Dr Andrew Meso
- 01202 962551
- ameso at bournemouth dot ac dot uk
- Senior Lecturer (Academic) in Psychology
- Poole House P251 (Above Dylans), Talbot Campus, Fern Barrow, Poole, BH12 5BB
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I studied in London, starting with Physics (BSc) and Medical Physics (MSc) before moving towards computational neuroscience and psychology to take on a research project on mechanisms of dynamic visual perception for my PhD (2008). After that, I worked on related themes as a post doctoral researcher in interdisciplinary vision groups. The first of these was at a Vision Research lab at McGill in Montreal (2009-2011) and then later for a Neuroscience institute of the French CNRS in Marseille (2011-2015). I spent a summer as a visiting scientist at the RIKEN Brain Sciences Institute in Japan training in the use of fMRI (Summer 2012). I joined Bournemouth University in 2016 both to teach and develop my research themes. I will also be a part of the Interdisciplinary Neuroscience Research Group in the Faculty of Science and Technology.
My expertise is in the use of visual psychophysics and eye movement recordings in combination with computational or mathematical approaches to try and shed light on how the human brain makes sense of dynamic scenes. In particular, I am interested in motion perception, spatial and temporal integration and the effect of mirror symmetry on vision. My current research questions include (1) How does the brain very quickly decide which parts within a viewed, moving scene to combine and which parts to process as separate entities? (2) How do our eyes effortlessly extract information about object symmetry in scenes and what role do eye movements play in this dynamic selection process? (3) How do the spatial scales within visual scenes impact on our interpretation of such scenes? In other words are we better at 'seeing', for example, smaller objects at certain distances (which determines size on the retina) and larger objects at different distances? For these question, eye movement recordings and visual pyschophysics detection and discrimination tasks with controlled synthetic stimuli are typically used alongside statistical and signal processing models. I have ongoing collaborations with the University of Western Australia, CNRS Paris and Marseille, and Royal Holloway University of London and other groups.
- Meso, A.I., Montagnini, A., Bell, J. and Masson, G.S., 2016. Looking for symmetry: Fixational eye movements are biased by image mirror symmetry. Journal of Neurophysiology, 116 (3), 1250-1260.
- Meso, A.I., Rankin, J., Faugeras, O., Kornprobst, P. and Masson, G.S., 2016. The relative contribution of noise and adaptation to competition during tri-stable motion perception. Journal of Vision, 16 (15).
- Meso, A.I. and Masson, G.S., 2015. Dynamic resolution of ambiguity during tri-stable motion perception. Vision Research, 107, 113-123.
- Bell, J., Manson, A., Edwards, M. and Meso, A.I., 2015. Numerosity and density judgments: Biases for area but not for volume. Journal of Vision, 15 (2).
- Meso, A.I. and Chemla, S., 2015. Perceptual fields reveal previously hidden dynamics of human visual motion sensitivity. Journal of Neurophysiology, 114 (3), 1360-1363.
- Meso, A.I. and Simoncini, C., 2014. Towards an understanding of the roles of visual areas MT and MST in computing speed. Frontiers in Computational Neuroscience, 8 (AUG).
- Rankin, J., Meso, A.I., Masson, G.S., Faugeras, O. and Kornprobst, P., 2014. Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration. Journal of Computational Neuroscience, 36 (2), 193-213.
- Bell, J., Sampasivam, S., McGovern, D.P., Meso, A.I. and Kingdom, F.A.A., 2014. Contour inflections are adaptable features. Journal of Vision, 14 (7).
- Meso, A.I., Durant, S. and Zanker, J.M., 2013. Perceptual separation of transparent motion components: the interaction of motion, luminance and shape cues. EXPERIMENTAL BRAIN RESEARCH, 230 (1), 71-86.
- Meso, A.I. and Hess, R.F., 2012. Evidence for multiple extra-striate mechanisms behind perception of visual motion gradients. Vision Research, 64, 42-48.
- Meso, A.I. and Hess, R.F., 2011. A visual field dependent architecture for second order motion processing. Neuroscience Letters, 503 (2), 77-82.
- Meso, A.I. and Hess, R.F., 2011. Orientation gradient detection exhibits variable coupling between first- and second-stage filtering mechanisms. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 28 (8), 1721-1731.
- Meso, A.I. and Hess, R.F., 2010. Visual motion gradient sensitivity shows scale invariant spatial frequency and speed tuning properties. Vision Research, 50 (15), 1475-1485.
- Meso, A.I. and Zanker, J.M., 2009. Perceiving motion transparency in the absence of component direction differences. VISION RESEARCH, 49 (17), 2187-2200.
- Meso, A.I. and Zanker, J.M., 2009. Speed encoding in correlation motion detectors as a consequence of spatial structure. BIOLOGICAL CYBERNETICS, 100 (5), 361-370.
- Vacher, J., Meso, A.I., Perrinet, L. and Peyre, G., 2015. Biologically inspired dynamic textures for probing motion perception. 1918-1926.
- Meso, A. and Zanker, J.M., 2008. Separating global motion components in transparent visual stimuli - A phenomenological analysis. 308-317.
Public Engagement & Outreach Activities
- Bournemouth University Active Vision Workshop (June 2016)
- Society for Neuroscience Annual Meeting 2016, Repulsion of perceived visual motion direction as an emergent property of deciding to unify or segregate sources, 12 November 2016, San Diego, California
- European Conference on Visual Perception, Enhanced sensitivity to scene symmetry as a consequence of saccadic spatio-temporal sampling, 28 August 2016, Barcelona
- Applied Vision Association (UK), Member (2007-),
- Institute of Physics (UK), Corporate Member,
- Society for Neuroscience, Member (2013-),