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Head: Prof. Nagy Zoltán, DSc, emeritus professor


  • Prof. Kozmann György†, DSc, emeritus professor
  • Dr. Juhász Zoltán, associate professor
  • Körmendi János PhD student

Our research focuses on the measurement and understanding of bioelectrical activity of the brain. Using high-density EEG technology (128 channels), we investigate how we can detect and register electrical changes generated by resting-state or task-related activities, what methods are needed to process these signals the most optimal way, and what information we can extract from these signals. High sampling rate EEG (above 1 kHz) can provide information on the dynamic changes in the brain at sub-millisecond temporal resolution, which is not possible with other brain imaging technologies (fMRI, PET, NIRS). We developed a new method, based on the sLORETA source imaging method, for extracting key features of brain activity. This method, called Single Channel Activity Laplacian Map (SICAL), can be used to investigate normal and disturbed motor activity. We have also developed new method for the removal of heart and ocular artifacts that are the major sources of signal distortions. Our method removes artefact more efficiently and with less signal distortion that other methods reported in the literature. Another line of research investigates the oscillatory behaviour of our brain. By investigating phase characteristics, we can describe changes in finger tapping execution of stroke patients and show that progress in rehabilitation is correlated with the normalisation of low-frequency phase disturbances. We are also interested in the fundamental questions of bioelectrical imaging, including forward and inverse problem calculations, characterising activity sources and current dipoles. Our research in brain connectivity led to the development of a new method for calculating high temporal resolution dynamic connectivity graphs, which allows us to describe changes in and evolution of task execution via at millisecond steps. We are also interested in the computing aspects of EEG processing, performing research in the development very fast and efficient processing methods. This requires the development of new, highly parallel GPU implementations that can use several thousands of processing cores efficiently. We collaborate with the following partners in our research: National Institute of Clinical Neurosciences, the Faculty of Modern Philology and Social Sciences at the University of Pannonia, and the University College Dublin.

Key results

  • New method for effective removal of heart and ocular EEG artifacts
  • SICAL EEG-based functional imaging method,
  • Optimised feature extraction algorithms
  • Analysis of dipole direction effects and signal-to-noise ratio in realistic head models
  • First analysis of age-dependent activity patterns during finger tapping task execution
  • New method for identifying handedness
  • Characterisation of post-stroke motor activity organisation
  • Estimation of source localisation errors in spherical and realistic head models
  • Interactive software of detecting epileptic zones using scalp and intracranial electrodes
  • Highly parallel GPU algorithms for EEG signal processing tasks.

