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Detection of input sites in scanning photostimulation data based on spatial correlations

Item Type:Article
Title:Detection of input sites in scanning photostimulation data based on spatial correlations
Creators Name:Bendels, M.H.K. and Beed, P. and Schmitz, D. and Johenning, F.W. and Leibold, C.
Abstract:Scanning photostimulation is a well-established method for studying the functional microcircuitry in brain slices. Light-evoked responses are thereby taken as an indicator for a connected presynaptic partner. Such an approach thus requires a clear distinction between the photo-evoked and the spontaneous responses. Here we show that, for a data set from entorhinal cortex layer II with high spontaneous synaptic rates of up to 10Hz, it is possible to identify presynaptic sites. The underlying detection algorithm is based on the finding that a presynaptic cell has several neighboring activation sites, resulting in the clustered appearance of specific photo-evoked inputs. The main idea behind this approach is to identify "hit" locations at which the number of intracellularly recorded synaptic events is significantly larger as expected from the hypothesis of statistical independence. The algorithm works without making use of EPSC amplitude information and for single trials, i.e., each site is stimulated only once. The hit maps are tested upon reliability by repeated stimulations and by blocking synaptically mediated responses via TTX. Furthermore, based on the hit density of surrogate data, we devise a Bayesian formalism to estimate the number of presynaptic partners. In these simulations we find good agreement between estimated and real number of input cells, which shows that the hit density can be used as a reliable measure for afferent connectivity.
Keywords:Laser Scanning Photostimulation, Optical Uncaging, Functional Anatomy, Entorhinal Cortex, Animals, Rats, Wistar Rats
Source:Journal of Neuroscience Methods
ISSN:0165-0270
Publisher:Elsevier (The Netherlands)
Volume:192
Number:2
Page Range:286-295
Date:15 October 2010
Official Publication:https://doi.org/10.1016/j.jneumeth.2010.08.006
PubMed:View item in PubMed

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