Our goal is to understand the computing architecture of the human mind and brain. We bring the mind to its computational limits by putting it in its natural environment, where it needs to cope with survival threats. This requires rapid actions with utmost precision and continuous updating. On the other hand, avoidance actions in the absence of real threat are a hallmark of several psychiatric conditions, such as anxiety disorder or post-traumatic stress disorder. We seek to unpack the underlying mechanisms and develop novel treatments. Experimentally, our approach is based on virtual reality, serious games, and associative learning.
What are we offering?
We are developing open-source technologies for eliciting human threat avoidance and escape in immersive virtual reality (https://osf.io/2b3k7/), data analysis pipelines including computational modelling for movement (https://bachlab.github.io/vrthreat/index.html) and psychophysiology data (https://bachlab.github.io/pspm/index.html), AI-based movement analysis, and statistical techniques for optimising experimental design (https://github.com/fmelinscak/coale-paper) and measurement.
What are we interested in for collaboration?
We are interested in all forms of collaboration, from informal discussions to technological exchange, support in using our tools, and developing joint projects – just contact us.
What platforms, analysis tools or facilities do we use and can share?
- immersive (wireless) virtual reality platforms
- markerless and marker-based motion capture
- human movement labs with up to 15 x 7 m free space
- human psychophysiology (stationary and wireless)
- wearable magnetoencephalography
- cognitive modelling tools (R, STAN, VBA)
- data analysis pipelines for human movement and psychophysiology data
- Bayesian experimental design and optimisation of behavioural measurement
Discover our homepage here.
To learn more about Prof. Dr. Dominik Bach follow him on ORCID or Twitter.
Methods
- immersive virtual reality in humans
- markerless and marker-based motion capture
- machine-learning based motion sequencing
- wearable magnetoencephalography (OPM-MEG)
- psychophysiology
- computational modelling of behaviour, biosignals, and neural systems
- psychopharmacology
5 selected publications
- Sporrer, J. K., Brookes, J., Hall, S., Zabbah, S., Hernandez, U. D. S., & Bach, D. R. (2022). Computational characteristics of human escape decisions. https://doi.org/10.31234/osf.io/z52tq
- Ojala KE, Staib M, Gerster S, Ruff CC, Bach DR (2022). Inhibiting human aversive memory by transcranial theta-burst stimulation to primary sensory cortex. Biological Psychiatry, 92, 149-157.
- Bach DR (2021). Cross-species anxiety tests in psychiatry – pitfalls and promises. Molecular Psychiatry, 27, 154-163.
- Bach DR, Melinščak F, Fleming SM, Voelkle M (2020). Calibrating the experimental measurement of psychological attributes. Nature Human Behaviour, 4, 1229-1235.
- Korn CW & Bach DR (2019). Minimizing threat via heuristic and optimal policies recruits hippocampus and medial prefrontal cortex. Nature Human Behavior, 3, 733-745.
