LIN Staff

Dr. Christoph Reichert

Scientist

Behavioral Neurology

Leibniz Institute for Neurobiology
Brenneckestr. 6
39118 Magdeburg
Germany
Phone: +49 391 6263 92311
Email: Christoph.Reichert@lin-magdeburg.de
ORCID: 0000-0002-8649-9791

  • Research interests

    Research interests

    Brain-Computer Interfaces (BCI)

     - attention-based communication through BCIs

     - collaborative BCIs

     - single trial decoding from MEG, EEG and ECoG signals

    Movement recognition

     - diagnosis of motor diseases using a data glove

  • Curriculum vitae

    Curriculum vitae

    Christoph Reichert studied at the Otto-von-Guericke University Magdeburg where he received his Diploma in computer science in 2007. Afterwards he worked as a researcher at the Department of Neurology in the University Medical Center in Magdeburg. In 2015 he started his work at the Leibniz Institute for Neurobiology. His PhD degree he received in 2016 from the University’s Faculty of Computer Science. His main interest is in application of machine learning techniques for decoding electrophysiological brain signals.

  • Publications

    Publications

    Wienke C, Bartsch M, Vogelgesang L, Reichert C, Hinrichs H, Heinze H-J, Dürschmid S. 2021. Mind-wandering Is Accompanied by Both Local Sleep and Enhanced Processes of Spatial Attention Allocation. Cerebral Cortex Communications. 2(1):Article tgab001. https://doi.org/10.1093/texcom/tgab001

    Reichert C, Tellez Ceja IF, Sweeney-Reed CM, Heinze H-J, Hinrichs H, Dürschmid S. 2020. Impact of Stimulus Features on the Performance of a Gaze-Independent Brain-Computer Interface Based on Covert Spatial Attention Shifts. Frontiers in Neuroscience. 14:591777. https://doi.org/10.3389/fnins.2020.591777

    Will M, Peter T, Hanses M, Elkmann N, Rose G, Hinrichs H, Reichert C. 2020. A robot control platform for motor impaired people. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE. pp. 2025-2030. (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/SMC42975.2020.9283104

    Reichert C, Dürschmid S, Bartsch MV, Hopf J-M, Heinze H-J, Hinrichs H. 2020. Decoding the covert shift of spatial attention from electroencephalographic signals permits reliable control of a brain-computer interface. Journal of Neural Engineering. 17(5):056012. https://doi.org/10.1088/1741-2552/abb692

    Vogelgesang L, Reichert C, Hinrichs H, Heinze HJ, Dürschmid S. 2020. Early Shift of Attention Is Not Regulated by Mind Wandering in Visual Search. Frontiers in Neuroscience. 14:Article 552637. https://doi.org/10.3389/fnins.2020.552637

    Krueger J, Reichert C, Dürschmid S, Krauth R, Vogt S, Huchtemann T, Lindquist S, Lamprecht J, Sailer M, Heinze HJ, Hinrichs H, Sweeney-Reed CM. 2020. Rehabilitation nach Schlaganfall: Durch Gehirn-Computer-Schnittstelle vermittelte funktionelle Elektrostimulation. Klinische Neurophysiologie. 51(3):144-155. https://doi.org/10.1055/a-1205-7467

    Reichert C, Dürschmid S, Hinrichs H. 2020. EEG als Steuersignal: Gehirnaktivität entschlüsseln und effizient als Kommunikationsmittel für Patienten mit motorischen Defiziten nutzen. Klinische Neurophysiologie. 51(3):161-166. https://doi.org/10.1055/a-1135-3782

    Dürschmid S, Reichert C, Walter N, Hinrichs H, Heinze H-J, Ohl FW, Tononi G, Deliano M. 2020. Self-regulated critical brain dynamics originate from high frequency-band activity in the MEG. PLoS ONE. 15(6):e0233589. https://doi.org/10.1371/journal.pone.0233589

    Dürschmid S, Reichert C, Kuhn J, Freund HJ, Hinrichs H, Heinze HJ. 2020. Deep brain stimulation of the nucleus basalis of Meynert attenuates early EEG components associated with defective sensory gating in patients with Alzheimer disease - a two-case study. European Journal of Neuroscience. 51(5):1201-1209. https://doi.org/10.1111/ejn.13749

    Dürschmid S, Reichert C, Hinrichs H, Heinze H-J, Kirsch HE, Knight RT, Deouell LY. 2019. Direct Evidence for Prediction Signals in Frontal Cortex Independent of Prediction Error. Cerebral Cortex. 29(11):4530-4538. https://doi.org/10.1093/cercor/bhy331

