- Poster Presentation
- Open Access
Optimal decision making with biologically realistic neural signals
© Caballero and Gurney; licensee BioMed Central Ltd. 2010
- Published: 20 July 2010
- Basal Ganglion
- Firing Rate
- Spike Train
- Decision Algorithm
- Neural Signal
Action selection in animals requires rapid decision making that can discriminate the most salient requests for behavioral expression. The basal ganglia (BG) are believed to play a critical role in resolving competition between these requests  and, recently it has been proposed that the BG and cortex, taken together, implement a decision algorithm known as the multi-hypothesis sequential probability ratio test (MSPRT) . Here, the cortex first integrates noisy ‘evidence’ indicating salience of action requests. The BG then examine this integrated evidence, and report the channel with maximal mean salience. The MSPRT is optimal in the sense that it guarantees the smallest decision time for a given error. The signals used in  assume cortical evidence - as neural firing rates - is supplied by Gaussian distributed signals. However, it is known that such rates are not distributed normally.
A critical parameter in the algorithm is the time step Δt used to sample the cortical input. The Gaussian, Inverse Gaussian, and Gamma cases are generated as stable Lévy processes and may be scaled indefinitely with decreasing Δt. However, unlike the MSPRT with Gaussian signals, we show that decision time for the inverse Gaussian, and Gamma decreases with Δt. Figure 1 use a Δt = 1 ms for all models and clearly shows a performance advantage for the cases with more realistic distributions (the lognormal case is shown with similar scaling even though it has not an associated Lévy process). Indefinitely small decision times may appear unrealistic, but we present an interpretation of cortical sampling that relates Δt to the inter-spike intervals of an ensemble of neural afferents impinging on the cortical ‘integrators’. This and, other mechanisms, provide a natural lower bound for Δt. We conclude that neurons may take advantage of the properties of natural spike trains to enhance decision making in the cortex-BG complex.
- Redgrave P, Prescott T, Gurney K: The basal ganglia: a vertebrate solution to the selection problem?. Neuroscience. 1999, 89: 1009-1023. 10.1016/S0306-4522(98)00319-4.View ArticlePubMedGoogle Scholar
- Bogacz R, Gurney K: The basal ganglia and cortex implement optimal decision making between alternative actions. Neural Comput. 2007, 19 (2): 442-477. 10.1162/neco.2007.19.2.442.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd.