P257 Basket cell computational modeling predicts signal filtering of Purkinje cell responses
Martina F. Rizza*1,Stefano Masoli1, Teresa Soda1, Francesca Prestori1, Egidio D’Angelo1,2
1Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy 2Digital Neuroscience Center, IRCCS Mondino Foundation, Pavia, Italy
*Email: martinafrancesca.rizza@unipv.it
Introduction Cerebellar basket cells (BC), located in the bottom 1/3 of the molecular layer (ML), play an important role in controlling the activity of Purkinje cells (PC) via inhibitory synaptic transmission. BCs receive excitatory synaptic inputs from parallel fibers (pf) and transmit inhibitory synaptic inputs to BCs and PCs. We reconstructed a multi-compartmental biophysically realistic BC model in Python-NEURON to investigate BC intrinsic and synaptic electrophysiological properties and their impact on PC model responses [1,2,3]. The SC model [4] was included to reconstruct a ML microcircuit. Simulationspredicted that BC and SC operate in tandem, setting the frequency band of PC transmission through the regulation of the PC frequency/response curve.
Methods Starting from morphological reconstructions taken from cerebellar tissue and patch-clamp recordings, we implemented conductance-basedmulti-compartmental models of BCwith Python 3 and NEURON 8.2[5].The model maximum ionic conductances were tuned to match the firing pattern revealed by whole-cell patch-clamp recordings from mice cerebellar slices.Mouse SC[4] and BC models were connected with a multi-compartmental mouse PC model[1,2,3] to test their impact when stimulated by excitatory synaptic inputs.Simulations were performed on an AMD Threadripper 7980X 64 cores using fixed time step (0.025ms) and temperature set to 32°.
Results Simulations reproduced whole-cell patch-clamp experimental results, showing autorhythmic activity, an almost linear I/O relationship to positive current injections, pauses generated after positive current injections,sag after the negative current injections,AMPA and NMDA receptors-mediated excitatory postsynaptic responses following pf inputs.SC and BCsimulations showed thefiltering properties on PC activity, highlighting thatBCs modulate low-frequency PC discharges through somatic GABAergic synapses, while SCs act on high-frequency responses through dendritic GABAergic synapses.
Discussion BC modeling reproduced the cellular intrinsic excitability and the synaptic activity, investigating thefrequency‑dependent short‑term dynamics at pf-BC synapses and the frequency-dependenceof BC input–output gain functions. Simulations predicted BC and SC filtering of PC responses, showing thatthe intensity and bandwidth of ML filtering is modulated by the number of active synapses between pfs-SCs-PCs and pfs-BCs-PCs. SCs and BCs emerge as critical elements controlling cerebellar processing in time and frequency domains. Tuning of transmission bandwidth and delay through specific membrane and synaptic mechanisms contributes to explain the role of SCs and BCs in motor learning and control.
Acknowledgements This project/research received funding from the European Union’s Horizon Europe Programme under the Specific Grant Agreement No. 101147319 (EBRAINS 2.0 Project) and the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Framework Partnership Agreement No. 650003 (HBP FPA). References 1.https://doi.org/10.3389/fncel.2015.00047 2.https://doi.org/10.1038/s42003-023-05689-y 3.https://doi.org/10.3389/fncel.2017.00278 4.https://doi.org/10.1038/s41598-021-83209-w 5.https://doi: 10.3389/neuro.11.001.2009
