Abstract
We investigated the connection between electrophysiological properties of neural populations and their ability to discriminate between the presence of one and two stimuli in a two-alternative forced choice task. The model is based on maximum likelihood estimation in a stimulus space that allows for the presence of multiple stimuli. Repetitive presentation of virtual stimuli yields receiver–operator–characteristics (ROC) curves and psychometric functions from noisy neural responses. For the case of one-dimensional stimuli like the movement direction of a random dot cloud we tested two coding strategies for discriminative ability. It turns out that narrow tuning curves and a variability of tuning widths within the neural population yields a high percentage of correct responses in the simulated psychophysical discrimination task. These results are similar to findings about the localization of single stimuli by neural populations: The examined encoding strategies lead to both an improvement of single stimulus estimation and discrimination between one and two stimuli.
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© 2005 Springer-Verlag Berlin Heidelberg
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Schulzke, E.L., Eurich, C.W. (2005). Neuronal Coding Strategies for Two-Alternative Forced Choice Tasks. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_38
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DOI: https://doi.org/10.1007/11550822_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28752-0
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