Selected publications

  • Issa M.F., Kozmann G., Juhasz Z. (2021) Increasing the Temporal Resolution of Dynamic Functional Connectivity with Ensemble Empirical Mode Decomposition. In: Jarm T., Cvetkoska A., Mahnič-Kalamiza S., Miklavcic D. (eds) 8th European Medical and Biological Engineering Conference. EMBEC 2020. IFMBE Proceedings, vol 80. Springer, Cham.
  • Juhasz, Zoltan. "Quantitative cost comparison of on-premise and cloud infrastructure based EEG data processing." Cluster Computing (2020): 1-17, doi: 10.1007/s10586-020-03141-y. (IF: 3.458)
  • Issa, M.F.; Juhasz, Z. Improved EOG Artifact Removal Using Wavelet Enhanced Independent Component Analysis. Brain Sci. 2019, 9, 355. (IF: 3.332).
  • Mohamed F. Issa, Gergely Tuboly, György Kozmann, Zoltan Juhasz, Automatic ECG artefact removal from EEG signals – Measurement Science Review, 19, (2019), No. 3, 101-108 (IF: 0.985)
  • M.F. Issa, Z. Juhasz, Gy. Kozmann, Automatic Removal of EOG artefacts from EEG based on Independent Component Analysis, Pannonian Conference on Advances in Information Technology (PCIT 2019), 31 May – 1 June, Veszprem, Hungary.
  • Mohamed F. Issa, Gyorgy Kozmann, Zoltan Nagy, Zoltan Juhasz, Functional Connectivity Biomarkers based on Resting-state EEG for Stroke Recovery, Measurement 2019, 12th International Conference on Measurement, May 27-29, Smolenice, Slovakia.
  • G. Benko and Z. Juhasz, GPU implementation of the FastICA algorithm, MIPRO 2019, 42th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, May 20-24, 2019.
  • Z. Juhasz and M.F. Issa, EEG based imaging of stroke location, extent and progress of recovery using a GPU architecture, MIPRO 2019, 42th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, May 20-24, 2019.
  • Zoltán Juhász, Mohammed F. Issa, János Körmendi, Ádám Gyulai, Zoltán Nagy, Quantitative EEG in stroke rehabilitation, 6th Neuroimaging Workshop, 19-20 Oct 2018, Pecs, Hungary.
  • Juhász Zoltán, Katona Melinda, Bodnár Péter, Tóth Eszter, Bozsik Bence, Bencsik Krisztina, Nyúl László, Vécsei László, Kincses Zsigmond Tamás, Az orvosi képalkotás klasszikus és új informatikai megoldásai, IME: INTERDISZCIPLINÁRIS MAGYAR EGÉSZSÉGÜGY / INFORMATIKA ÉS MENEDZSMENT AZ EGÉSZSÉGÜGYBEN, XVII : 9 pp. 56-61, (2018)
  • Mohamed F. Issa, Zoltan Juhasz and Gyorgy Kozmann, EEG analysis methods in neurolinguistics: a short review, IME: INTERDISZCIPLINÁRIS MAGYAR EGÉSZSÉGÜGY / INFORMATIKA ÉS MENEDZSMENT AZ EGÉSZSÉGÜGYBEN XVII : 2 pp. 48-54, (2018)
  • Z. Juhasz, "Highly parallel online bioelectrical signal processing on GPU architecture," MIPRO 2017, 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, 2017, pp. 340-346. doi: 10.23919/MIPRO.2017.7973446
  • Z Juhasz, G Kozmann, “A GPU-based Soft Real-Time System for Simultaneous EEG Processing and Visualization”, Scalable Computing: Practice and Experience 17 (2), 61-78.
  • 21. Z Juhasz, I Vassanyi, A G Nagy, A Papp, D Fabo, Gy Kozmann, SOLO: An EEG Processing Software Framework for Localising Epileptogenic Zones, In: Ján Manka, Milan Tysler, Viktor Witkovsky, Ivan Frollo (szerk.) Measurement 2013: 9th International Conference on Measurement. Konferencia helye, ideje: Smolenice, Szlovákia, 2013.05.27-2013.05.30. Bratislava: Vydavatelstvo Slovenskej Akadémie Vied (VEDA), 2013. pp. 105-108.
  • Colombo G, Merico D, Boncoraglio G, De Paoli F, Ellul J, Frisoni G, Nagy Z, van der Lugt A, Vassányi I, Antoniotti M.: "An ontological modeling approach to cerebrovascular disease studies: The NEUROWEB case." Journal of Biomedical Informatics, 2010 Aug, 43(4):469-84 (SCI impact factor: 1.94)
  • de Vico Fallani F, Astolfi L, Cincotti F, Mattia D, la Rocca D, Maksuti E, Salinari S, Babiloni F, Vegso B, Kozmann G, Nagy Z.: Evaluation of the brain network organization from EEG signals: preliminary evidence in stroke patient. Anat Rec.  2009 dec; 292(12): 2023-31. (SCI impact factor: 1.569)
  • Vassányi I, Dulai T, Muhi D: "Mapping Clinical Databases to the Neuroweb Ontology: Lessons Learned" Med-e-Tel Conference, 16-18 April 2008, Luxembourg. In Malina Jordanova (ed.) "Global Telemedicine and eHealth Updates: Knowledge Resources", Vol. I, April 2008, ISSN 1998-5509, pp. 84-88.
  • Kozmann G, Cserti P, Nagy Z: New approach of spatio-temporal cortical activation assessment in finger-tapping studies. In: Lecture notes of the ICB Seminar on Variability in Biomedical Signals, pp: 3-4. 128th ICB Seminar, Warsaw, November 4-7, 2012.
  • Juhasz Z, Vassanyi I, Nagy GA, Papp A, Fabo D, Kozmann G: SOLO: An EEG Processing Software Framework for Localising Epileptogenic Zones. Proc. 9th Int. Conf. on Measurement, May 2013, Smolenice, Slovakia, ISBN 978-80-969-672-5-4 pp 105-108.

Biography of the Head of the Laboratory

Prof Zoltan Nagy is a neuroscientist and neurologist. He received his PhD in medicine in 1981 and became the Doctor of the Hungarian Academy of Sciences in 1992. He led the Department of Neurology of the Haynal Imre University of Medical Sciences until its integration into Semmelweis University in 2000. He was appointed as director of the National Stroke Center in 1993 and the National Institute of Psychiatry and Neurology from 2002 to its termination 2007. From 2008 he is research professor in Faculty of Information Technology of the University of Pannonia and a senior advisor in the Department Section of Cardiovascular Clinic in the Semmelweis University. Between 2012 and 2018 he was the appointed director the National Institute of Clinical Neuroscience. In 2011 he received the Knight's Cross of the Order of Merit of the Republic of Hungary. He has over 390 refereed publications, with overall SCI impact factor of 265.3. His citations are over 3000. He is a member of the Research Ethics Committee of Health Council. He is a core member of the Doctoral School of the University of Pannonia, programme director of the Neuroscience Doctoral School of the Semmelweis University. To date he supervised 27 PhD students. His key research areas are the mesoscopic level characterisation of brain activity and the theory of brain plasticity.