My research looks at human vision and eye movements. I am interested in how individual sensitivity and patterns of eye movements reveal computational principles applied within the sensory and motor brain. Using models to test and unpack these processing rules can reveal unexpected influences on perception and improve our understanding of how things can go wrong.

My teaching mainly covers two areas:

• The first is a course that aims to develop in neuroscientists 'The Principles of Transparent and Reproducible Research'.
• The second is a quantitative and computational skills course titled 'Statistics, Coding and Mathematics for Scientists'.

Please see my Research Staff Profile for more detail.

Key publications:

• Meso et al., 2020. Evidence of inverted gravity‐driven variation in predictive sensorimotor function. Eur J Neurosci.
• Vacher et al., 2018. Bayesian modeling of motion perception using dynamical stochastic textures. Neural Computation.
• Gekas et al., 2017. A normalization mechanism for estimating visual motion across speeds and scales. Current Biology.
• Meso et al., 2016. The relative contribution of noise and adaptation to tri-stable motion perception. Journal of Vision.
• Meso et al., 2016. Looking for symmetry: Fixational eye movements are biased by image mirror symmetry. Journal of Neurophysiology.

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Key collaborators:

• Dr Anna Montagnini, Institut de Neuroscience de la Timone
• Dr Guillaume Masson, Institut de Neuroscience de la Timone
• Dr Jason Bell, University of Western Australia