open is not enough. Let’s take the next step: An integrated, community-driven computing platform for neuroscience. Frontiers in Neuroinformatics, 6:22.

Poline, J.-B., Breeze, J. L., Ghosh, S. S., Gorgolewski, K. F., Halchenko, Y. O., Hanke, M., Haselgrove, C., Helmer, K. G., Keator, D. B., Marcus, D. S., Poldrack, R. A., Schwartz, Y., Ashburner, J. and Kennedy, D. N. (2012). Data sharing in neuroimaging research. Frontiers in Neuroinformatics, 6:9.

Connolly, A. J., Guntupalli, J. S., Gors, J., Hanke, M., Halchenko, Y. O., Wu, Y. C., Abdi, H. & Haxby, J. V. (2012). Representation of Biological Classes in the Human Brain. Journal of Neuroscience, 32, 2608-2618.

Haxby, J. V., Guntupalli, J. S., Connolly, A. C., Halchenko, Y. O., Conroy, B. R., Gobbini, M. I., Hanke, M. & Ramadge, P. J. (2011). A common, high-dimensional model of the representational space in human ventral temporal cortex. Neuron, 72, 404-416.

Hanke, M. & Halchenko, Y. O. (2011). Neuroscience runs on GNU/Linux. Frontiers in Neuroinformatics, 5:8.

Lee, Y. S., Janata, P., Frost, C., Hanke, M. & Granger, R. (2011). Investigation of melodic contour processing in the brain using multivariate pattern-based fMRI. NeuroImage, 57, 293--300.

Tille, A., Möller, S., Hanke, M & Halchenko, Y. O. (2011). Debian Med: Integrated software environment for all medical purposes based on Debian GNU/Linux. In Jordanova, M. & Lievens, F. (Eds.), Global Telemedicine and eHealth Updates: Knowledge Resources, Vol. 4. Luxembourg: ISfTeH.

Hanke, M., Halchenko, Y. O., Haxby, J. V., & Pollmann, S. (2010). Statistical learning analysis in neuroscience: aiming for transparency. Frontiers in Neuroscience, 4, 38--43.

Halchenko, Y. O. & Hanke, M. (2010). Advancing Neuroimaging Research with Predictive Multivariate Pattern Analysis (MVPA). The Neuromorphic Engineer.

Hanke, M. (2009). Advancing the understanding of brain function with multivariate pattern analysis (Doctoral dissertation), Otto-von-Guericke University Magdeburg, Magdeburg, Germany.

Hanke, M., Halchenko, Y. O., Sederberg, P. B., Olivetti, E., Fründ, I., Rieger, J. W., Herrmann, C. S., Haxby, J. V., Hanson, S. J. and Pollmann, S. (2009). PyMVPA: a unifying approach to the analysis of neuroscientific data. Frontiers in Neuroinformatics, 3:3.

Hanke, M., Halchenko, Y. O., Sederberg, P. B., Hanson, S. J., Haxby, J. V. & Pollmann, S. (2009). PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data. Neuroinformatics, 7, 37--53. [view]

Maertens, M., Pollmann, S., Hanke, M., Mildner, T. & Möller, H.E. (2008). Retinotopic activation in response to subjective contours in primary visual cortex. Frontiers in Human Neuroscience, 2:2.

Lukas, J., & Hanke, M. (2004). Wie die Bilder laufen lernten: Kognitive Prozesse bei der Bewegungswahrnehmung. Scientia halensis, 4, 21--22.