Professor Luc Berthouze
Network physiology; motor neuroscience; criticality in brain
The notion of the brain operating at, or near, a critical bifurcation has been receiving a lot of attention due to the potential benefits of such a regime, namely, meta-stability and maximized dynamic range of processing. However, ascertaining that the brain is operating at criticality and establishing how it may tune to criticality raises a number of methodological challenges, both in terms of analyzing empirical data and developing computational models that are both analytically tractable and amenable to experimental predictions. Our team specializes in the development of methods for detecting markers of criticality in macroscopic brain activity, particularly EEG/MEG and EMG signals. Our work is both theoretical and empirical. We are co-located between University of Sussex and Queen Square, University College London making it possible to deal with a wide range of research questions in both health and disease.
Currently, we are particularly interested in the role of network structure in criticality of phase synchronisation, particularly in relation to oscillopathies such as epilepsy or Parkinson's Disease. There is great scope for lab rotations and/or PhD projects concerned with:
- Characterising criticality of synchronisation in the M/EEG, in health and disease
- Investigating through modelling the role of network structure in the emergence of oscillatory activity
- Investigating how localised stimulation can facilitate or frustrate synchronisation in models of synchronisation on structured networks
Most of our activities will suit students with a background or strong interest in computer science, mathematics and/or physics. However, we are also involved in empirical work (e.g., kinematic and EMG recordings, M/EEG) such that students interested in experimentally tackling questions relevant to criticality are encouraged to apply and/or talk to us!
Key references
- West TO, Berthouze L, Farmer SF, Cagnan H, Litvak V (2021). Inference of brain networks with approximate Bayesian computation – assessing face validity with an example application in Parkinsonism. NeuroImage, 236, 118020.
- West T, Berthouze L, Halliday DM, Litvak V, Sharott A, Magill PJ, Farmer SF (2018). Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat. Journal of Neurophysiology 119:5, 1608-1628.
- West T, Farmer S, Berthouze L, Jha A, Beudel M, Foltynie T, Limousin P, Zrinzo L, Brown P, Litvak V (2017). The Parkinsonian Basal Ganglia network: Measures of power, linear and non-linear synchronization and their relationship to L-DOPA treatment and OFF state motor severity. Frontiers in Human Neuroscience, 10:517
- Barnard R, Kiss IZ, Famer SF, and Berthouze L (2017). Clustered arrangement of neurons can lead to instability in the dynamics of a spatially-embedded activity-dependent neuronal network growth model. In van Ooyen and Butz-Ostendorf, editors, The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain, Elsevier
- Botcharova M, Farmer SF, Berthouze L (2014). Markers of criticality in phase synchronisation. Frontiers in Systems Neuroscience, 8:176
- Berthouze L, Farmer SF (2012). Adaptive time-varying Detrended Fluctuation Analysis. Journal of Neuroscience Methods, 209:178-188.
For a full list of publications, visit Luc Berthouze’s staff profile.