Reverse engineering is a technology to identify an unknown system in a data-driven fashion based on pairs of its input and output. In this talk, I present several studies to identify neural systems which employ reverse engineering methods. Since we are interested in dynamical functions of neural systems, we rely on time-lapse imaging techniques. First, I introduce a study to identify a hippocampal neuronal network based on functional multi-neuron calcium imaging data. When identifying the neuronal network, we used a sparse estimation method for a generalized linear model. For the estimation, a robust false positive control in the multiple simultaneous testing in terms of empirical Bayesian statistics was performed. As a result, we obtained two clusters of functional connectivity; the first one was of short latency and occupied by facilitating connections, and the second one was of rather long latency and included suppressive connections. A similar technique was then applied to identifying a neuron-glia system, employing an extended version of the generalized linear model. According to the reverse engineering-based method, we found that glia affect neuronal activities with the peak latency of about 500msec, being consistent with the knowledge from existing experimental studies. Next, I introduce a study to identify neuronal functions involved in the thermotaxis system of C. Elegans. The worms have sensory neurons that response to the external temperature and drive exploitative or explorative behaviors to reach their preferable temperature. Our reverse engineering-based method has elucidated some important characters of the neurons; for example, they detect the temperature difference regardless of the individuals or the preferred temperature. As such, the reverse engineering-based methods can provide a powerful analysis tool to data-driven neuroscience especially when the underlying mechanisms that emerge various neural functions are largely unknown. This study was partly supported by a contract with the Ministry of Internal Affairs and Communications entitled 'Novel and innovative R & D making use of brain structures'.