Luminance Information Is Required for the Accurate Estimation of Contrast in Rapidly Changing Visual Contexts.

2020

Summary Visual perception scales with changes in the visual stimulus, or contrast, irrespective of background illumination. However, visual perception is challenged when adaptation is not fast enough to deal with sudden declines in overall illumination, for example, when gaze follows a moving object from bright sunlight into a shaded area. Here, we show that the visual system of the fly employs a solution by propagating a corrective luminance-sensitive signal. We use in vivo 2-photon imaging and behavioral analyses to demonstrate that distinct OFF-pathway inputs encode contrast and luminance. Predictions of contrast-sensitive neuronal responses show that contrast information alone cannot ex…

An optimal population code for global motion estimation in local direction-selective cells

2021

AbstractNervous systems allocate computational resources to match stimulus statistics. However, the physical information that needs to be processed depends on the animal’s own behavior. For example, visual motion patterns induced by self-motion provide essential information for navigation. How behavioral constraints affect neural processing is not known. Here we show that, at the population level, local direction-selective T4/T5 neurons in Drosophila represent optic flow fields generated by self-motion, reminiscent to a population code in retinal ganglion cells in vertebrates. Whereas in vertebrates four different cell types encode different optic flow fields, the four uniformly tuned T4/T5…

Author response: ON selectivity in the Drosophila visual system is a multisynaptic process involving both glutamatergic and GABAergic inhibition

2019

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

2022

The accurate processing of contrast is the basis for all visually guided behaviors. Visual scenes with rapidly changing illumination challenge contrast computation because photoreceptor adaptation is not fast enough to compensate for such changes. Yet, human perception of contrast is stable even when the visual environment is quickly changing, suggesting rapid post receptor luminance gain control. Similarly, in the fruit fly Drosophila, such gain control leads to luminance invariant behavior for moving OFF stimuli. Here, we show that behavioral responses to moving ON stimuli also utilize a luminance gain, and that ON-motion guided behavior depends on inputs from three first-order interneuro…

(A,B) In vivo GCaMP6f signals recorded in layers M1, M5 and M9/10 of Mi1 (A) and Tm3 (B) neurons, before (blue, green) and after (gray, red) applicat…

2019

Sensory systems sequentially extract increasingly complex features. ON and OFF pathways, for example, encode increases or decreases of a stimulus from a common input. This ON/OFF pathway split is thought to occur at individual synaptic connections through a sign-inverting synapse in one of the pathways. Here, we show that ON selectivity is a multisynaptic process in the Drosophila visual system. A pharmacogenetics approach demonstrates that both glutamatergic inhibition through GluClα and GABAergic inhibition through Rdl mediate ON responses. Although neurons postsynaptic to the glutamatergic ON pathway input L1 lose all responses in GluClα mutants, they are resistant to a cell-type-specifi…

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

2022

Source data of the paper Ketkar, Gür, Molina-Obando et al. 2022, eLife. We analyzed the behavioral contribution and physiological response properties of first order interneurons L1, L2 and L3 in the Drosophila melanogaster visual system. Data are sorted by figures and comprise either behavioral measurements of flies walking on an air-cushioned ball while being shown visual stimuli, or in vivo two photon microscopy recordings of L1-L3 calcium responses. Please find all relevant information to use the data in the README file. The code to analyze the data, either written in Matlab or Python, is found at https://github.com/silieslab/Ketkar-Gur-MolinaObando-etal2022