Models of human cortex propose the existence of neuroanatomical pathways specialized for different behavioral functions. These pathways include a ventral pathway for object recognition, a dorsal pathway for performing visually guided physical actions, and a recently proposed third pathway for social perception. In the current study, we tested the hypothesis that different categories of moving stimuli are differentially processed across the dorsal and third pathways according to their behavioral implications. Human participants ( n = 30) were scanned with fMRI while viewing moving and static stimuli from four categories (faces, bodies, scenes, and objects). A whole-brain group analysis showed that moving bodies and moving objects increased neural responses in the bilateral posterior parietal cortex, parts of the dorsal pathway. By contrast, moving faces and moving bodies increased neural responses, the superior temporal sulcus, part of the third pathway. This pattern of results was also supported by a separate ROI analysis showing that moving stimuli produced more robust neural responses for all visual object categories, particularly in lateral and dorsal brain areas. Our results suggest that dynamic naturalistic stimuli from different categories are routed in specific visual pathways that process dissociable behavioral functions.

Aesthetic experiences during natural vision are varied: They can arise from viewing scenic landscapes, interesting architecture, or attractive people. Recent research in the field of neuroaesthetics has taught us a lot about where in the brain such aesthetic experiences are represented. Much less is known about when such experiences arise during the cortical processing cascade. Particularly, the dynamic neural representation of perceived attractiveness for rich natural scenes is not well understood. Here, I present data from an EEG experiment, in which participants provided attractiveness judgments for a set of diverse natural scenes. Using multivariate pattern analysis, I demonstrate that scene attractiveness is mirrored in early brain signals that arise within 200 msec of vision, suggesting that the aesthetic appeal of scenes is first resolved during perceptual processing. In more detailed analyses, I show that even such early neural correlates of scene attractiveness are partly related to interindividual variation in aesthetic preferences and that they generalize across scene contents. Together, these results characterize the time-resolved neural dynamics that give rise to aesthetic experiences in complex natural environments.

During natural vision, our brains are constantly exposed to complex, but regularly structured, environments. Real-world scenes are defined by typical part–whole relationships, where the meaning of the whole scene emerges from configurations of localized information present in individual parts of the scene. Such typical part–whole relationships suggest that information from individual scene parts is not processed independently, but that there are mutual influences between the parts and the whole during scene analysis. Here, we review recent research that used a straightforward, but effective approach to study such mutual influences: By dissecting scenes into multiple arbitrary pieces, these studies provide new insights into how the processing of whole scenes is shaped by their constituent parts and, conversely, how the processing of individual parts is determined by their role within the whole scene. We highlight three facets of this research: First, we discuss studies demonstrating that the spatial configuration of multiple scene parts has a profound impact on the neural processing of the whole scene. Second, we review work showing that cortical responses to individual scene parts are shaped by the context in which these parts typically appear within the environment. Third, we discuss studies demonstrating that missing scene parts are interpolated from the surrounding scene context. Bridging these findings, we argue that efficient scene processing relies on an active use of the scene's part–whole structure, where the visual brain matches scene inputs with internal models of what the world should look like.

Objects belonging to different categories evoke reliably different fMRI activity patterns in human occipitotemporal cortex, with the most prominent distinction being that between animate and inanimate objects. An unresolved question is whether these categorical distinctions reflect category-associated visual properties of objects or whether they genuinely reflect object category. Here, we addressed this question by measuring fMRI responses to animate and inanimate objects that were closely matched for shape and low-level visual features. Univariate contrasts revealed animate- and inanimate-preferring regions in ventral and lateral temporal cortex even for individually matched object pairs (e.g., snake–rope). Using representational similarity analysis, we mapped out brain regions in which the pairwise dissimilarity of multivoxel activity patterns (neural dissimilarity) was predicted by the objects' pairwise visual dissimilarity and/or their categorical dissimilarity. Visual dissimilarity was measured as the time it took participants to find a unique target among identical distractors in three visual search experiments, where we separately quantified overall dissimilarity, outline dissimilarity, and texture dissimilarity. All three visual dissimilarity structures predicted neural dissimilarity in regions of visual cortex. Interestingly, these analyses revealed several clusters in which categorical dissimilarity predicted neural dissimilarity after regressing out visual dissimilarity. Together, these results suggest that the animate–inanimate organization of human visual cortex is not fully explained by differences in the characteristic shape or texture properties of animals and inanimate objects. Instead, representations of visual object properties and object category may coexist in more anterior parts of the visual system.