Publications

Scharnowski F. Personode: A Toolbox for ICA Map Classification and Individualized ROI Definition. Neuroinformatics. 2020 Jun;18(3):339-349. doi: 10.1007/s12021-019-09449-4

Scharnowski F. Network-based fMRI-neurofeedback training of sustained attention. NeuroImage. 2020;221:117194. doi: 10.1016/j.neuroimage.2020.117194

Skouras S, Scharnowski F. The effects of psychiatric history and age on self-regulation of the default mode network. NeuroImage. 2019 Sep;198:150-159. 31103786. doi: 10.1016/j.neuroimage.2019.05.008

Kopel R, Sladky R, Laub P, Koush Y, Robineau F, Hutton C et al. No time for drifting: Comparing performance and applicability of signal detrending algorithms for real-time fMRI. NeuroImage. 2019 Mai 1;191: 421-429. doi: 10.1016/j.neuroimage.2019.02.058

Robineau F, Saj A, Neveu R, Van De Ville D, Scharnowski F, Vuilleumier P. Using real-time fMRI neurofeedback to restore right occipital cortex activity in patients with left visuo-spatial neglect: proof-of-principle and preliminary results. Neuropsychological Rehabilitation. 2019 Apr 6;29(3):339-360. doi: 10.1080/09602011.2017.1301262

Koush Y, Pichon S, Eickhoff SB, Van De Ville D, Vuilleumier P, Scharnowski F. Brain networks for engaging oneself in positive-social emotion regulation. NeuroImage. 2019 Apr 1;189:106-115. doi: 10.1016/j.neuroimage.2018.12.049

Ekanayke J, Ridgeway G, Winston JS, Feredoes E, Razi A, Koush Y et al. Volitional modulation of higher-order visual cortex alters human perception. NeuroImage. 2019 Mär;188:291-301. doi: 10.1016/j.neuroimage.2018.11.054

Sorger B, Scharnowski F, Linden DEJ, Hampson M, Young KD. Control Freaks: Towards Optimal Selection of Control Conditions for Neurofeedback Studies. NeuroImage. 2019 Feb 1;186:256-265. doi: 10.1016/j.neuroimage.2018.11.004

Steyrl D, Müller-Putz GR. Artifacts in EEG of simultaneous EEG-fMRI: pulse artifact remainders in the gradient artifact template are a source of artifact residuals after average artifact subtraction. Journal of Neural Engineering. 2019 Feb;16(1):016011. doi: 10.1088/1741-2552/aaec42

Koush Y, Masala N, Scharnowski F, Van De Ville D. Data-driven tensor independent component analysis for model-based connectivity neurofeedback. NeuroImage. 2019 Jan 1;184:214-226. doi: 10.1016/j.neuroimage.2018.08.067

Doerig A, Scharnowski F, Herzog M. Building perception block by block: a response to Fekete et al. Neuroscience of Consciousness. 2019;2019(1):niy012. doi: 10.1093/nc/niy012

Steyrl D. Improving the quality of the electroencephalogram simultaneously recorded with functional magnetic resonance imaging. 2018.

Kirschner M, Sladky R, Haugg A, Stämpfli P, Jehli E, Hodel M et al. Self-regulation of the Dopaminergic Reward Circuit in Cocaine Users with Mental Imagery and Neurofeedback. EBioMedicine. 2018 Nov;37:489-498. doi: 10.1016/j.ebiom.2018.10.052

Schulz L, Ischebeck A, Wriessnegger SC, Steyrl D, Müller-Putz GR. Action affordances and visuo-spatial complexity in motor imagery: An fMRI study. Brain and Cognition. 2018 Jul;124:37-46. doi: 10.1016/j.bandc.2018.03.012

Scharnowski F, Ekanayake J, Hutton C, Ridgway G, Weiskopf N, Rees G. Real-time decoding of covert attention in higher-order visual areas. NeuroImage. 2018 Apr 1;169:462-472. doi: 10.1016/j.neuroimage.2017.12.019

Steyrl D, Krausz G, Koschutnig K, Edlinger G, Müller-Putz GR. Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF). Brain Topography: journal of functional neurophysiology. 2018 Jan;31(1):129–149. Epub 2017 Nov 9. doi: 10.1007/s10548-017-0606-7

