Summer school on Hybrid Neural Interfaces

Summer school 24 Schedule

Summer school 24 Agenda


Venue: Faculty of Electrical Engineering and Computer Science, Koroška cesta 46, 2000 Maribor (classroom Alpha).

One week of educational and networking activities was designed to provide participants with a comprehensive understanding of the latest advancements in hybrid neural interfaces. Throughout the program, attendees explored diverse topics ranging from high-density surface and high-density intramuscular electromyogram analysis to movement augmentation, motor-cognitive interventions, and neural interfaces for managing movement disorders.

The Summer School began with an in-depth examination of high-density surface electromyogram (HDEMG) analysis, exploring the latest developments in motor unit identification techniques and motor unit identification pipelines. Participants gained insights into the intricacies of motor unit behaviour in both voluntary and elicited contractions, illuminating the underlying mechanisms driving movement control and coordination.

Moving beyond muscle activity, the program shifted focus to functional brain connectivity as assessed by electroencephalograms (EEG). Attendees explored the dynamic interplay between cortical centres and muscular output, unlocking novel pathways for understanding neural movement control. Furthermore, they examined the intersection of motor-cognitive interventions in gait and balance studies and offer insights into innovative approaches to managing movement disorders through neural interfaces. The possibilities of neural code exploitation in movement augmentation were also explained.

Incorporating practical application, the summer school offered hands-on training and advice from leading experts and fellow students. Sessions covered vital topics, such as optimising HDEMG acquisition quality for motor unit identification and transferring information from HDEMG to EEG with the help of motor unit-based EEG filters for cortical activity assessment.

Participants had the opportunity to showcase their work, fostering collaboration and learning experiences among peers. After the regular program, the summer school aimed to create a relaxed social atmosphere with numerous opportunities for networking and cultural exchange.

Participating experts:
  • A. Holobar (University of Maribor, Slovenia): MU identification pipelines
  • J. Škarabot (Loughborough University, UK): MU behaviour in voluntary & elicited contractions
  • M.A. Mañanas (UPC - Universitat Politècnica de Catalunya, Spain): Functional brain connectivity assessed by EEG
  • U. Marušič (Science and Research Centre Koper, Slovenia): Motor-cognitive interventions in gait and balance studies
  • D. Farina (Imperial College London, UK): Movement augmentation
  • A. P. Valdunciel (Imperial College London, UK): Neural interfaces for managing movement disorders
  • S. Muceli (Chalmers, Sweden): Beyond the surface: high-density intramuscular EMG
  • B. G. Sgambato (Imperial College London, UK): Ultrasound neural interfaces
Hands-on & practical advice from our students:
  • M. Kramberger (University of Maribor, Slovenia): How to improve the EMG acquisition: quality control for MU identification
  • N. Murks (University of Maribor, Slovenia): From muscles to the brain: MU-based EEG filters
  • M. Šavc, N. Murks, M. Kramberger (University of Maribor, Slovenia), M. Kalc (Science and Research Centre Koper, Slovenia): HNI2024 Summer challenge: Science & Sport.

July 8th (Day 1) - Surface HDEMG interfaces:

The first day focused on surface high-density electromyograms (HDEMG):

