Hjorth et al. 2020

Authors: Johannes Hjorth^2,*, Alexander Kozlov^1,2,*, Ilaria Carannante^2,**, Johanna Frost Nylén^1,**, Robert Lindroos^1,2,**, Yvonne Johansson^1,***, Anna Tokarska^1,***, Matthijs C. Dorst^1,***, Shreyas M Suryanarayana¹, Gilad Silberberg¹, Jeanette Hellgren Kotaleski^2,****, Sten Grillner^1,****

Author information: ¹Department of Neuroscience, Karolinska Institutet, SE 17165 Stockholm and ²Science for Life Laboratory, School of Computer Science and Communication, KTH Royal Institute of Technology, SE-10044, Stockholm, Sweden.

*JH and AK, overall design of the striatal simulation (equal contribution); **IC, JFN and RL contributed equally in simulating different subtypes of neurons and reconstructing their morphology and the dopaminergic input; ***YJ, AT and MD recorded experimentally subtypes of neurons and their connectivity that were modelled by the other team (equal contribution); SMS contributed with overall implementation; GS supervised the experimental part; ****JHK and SG supervised all aspects of the project (equal contribution).

Corresponding author: Sten Grillner (sten.grillner@ki.se)

Journal: Proc. Natl. Acad. Sci. USA

Download Url: https://www.pnas.org/content/early/2020/04/21/2000671117

Citation: Hjorth J, Kozlov A, Carannante I, Frost Nylén J, Lindroos R, Johansson Y, Tokarska A, Dorst MC, Suryanarayana SM, Silberberg G, Hellgren Kotaleski J, Grillner S (2020) The microcircuits of striatum in silico. Proc Natl Acad Sci USA 2020.

DOI: https://doi.org/10.1073/pnas.2000671117

Licence: the Creative Commons Attribution (CC BY) license applies for all files. Under this Open Access license anyone may copy, distribute, or reuse the files as long as the authors and the original source are properly cited.

Abstract:

The basal ganglia play an important role in decision-making and selection of action primarily based on input from cortex, thalamus and the dopamine system. Their main input structure, striatum, is central to this process. It consists of two types of projection neurons, together representing 95% of the neurons, and 5% of interneurons, among which are the cholinergic, fastspiking and low threshold spiking subtypes. The membrane-properties, soma-dendritic shape and intrastriatal- and extrastriatal synaptic interactions of these neurons are quite well described in the mouse, and therefore they can be simulated in sufficient detail to capture their intrinsic properties, as well as the connectivity. We focus on simulation at the striatal cellular/microcircuit level, in which the molecular/subcellular and systems levels meet. We present for the first time a nearly full-scale model of the mouse striatum using available data on synaptic connectivity, cellular morphology and electrophysiological properties to create a microcircuit mimicking the real network. A striatal volume is populated with reconstructed neuronal morphologies with appropriate cell densities, and then we connect neurons together based on appositions between neurites as possible synapses and constrain them further with available connectivity data. Moreover, we simulate a subset of the striatum involving 10 000 neurons, with input from cortex, thalamus and the dopamine system, as a proof of principle. Simulation at this biological scale should serve as an invaluable tool to understand the mode of operation of this complex structure. This platform will be updated with new data and expanded to simulate the entire striatum.

Resources

Striatum anatomy

Location of the striatum within the mouse brain, cell composition and neuron circuitry

Dorsal striatum (transparent light blue) and reference volume (500 μm cube, red) are shown using SBA Composer (Scalable Brain Atlas Composer, INCF):
Striatal microcircuit structure
The C57BL/7J mouse striatum is around 21.5 mm³ (Allen Mouse Brain) with a total of 1.72 million neurons, which corresponds to a density of 80,500 neurons/mm³. The cell populations are subdivided as follows assuming 95% of striatal projection neurons, in equal proportion for the direct pathway and indirect pathway (dSPN and iSPN, respectively), 1.3% fast-spiking interneurons (FS), 1.1% cholinergic interneurons (ChIN) and 0.8% low threshold-spiking interneurons (LTS). The striatal circuitry is generic for the entire structure.

Single-cell models

SPN
FS
LTS
ChIN

str-dspn-e150602_c1_D1-mWT-0728MSN01-v20190508

Model

Experimental data
str-dspn-e150917_c10_D1-mWT-P270-20-v20190521

Model

Experimental data
str-dspn-e150917_c6_D1-m21-6-DE-v20190503

Model

Experimental data
str-dspn-e150917_c9_d1-mWT-1215MSN03-v20190521

Model

Experimental data
str-ispn-e150908_c4_D2-m51-5-DE-v20190611

Model

Experimental data
str-ispn-e150917_c11_D2-mWT-MSN1-v20190603

Model

Experimental data
str-ispn-e151123_c1_D2-mWT-P270-09-v20190527

Model

Experimental data
str-ispn-e160118_c10_D2-m46-3-DE-v20190529

Model

Experimental data

str-fs-e160628_FS2-mMTC180800A-IDB-v20190226

Model

Experimental data
str-fs-e161024_FS16-mDR-rat-Mar-13-08-1-536-R-v20190225

Model

Experimental data
str-fs-e161205_FS1-mMTC180800A-IDB-v20190312

Model

Experimental data
str-fs-e180418_FS5-mMTC251001A-IDB-v20190301

Model

Experimental data

str-lts-Experiment-9862_20181211

Model parameters

Experimental data
20181211_7_8_slice_L4_long.pxp (478 MB)

Selected traces

str-chin-sbj4-170614_cell6-v20190816

Model parameters

Experimental data
sbj4-170614_cell6_original__md_20170614_cell_5_6_ChIN.pxp (81 MB)

Selected traces

Simulation and analysis

Making striatal microcircuit using Snudda software (see Source code below) is illustrated in a Jupyter notebook with step-by-step instructions for simulation and analysis of the outputs. For demonstration purpose, a tiny piece of the dorsal striatum containing only 100 neurons is simulated.

Jupyter notebook StriatumScaffoldExample-tiny on GitHub.com.

Source code

The complete source code of the model building software Snudda is available on GitHub.com.

The microcircuits of striatum in silico

Abstract:

Resources