We proposed a new functional architecture for the basal ganglia (BG) based on the premise that these brain structures play a central role in behavioural action selection. The papers quantitatively describes the properties of the model using analysis and simulation. In the first paper, we show that the decomposition of the BG into selection and control pathways is supported in several ways. First, several elegant features are exposed--capacity scaling, enhanced selectivity and synergistic dopamine modulation--which might be expected to exist in a well designed action selection mechanism. Second, good matches between model GPe output and GPi and SNr output, and neurophysiological data, have been found. Third, the behaviour of the model as a signal selection mechanism has parallels with some kinds of action selection observed in animals under various levels of dopaminergic modulation. In the second paper, we extend the BG model to include new connections, and show that action selection is maintained. In addition, we provide quantitative measures for defining different forms of selection, and methods for assessing performance changes in computational neuroscience models.
Model Type: Realistic Network
Region(s) or Organism(s): Basal ganglia
Implementer(s): Humphries, Mark D [m.d.humphries at shef.ac.uk]
Gurney KN, Humphries M, Wood R, Prescott TJ, Redgrave P. (2004). Testing computational hypotheses of brain systems function: a case study with the basal ganglia. Network (Bristol, England). 15 [PubMed]