Institute of Developmental and Neurobiology, Johannes-Gutenberg University Mainz, Hanns-Dieter-Hüsch-Weg 15, 55128 Mainz, Germany.
Max Planck Institute for Brain Research, Max-von-Laue-Straße 4, 60438 Frankfurt am Main, Germany; Department of Neurophysiology, Radboud University, Heyendaalseweg 135, 6525 EN Nijmegen, the Netherlands.
Curr Biol. 2023 Jul 10;33(13):2632-2645.e6. doi: 10.1016/j.cub.2023.05.024. Epub 2023 Jun 6.
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.
动物在自然环境中导航时,必须应对其感官输入的巨大变化。例如,视觉系统在许多时间尺度上处理亮度变化,从白天的缓慢变化到活动行为期间的快速变化。为了保持亮度不变的感知,视觉系统必须在不同的时间尺度上调整其对变化亮度的敏感性。我们证明,仅在光感受器中进行亮度增益控制不足以解释快速和慢速时间尺度上的亮度不变性,并揭示了在果蝇眼中调整增益超过光感受器的算法。我们结合成像和行为实验以及计算建模,表明在光感受器下游,从单个亮度敏感神经元类型 L3 接收输入的电路在快速和慢速时间尺度上实现增益控制。这种计算是双向的,因为它可以防止在低亮度下低估对比度和在高亮度下高估对比度。算法模型分离了这些多方面的贡献,并表明双向增益控制发生在两个时间尺度上。该模型实现了亮度和对比度的非线性相互作用,以在快速时间尺度上实现增益校正,并实现了暗敏感通道,以在慢速时间尺度上提高对暗刺激的检测。总之,我们的工作展示了单个神经元通道如何执行多种计算,以在多个时间尺度上实现增益控制,这些控制对于在自然环境中导航都很重要。