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. 2019 Oct 23;10:4814. doi: 10.1038/s41467-019-12736-y

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — Modelling TC summation recapitulates spiking phenotypes of Fmr1-KO layer 4 SCs. a Schematic of modelling approach. Left: Five grouped covariates measured from Fmr1^+/Y and Fmr1^−/Y recordings used in simulation. Centre: Simulated synaptic inputs were tuned with kinetics of recorded currents. Right: Parameter spaces were explored in silico to find conditions that either enhanced or suppressed firing in the Fmr1-KO model compared with the WT model. b Left: Input frequency dependence of simulated spiking responses for model Layer 4 neurons receiving different strengths of FFI (G/A ratios between 0 and 10 tested). Coloured areas for each modelled genotype indicate combinations of FFI strength/stimulation frequency at which the models fired at least one spike per trial. Red indicates firing parameter ranges in addition to those of the WT model. Note: (1) moderate strength FFI in the WT model prevents spike firing even at high input frequencies (2) the increased number of simulation conditions leading to spiking in the Fmr1^−/Y model, (3) the insensitivity of spiking regulation in the Fmr1^−/Y model to inhibitory tone even with FFI strengths elevated to extreme levels (10 trials overlaid). Right: example traces for simulated spiking by the two models at different parameter combinations. Inset: note later and more variable spike times in the Fmr1^−/Y model. Scale: 20 mV/50 ms. c In addition to affecting the overall spike firing response shown in (b), genotype-dependent effects were observed in the latency, timing variability and count of spikes fired. Spikes fired later and with lower temporally precision in the Fmr1^−/Y model across a broad range of model conditions, even with the FFI strength increased to the extreme values as observed in the Fmr1^−/Y recordings. More conditions led to spiking in the Fmr1^−/Y, despite a slight decrease in numbers of spikes fired per trial across the distribution compared with Fmr1^+/Y simulations