Data-driven model of striatal external input Ilaria Carannante1, Yvonne Johansson2, Johannes Hjorth1, Gilad Silberberg 2, Jeanette Hellgren Kotaleski1,2 1 KTH Royal Institute of Technology, Department of Computational Science and Technology, Stockholm, Sweden. 2 Karolinska Institutet, Department of Neuroscience, Stockholm, Sweden. The basal ganglia play an important role in a variety of functions including decision making and action selection mainly based on input from cortex, thalamus and the dopamine system. Striatum is the input stage of the basal ganglia. Here we present a new approach to model the postsynaptic currents mediated by NMDA or AMPA receptors which allows a more accurate description of them. Then we model the extrinsic inputs from cortex and thalamus to the different populations of striatal neurons (striatal projection neurons (dSPNs and iSPNs); cholinergic (ChIN), fast-spiking (FS), and low-threshold spiking (LTS) interneurons). We present a data-driven model of the postsynaptic currents mediated by AMPA or NMDA (average currents are shown in Fig2). We describe the dynamics using three exponentials: one for the rising and two for the decay phases. The use of three exponentials (instead of the generally used two) allows a more accurate description of the currents without compromising the performace of the models. A comparison between the different current models is shown in Fig3. We introduce a classification of the synaptic traces for each input region and each cell type. Traces belonging to the same class are normalized and the average trace is extracted. An example of this process is shown in Fig4. We simulate the extrinsic inputs by placing and stimulating the glutamatergic synapses on multicompartmental neuron models. These are based on detailed reconstructed morphology and include ion channels models according to RNA-seq data. An example of LTS models is shown in Fig5. The models are able to capture both subthreshold and suprathreshold current-voltage responses. [1] Hjorth, J. J., Kozlov, A., Carannante, I., Nylén, J. F., Lindroos, R., Johansson, Y., ... & Grillner, S. (2020). The microcircuits of striatum in silico. Proceedings of the National Academy of Sciences, 117(17), 9554-9565. [2] Johansson, Y., & Silberberg, G. (2020). The functional organization of cortical and thalamic inputs onto five types of striatal neurons is determined by source and target cell identities. Cell reports, 30(4), 1178-1194. [3] Uziel, A., & Markram, H. (2000). Synchrony Generation in Recurrent Networks with Frequency-Dependent Synapses. Journal of Neuroscience, 20(1), RC50-RC50. Funding: The study was supported by the Swedish research council (VR-M-2020-01652); Swedish e-Science Research Centre (SeRC); EU/Horizon 2020 no. 945539 (HBP SGA3); KTH Digital Futures. The simulations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC KTH partially funded by the Swedish Research Council through grant agreement no. 2018-05973. We acknowledge the use of Fenix Infrastructure resources, which are partially funded from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858. Conclusions and future works Synapses are critical when investigating microcircuit functions and dynamics, therefore it is necessary to have a computationally efficient and accurate framework to model them. Here we are improving such a pipeline using morphologically detailed neurons. Our method is generic and hence applicable to any brain region. We are working on the integration of these models into large scale networks [1] as part of our ongoing effort to create detailed simulations of the entire striatum. We optimise the parameters of a Tsodyks-Markram model [3] to match and reproduce the different behaviours observed experimentally [2]. A comparison between the different synapse models (based on the different current models of NMDA and AMPA