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Department of Applied Mathematics and Theoretical Physics

Linda Bowns is currently a member of the Department of Applied Mathematics and Theoretical Physics, Cambridge Computational Biology Institute research group, University of Cambridge. Her current research interests are developing computer programmes for measuring early cortical visual processing, and computing optic flow fields based on human motion processing. She completed a PhD at the University of Cambridge in 1989, followed by post-doctoral research at York University, Canada, and the University of Edinburgh. She joined the University of Nottingham in 1992 as a faculty member and remained there until 2014. Her main interests over this former period have been empirical investigations into the mechanisms underlying human motion processing. 



L Bowns. Motion estimation: A biologically inspired model. Vision Res, 150:44–53, Aug 2018.

Linda Bowns and William H A Beaudot. Measuring early cortical visual processing in the clinic. Iperception, 8(3):2041669517702915, 2017.

Linda Bowns. An explanation of why component contrast affects perceived pattern motion. Vision Res, 86:1–5, Jun 2013.

Linda Bowns. Taking the energy out of spatio-temporal energy models of human motion processing: the component level feature model. Vision Res, 51(23-24):2425–30, Dec 2011.

Linda Bowns and Horace B Barlow. Perceived motion is influenced by random dynamic information. Perception, 40(2):135–42, 2011.

Linda Bowns and Alexander J S Beckett. An independent effect of spatial frequency on motion integration reveals orientation resolution. Vision Res, 50(15):1445–51, Jul 2010.

Linda Bowns and David Alais. Large shifts in perceived motion direction reveal multiple global motion solutions. Vision Res, 46(8-9):1170–7, Apr 2006.

Linda Bowns. ’squaring’ is better at predicting plaid motion than the vector average or intersection of constraints. Perception, 35(4):469–81, 2006.

Craig Aaen-Stockdale and Linda Bowns. Motion-detection thresholds for first- and second-order gratings and plaids. Vision Res, 46(6-7):925–31, Mar 2006.

L Bowns. Can spatio-temporal energy models of motion predict feature motion? Vision Res, 42(13):1671–81, Jun 2002.

L Bowns. Ioc, vector sum, and squaring: three different motion effects or one? Vision Res, 41(7):965–72, Mar 2001.

L Bowns. Features derived from first-order motion mechanisms predict anomalies in motion perception. Perception, 30(1):9–19, 2001.

 L Bowns. Evidence for a feature tracking explanation of why type ii plaids move in the vector sum direction at short durations. Vision Res, 36(22):3685–94, Nov 1996.

L Bowns, L Kirshner, and M Steinbach. Hemifield relative motion bias in adults monocularly enucleated at an early age. Vision Res, 34(24):3389–95, Dec 1994.

L Bowns and M J Morgan. Facial features and axis of symmetry extracted using natural orientation information. Biological Cybernetics, 70(2):137–144, 1993. 


Research Group

Computational Biology




01223 337876