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 trans- formation 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 transfor...多数感觉系统的外周神经元（peripheral neurons）响应会随刺激强度升高而增强。但行为响应却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的，也可通过联想学习获得。习得此类偏好，需要将感觉外周处的单调刺激表征（stimulus representation），转换为运动指令（motor command）所需的非单调表征，且该转换过程具备可调节性。神经系统是如何完成这一任务的？我们聚焦果蝇的气味强度学习这一方向来解答这一通用问题：果蝇的一级与二级嗅觉神经元（olfactory neurons）均呈现单调的刺激-响应曲线（stimulus–response curves）。但果蝇仍可形成针对特定训练气味强度的联想记忆（associative memories）。因此，在嗅觉处理的前两层下游区域，气味强度必须经过重新编码，才能实现针对强度的特异性联想学习。我们提出了一个极简的前馈（feed-forward）三层神经环路，可实现上述所需的转换……