{"intvolume":" 27","type":"journal_article","extern":1,"volume":27,"publist_id":"2391","date_updated":"2021-01-12T07:52:26Z","abstract":[{"lang":"eng","text":"Although dendritic signal processing has been extensively investigated in hippocampal pyramidal cells, only little is known about dendritic integration of synaptic potentials in dentate gyrus granule cells, the first stage in the hippocampal trisynaptic circuit. Here we combined dual whole-cell patch-clamp recordings with high-resolution two-photon microscopy to obtain detailed passive cable models of hippocampal granule cells from adult mice. Passive cable properties were determined by direct fitting of the compartmental model to the experimentally measured voltage responses to short and long current pulses. The data are best fit by a cable model with homogenously distributed parameters, including an average specific membrane resistance (R(m)) of 38.0 kohms cm2, a membrane capacitance (C(m)) of 1.0 microF cm(-2), and an intracellular resistivity (R(i)) of 194 ohms cm. Computational analysis shows that signal propagation from somata into dendrites is more efficient in granule cells compared with CA1 pyramidal cells for both steady-state and sinusoidal voltage waveforms up to the gamma frequency range (f50% of 74 Hz). Similarly, distal synaptic inputs from entorhinal fibers can efficiently depolarize the somatic membrane of granule cells. Furthermore, the time course of distal dendritic synaptic potentials is remarkably fast, and temporal summation is restricted to a narrow time window in the range of approximately 10 ms attributable to the rapid dendritic charge redistribution during transient voltage signals. Therefore, the structure of the granule cell dendritic tree may be critically important for precise dendritic signal processing and coincidence detection during hippocampus-dependent memory formation and retrieval."}],"publication_status":"published","issue":"31","publication":"Journal of Neuroscience","title":"Subthreshold dendritic signal processing and coincidence detection in dentate gyrus granule cells","quality_controlled":0,"author":[{"first_name":"Christoph","full_name":"Schmidt-Hieber, Christoph","last_name":"Schmidt Hieber"},{"first_name":"Peter M","full_name":"Peter Jonas","orcid":"0000-0001-5001-4804","last_name":"Jonas","id":"353C1B58-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Bischofberger, Josef","first_name":"Josef","last_name":"Bischofberger"}],"doi":"10.1523/JNEUROSCI.1787-07.2007","_id":"3821","date_created":"2018-12-11T12:05:21Z","month":"01","citation":{"chicago":"Schmidt Hieber, Christoph, Peter M Jonas, and Josef Bischofberger. “Subthreshold Dendritic Signal Processing and Coincidence Detection in Dentate Gyrus Granule Cells.” Journal of Neuroscience. Society for Neuroscience, 2007. https://doi.org/10.1523/JNEUROSCI.1787-07.2007.","ista":"Schmidt Hieber C, Jonas PM, Bischofberger J. 2007. Subthreshold dendritic signal processing and coincidence detection in dentate gyrus granule cells. Journal of Neuroscience. 27(31), 8430–8441.","apa":"Schmidt Hieber, C., Jonas, P. M., & Bischofberger, J. (2007). Subthreshold dendritic signal processing and coincidence detection in dentate gyrus granule cells. Journal of Neuroscience. Society for Neuroscience. https://doi.org/10.1523/JNEUROSCI.1787-07.2007","short":"C. Schmidt Hieber, P.M. Jonas, J. Bischofberger, Journal of Neuroscience 27 (2007) 8430–8441.","ama":"Schmidt Hieber C, Jonas PM, Bischofberger J. Subthreshold dendritic signal processing and coincidence detection in dentate gyrus granule cells. Journal of Neuroscience. 2007;27(31):8430-8441. doi:10.1523/JNEUROSCI.1787-07.2007","mla":"Schmidt Hieber, Christoph, et al. “Subthreshold Dendritic Signal Processing and Coincidence Detection in Dentate Gyrus Granule Cells.” Journal of Neuroscience, vol. 27, no. 31, Society for Neuroscience, 2007, pp. 8430–41, doi:10.1523/JNEUROSCI.1787-07.2007.","ieee":"C. Schmidt Hieber, P. M. Jonas, and J. Bischofberger, “Subthreshold dendritic signal processing and coincidence detection in dentate gyrus granule cells,” Journal of Neuroscience, vol. 27, no. 31. Society for Neuroscience, pp. 8430–8441, 2007."},"date_published":"2007-01-01T00:00:00Z","day":"01","page":"8430 - 8441","status":"public","publisher":"Society for Neuroscience","year":"2007"}