We are delighted that our forthcoming Sir Charles Sherrington Prize Lecture will be delivered by Professor Tony Movshon on 13 March. In anticipation of this lecture, we have spoken to Professor Movshon about his career.
Professor J. Anthony Movshon is a world-renowned neuroscientist whose work has shaped how scientists understand the computations of the visual brain. Based at New York University, Movshon’s research spans how the brain interprets form, motion and texture, how visual experience shapes development, and how neural activity guides sight and action. He is a Fellow of the Royal Society, Member of the U.S. National Academy of Sciences, and recipient of multiple honours including the António Champalimaud Vision Award and the Karl Spencer Lashley Award.
In this interview, Professor Movshon discusses the real-world impact of his research, where the field is heading, his inspirations, and advice for early career scientists.
What impact has your scientific research had outside the laboratory?
'My work has focused on the basic mechanisms by which the visual cortex interprets what we see — from simple line detection to how complex patterns and motion are computed by networks of neurons. This might seem abstract, but it underpins everything from clinical approaches to visual disorders to how artificial systems emulate human vision,' he explains.
'In addition, my laboratory has a second focus studying the way that vision develops in early life, and how that development is affected by abnormal visual experience. This is the foundation of amblyopia, a partial sight loss that affects 1-2% of the population,' he continues. 'Our work has helped to explain how amblyopia develops in children, and how brain plasticity mechanisms can be recruited to prevent or treat it'.
'In all kinds of research, basic science is the foundation upon which applied advances are built — whether in neural prosthetics, rehabilitation strategies, machine vision,' he adds. It is also notable that the modern AI systems that are transforming the modern world are based on computational models of visual processing like those developed by Movshon and his colleagues.
'Our research seeks to understand the organization and function of visual cortex, which is of interest both because of its potential as a substrate for visual loss and recovery after brain damage, and because is forms the processing chain by which visual signals are transformed to form decisions, guide actions, and create enduring memories of evanescent events.'
Looking ahead, how do you see your research developing over the next few years?
'The landscape of vision science is rapidly evolving, with new imaging technologies and analytical tools,' he says. 'I see the field delving deeper into how individual neurons and populations contribute to complex perceptual decisions and linking those neural signals more directly to behaviour.'
He notes that computational and theoretical approaches are helping to bridge gaps between biological and artificial vision systems, offering exciting cross-disciplinary opportunities for new discovery in both domains.
What first inspired you to become a scientist, and how did you come to specialise in visual neuroscience?
'I became interested in science at school. I suspect that a key motivator was that my parents, both accomplished in their fields, were not scientists — science was my own domain. It was during my time at Cambridge University that I connected with the questions of vision and perception,' he recalls. 'As it often the case, a particular field engages you not because of its intrinsic merit, but because the people who work in that field engage you. In my case, Colin Blakemore — my undergraduate teacher, PhD advisor, and lifelong friend — inspired my particular interest'. He concludes 'It is a particular honour to give my lecture in the auditorium that bears his name.'
Is there advice you would give to early career research scientists — or to a younger you?
'Science is filled with challenges. Data don’t always behave, and experiments will fail. But be rigorous and persistent, and, above all, keep an open mind — a principle best captured by the great writer Douglas Adams: " … a scientist must also be absolutely like a child. If he sees a thing, he must say that he sees it, whether it was what he thought he was going to see or not. See first, think later, then test. But always see first. Otherwise you will only see what you were expecting."
Douglas Adams, So Long and Thanks for All the Fish'.