Existence and control of Go/No-Go decision transition threshold in the striatum

PLoS Comput Biol. 2015 Apr 24;11(4):e1004233. doi: 10.1371/journal.pcbi.1004233. eCollection 2015 Apr.

Abstract

A typical Go/No-Go decision is suggested to be implemented in the brain via the activation of the direct or indirect pathway in the basal ganglia. Medium spiny neurons (MSNs) in the striatum, receiving input from cortex and projecting to the direct and indirect pathways express D1 and D2 type dopamine receptors, respectively. Recently, it has become clear that the two types of MSNs markedly differ in their mutual and recurrent connectivities as well as feedforward inhibition from FSIs. Therefore, to understand striatal function in action selection, it is of key importance to identify the role of the distinct connectivities within and between the two types of MSNs on the balance of their activity. Here, we used both a reduced firing rate model and numerical simulations of a spiking network model of the striatum to analyze the dynamic balance of spiking activities in D1 and D2 MSNs. We show that the asymmetric connectivity of the two types of MSNs renders the striatum into a threshold device, indicating the state of cortical input rates and correlations by the relative activity rates of D1 and D2 MSNs. Next, we describe how this striatal threshold can be effectively modulated by the activity of fast spiking interneurons, by the dopamine level, and by the activity of the GPe via pallidostriatal backprojections. We show that multiple mechanisms exist in the basal ganglia for biasing striatal output in favour of either the `Go' or the `No-Go' pathway. This new understanding of striatal network dynamics provides novel insights into the putative role of the striatum in various behavioral deficits in patients with Parkinson's disease, including increased reaction times, L-Dopa-induced dyskinesia, and deep brain stimulation-induced impulsivity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials / physiology*
  • Animals
  • Computer Simulation
  • Corpus Striatum / physiology*
  • Decision Making / physiology*
  • Dopaminergic Neurons / physiology*
  • Humans
  • Models, Neurological*
  • Nerve Net / physiology*
  • Receptors, Dopamine / physiology

Substances

  • Receptors, Dopamine

Grant support

This work was supported by the German Federal Ministry of Education and Research (BMBF 01GQ0420 to BCCN Freiburg and 01GQ0830 to BFNT Freiburg/Tu ¨bingen), the BrainLinks-BrainTools Cluster of Excellence funded by the German Research Foundation (DFG #EXC 1086), the EU (INTERREG-V Grant to Neurex: TriNeuron) and the German-Israeli Foundation. AK and AA acknowledge INTERREG IV Rhin supérieur program and european funds for regional development (FEDER) through the project TIGER A31. We also thank the Albert Ludwigs University Freiburg in the funding programme Open Access Publishing.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.