fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli

Abstract

The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of global form.

Orientation Decoding in Human Visual Cortex: New Insights from an Unbiased Perspective

“…The response is broadband. This is in agreement with studies showing that information for orientation decoding is not strongly localized to either low or high spatial frequency patterns of activation in the cortex, which are the predictions of the global map and hyperacuity accounts respectively (Kamitani and Sawahata, 2010;Kriegeskorte et al, 2010;Op de Beeck, 2010;Swisher et al, 2010;Freeman et al, 2011;Alink et al, 2013), albeit this is somewhat oversimplified.…”

“…The results, however, have been equivocal (Kamitani and Sawahata, 2010;Kriegeskorte et al, 2010;Swisher et al, 2010;Alink et al, 2013). Freeman et al (2011) attempted to establish what information is "necessary" and "sufficient" for decoding; but again the findings were not so clear-cut (Alink et al, 2013). Finally there was a stimulus-based approach, spurred by the argument that radially balanced spirals should not be decodable if decoding relies solely on a radial bias, but this again was not definitive (Mannion et al, 2009;Freeman et al, 2013).…”

“…Spatial filtering of the fMRI data initially seemed to yield straightforward predictions (Op de Beeck, 2010). The results, however, have been equivocal (Kamitani and Sawahata, 2010;Kriegeskorte et al, 2010;Swisher et al, 2010;Alink et al, 2013). Freeman et al (2011) attempted to establish what information is "necessary" and "sufficient" for decoding; but again the findings were not so clear-cut (Alink et al, 2013).…”

Prospective motion correction improves the sensitivity of fMRI pattern decoding

“…Visual gratings were chosen as stimuli because their encoding in visual cortical response patterns is reasonably well understood. In particular, we examined the accuracy of multivariate decoding in the primary visual cortex (V1), which is generally high (Alink, Krugliak, Walther, & Kriegeskorte, 2013; Kamitani & Tong, 2005; Tong et al, 2010). …”

“…Specifically, neurons responding to radial orientations with respect to the fixation point appear to be more frequent, creating a global areal map of radial orientation frequencies (Freeman, Heeger, & Merriam, 2013; Sasaki et al, 2006). Neurons responding independently of radial bias are organized in a much finer‐grained columnar map of orientation preference (Alink et al, 2013; Swindale, Grinvald, & Shmuel, 2003; Tong et al, 2010). The different spatial frequencies of these two nested organizations leads us to expect that that the effectiveness of PMC may vary with the spatial scale of the fMRI measurement, and with the visual field coverage of a given region of interest.…”