A simulation framework for acute extracellular recordings

Extracellular recordings are a key tool to study the activity of neurons in vivo. Especially in the case of experiments with behaving animals, however, the procedure of electrode placement can take a considerable amount of expensive and restricted experimental time. Furthermore, due to tissue drifts and other sources of variability in the recording setup, the position of electrodes with respect to the neurons under study can change, causing degraded recording quality (non-stationarities).

Here we devloped a simulation framework for acute extracellular recordings. Neurons and electrodes are modelled as objects in a spatio-temporal state space. A generative data model allows to construct putative voltage traces at electrode positions, as the superposition of time-and-distant-dependant characteristic waveforms of the simulated single neurons. All objects may be positioned arbitrarily during the simulation. This kind of framework allows to simulate acute experimental conditions and provides grounds to evaluate feedback-dependant algorithms (positioning systems, online/adaptive spikesorting). The simulated data was found to resemble data acquired from acute extracellular recordings from PFC of awake behaving maquac.