The Pearson correlation coefficient squared, r 2, is an important tool used in the analysis of
neural data to quantify the similarity between neural tuning curves. Yet this metric is biased …

Signal correlation (rs) is commonly defined as the correlation between the tuning curves of
two neurons and is widely used as a metric of tuning similarity. It is fundamental to how …

The correlation coefficient squared, r 2, is commonly used to validate quantitative models on
neural data, yet it is biased by trial-to-trial variability: as trial-to-trial variability increases …

Cortical responses to repeated presentations of a sensory stimulus are variable. This
variability is sensitive to several stimulus dimensions, suggesting that it may carry useful …

Cortical responses to repeated presentations of a stimulus are variable. This variability is
sensitive to experimental manipulations that are also known to engage divisive …

Sensory neurons often have variable responses to repeated presentations of the same
stimulus, which can significantly degrade the stimulus information contained in those …

Sensory neurons often have variable responses to repeated presentations of the same
stimulus. Simultaneous recordings of neural populations demonstrate that such variability is …

Good metrics of the performance of a statistical or computational model are essential for
model comparison and selection. Here, we address the design of performance metrics for …

Neurons in many brain areas exhibit high trial-to-trial variability, with spike counts that are
overdispersed relative to a Poisson distribution. Recent work (Goris, Movshon, & …

Statistical models are increasingly being used to understand the complexity of stimulus
selectivity in primary visual cortex (V1) in the context of complex time-varying stimuli …