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Mapping Inhibitory Neuronal Circuits by Laser Scanning Photostimulation
Published on: October 6, 2011
Detection of input sites in scanning photostimulation data based on spatial correlations
Michael H K Bendels1, Prateep Beed, Dietmar Schmitz
1Division of Neurobiology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Journal of Neuroscience Methods
|August 14, 2010
Summary
This study introduces a new algorithm to identify presynaptic sites in brain slices, even with high spontaneous activity. The method reliably detects neuronal connections by analyzing clusters of light-evoked responses.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Synaptic Plasticity
Background:
- Scanning photostimulation is crucial for mapping functional microcircuits in brain slices.
- Distinguishing light-evoked from spontaneous synaptic responses is essential for identifying presynaptic partners.
- High spontaneous synaptic rates can challenge the accurate identification of neuronal connections.
Purpose of the Study:
- To develop and validate a novel algorithm for identifying presynaptic sites in the entorhinal cortex layer II.
- To overcome challenges posed by high spontaneous synaptic rates (up to 10Hz) in functional circuit analysis.
- To establish a reliable method for quantifying afferent connectivity based on photostimulation data.
Main Methods:
- Developed a detection algorithm identifying 'hit' locations where photo-evoked synaptic events significantly exceed statistical independence.
- Algorithm operates on single trials without using EPSC amplitude information.
- Validated reliability through repeated stimulations and TTX-induced synaptic blockade; employed Bayesian formalism for estimating presynaptic partner numbers.
Main Results:
- Successfully identified presynaptic sites in entorhinal cortex layer II despite high spontaneous synaptic rates.
- Demonstrated that hit density is a reliable indicator of afferent connectivity.
- Bayesian estimation showed good agreement between predicted and actual numbers of input cells.
Conclusions:
- The developed algorithm reliably identifies presynaptic sites and quantifies neuronal connectivity in complex network conditions.
- Hit density serves as a robust metric for assessing afferent synaptic connections.
- This method enhances the study of functional microcircuitry in brain slices with high spontaneous activity.