    Farahat A, Reichert C, Sweeney-Reed C, Hinrichs H. 2019. Convolutional neural networks for decoding of covert attention focus and saliency maps for EEG feature visualization. Journal of Neural Engineering. 16(6):066010. https://doi.org/10.1088/1741-2552/ab3bb4

    Reichert C, Heinze N, Pfeiffer T, Dürschmid S, Hinrichs H. 2018. P63. Detection of error potentials from EEG and MEG recordings and its value for BMI control. Clinical Neurophysiology. 129(8):e93. https://doi.org/10.1016/j.clinph.2018.04.698

    Reichert C, Dürschmid S, Heinze HJ, Hinrichs H. 2017. A comparative study on the detection of covert attention in event-related EEG and MEG signals to control a BCI. Frontiers in Neuroscience. 11(OCT):Article 575. https://doi.org/10.3389/fnins.2017.00575

    Dürschmid S, Edwards E, Reichert C, Dewar C, Hinrichs H, Heinze HJ, Kirsch HE, Dalal SS, Deouell LY, Knight RT. 2016. Hierarchy of prediction errors for auditory events in human temporal and frontal cortex. Proceedings of the National Academy of Sciences of the United States of America. 113(24):6755-6760. https://doi.org/10.1073/pnas.1525030113

    Reichert C, Dürschmid S, Kruse R, Hinrichs H. 2016. An efficient decoder for the recognition of event-related potentials in high-density MEG recordings. Computers. 5(2):Article 5. https://doi.org/10.3390/computers5020005

    Reichert C, Dürschmid S, Hinrichs H, Kruse R. 2015. Efficient recognition of event-related potentials in high-density MEG recordings. In 2015 7th Computer Science and Electronic Engineering Conference, CEEC 2015 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. pp. 81-86. https://doi.org/10.1109/CEEC.2015.7332704

    Reichert C, Kennel M, Kruse R, Heinze H-J, Schmucker U, Hinrichs H, Rieger JW. 2015. Brain-Controlled Selection of Objects Combined with Autonomous Robotic Grasping. Londral RA, Encarnação P, Rovira PJL, editors. In Springer Series in Computational Neuroscience: Neurotechnology, Electronics, and Informatics: Revised Selected Papers from Neurotechnix 2013. Cham: Springer International Publishing. pp. 65-77. https://doi.org/10.1007/978-3-319-15997-3_5

    Reichert C, Fendrich R, Bernarding J, Tempelmann C, Hinrichs H, Rieger JW. 2014. Online tracking of the contents of conscious perception using real-time fMRI. Frontiers in Neuroscience. 8:Article 116. https://doi.org/10.3389/fnins.2014.00116

    Reichert C, Kennel M, Kruse R, Hinrichs H, Rieger JW. 2013. Efficiency of SSVEF recognition from the magnetoencephalogram a comparison of spectral feature classification and CCA-based prediction. In NEUROTECHNIX 2013 - Proceedings of the International Congress on Neurotechnology, Electronics and Informatics. pp. 233-237.

    Reichert C, Kennel M, Kruse R, Heinze HJ, Schmucker U, Hinrichs H, Rieger JW. 2013. Robotic grasp initiation by gaze independent brain-controlled selection of virtual reality objects. In Neurotechnix:Proceedings of the International Congress on Neurotechnology, Electronics and Informatics. pp. 5-12.

    Quandt F, Reichert C, Schneider B, Dürschmid S, Richter D, Hinrichs H, Rieger JW. 2012. Grundlagen und Anwendung von Brain-Machine Interfaces (BMI) *. Klinische Neurophysiologie. 43(2):158-167. https://doi.org/10.1055/s-0032-1308970

    Quandt F, Reichert C, Hinrichs H, Heinze HJ, Knight RT, Rieger JW. 2012. Single trial discrimination of individual finger movements on one hand: A combined MEG and EEG study. NeuroImage. 59(4):3316-3324. https://doi.org/10.1016/j.neuroimage.2011.11.053

    Rieger JW, Reichert C, Gegenfurtner KR, Noesselt T, Braun C, Heinze HJ, Kruse R, Hinrichs H. 2008. Predicting the recognition of natural scenes from single trial MEG recordings of brain activity. NeuroImage. 42(3):1056-1068. https://doi.org/10.1016/j.neuroimage.2008.06.014
  • Third party funds

    Third party funds

    2019 - 2022 (LSA)
    Diagnostic Glove: Disease diagnosis in daily life from wearable kinematics"

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