CHBH Seminar Series: Adrien Doerig

Gisbert Kapp NG16
Lectures Talks and Workshops, Life and Environmental Sciences, Medical and Dental Sciences, Research, Students
Thursday 14th November 2019 (13:00-14:00)
Download the date to your calendar (.ics file)

Dr Ali Mazaheri:
Mr Chris Anderson:
Dr Emily Loftus:

We pleased to announce that Adrien Doerig, will be giving a CHBH Seminar on Thursday 14th November. Adrien studied Neuroscience and Theoretical Physics at EPFL, Switzerland. He is currently finishing his PhD in the Laboratory of Psychophysics, EPFL, focussing on modelling psychophysical experiments in neural networks to gain insights about the visual system's architecture. He is also working on how science can address empirical data about consciousness, and how theories can be compared.

Title: Crowding, Neural Networks and the Architecture of the Visual System

Adrien Doerig
Laboratory of Psychophysics, Brian Mind Institute, EPFL, Switzerland

Classically, vision is seen as a cascade of local, feedforward computations. This framework has been tremendously successful, inspiring a wide range of ground-breaking findings in neuroscience and computer vision. Recently, feedforward Convolutional Neural Networks (ffCNNs), inspired by this classic framework, have revolutionized computer vision and been adopted as tools in neuroscience. However, despite these successes, there is much more to vision. I will present our work using visual crowding and related psychophysical effects as probes into visual processes that go beyond the classic framework. In crowding, perception of a target deteriorates in clutter. We focus on global aspects of crowding, in which perception of a small target is strongly modulated by the global configuration of elements across the visual field. We show that models based on the classic framework, including ffCNNs, cannot explain these effects for principled reasons and identify recurrent grouping and segmentation as a key missing ingredient. Then, we show that capsule networks, a recent kind of deep learning architecture combining the power of ffCNNs with recurrent grouping and segmentation, naturally explain these effects. We provide psychophysical evidence that humans indeed use a similar recurrent grouping and segmentation strategy in global crowding effects. In crowding, visual elements interfere across space. To study how elements interfere over time, we use the Sequential Metacontrast psychophysical paradigm, in which perception of visual elements depends on elements presented hundreds of milliseconds later. We psychophysically characterize the temporal structure of this interference and propose a simple computational model. Our results support the idea that perception is a discrete process. Together, the results presented here provide stepping-stones towards a fuller understanding of the visual system by suggesting architectural changes needed for more human-like neural computations.


CHBH Seminars are free to attend and are open to all, both within and outside the University. Booking is not required.

If you have any questions, please contact Dr Ali Mazaheri (, Mr Chris Anderson ( or Dr Emily Loftus (