  • Lecture 1: Movement augmentation. Prof. Dario Farina (IMPERIAL, QS) presented the latest prospects in movement augmentation and methodologies for assessing degrees of freedom in neural codes sent to skeletal muscles. Prof. Farina reviewed the latest advances in decoding the basis of motor control from the muscles and how this neural code can be exploited to develop movement augmentation paradigms.
    Further reading:
  • - Eden J, Bräcklein M, Ibáñez J, Barsakcioglu DY, Di Pino G, Farina D, Burdet E, Mehring C. Principles of human movement augmentation and the challenges in making it a reality. Nat Commun. 2022 Mar 15;13(1):1345.
    https://www.nature.com/articles/s41467-022-28725-7
  • - Bräcklein M, Ibáñez J, Barsakcioglu DY, Farina D. Towards human motor augmentation by voluntary decoupling beta activity in the neural drive to muscle and force production. J Neural Eng. 2021 Feb 11;18(1).
    https://iopscience.iop.org/article/10.1088/1741-2552/abcdbf
  • - Bräcklein M, Barsakcioglu DY, Ibáñez J, Eden J, Burdet E, Mehring C, Farina D. The control and training of single motor units in isometric tasks are constrained by a common input signal. Elife. 2022 Jun 7;11:e72871.
    https://elifesciences.org/articles/72871
  • - Aszmann OC, Roche AD, Salminger S, Paternostro-Sluga T, Herceg M, Sturma A, Hofer C, Farina D. Bionic reconstruction to restore hand function after brachial plexus injury: a case series of three patients. Lancet. 2015 May 30;385(9983):2183-9.
    https://www.researchgate.net/publication/272945462_Bionic_reconstruction_to_restore_hand_function_after_brachial_plexus_injury_A_case_series_of_three_patients
  • Lecture 2: Motor unit behaviour in voluntary & elicited contractions. Jakob Škarabot (Loughborough University, UK, QS) was invited as a consortium-external speaker to present the results of motor unit identification in different voluntary and electrically elicited contractions. He will discuss the typical motor unit discharge patterns and behavior, and techniques for their assessment.
    Slides: Motor unit behaviour in voluntary & elicited contractions
  • Hands-on 1: How to improve the EMG acquisition: quality control for motor unit identification. Matej Kramberger (UM, PhD, YR) presented practical advice and describe crucial steps in acquiring HDEMG signals, especially when the HDEMG signals are to be decomposed into contributions of individual motor units. This included practical demonstrations of HDEMG signals with different levels of quality and practical guidelines on quantifying the quality of HDEMG signals.
    Slides: How to improve the EMG acquisition: quality control for MU identification
    Further reading:
  • - Holobar, Ales, and Dario Farina. "Noninvasive neural interfacing with wearable muscle sensors: Combining convolutive blind source separation methods and deep learning techniques for neural decoding." IEEE Signal Processing Magazine 38, no. 4 (2021): 103-118.
    https://ieeexplore.ieee.org/abstract/document/9467400
  • - Martinez-Valdes, Eduardo, Roger M. Enoka, Aleš Holobar, Kevin McGill, Dario Farina, Manuela Besomi, François Hug et al. "Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix." Journal of Electromyography and Kinesiology 68 (2023): 102726.
    https://www.sciencedirect.com/special-issue/10CFPDX6CN9
  • - Karpati, George (2010). Disorders of Voluntary Muscle (PDF). Cambridge University Press. ISBN 9780521876292.
    http://assets.cambridge.org/97805218/76292/excerpt/9780521876292_excerpt.pdf
  • - Campanini I, Merlo A, Disselhorst-Klug C, Mesin L, Muceli S, Merletti R. Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors. Sensors (Basel).
    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185290/
  • Student's project presentations with expert feedback - Part 1: Participants presented their projects/work and discuss their hypothesis, goals and methodology with QS. This contributed to the networking and is expected to increase the dissemination of the know-how and the impact of the HybridNeuro project.
  • Opening reception: the first day closed with an opening reception, offering opportunities for informal networking and exchange of research ideas among the participants.

July 9th (Day 2) - EEG interfaces

The second day focused on interfaces and processing of electroencephalographic (EEG) signals:

