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Vision Dynamically Changing Environments

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Seminar✓ Recording AvailableNeuroscience

Vision in dynamically changing environments

Marion Silies

Prof

Johannes Gutenberg-Universität Mainz, Germany

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Sunday, May 17, 2020

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Sunday, May 17, 2020

2:00 PM Europe/London

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Host: Sussex Visions

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Sussex Visions

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Abstract

Many visual systems can process information in dynamically changing environments. In general, visual perception scales with changes in the visual stimulus, or contrast, irrespective of background illumination. This is achieved by adaptation. However, visual perception is challenged when adaptation is not fast enough to deal with sudden changes in overall illumination, for example when gaze follows a moving object from bright sunlight into a shaded area. We have recently shown that the visual system of the fly found a solution by propagating a corrective luminance-sensitive signal to higher processing stages. Using in vivo two-photon imaging and behavioural analyses we showed that distinct OFF-pathway inputs encode contrast and luminance. The luminance-sensitive pathway is particularly required when processing visual motion in contextual dim light, when pure contrast sensitivity underestimates the salience of a stimulus. Recent work in the lab has addressed the question how two visual pathways obtain such fundamentally different sensitivities, given common photoreceptor input. We are furthermore currently working out the network-based strategies by which luminance- and contrast-sensitive signals are combined to guide appropriate visual behaviour. Together, I will discuss the molecular, cellular, and circuit mechanisms that ensure contrast computation, and therefore robust vision, in fast changing visual scenes.

Topics

OFF-pathwayadaptationcontrast sensitivitydrosophilaelectrophsyiologyinvertebratesluminancephotoreceptor inputretinatwo-photon imagingvisionvisual motionvisual pathwaysvisual perception

About the Speaker

Marion Silies

Prof

Johannes Gutenberg-Universität Mainz, Germany

Contact & Resources

Personal Website

ncl-idn.biologie.uni-mainz.de

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