Abstract
The idea of closed-loop interaction in in vitro and in vivo electrophysiology has been successfully implemented in the dynamic clamp concept strongly impacting the research of membrane and synaptic properties of neurons. In this paper we show that this concept can be easily generalized to build other kinds of closed-loop protocols beyond (or in addition to) electrical stimulation and recording in neurophysiology and behavioral studies for neuroethology. In particular, we illustrate three different examples of goal-driven real-time closed-loop interactions with drug microinjectors, mechanical devices and video event driven stimulation. Modern activity-dependent stimulation protocols can be used to reveal dynamics (otherwise hidden under traditional stimulation techniques), achieve control of natural and pathological states, induce learning, bridge between disparate levels of analysis and for a further automation of experiments. We argue that closed-loop interaction calls for novel real time analysis, prediction and control tools and a new perspective for designing stimulus-response experiments, which can have a large impact in neuroscience research.
Highlights
The idea of a direct closed-loop interaction with neurons goes back to the beginnings of electrophysiology in the 1940s when the work of George Marmount and Kenneth Cole resulted in the voltage clamp technique that measures currents across the membrane of excitable cells while holding the membrane voltage at a set level [1,2]
A further complication is that neural systems are highly nonlinear and adaptive, usually working in transient regime [21,22,23], which adds to the problem of partial observation
Closed-loop Drug-microinjection In dynamic clamp protocols, microelectrodes are used to record voltage and deliver currents in an activity-dependent manner. Such closed-loop allows to build an artificial chemical synapse by modeling the dynamics of a synaptic current triggered by a presynaptic spike
Summary
The idea of a direct closed-loop interaction with neurons goes back to the beginnings of electrophysiology in the 1940s when the work of George Marmount and Kenneth Cole resulted in the voltage clamp technique that measures currents across the membrane of excitable cells while holding the membrane voltage at a set level [1,2]. The mechanisms to extract information from them and the way to drive effective stimulation are very limited. In this context, closed-loop interaction provides a large variety of possibilities to characterize dynamics from partial measurements and to exert control or induce learning through activity-dependent stimulation
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