抄録
From the system theoretic point of view, methods for exploring neural mechanism could be categorized into those that use (1) the transient response of the neural system to an input, (2) the response of the neural system to additional perturbation, and (3) the steady state properties of neural system when there is a steady input. By observing these responses and properties, we can explore the neural mechanisms of brain functions. In this talk, I present examples for approaches (1) and (2). (1) We analyzed population behaviors of face-responsive neurons in the IT cortex. To clarify their transient responses, we applied Principal Component and Mixture of Gaussian analyses to single neuron responses recorded by Sugase et al. (1999). We found that the population vectors of neural responses split into three clusters corresponding to human faces, monkey faces and other simple shapes in the early phase of the response (90-140msec) and that these three clusters split into sub-clusters corresponding to finer categorizations in the later phase (140-190msec). (2) We investigated the neural mechanism for transcranial magnetic stimulation (TMS). We found that the temporal properties of visual percept suppression induced by TMS can be well explained by either an isolated single neuron model (Kamitani et al, 2001) or a simple excitatory-inhibitory balanced network. Secondly, we show that sustained inhibitory effect of subthreshold TMS is reproduced by the network model, but not by the single neuron model. Then, we conclude that the TMS can be used as a powerful tool to perturb neural computation in population level rather than single neuron level. [Jpn J Physiol 54 Suppl:S15 (2004)]
