Abstract
Biological vision relies on representations of the physical world at different levels of complexity. Relevant features span from simple low-level properties, as contrast and spatial frequencies, to object-based attributes, as shape and category. However, how these features are integrated into coherent percepts is still debated. Moreover, these dimensions often share common biases: for instance, stimuli from the same category (e.g., tools) may have similar shapes. Here, using magnetoencephalography, we revealed the temporal dynamics of feature processing in human subjects attending to objects from six semantic categories. By employing Relative Weights Analysis, we mitigated collinearity between model-based descriptions of stimuli and showed that low-level properties (contrast and spatial frequencies), shape (medial-axis) and category are represented within the same spatial locations early in time: 100–150 ms after stimulus onset. This fast and overlapping processing may result from independent parallel computations, with categorical representation emerging later than the onset of low-level feature processing, yet before shape coding. Categorical information is represented both before and after shape, suggesting a role for this feature in the refinement of categorical matching.
Highlights
The primary visual cortex (V1) provides an optimal encoding of natural image statistics based on local contrast, orientation and spatial frequencies[2,3], and these low-level features significantly correlate with brain activity in higher-level visual areas[4,5]
To investigate the spatiotemporal dynamics of object processing, we combined model-based descriptions of pictures, MEG brain activity patterns and a statistical procedure (Relative Weights Analysis; RWA17,) that mitigate the effects of common biases across different dimensions
By taking into account model collinearity, we revealed the spatiotemporal dynamics of joint feature processing within the human visual system, to assess the relative contribution of low-level, shape and category features in predicting MEG-based representations
Summary
Occipital, temporal and parietal modules process object shape[6,7,8,9] and categorical knowledge[10,11,12] All these features are relevant to our brain, their relative contribution in producing discrete and coherent percepts has not yet been clarified. We observed fast (100–150 ms) and overlapping representations of low-level properties (contrast and spatial frequencies), shape (medial-axis) and category in posterior sensors. These results may be interpreted as macroscale dynamics resulting in independent parallel processing, and may suggest a role for shape in the refinement of categorical matching
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