Data from: Title: A model for non-monotonic intensity coding

Peripheral neurons of most sensory systems increase their response with increasing stimulus intensity. Behavioural responses, however, can be specific to some intermediate intensity level whose particular value might be innate or associatively learned. Learning such a preference requires an adjustable transformation from a monotonic stimulus representation at the sensory periphery to a non-monotonic representation for the motor command. How do neural systems accomplish this task? We tackle this general question focusing on odour intensity learning in the fruit fly, whose first- and second-order olfactory neurons show monotonic stimulus-response curves. Nevertheless, flies form associative memories specific to particular trained odour intensities. Thus, downstream of the first two olfactory processing layers, odour intensity must be re-coded to enable intensity-specific associative learning. We present a minimal, feed-forward, three-layer circuit, which implements the required transformation by combining excitation, inhibition, and, as decisive third element, homeostatic plasticity. Key features of this circuit motif are consistent with the known architecture and physiology of the fly olfactory system, whereas alternative mechanisms are either not composed of simple, scalable building blocks or not compatible with physiological observations. The simplicity of the circuit and the robustness of its function under parameter changes make this computational motif an attractive candidate for tunable non-monotonic intensity coding.

多数感觉系统的外周神经元（peripheral neurons）的响应会随刺激强度升高而增强。然而，行为反应可特异性对应某一中间强度水平，该水平的具体数值既可能是先天固有，也可通过联想学习获得。习得这类偏好需要完成一项可调节的转换：将感觉外周处的单调刺激表征转换为适配运动指令的非单调表征。神经系统如何完成这一任务？我们以果蝇的气味强度学习为研究对象，聚焦这一通用问题。果蝇的一级和二级嗅觉神经元呈现单调的刺激-反应曲线，但果蝇仍能形成针对特定训练过的气味强度的联想记忆。因此，在嗅觉加工的前两层下游，气味强度必须被重新编码，以支持强度特异性的联想学习。我们提出了一种极简的前馈三层环路，通过结合兴奋、抑制，以及作为决定性第三要素的稳态可塑性（homeostatic plasticity），实现了所需的转换。该环路基序的关键特征与果蝇嗅觉系统已知的结构和生理特性相符；而替代机制要么无法由简单、可扩展的基本单元构成，要么与生理观测结果不兼容。该环路结构简洁，且其功能在参数变化下仍具备鲁棒性，因此这一计算基序是实现可调谐非单调强度编码的极具吸引力的候选方案。