A previously undescribed scene-selective site is the key to encoding ego-motion in naturalistic environments

Current models of scene processing in the human brain include three scene-selective areas: the parahippocampal place area (or the temporal place areas), the restrosplenial cortex (or the medial place area), and the transverse occipital sulcus (or the occipital place area). Here, we challenged this model by showing that at least one other scene-selective site can also be detected within the human posterior intraparietal gyrus. Despite the smaller size of this site compared to the other scene-selective areas, the posterior intraparietal gyrus scene-selective (PIGS) site was detected consistently in a large pool of subjects (n = 59; 33 females). The reproducibility of this finding was tested based on multiple criteria, including comparing the results across sessions, utilizing different scanners (3T and 7T) and stimulus sets. Furthermore, we found that this site (but not the other three scene-selective areas) is significantly sensitive to ego-motion in scenes, thus distinguishing the role of PIGS in scene perception relative to other scene-selective areas. These results highlight the importance of including finer scale scene-selective sites in models of scene processing - a crucial step toward a more comprehensive understanding of how scenes are encoded under dynamic conditions.

Processing of Egomotion-Consistent Optic Flow in the Rhesus Macaque Cortex

The cortical network that processes visual cues to self-motion was characterized with functional magnetic resonance imaging in 3 awake behaving macaques. The experimental protocol was similar to previous human studies in which the responses to a single large optic flow patch were contrasted with responses to an array of 9 similar flow patches. This distinguishes cortical regions where neurons respond to flow in their receptive fields regardless of surrounding motion from those that are sensitive to whether the overall image arises from self-motion. In all 3 animals, significant selectivity for egomotion-consistent flow was found in several areas previously associated with optic flow processing, and notably dorsal middle superior temporal area, ventral intra-parietal area, and VPS. It was also seen in areas 7a (Opt), STPm, FEFsem, FEFsac and in a region of the cingulate sulcus that may be homologous with human area CSv. Selectivity for egomotion-compatible flow was never total but was particularly strong in VPS and putative macaque CSv. Direct comparison of results with the equivalent human studies reveals several commonalities but also some differences.

Future challenges for vection research: definitions, functional significance, measures, and neural bases

This paper discusses four major challenges facing modern vection research. Challenge 1 (Defining Vection) outlines the different ways that vection has been defined in the literature and discusses their theoretical and experimental ramifications. The term vection is most often used to refer to visual illusions of self-motion induced in stationary observers (by moving, or simulating the motion of, the surrounding environment). However, vection is increasingly being used to also refer to non-visual illusions of self-motion, visually mediated self-motion perceptions, and even general subjective experiences (i.e., “feelings”) of self-motion. The common thread in all of these definitions is the conscious subjective experience of self-motion. Thus, Challenge 2 (Significance of Vection) tackles the crucial issue of whether such conscious experiences actually serve functional roles during self-motion (e.g., in terms of controlling or guiding the self-motion). After more than 100 years of vection research there has been surprisingly little investigation into its functional significance. Challenge 3 (Vection Measures) discusses the difficulties with existing subjective self-report measures of vection (particularly in the context of contemporary research), and proposes several more objective measures of vection based on recent empirical findings. Finally, Challenge 4 (Neural Basis) reviews the recent neuroimaging literature examining the neural basis of vection and discusses the hurdles still facing these investigations.

Vestibular function in the temporal and parietal cortex: distinct velocity and inertial processing pathways

A number of behavioral and neuroimaging studies have reported converging data in favor of a cortical network for vestibular function, distributed between the temporo-parietal cortex and the prefrontal cortex in the primate. In this review, we focus on the role of the cerebral cortex in visuo-vestibular integration including the motion sensitive temporo-occipital areas i.e., the middle superior temporal area (MST) and the parietal cortex. Indeed, these two neighboring cortical regions, though they both receive combined vestibular and visual information, have distinct implications in vestibular function. In sum, this review of the literature leads to the idea of two separate cortical vestibular sub-systems forming (1) a velocity pathway including MST and direct descending pathways on vestibular nuclei. As it receives well-defined visual and vestibular velocity signals, this pathway is likely involved in heading perception and rapid top-down regulation of eye/head coordination and (2) an inertial processing pathway involving the parietal cortex in connection with the subcortical vestibular nuclei complex responsible for velocity storage integration. This vestibular cortical pathway would be implicated in high-order multimodal integration and cognitive functions, including world space and self-referential processing.

A representation of changing heading direction in human cortical areas pVIP and CSv

When we move around in the environment, we continually change direction. Much work has examined how the brain extracts instantaneous direction of heading from optic flow but how changes in heading are encoded is unknown. Change could simply be inferred cognitively from successive instantaneous heading values, but we hypothesize that heading change is represented as a low-level signal that feeds into motor control with minimal need for attention or cognition. To test this, we first used functional MRI to measure activity in several predefined visual areas previously associated with processing optic flow (hMST, hV6, pVIP, and CSv) while participants viewed flow that simulated either constant heading or changing heading. We then trained a support vector machine (SVM) to distinguish the multivoxel activity pattern elicited by rightward versus leftward changes in heading direction. Some motion-sensitive visual cortical areas, including hMST, responded well to flow but did not appear to encode heading change. However, visual areas pVIP and, particularly, CSv responded with strong selectivity to changing flow and also allowed direction of heading change to be decoded. This suggests that these areas may construct a representation of heading change from instantaneous heading directions, permitting rapid and accurate preattentive detection and response to change.