Basal Ganglia


  • The first version of the microcircuit will be available via the Brain Simulation Platform (BSP). Currently the mouse striatum, an input stage of the basal ganglia is implemented (Collab, Jupyter notebook).
  • Online use case on single cell building (BSP, Optimise a striatal fast-spiking interneuron).
  • Online use case on validation of single cell models: MSN D1 and MSN D2 (BSP, Basal ganglia – BluePyOpt optimised model validation – multiple HOF).
  • Single cell model of striatal MSN D1 (ModelDB, Lindroos et al., 2018).
  • Experimental electrophysiological data for single neurons: FS, MSN D1, MSN D2, ChIN (Collab, Storage/Electrophysiology).
  • Electro-physiological feature extraction example (Collab, Jupyter notebook).
  • Single cell optimisations of individual neurons: MSN D1, MSN D2, FS, ChIN (Collab, Storage/Optimisations; see also example, Jupyter notebook).
  • Collection of morphological reconstructions used for striatal simulations, raw and repaired/regularised (Collab, Storage / Morphology).

If you do not have an account to access the Brain Simulation Platform, please email


A list of recent and relevant publications:


The basal ganglia is an evolutionarily conserved key structure for the control of action (Grillner and Robertson, 2015). It plays a crucial role in decision-making and motor control. The output of the basal ganglia consists of tonically active GABAergic neurons, a proportion of which project to different brainstem centres and another part projects to the thalamus and back to the cortex. The target areas are tonically inhibited under resting conditions. These centres will be disinhibited when called into action.

What makes the basal ganglia special?

The basal ganglia is a highly interconnected structure within the brain which includes multiple distinct nuclei. The detailed structure of these nuclei at the meso- and micro-circuit levels is largely unknown and is a subject of intensive research. It exhibits a great degree of plasticity being a target of neuromodulatory systems (dopamine, serotonin and histamine). It also plays an important role in the regulation of the midbrain dopamine system, which is involved in reward, disappointment, aversion, etc.

What are the specific questions we want to address in the HBP?

The model will provide a ‘scaffold’ for a first data-driven model of the whole basal ganglia, including selected downstream motor centres and feedback via the thalamus to the cortex. The model will also provide a basis for investigations of the role of the basal ganglia in action selection and motor learning. The important question is to understand how a decision is made when provided with multiple conflicting alternative actions that could be taken? How is the correct decision learnt and facilitated in future tasks? What is the role of neuromodulators in shaping the dynamics of the basal ganglia network?

What is our specific take?

A multi-pronged strategy, culminating in a scaffold detailed computer model of a rodent basal ganglia, starting with the striatum.



In the two years, April 2018-March 2020:

  • Will further develop the striatal circuit model based on compartmental models with interneurons, MSNs – D1 and D2 and the input from cortex and thalamus, considering the circuits involving both action-selection and evaluation.
  • Modulation of cellular electrophysiology by dopamine and acetylcholine, and its influence on the striatal function. Study of the effects of neuromodulators on ion channels and synapses in different cell types; and matching the net effects of the striatal microcircuit to the experimental data.
  • Regulation of the midbrain dopamine system by the striatum via habenula (to be initiated). Closing the control loop by simulating dynamic response of the striatal microcircuit to varying dopamine release.
  • Interaction of different basal ganglia nuclei will be studied; the results will be progressively added to the system at the pace of acquisition of the data and knowledge.


Who is Involved

Building a model of the basal ganglia from sparse, fragmented data and improving our understanding of the basal ganglia function requires a critical mass of experimental data and expertise. 

The following people and their teams are driving this effort:

Sten Grillner (Professor), Department of Neurophysiology, Karolinska Institute, Sweden

Alexander Kozlov (PhD), Science for Life Laboratory, KTH Royal Institute of Technology, Sweden

Johannes Hjorth (PhD), Science for Life Laboratory, KTH Royal Institute of Technology, Sweden

Ilaria Carannante (PhD student), Science for Life Laboratory, KTH Royal Institute of Technology, Sweden

Johanna Frost-Nylén (PhD student), Department of Neurophysiology, Karolinska Institute, Sweden


Benefits to the Community

Model use: If you would like to use some of the results of this work (e.g. take a striatal projection neuron for a spin, create your own variant thereof, analyse a striatal network, etc.) you can simply go to the Brain Simulation Platform and launch one of the respective use cases. Alternatively, you can download the data and models as indicated under Resources.