Neural Comput - Sample skewness as a statistical measurement of neuronal tuning sharpness.

Tópicos

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Resumo

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition.

Resumo Limpo

propos use statist measur sampl skew distribut mean fire rate tune curv quantifi sharp tune featur like binocular dispar tune curv best describ relat complex sometim divers function make difficult quantifi sharp singl function paramet skew provid robust nonparametr measur tune curv sharp invari respect mean varianc tune curv straightforward appli wide rang tune includ simpl orient tune curv complex object tune curv often even describ parametr skew depend specif model function tune especi appeal case sharpen recurr interact among neuron produc sharper tune curv deviat complex manner feedforward function tune sinc tune curv neuron typic well describ singl parametr function model independ addit allow skew appli record neuron maxim statist power set data also compar skew nonparametr measur tune curv sharp select compar nonparametr measur test skew best use captur sharp multimod tune curv defin narrow peak maximum broad valley minima final provid formal definit sharp use shapebas inform gain measur deriv show skew correl definit

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