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Gurney, K. N.

Publications and source records attributed to Gurney, K. N..

2 recordsLinked to original sources

Differential dopamine receptor-dependent sensitivity improves action selection in the basal ganglia

The problem of selecting one action from a set of different possible actions, simply referred to as the problem of action selection, is a ubiquitous challenge in the animal world. For vertebrates, the basal ganglia (BG) are widely thought to implement the core computation to solve this problem, as the anatomy and physiology of the BG are well-suited to this end. However, the BG still displays physiological features whose role in achieving efficient action selection remains unclear. In particular, it is known that the two types of dopaminergic receptors (D1 and D2) present in the BG give rise to mechanistically different responses. The overall effect will be a difference in sensitivity to dopamine which may have ramifications for action selection. However, which receptor type leads to a stronger response is, a priori, unclear, due to the complexity of the intracellular mechanisms involved. In this study, we use the action selection hypothesis to predict which of D1 or D2 has the greater sensitivity. Thus, we ask - what sensitivity ratio would result in enhanced action selection functionality in the basal ganglia? To do this, we incorporated differential D1 and D2 sensitivity in an existing, high level computational model of the macro-architecture of the basal ganglia, via a simple weighting variable. We then quantitatively assessed the models capacity to perform action selection as we parametrically manipulated the new feature. We show that differential (rather than equal) D1 and D2 sensitivity to dopaminergic input improves action selection, and specifically, that greater D1 sensitivity (compared to that for D2) leads to these improvements.

neuroscience↗

Basal Ganglia Control Of Reflexive Saccades: A Computational Model Integrating Physiology Anatomy And Behaviour

It is hypothesised that the basal ganglia play a key role in solving the problem of action selection. Here we investigate this hypothesis through computational modelling of the primate saccadic oculomotor system. This system is an excellent target for computational modelling because it is supported by a reasonably well understood functional anatomy, has limited degrees of freedom, and there is a wealth of behavioural and electrophysiological data for model comparison. Here, we describe a computational model of the reflexive saccadic oculomotor system incorporating the basal ganglia, key structures in motor control and competition between possible actions. To restrict the likelihood of overfitting the model it is structured and parameterised by the known anatomy and neurophysiology along with data from a single experimental behavioural paradigm, then validated by testing against several additional behavioural experimental data without modification of the parameters. With this model we reproduce a range of fundamental reflexive saccadic results both qualitatively and quantitatively, comprising: the distribution of saccadic latencies; the effect of eccentricity, luminance and fixation-target interactions on saccadic latencies; and the effect of competing targets on saccadic endpoint. By investigating the model dynamics we are able to provide mechanistic explanations for the sources of these behaviours. Further, because of its accesibility, the oculomotor system has also been used to study general principle of sensorimotor control. We interpret the ability of the basal ganglia to successfully control saccade selection in our model as further evidence for the action selection hypothesis.

neuroscience↗