  • Lecture 3: Functional brain connectivity assessed by EEG. Dr. Miguel Ángel Mañanas (UPC, QS) presented the current methodologies and procedures for EEG acquisition and posterior data processing, filtering, and interpretation for the assessment of functional brain connectivity.
    Slides: Functional brain connectivity assessed by EEG
    Further reading:
  • - Vigasina, K.D., Proshina, E.A., Gotovtsev, P.M. et al. Approaches to the Use of Graph Theory to Study the Human EEG in Health and Cerebral Pathology. Neurosci Behav Physi 53, 381-398 (2023). https://doi.org/10.1007/s11055-023-01437-1
    https://link.springer.com/article/10.1007/s11055-023-01437-1
  • - Giovanni Chiarion, Laura Sparacino, Yuri Antonacci, Luca Faes, Luca Mesin "Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends" Bioengineering (Basel). 2023 Mar 17;10(3):372. doi: 10.3390/bioengineering10030372
    https://www.mdpi.com/2306-5354/10/3/372
  • - Joan Francesc Alonso, Sergio Romero, Miquel Àngel Mañanas, Jordi Riba, Serotonergic Psychedelics Temporarily Modify Information Transfer in Humans, International Journal of Neuropsychopharmacology, Volume 18, Issue 8, June 2015, pyv039, https://doi.org/10.1093/ijnp/pyv039
    https://pubmed.ncbi.nlm.nih.gov/25820842/
  • - Marta Borràs, Sergio Romero, Joan F Alonso, Alejandro Bachiller, Leidy Y Serna, Carolina Migliorelli, Miguel A Mañanas, "Influence of the number of trials on evoked motor cortical activity in EEG recordings” J Neural Eng . 2022 Aug 26;19(4). https://doi.org/10.1088/1741-2552/ac86f5
    https://iopscience.iop.org/article/10.1088/1741-2552/ac86f5
  • Lecture 4: Motor-cognitive interventions in gait and balance studies. Dr. Uroš Marušič (The Science and Research Centre Koper, Slovenia, QS) was invited as a consortium-external speaker. He is the coordinator of the TwinBrain project (HORIZON 2020. WIDESPREAD-05-2020 - Twinning). He presented the state-of-the-art methodologies and the latest findings in motor-cognitive interventions, including the results of the TwinBrain project.
    Further reading:
  • - Marusic U, Verghese J, Mahoney JR. "Cognitive-Based Interventions to Improve Mobility: A Systematic Review and Meta-analysis". J Am Med Dir Assoc. 2018 Jun;19(6):484-491.e3. DOI: 10.1016/j.jamda.2018.02.002.
    https://www.jamda.com/article/S1525-8610(18)30078-1/abstract
  • - Marusic U, Taube W, Morrison SA, Biasutti L, Grassi B, De Pauw K, Meeusen R, Pisot R, Ruffieux J. "Aging effects on prefrontal cortex oxygenation in a posture-cognition dual-task: an fNIRS pilot study". Eur Rev Aging Phys Act. 2019 Jan 11;16:2. DOI: 10.1186/s11556-018-0209-7.
    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329111/
  • - Gorjan D, Gramann K, De Pauw K, Marusic U. "Removal of movement-induced EEG artifacts: current state of the art and guidelines". J Neural Eng. 2022 Feb 28;19(1). DOI: 10.1088/1741-2552/ac542c.
    https://iopscience.iop.org/article/10.1088/1741-2552/ac542c
  • Hands-on 2: From muscles to the brain: MU-based EEG filters. Nina Murks (UM, YR) presented recent findings and the methodology developed in the HybridNeuro project, aiming to exploit the robustness of muscle-computer interfaces to increase the robustness of brain-computer interfaces. She demonstrated how to transfer the HDEMG-based motor unit filters to the EEG signals.
    Slides: From muscles to the brain MU based EEG filters
    Further reading:
  • - A. Holobar and D. Zazula, "Multichannel Blind Source Separation Using Convolution Kernel Compensation". IEEE Transactions on Signal Processing, vol. 55, no. 9, pp. 4487-4496, Sept. 2007, doi: 10.1109/TSP.2007.896108.
    https://ieeexplore.ieee.org/document/4291854
  • - Demuse tool.
    https://demuse.feri.um.si/
  • - Holobar, Aleš, Juan A. Gallego, Jernej Kranjec, Eduardo Rocon, Juan P. Romero, Julián Benito-León, José L. Pons, and Vojko Glaser. "Motor unit-driven identification of pathological tremor in electroencephalograms." Frontiers in neurology 9 (2018): 879
    https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2018.00879/full
  • - Škarabot, Jakob, Claudia Ammann, Thomas G. Balshaw, Matjaž Divjak, Filip Urh, Nina Murks, Guglielmo Foffani, and Aleš Holobar. "Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulation." The Journal of Physiology 601, no. 10 (2023): 1719-1744.
    https://physoc.onlinelibrary.wiley.com/doi/full/10.1113/JP284043
  • Student's project presentations with expert feedback - Part 2: Participants presented their projects and discuss their hypothesis, goals and methodology with qualified scientists. This contributed to the networking and is expected to increase the dissemination of the know-how and the impact of the HybridNeuro project.