Statthaler K, Schwarz A, Steyrl D, Kobler R, Höller MK, Brandstetter J et al. Cybathlon experiences of the Graz BCI racing team Mirage91 in the brain-computer interface discipline. Journal of NeuroEngineering and Rehabilitation . 2017 Dez;14(1):129. doi: 10.1186/s12984-017-0344-9

Koush Y, Ashburner J, Prilepin E, Sladky R, Zeidman P, Bibikov S et al. Real-time fMRI data for testing OpenNFT functionality. Data in Brief. 2017 Okt;14:344-347. doi: 10.1016/j.dib.2017.07.049

Koush Y, Ashburner J, Prilepin E, Sladky R, Zeidman P, Bibikov S et al. OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis. NeuroImage. 2017 Aug;156:489-503. doi: 10.1016/j.neuroimage.2017.06.039

Scharnowski F, Robineau F, Meskaldji DE, Koush Y, Rieger SW, Mermoud C et al. Maintenance of Voluntary Self-regulation Learned through Real-Time fMRI Neurofeedback. Frontiers in Human Neuroscience. 2017 Mär 23;11:131. doi: 10.3389/fnhum.2017.00131

Steyrl D, Krausz G, Koschutnig K, Edlinger G, Müller-Putz GR. Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI. Journal of Neural Engineering. 2017 Feb 3;14(2):026003. doi: 10.1088/1741-2552/14/2/026003

Scharnowski F, Sitaram R, Ros T, Stoeckel L, Haller S, Lewis-Peacock J et al. Closed-loop brain training: the science of neurofeedback. Nature reviews. Neuroscience. 2017 Feb;18(2):86-100. doi: 10.1038/nrn.2016.164

Scharnowski F, Koush Y, Meskaldji DE, Pichon S, Rey G, Rieger SW et al. Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback. Cerebral Cortex. 2017 Feb;27(2):1193-1202. doi: 10.1093/cercor/bhv311

Schwarz A, Steyrl D, Müller-Putz G. Brain-Computer Interface adaptation for an end user to compete in the Cybathlon. in 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. 2017. S. 1803-1808 doi: 10.1109/SMC.2016.7844499

Scharnowski F, Kopel R, Emmert K, Haller S, Van De Ville D. Distributed Patterns of Brain Activity Underlying Real-Time fMRI Neurofeedback Training. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. 2017;64(6):1228-1237. doi: 10.1109/tbme.2016.2598818

Müller-Putz G, Steyrl D, (ed.), Wriessnegger SC, (ed.), Scherer R, (ed.). Proceedings of the 7th Graz Brain-Computer Interface Conference 2017: From Vision to Reality. Graz: Verlag der Technischen Universität Graz, 2017. doi: 10.3217/978-3-85125-533-1

Wriessnegger SC, Steyrl D, Koschutnig K, Müller-Putz GR. Cooperation in mind: Motor imagery of joint and single actions is represented in different brain areas. Brain and Cognition. 2016 Nov;109:19-25. doi: 10.1016/j.bandc.2016.08.008

Schwarz A, Steyrl D, Höller MK, Statthaler K, Müller-Putz G. BCI adaption for end user: The GRAZ-BCI approach. in Cybathlon Symposium Booklet, ETH. 2016

Höller MK, Schwarz A, Steyrl D, Statthaler K, Müller-Putz G. First contact screening of a BCI Pilot. in Cybathlon Symposium Booklet, ETH. 2016 doi: 10.13140/RG.2.2.23819.72482

Statthaler K, Steyrl D, Schwarz A, Höller MK, Müller-Putz G. Optimized individual mental tasks to control BCIs. in Cybathlon Symposium Booklet, ETH. Kloten: ETH Zurich. 2016. S. 23-23

Steyrl D, Schwarz A, Müller-Putz G. The MIRAGE91 Brain–Computer Interface. in Cybathlon Symposium Booklet, ETH. Kloten: ETH Zurich. 2016. S. 77-77

Steyrl D, Kobler R, Müller-Putz G. On similarities and differences of invasive and non-invasive electrical brain signals in brain-computer interfacing. Journal of Biomedical Science and Engineering. 2016 Jun 30;9(8):393-398. doi: 10.4236/jbise.2016.98034

Müller-Putz G, Schwarz A, Steyrl D. Mirage91: The Graz BCI-Racing Team – making students familiar with BCI research. in Proceedings of the 6th International Brain-Computer Interface Meeting, Asilomar Conference Center, Pacific Grove, California, USA. 2016 doi: 10.3217/978-3-85125-467-9-63

