Abstract
GABAergic interneurons in cortical circuits control the activation of principal cells and orchestrate network activity patterns, including oscillations at different frequency ranges. Recruitment of interneurons depends on integration of convergent synaptic inputs along the dendro-somatic axis; however, dendritic processing in these cells is still poorly understood.
In this chapter, we summarise our results on the cable properties, electrotonic structure and dendritic processing in “basket cells” (BCs; Nörenberg et al. 2010), one of the most prevalent types of cortical interneurons mediating perisomatic inhibition. In order to investigate integrative properties, we have performed two-electrode whole-cell patch clamp recordings, visualised and reconstructed the recorded interneurons and created passive single-cell models with biophysical properties derived from the experiments. Our results indicate that membrane properties, in particular membrane resistivity, are inhomogeneous along the somato-dendritic axis of the cell. Derived values and the gradient of membrane resistivity are different from those obtained for excitatory principal cells. The divergent passive membrane properties of BCs facilitate rapid signalling from proximal basal dendritic inputs but at the same time increase synapse-to-soma transfer for slow signals from the distal apical dendrites.
Our results demonstrate that BCs possess distinct integrative properties. Future computational models investigating the diverse functions of neuronal circuits need to consider this diversity and incorporate realistic dendritic properties not only of excitatory principal cells but also various types of inhibitory interneurons.
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Notes
- 1.
All model BCs can be downloaded from ModelDB (#140789; http://senselab.med.yale.edu/modeldb/).
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Matthiä, A., Bartos, M., Vida, I. (2014). Role of Non-uniform Dendrite Properties on Input Processing by GABAergic Interneurons. In: Cuntz, H., Remme, M., Torben-Nielsen, B. (eds) The Computing Dendrite. Springer Series in Computational Neuroscience, vol 11. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8094-5_19
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