Neuronal receptive fields (RFs) play crucial roles in visual processing. While the linear RFs of early neurons have been well studied, RFs of cortical complex cells are nonlinear and therefore difficult to characterize, especially in the context of natural stimuli. In this study, we used a nonlinear technique to compute the RFs of complex cells from their responses to natural images. We found t...

Experimental neuroscience increasingly requires tractable models for analyzing and predicting the behavior of neurons and networks. The generalized linear model (GLM) is an increasingly popular statistical framework for analyzing neural data that is flexible, exhibits rich dynamic behavior and is computationally tractable (Paninski, 2004; Pillow et al., 2008; Truccolo et al., 2005). What follow...

We develop a group-theoretical analysis of slow feature analysis for the case where the input data are generated by applying a set of continuous transformations to static templates. As an application of the theory, we analytically derive nonlinear visual receptive fields and show that their optimal stimuli, as well as the orientation and frequency tuning, are in good agreement with previous sim...

In the present study, we examined the way that scene complexity and saccades combine to sculpt the temporal response patterns of V1 neurons. To bridge the gap between conventional and free viewing experiments, we compared responses of neurons across four paradigms ranging from less to more natural. An optimal bar stimulus was either flashed into a receptive field (RF) or brought into it via sac...

Using data from an e-voting experiment conducted in the 2005 Congressional Election in Argentina, we estimate the effect of different e-voting technologies on the likelihood that citizens cast their vote for different parties for the National Congress and the Legislature of Buenos Aires. Our results indicate that voters are extremely receptive to the information cues provided by the different v...

Data from the Head Start Impact Study (N=3,185) were used to determine whether Head Start differentially benefited children from homes with high, middle, and low levels of parental preacademic stimulation on three academic outcome domains – early literacy, receptive vocabulary, and early math – after one year. Results from residualized growth models showed positive impacts of random assignment ...