Scharnowski F, Herzog MH, Kammer T. Time Slices: What Is the Duration of a Percept? PLoS Biology. 2016 Apr 12;14(4):e1002433. doi: 10.1371/journal.pbio.1002433

Steyrl D, Scherer R, Faller J, Müller-Putz GR. Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier. Biomedical Engineering / Biomedizinische Technik. 2016 Feb 1;61(1):77-86. doi: 10.1515/bmt-2014-0117

Schwarz A, Steyrl D, Höller MK, Statthaler K, Müller-Putz GR. BCI adaptation for end users The Graz-BCI approach. 2016. doi: 10.13140/RG.2.2.17108.83846

Steyrl D. Improving the vividness of motor imagery tasks for future application in Brain-Computer Interfaces. 2016. doi: 10.13140/RG.2.2.13753.39528

Schwarz A, Scherer R, Steyrl D, Faller J. Mirage91: The Graz BCI-Racing Team - making students familiar with BCI research. 2016. doi: 10.13140/RG.2.2.25497.44641

Müller-Putz G, (ed.), Huggins J, (ed.), Steyrl D, (ed.). Proceedings of the 6th International Brain-Computer Interface Meeting: BCI Past, Present, and Future. Graz: Verlag der Technischen Universität Graz, 2016. 261 S. doi: 10.3217/978-3-85125-467-9

Steyrl D, Schwarz A, Müller-Putz GR. The MIRAGE91 Brain-Computer Interface. 2016. doi: 10.13140/RG.2.2.30530.61125

Scharnowski F, Weiskopf N. Cognitive enhancement through real-time fMRI neurofeedback. Current Opinion in Behavioral Sciences. 2015 Aug 1;4:122-127. doi: 10.1016/j.cobeha.2015.05.001

Schwarz A, Scherer R, Steyrl D, Faller J, Muller-Putz GR. A co-adaptive sensory motor rhythms Brain-Computer Interface based on common spatial patterns and Random Forest. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. IEEE. 2015. S. 1049-1052 doi: 10.1109/embc.2015.7318545

Scherer R, Faller J, Opisso E, Costa U, Steyrl D, Muller-Putz GR. Bring mental activity into action! An enhanced online co-adaptive brain-computer interface training protocol. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. IEEE. 2015. S. 2323-2326 doi: 10.1109/embc.2015.7318858

Steyrl D, Patz F, Krausz G, Edlinger G, Muller-Putz GR. Reduction of EEG artifacts in simultaneous EEG-fMRI: Reference layer adaptive filtering (RLAF). in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. IEEE. 2015. S. 3803-3806 doi: 10.1109/embc.2015.7319222

Schwarz A, Scherer R, Steyrl D, Faller J, Müller-Putz GR. A Co-adaptive SMR-BCI Based on Common Spatial Patterns and Random Forest. 2015. doi: 10.13140/RG.2.2.27175.16809

Scharnowski F, Veit R, Zopf R, Studer P, Bock S, Diedrichsen J et al. Manipulating motor performance and memory through real-time fMRI neurofeedback. Biological Psychology. 2015;108:85-97. doi: 10.1016/j.biopsycho.2015.03.009

Robineau F, Rieger SW, Mermoud C, Pichon S, Koush Y, Van De Ville D et al. Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training. NeuroImage. 2014 Okt 15;100:1-14. doi: 10.1016/j.neuroimage.2014.05.072

Muller-Putz GR, Steyrl D, Faller J. Adaptive hybrid brain-computer interaction: Ask a trainer for assistance! in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Chicago: IEEE. 2014. S. 1493-1496 doi: 10.1109/embc.2014.6943884

Bauernfeind G, Steyrl D, Brunner C, Muller-Putz GR. Single trial classification of fNIRS-based brain-computer interface mental arithmetic data: A comparison between different classifiers. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Chicago: IEEE. 2014. S. 2004-2007 doi: 10.1109/embc.2014.6944008

Wriessnegger SC, Steyrl D, Koschutnig K, Müller-Putz GR. Short time sports exercise boosts motor imagery patterns: implications of mental practice in rehabilitation programs. Frontiers in Human Neuroscience. 2014 Jun 30;8:469. doi: 10.3389/fnhum.2014.00469