Multifaceted luminance gain control beyond photoreceptors in Drosophila.

Animals 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 the 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.

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

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 interneurons L1, L2, and L3. Each of these neurons encodes contrast and luminance differently and distributes information asymmetrically across both ON and OFF contrast-selective pathways. Behavioral responses to both ON and OFF stimuli rely on a luminance-based correction provided by L1 and L3, wherein L1 supports contrast computation linearly, and L3 non-linearly amplifies dim stimuli. Therefore, L1, L2, and L3 are not specific inputs to ON and OFF pathways but the lamina serves as a separate processing layer that distributes distinct luminance and contrast information across ON and OFF pathways to support behavior in varying conditions.

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

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 explain behavioral responses in sudden dim light. The luminance-sensitive pathway via the L3 neuron is required for visual processing in such rapidly changing light conditions, ensuring contrast constancy when pure contrast sensitivity underestimates a stimulus. Thus, retaining a peripheral feature, luminance, in visual processing is required for robust behavioral responses.

A Class of Visual Neurons with Wide-Field Properties Is Required for Local Motion Detection.

Visual motion cues are used by many animals to guide navigation across a wide range of environments. Long-standing theoretical models have made predictions about the computations that compare light signals across space and time to detect motion. Using connectomic and physiological approaches, candidate circuits that can implement various algorithmic steps have been proposed in the Drosophila visual system. These pathways connect photoreceptors, via interneurons in the lamina and the medulla, to direction-selective cells in the lobula and lobula plate. However, the functional architecture of these circuits remains incompletely understood. Here, we use a forward genetic approach to identify the medulla neuron Tm9 as critical for motion-evoked behavioral responses. Using in vivo calcium imaging combined with genetic silencing, we place Tm9 within motion-detecting circuitry. Tm9 receives functional inputs from the lamina neurons L3 and, unexpectedly, L1 and passes information onto the direction-selective T5 neuron. Whereas the morphology of Tm9 suggested that this cell would inform circuits about local points in space, we found that the Tm9 spatial receptive field is large. Thus, this circuit informs elementary motion detectors about a wide region of the visual scene. In addition, Tm9 exhibits sustained responses that provide a tonic signal about incoming light patterns. Silencing Tm9 dramatically reduces the response amplitude of T5 neurons under a broad range of different motion conditions. Thus, our data demonstrate that sustained and wide-field signals are essential for elementary motion processing.