Louis Vinke

Neurons within early visual cortex are selective for basic image statistics, including spatial frequency. However, these neurons are thought to act as band-pass filters, with the window of spatial frequency sensitivity varying across the visual field and across visual areas. Although a handful of previous functional (f)MRI studies have examined human spatial frequency sensitivity using conventional designs and analysis methods, these measurements are time consuming and fail to capture the precision of spatial frequency tuning (bandwidth). In this study, we introduce a model-driven approach to fMRI analyses that allows for fast and efficient estimation of population spatial frequency tuning (pSFT) for individual voxels. Blood oxygen level-dependent (BOLD) responses within early visual cortex were acquired while subjects viewed a series of full-field stimuli that swept through a large range of spatial frequency content. Each stimulus was generated by band-pass filtering white noise with a central frequency that changed periodically between a minimum of 0.5 cycles/degree (cpd) and a maximum of 12 cpd. To estimate the underlying frequency tuning of each voxel, we assumed a log-Gaussian pSFT and optimized the parameters of this function by comparing our model output against the measured BOLD time series. Consistent with previous studies, our results show that an increase in eccentricity within each visual area is accompanied by a drop in the peak spatial frequency of the pSFT. Moreover, we found that pSFT bandwidth depends on eccentricity and is correlated with the pSFT peak; populations with lower peaks possess broader bandwidths in logarithmic scale, whereas in linear scale this relationship is reversed. NEW & NOTEWORTHY Spatial frequency selectivity is a hallmark property of early visuocortical neurons, and mapping these sensitivities gives us crucial insight into the hierarchical organization of information within visual areas. Due to technical obstacles, we lack a comprehensive picture of the properties of this sensitivity in humans. Here, we introduce a new method, coined population spatial frequency tuning mapping, which circumvents the limitations of the conventional neuroimaging methods, yielding a fuller visuocortical map of spatial frequency sensitivity.

Language and music epitomize the complex representational and computational capacities of the human mind. Strikingly similar in their structural and expressive features, a longstanding question is whether the perceptual and cognitive mechanisms underlying these abilities are shared or distinct -either from each other or from other mental processes. One prominent feature shared between language and music is signal encoding using pitch, conveying pragmatics and semantics in language and melody in music. We investigated how pitch processing is shared between language and music by measuring consistency in individual differences in pitch perception across language, music, and three control conditions intended to assess basic sensory and domain-general cognitive processes. Individuals' pitch perception abilities in language and music were most strongly related, even after accounting for performance in all control conditions. These results provide behavioral evidence, based on patterns of individual differences, that is consistent with the hypothesis that cognitive mechanisms for pitch processing may be shared between language and music.