Local visual energy mechanisms revealed by detection of global patterns

A central goal of visual neuroscience is to relate the selectivity of individual neurons to perceptual judgments, such as detection of a visual pattern at low contrast or in noise. Since neurons in early areas of visual cortex carry information only about a local patch of the image, detection of global patterns must entail spatial pooling over many such neurons. Physiological methods provide access to local detection mechanisms at the single-neuron level but do not reveal how neural responses are combined to determine the perceptual decision. Behavioral methods provide access to perceptual judgments of a global stimulus but typically do not reveal the selectivity of the individual neurons underlying detection. Here we show how the existence of a nonlinearity in spatial pooling does allow properties of these early mechanisms to be estimated from behavioral responses to global stimuli. As an example, we consider detection of large-field sinusoidal gratings in noise. Based on human behavioral data, we estimate the length and width tuning of the local detection mechanisms and show that it is roughly consistent with the tuning of individual neurons in primary visual cortex of primate. We also show that a local energy model of pooling based on these estimated receptive fields is much more predictive of human judgments than competing models, such as probability summation. In addition to revealing underlying properties of early detection and spatial integration mechanisms in human cortex, our findings open a window on new methods for relating system-level perceptual judgments to neuron-level processing.