July 10th (Day 3) - Corticomuscular coupling

The third day focused on Neural interfaces for movement augmentation and management of neural disorders:

  • Lecture 5: Motor unit identification pipelines: state of the art and perspectives. Aleš Holobar (UM, QS) opened the summer school and present the HybridNeuro project and the latest developments and challenges in identifying motor unit discharge patterns from HDEMG signals using signal processing pipelines.
    Slides: MU filters and hdEMG processing pipelines
    Further reading:
  • - Urh, Filip, and Aleš Holobar. "Automatic identification of individual motor unit firing accuracy from high-density surface electromyograms." IEEE Transactions on Neural Systems and Rehabilitation Engineering 28, no. 2 (2020): 419-426.
    https://ieeexplore.ieee.org/abstract/document/8949694
  • - Frančič, Aljaž, and Aleš Holobar. "On the reuse of motor unit filters in high density surface electromyograms recorded at different contraction levels." Ieee Access 9 (2021): 115227-115236.
    https://ieeexplore.ieee.org/abstract/document/9513317
  • - Kramberger, Matej, and Aleš Holobar. "On the prediction of motor unit filter changes in blind source separation of high-density surface electromyograms during dynamic muscle contractions." IEEE Access 9 (2021): 103533-103540.
    https://ieeexplore.ieee.org/abstract/document/9492127
  • - Kalc, Miloš, Jakob Škarabot, Matjaž Divjak, Filip Urh, Matej Kramberger, Matjaž Vogrin, and Aleš Holobar. "Identification of motor unit firings in H-reflex of soleus muscle recorded by high-density surface electromyography." IEEE Transactions on Neural Systems and Rehabilitation Engineering 31 (2022): 119-129.
    https://ieeexplore.ieee.org/abstract/document/9933635
  • - Šavc, Martin, and Aleš Holobar. "Non-Negative matrix factorization of simulated high density surface electromyograms reflects both muscle excitation and muscle shortening." IEEE Access 9 (2021): 70548-70555.
    https://ieeexplore.ieee.org/abstract/document/9427096
  • Lecture 6: Neural interfaces for managing movement disorders. Dr. Alejandro Pascual Valdunciel (IMPERIAL, YR) presented the applications of neural interfaces in managing neural diseases with motor alterations. He introduced how the latest advances in electrophysiology can be applied to unveil the pathophysiology of movement disorders. He also explain the basis of neuromodulation, reviewing different techniques to stimulate the nervous system and emphasising the relevance of bi-directional neural interfaces.
    Further reading:
  • - Shih LC, Pascual-Leone A. Non-invasive Brain Stimulation for Essential Tremor. Tremor Other Hyperkinet Mov (N Y). 2017 Mar 28;7:458.
    https://tremorjournal.org/articles/10.5334/tohm.377 DOI: 10.7916/D8G44W01
  • - Wolpaw JR, Kamesar A. Heksor: the central nervous system substrate of an adaptive behaviour. J Physiol. 2022 Aug;600(15):3423-3452.
    https://physoc.onlinelibrary.wiley.com/doi/10.1113/JP283291 DOI: 10.1113/JP283291
  • - Pascual-Valdunciel A, Rajagopal A, Pons JL, Delp S. Non-invasive electrical stimulation of peripheral nerves for the management of tremor. J Neurol Sci. 2022 Apr 15;435:120195. doi: 10.1016/j.jns.2022.120195. Epub 2022 Feb 19.
    https://linkinghub.elsevier.com/retrieve/pii/S0022-510X(22)00057-0 DOI 10.1016/j.jns.2022.120195
  • HNI2024 Summer challenge: Science & Sport. Researchers from UM demonstrated motion tracking with the help of low-cost video cameras and deep neural networks. Participants assessed the motion tracking performance, such as accuracy and responsiveness, in different practical setups, including sports activities. Acquisition of surface HDEMG during these different setups was demonstrated and practised. These practical demonstrations were used to boost the participants' networking and open discussions on the challenges and opportunities behind the kinematic and neural interfaces and their exploitation in different applications.

