Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye-of-origin from fMRI data

Multivariate pattern analysis of functional MRI (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye-of-origin from fMRI measurements in human visual cortex with predictions based on the columnar organisation of each feature, and estimated the spatial scales of patterns driving decoding. Both orientation and eye-of-origin could be decoded significantly above chance in early visual areas (V1-V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye-of-origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1-V3. Similarly, binning by hemifield significantly improved decoding performance for eye-of-origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas.

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