Multifaceted luminance gain control beyond photoreceptors inDrosophila

Abstract

AbstractAnimals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that, downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments.Significance StatementLuminance varies slowly throughout the day, or rapidly during movements. Yet, animals show luminance-invariant behaviors to visual cues across these scenarios. Combining in vivo imaging, behavioral analyses and computational modeling, we here show that diverse luminance gain control operations required for robust visual processing exist in the fly visual circuitry beyond photoreceptors. Despite relying on a single luminance-sensitive neuron type, this luminance gain control is multifaceted, in that it achieves both gain increments and decrements at two different timescales. Overall, the study sheds light on a circuit gain control strategy operating at multiple timescales, which together challenge luminance-invariant visual behaviors in natural environments.