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Estimating Neural Background Input with Controlled and Fast Perturbations: A Bandwidth Comparison between Inhibitory Opsins and Neural Circuits

To test the importance of a certain cell type or brain area it is common to make a “lack of function” experiment in which the neuronal population of interest is inhibited. Here we review physiological and methodological constraints for making controlled perturbations using the corticothalamic circui...

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Detalles Bibliográficos
Autor principal: Eriksson, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4983554/
https://www.ncbi.nlm.nih.gov/pubmed/27574506
http://dx.doi.org/10.3389/fncir.2016.00058
Descripción
Sumario:To test the importance of a certain cell type or brain area it is common to make a “lack of function” experiment in which the neuronal population of interest is inhibited. Here we review physiological and methodological constraints for making controlled perturbations using the corticothalamic circuit as an example. The brain with its many types of cells and rich interconnectivity offers many paths through which a perturbation can spread within a short time. To understand the side effects of the perturbation one should record from those paths. We find that ephaptic effects, gap-junctions, and fast chemical synapses are so fast that they can react to the perturbation during the few milliseconds it takes for an opsin to change the membrane potential. The slow chemical synapses, astrocytes, extracellular ions and vascular signals, will continue to give their physiological input for around 20 ms before they also react to the perturbation. Although we show that some pathways can react within milliseconds the strength/speed reported in this review should be seen as an upper bound since we have omitted how polysynaptic signals are attenuated. Thus the number of additional recordings that has to be made to control for the perturbation side effects is expected to be fewer than proposed here. To summarize, the reviewed literature not only suggests that it is possible to make controlled “lack of function” experiments, but, it also suggests that such a “lack of function” experiment can be used to measure the context of local neural computations.