Neuroscience Institute, NYU Langone Health, New York, NY 10016, USA.
Neural Computation Laboratory, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy.
Science. 2020 Jun 19;368(6497). doi: 10.1126/science.aba2357.
How does neural activity generate perception? Finding the combinations of spatial or temporal activity features (such as neuron identity or latency) that are consequential for perception remains challenging. We trained mice to recognize synthetic odors constructed from parametrically defined patterns of optogenetic activation, then measured perceptual changes during extensive and controlled perturbations across spatiotemporal dimensions. We modeled recognition as the matching of patterns to learned templates. The templates that best predicted recognition were sequences of spatially identified units, ordered by latencies relative to each other (with minimal effects of sniff). Within templates, individual units contributed additively, with larger contributions from earlier-activated units. Our synthetic approach reveals the fundamental logic of the olfactory code and provides a general framework for testing links between sensory activity and perception.
神经活动如何产生知觉?发现对知觉有影响的空间或时间活动特征(如神经元身份或潜伏期)的组合仍然具有挑战性。我们训练老鼠识别由光遗传学激活的参数定义模式构建的合成气味,然后在广泛和受控的时空维度干扰下测量感知变化。我们将识别建模为模式与学习模板的匹配。最佳预测识别的模板是按彼此相对潜伏期排序的空间识别单元序列(嗅探的影响最小)。在模板内,各个单元以累加的方式做出贡献,较早激活的单元贡献更大。我们的合成方法揭示了嗅觉编码的基本逻辑,并为测试感官活动与知觉之间的联系提供了一个通用框架。