Biologically Constrained Basal Ganglia model (BCBG model) (Lienard, Girard 2014)


We studied the physiology and function of the basal ganglia through the design of mean-field models of the whole basal ganglia. The parameterizations are optimized with multi-objective evolutionary algorithm to respect best a collection of numerous anatomical data and electrophysiological data. The main outcomes of our study are: • The strength of the GPe to GPi/SNr connection does not support opposed activities in the GPe and GPi/SNr. • STN and MSN target more the GPe than the GPi/SNr. • Selection arises from the structure of the basal ganglia, without properly segregated direct and indirect pathways and without specific inputs from pyramidal tract neurons of the cortex. Selection is enhanced when the projection from GPe to GPi/SNr has a diffuse pattern.

Model Type: Realistic Network; Axon; Channel/Receptor; Dendrite; Neural mass

Region(s) or Organism(s): Basal ganglia

Cell Type(s): Neostriatum medium spiny direct pathway GABA cell; Neostriatum medium spiny indirect pathway GABA cell; Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; Substantia nigra pars reticulata principal GABA cell; Subthalamus nucleus projection neuron; Globus pallidus neuron; Neostriatum fast spiking interneuron; Neostriatum spiny neuron

Receptors: GabaA; AMPA; NMDA

Transmitters: Gaba; Glutamate

Model Concept(s): Parameter Fitting; Pathophysiology; Parkinson's; Winner-take-all; Action Selection/Decision Making

Simulation Environment: C or C++ program

Implementer(s): Girard, Benoit [girard at isir.upmc.fr]; Liénard, Jean [lienard at isir.upmc.fr]

References:

Liénard J, Girard B. (2014). A biologically constrained model of the whole basal ganglia addressing the paradoxes of connections and selection. Journal of computational neuroscience. 36 [PubMed]


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