Applying Information Theory to Neuronal Networks: From Theory to Experiments

摘要: Information-theory is being increasingly used to analyze complex, self-organizing processes on networks, predominantly in analytical and numerical studies. Perhaps one of the most paradigmatic complex systems a network neurons, which cognition arises from information storage, transfer, processing among individual neurons. In this article we review experimental techniques suitable for validating information-theoretical predictions simple neural as well generating new hypotheses. Specifically, focus that may be measure both (microcircuit) anatomy neuronal activity simultaneously. This needed study role structure emergent collective dynamics, reasons characteristics processing. We discuss detail two techniques, namely calcium imaging application multi-electrode arrays networks culture, their advantages limitations an accessible manner non-experts. particular, show each technique induces qualitatively different type error measured mutual information. The ultimate goal work bridge gap between theorists experimentalists shared understanding behavior