Statistically efficient estimation using population coding
Neural Computation
Probabilistic interpretation of population codes
Neural Computation
Mutual information, Fisher information, and population coding
Neural Computation
Neuronal tuning: to sharpen or broaden
Neural Computation
Narrow versus wide turning curves: what's best for a population code?
Neural Computation
The effect of correlated variability on the accuracy of a population code
Neural Computation
Seeing white: qualia in the context of decoding population codes
Neural Computation
The effect of correlations on the Fisher information of population codes
Proceedings of the 1998 conference on Advances in neural information processing systems II
Parameter extraction from population codes: A critical assessment
Neural Computation
Population coding and decoding in a neural field: a computational study
Neural Computation
Difficulty of Singularity in Population Coding
Neural Computation
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Is the homunculus "aware" of sensory adaptation?
Neural Computation
Modeling attention: from computational neuroscience to computer vision
WAPCV'04 Proceedings of the Second international conference on Attention and Performance in Computational Vision
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This study investigates the influence of attention modulation on neural tuning functions. It has been shown in experiments that attention modulation alters neural tuning curves. Attention has been considered at least to serve to resolve limiting capacities and to increase the sensitivity to attended stimulus, while the exact functions of attention are still under debate. Inspired by recent experimental results on attention modulation, we investigate the influence of changes in the height and base rate of the tuning curve on the encoding accuracy, using the Fisher information. Under an assumption of stimulus-conditional independence of neural responses, we derive explicit conditions that determine when the height and base rate should be increased or decreased to improve encoding accuracy. Notably, a decrease in the tuning height and base rate can improve the encoding accuracy in some cases. Our theoretical results can predict the effective size of attention modulation on the neural population with respect to encoding accuracy. We discuss how our method can be used quantitatively to evaluate different aspects of attention function.