July 11th (Day 4) - Corticomuscular coupling

The fourth day focused on intramuscular and ultrasound interfaces:

  • Lecture 7: Beyond the surface: multichannel intramuscular EMG. Prof. Silvia Muceli (CHALMERS, QS) presented the possibilities and challenges in acquiring intramuscular HDEMG signals, including their state-of-the-art processing methodologies and the latest findings, supported by intramuscular HDEMG analysis.
    Slides: Beyond the surface: multichannel intramuscular EMG
    Further reading:
  • - Muceli, S., Poppendieck, W., Negro, F., Yoshida, K., Hoffmann, K.P., Butler, J.E., Gandevia, S.C. and Farina, D. (2015), Accurate and representative decoding of the neural drive to muscles in humans with multi-channel intramuscular thin-film electrodes. J Physiol, 593: 3789-3804. https://doi.org/10.1113/JP270902
    https://physoc.onlinelibrary.wiley.com/doi/epdf/10.1113/JP270902?casa_token=gtywSyugHssAAAAA%3AlD5g9RvNZ_Kn7sUYDa1VTlSWY5i5To2S668vy3TVIHsXGJLqqQx_5Nrq0ZIiB_kE8kOTuOMJhHWvjRQ
  • - Muceli S, Poppendieck W, Holobar A, Gandevia S, Liebetanz D, Farina D. Blind identification of the spinal cord output in humans with high-density electrode arrays implanted in muscles. Sci Adv. 2022 Nov 18;8(46):eabo5040. DOI: 10.1126/sciadv.abo5040.
    https://www.science.org/doi/10.1126/sciadv.abo5040
  • - Muceli S, Bergmeister KD, Hoffmann KP, Aman M, Vukajlija I, Aszmann OC, Farina D. Decoding motor neuron activity from epimysial thin-film electrode recordings following targeted muscle reinnervation. J Neural Eng. 2019 Feb;16(1):016010. DOI: 10.1088/1741-2552/aaed85. Epub 2018 Nov 1.
    https://iopscience.iop.org/article/10.1088/1741-2552/aaed85/meta
  • - Muceli S, Poppendieck W, Hoffmann KP, Dosen S, Benito-León J, Barroso FO, Pons JL, Farina D. A thin-film multichannel electrode for muscle recording and stimulation in neuroprosthetics applications. J Neural Eng. 2019 Apr;16(2):026035. DOI: 10.1088/1741-2552/ab047a.
    https://iopscience.iop.org/article/10.1088/1741-2552/ab047a/meta
  • Lecture 8: Ultrasound neural interfaces. Mr. Bruno Grandi Sgambato (Imperial College London, UK) presented the use of ultrasound as a novel approach to neural interfacing. He discussed, from the beginning, the basics of ultrasound, recording techniques, and its potential as a tool for neural interfacing. He also reviewed results showing its potential in motor unit decomposition and prosthetic control.
  • University of Maribor & city tour: Researchers of UM presented to the participants the infrastructure at UM, possibilities of research work collaboration, PhD study programs and postdoc opportunities. The University of Maribor and Maribor City sightseeing tour followed, focusing on networking, the city's lifestyle and Slovenian cultural heritage.

July 12th (Day 5) - Neural Interfaces in practice

The fifth day discussed the challenges and opportunities the neural interfaces offer in clinical practice and their potential for exploitation as experienced by the Slovenian industrial partners. We presented the HybridNeuro Hub initiative to all the participants and organise the 2nd HybridNeuro Hub day.

  • HybridNeuro Hub Day: Clinical perspectives & challenges. Representatives of Slovenian clinical institutions have been invited to present state-of-the-art clinical practice and challenges in work with neural interfaces.
  • HybridNeuro Hub Day: Industry & key enabling technologies. Main industrial partners and regional development agencies have been invited to present their products and services and to express their challenges in the use of neural interfaces in applications. They presented and discuss their expectations, topics and services that HybridNeuro Hub should and should not feature.


This Summer School has received funding from the European Union's Horizon Europe Research and Innovation Programme under grant agreement no. 101079392 and from the UK Research and Innovation (UKRI) government's Horizon Europe funding guarantee scheme under grant agreement no. 10052152.

Funded by the European Union Funded by UKRI