Orientation decoding: Sense in spirals?

Clifford, Colin W. G.; Mannion, Damien J.

doi:10.1016/j.neuroimage.2014.12.055

Cited by 13 publications

(9 citation statements)

References 35 publications

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“…In fMRI, a decade-long debate over the information source underlying orientation decoding from patterns of BOLD activation persists (e.g. Kamitani & Tong, 2005;Haynes & Rees, 2005;Mannion et al, 2009;Swisher et al, 2010;Freeman et al, 2011;Freeman et al, 2013;Alink et al, 2013;Carlson, 2014;Maloney, 2015;Clifford and Mannion, 2015;Carlson and Wardle, 2015). As orientation columns are at a finer scale than fMRI voxels, it has been suggested that orientation decoding from V1 is evidence that finer-scale information can be accessed at the level of cortical columns with multivariate fMRI (Kamitani & Tong, 2005).…”

Section: Discussionmentioning

confidence: 99%

Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG

et al. 2016

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Section: Discussionmentioning

confidence: 99%

Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG

et al. 2016

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“…The linear RFs in the model are hypothesized to be a basis set of orientation and spatial frequency tuning curves of V1 neurons; any invertible linear transform of the basis set can be substituted ( Freeman and Adelson, 1991 ; Simoncelli et al, 1992 ; Simoncelli, 1993 ) and different such transforms can be substituted at each spatial location, consistent with the diversity in the tuning properties of V1 neurons, without changing the nature of the representation. The model was designed so that the filters evenly tile retinotopic space, orientation, and spatial frequency to avoid any possibility of the kind of artifact that was suggested to underlie Carlson (2014) simulation results ( Clifford and Mannion, 2015 ).…”

Section: Methodsmentioning

confidence: 99%

Stimulus vignetting and orientation selectivity in human visual cortex

Roth

Heeger

Merriam

2018

eLife

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Neural selectivity to orientation is one of the simplest and most thoroughly-studied cortical sensory features. Here, we show that a large body of research that purported to measure orientation tuning may have in fact been inadvertently measuring sensitivity to second-order changes in luminance, a phenomenon we term ‘vignetting'. Using a computational model of neural responses in primary visual cortex (V1), we demonstrate the impact of vignetting on simulated V1 responses. We then used the model to generate a set of predictions, which we confirmed with functional MRI experiments in human observers. Our results demonstrate that stimulus vignetting can wholly determine the orientation selectivity of responses in visual cortex measured at a macroscopic scale, and suggest a reinterpretation of a well-established literature on orientation processing in visual cortex.

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“…Both spiral stimuli (clockwise and anti-clockwise), when centered on fixation, have an equal absolute orientation disparity to the radius (±45°) everywhere. Thus, a global preference map for radial orientations will yield an equal global activation pattern for each spiral (Mannion et al, 2009; Seymour et al, 2010; Clifford et al, 2011). In order to obliterate the global form of the stimuli, we divided these stimuli into a log-polar array of tiles (3 concentric rings, 12 radial wedges).…”

Section: Introductionmentioning

confidence: 99%

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

Alink¹,

Krugliak²,

Walther³

et al. 2013

Front. Psychol.

118

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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.

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Orientation decoding: Sense in spirals?

Cited by 13 publications

References 35 publications

Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG

Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG

Stimulus vignetting and orientation selectivity in human visual cortex

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

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