Portrait of Mahan Hosseini

Mahan Hosseini, PhD

Postdoctoral Researcher in Computational Neuroscience Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich

Contact

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Research Interests

Towards a quantitative, cross-species neuroscience of motor control.

I study how the nervous system controls movement, and how this control changes with ageing and disease across species. To make such comparisons possible at scale, I build open-source tools that automate the analysis of animal and human movement. With AutoGaitA, we showed that ageing affects fly, mouse and human gait in similar ways despite their distinct biomechanics. The next tool, AutoStepA, is still in development and will use machine learning models to split continuous movement recordings into behavioural episodes such as single steps.

I also investigate cross-species motor control of upper-limb movements. I currently am obtaining a multimodal (EEG and finger kinematics) dataset while healthy human subjects correct reaching movements in real time. This data will be used to identify the neural signatures of online motor control, how they break down in movement disorders and whether they differ from the control structures of monkeys.

During my PhD, I built the 2f-ST2 computational model accounting for distractor intrusion errors in rapid serial visual presentation (RSVP) experiments. I also developed Dynamic Time Warping methods to measure the timing of EEG components, and showed how machine-learning classification of brain data can overfit in unexpected ways.

Education & Background

I am a Postdoctoral Researcher in Computational Neurology at the Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, where I have worked with Prof Silvia Daun since 2023. I received my PhD in Computer Science from the University of Kent (2017–2022), supervised by Prof Howard Bowman and Dr Srivas Chennu, with a dissertation titled “My mind’s playing tricks on me. Understanding event integration in rapid stimulus streams.” Before that, I completed an MSc in Cognitive Neuroscience at Maastricht University (2015–2016, cum laude) and a BSc in Psychology at the University of Groningen (2012–2015).

Publications

Peer-reviewed

  • Hosseini, M., Klein, I., Wunderle, V., Haustein, M., Semmler, C., Kramer, A., Tolve, M., Mardare, V., Galvao, A., Kuzu, T. D., Grefkes, C., Korotkova, T., Bueschges, A., Fink, G. R., Weiss, P. H., Daun, S., & Gatto, G. (2026). Cross-species identification of conserved and divergent locomotor kinematic strategies using AutoGaitA. Proceedings of the National Academy of Sciences, 123(35), e2534093123.

    https://doi.org/10.1073/pnas.2534093123

  • Hosseini, M., Zivony, A., Eimer, M., Wyble, B., & Bowman, H. (2024). Transient attention gates access consciousness: Coupling N2pc and P3 latencies using dynamic time warping. The Journal of Neuroscience, 44(26), e1798232024.

    https://doi.org/10.1523/JNEUROSCI.1798-23.2024

  • Hosseini, M., Powell, M., Collins, J., Callahan-Flintoft, C., Jones, W., Bowman, H., & Wyble, B. (2020). I tried a bunch of things: The dangers of unexpected overfitting in classification of brain data. Neuroscience & Biobehavioral Reviews, 119, 456–467.

    https://doi.org/10.1016/j.neubiorev.2020.09.036

Under review

  • Hosseini, M., Zivony, A., Eimer, M., Wyble, B., & Bowman, H. (2026). The 2-feature Simultaneous Type/Serial Token Model of temporal feature conjunctions: Successes are merely fortunate conjunctions. bioRxiv (in review at Neural Networks).

    https://doi.org/10.64898/2026.09.07.749788

  • Jefferis, T., Nayak, A., Hosseini, M., Dogan, C., Ramaswamy, P., & Bowman, H. Amplitude and jitter biases in jackknife ERP latency estimates. In review at NeuroImage.

Preprints

  • Tutas, J., Tolve, M., Özer-Yildiz, E., Ickert, L., Klein, I., Hosseini, M., Liebsch, F., Dethloff, F., Gavalisco, P., Endepols, H., Yang, M., Georgomanolis, T., Neumaier, B., Drzezga, A., Daun, S., Schwarz, G., Thorens, B., Gatto, G., Frezza, C., & Kononenko, N. (2024). Autophagy regulator ATG5 preserves cerebellar function by safeguarding its glycolytic activity. bioRxiv, 2024.01.27.577372.

    https://doi.org/10.1101/2024.01.27.577372

Research Software

  • AutoGaitA

    Automated Gait Analysis.

    Open-source Python toolbox for kinematic analysis of rhythmic behaviours across species and tracking methods.

    GitHub

  • NeuroWarp

    Open-source Python and MATLAB toolboxes for measuring temporal differences and correlations between time series, developed for EEG data analysis.

    GitHub

  • AutoStepA

    Machine-learning tool that segments continuous movement data into behavioural episodes such as step cycles. In development.

Supervision & Teaching

Supervision

  1. 2026 – present

    One Bachelor’s thesis (Neuroscience), University of Cologne

  2. 2025 – 2026

    Two DAAD RISE Professional internships, interns from the University of Utah and the University of Toronto

  3. 2024 – 2025

    Two undergraduate practical semesters (Neuroscience), University of Cologne

Teaching

  1. 2024 – present

    Lecturer, undergraduate neuroscience programme, University of Cologne

    Introduction to Python for data analysis and machine learning

  2. 2021

    Lecturer, Landesverband freie ambulante Krankenpflege NRW e.V.

    Lectures for caregivers on perception, communication, systematic work and time management

  3. 2017 – 2021

    Teaching Assistant, School of Computing, University of Kent (seven semesters)

    Cognitive Neural Networks, Foundations of Computing II, Human Computer Interaction, Solving Problems with Data

Grants & Awards

Grants

  • 2025

    Two DAAD RISE Professional grants

    Scholarships for two graduate students from the USA and Canada to undertake three-month internships at Forschungszentrum Jülich (INM-3)

Awards

  • 2026

    Poster Award, Collaborative Research Centre (CRC) 1451 ECR Retreat

  • 2024

    Poster Award, Collaborative Research Centre (CRC) 1451 Retreat

  • 2023

    Poster Award, Cologne Neuroscience Day 2

Additional Activities

  • 2025 – present

    Organiser of the BrainFast lecture series for early-career researchers, INM-3, Forschungszentrum Jülich

  • 2025 – present

    Data steward for dataset repositories, INM-3, Forschungszentrum Jülich