Motion parallax links visual motion areas and scene regions

Common and specific activations supporting optic flow processing and navigation as revealed by a meta-analysis of neuroimaging studies

Optic flow provides useful information in service of spatial navigation. However, whether brain networks supporting these two functions overlap is still unclear. Here we used Activation Likelihood Estimation (ALE) to assess the correspondence between brain correlates of optic flow processing and spatial navigation and their specific neural activations. Since computational and connectivity evidence suggests that visual input from optic flow provides information mainly during egocentric navigation, we further tested the correspondence between brain correlates of optic flow processing and that of both egocentric and allocentric navigation. Optic flow processing shared activation with egocentric (but not allocentric) navigation in the anterior precuneus, suggesting its role in providing information about self-motion, as derived from the analysis of optic flow, in service of egocentric navigation. We further documented that optic flow perception and navigation are partially segregated into two functional and anatomical networks, i.e., the dorsal and the ventromedial networks. Present results point to a dynamic interplay between the dorsal and ventral visual pathways aimed at coordinating visually guided navigation in the environment.

Functional organization of the caudal part of the human superior parietal lobule

Like in macaque, the caudal portion of the human superior parietal lobule (SPL) plays a key role in a series of perceptive, visuomotor and somatosensory processes. Here, we review the functional properties of three separate portions of the caudal SPL, i.e., the posterior parieto-occipital sulcus (POs), the anterior POs, and the anterior part of the caudal SPL. We propose that the posterior POs is mainly dedicated to the analysis of visual motion cues useful for object motion detection during self-motion and for spatial navigation, while the more anterior parts are implicated in visuomotor control of limb actions. The anterior POs is mainly involved in using the spotlight of attention to guide reach-to-grasp hand movements, especially in dynamic environments. The anterior part of the caudal SPL plays a central role in visually guided locomotion, being implicated in controlling leg-related movements as well as the four limbs interaction with the environment, and in encoding egomotion-compatible optic flow. Together, these functions reveal how the caudal SPL is strongly implicated in skilled visually-guided behaviors.

Effect of optic flow on spatial updating: insight from an immersive virtual reality study

Self-motion information is required to keep track of where we are with respect to our environment (spatial updating). Visual signals such as optic flow are relevant to provide information about self-motion, especially in the absence of vestibular and/or proprioceptive cues generated by physical movement. However, the role of optic flow on spatial updating is still debated. A virtual reality system based on a head-mounted display was used to allow participants to experience a self-motion sensation within a naturalistic environment in the absence of physical movement. We asked participants to keep track of spatial positions of a target during simulated self-motion while manipulating the availability of optic flow coming from the lower part of the environment (ground plane). In each trial, the ground could be a green lawn (optic flow ON) or covered in snow (optic flow OFF). We observed that the lack of optic flow on the ground had a detrimental effect on spatial updating. Furthermore, we explored the interaction between the optic flow availability and different characteristics of self-motion: we observed that increasing self-motion speed had a detrimental effect on spatial updating, especially in the absence of optic flow, while self-motion direction (leftward, forward, rightward) and path (translational and curvilinear) had no statically significant effect. Overall, we demonstrated that, in the absence of some idiothetic cues, the optic flow provided by the ground has a dominant role for the self-motion estimation and, hence, for the ability to update the spatial relationships between one's position and the position of the surrounding objects.

A common neural substrate for processing scenes and egomotion-compatible visual motion

Neuroimaging studies have revealed two separate classes of category-selective regions specialized in optic flow (egomotion-compatible) processing and in scene/place perception. Despite the importance of both optic flow and scene/place recognition to estimate changes in position and orientation within the environment during self-motion, the possible functional link between egomotion- and scene-selective regions has not yet been established. Here we reanalyzed functional magnetic resonance images from a large sample of participants performing two well-known “localizer” fMRI experiments, consisting in passive viewing of navigationally relevant stimuli such as buildings and places (scene/place stimulus) and coherently moving fields of dots simulating the visual stimulation during self-motion (flow fields). After interrogating the egomotion-selective areas with respect to the scene/place stimulus and the scene-selective areas with respect to flow fields, we found that the egomotion-selective areas V6+ and pIPS/V3A responded bilaterally more to scenes/places compared to faces, and all the scene-selective areas (parahippocampal place area or PPA, retrosplenial complex or RSC, and occipital place area or OPA) responded more to egomotion-compatible optic flow compared to random motion. The conjunction analysis between scene/place and flow field stimuli revealed that the most important focus of common activation was found in the dorsolateral parieto-occipital cortex, spanning the scene-selective OPA and the egomotion-selective pIPS/V3A. Individual inspection of the relative locations of these two regions revealed a partial overlap and a similar response profile to an independent low-level visual motion stimulus, suggesting that OPA and pIPS/V3A may be part of a unique motion-selective complex specialized in encoding both egomotion- and scene-relevant information, likely for the control of navigation in a structured environment.

Neural bases of self- and object-motion in a naturalistic vision

To plan movements toward objects our brain must recognize whether retinal displacement is due to self-motion and/or to object-motion. Here, we aimed to test whether motion areas are able to segregate these types of motion. We combined an event-related functional magnetic resonance imaging experiment, brain mapping techniques, and wide-field stimulation to study the responsivity of motion-sensitive areas to pure and combined self- and object-motion conditions during virtual movies of a train running within a realistic landscape. We observed a selective response in MT to the pure object-motion condition, and in medial (PEc, pCi, CSv, and CMA) and lateral (PIC and LOR) areas to the pure self-motion condition. Some other regions (like V6) responded more to complex visual stimulation where both object- and self-motion were present. Among all, we found that some motion regions (V3A, LOR, MT, V6, and IPSmot) could extract object-motion information from the overall motion, recognizing the real movement of the train even when the images remain still (on the screen), or moved, because of self-movements. We propose that these motion areas might be good candidates for the "flow parsing mechanism," that is the capability to extract object-motion information from retinal motion signals by subtracting out the optic flow components.

Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

Theoretical neuroscience investigation shows valuable information on the mechanism for recognizing the biological movements in the mammalian visual system. This involves many different fields of researches such as psychological, neurophysiology, neuro-psychological, computer vision, and artificial intelligence (AI). The research on these areas provided massive information and plausible computational models. Here, a review on this subject is presented. This paper describes different perspective to look at this task including action perception, computational and knowledge based modeling, psychological, and neuroscience approaches.

Egomotion-related visual areas respond to active leg movements

Monkey neurophysiology and human neuroimaging studies have demonstrated that passive viewing of optic flow stimuli activates a cortical network of temporal, parietal, insular, and cingulate visual motion regions. Here, we tested whether the human visual motion areas involved in processing optic flow signals simulating self-motion are also activated by active lower limb movements, and hence are likely involved in guiding human locomotion. To this aim, we used a combined approach of task-evoked activity and resting-state functional connectivity by fMRI. We localized a set of six egomotion-responsive visual areas (V6+, V3A, intraparietal motion/ventral intraparietal [IPSmot/VIP], cingulate sulcus visual area [CSv], posterior cingulate sulcus area [pCi], posterior insular cortex [PIC]) by using optic flow. We tested their response to a motor task implying long-range active leg movements. Results revealed that, among these visually defined areas, CSv, pCi, and PIC responded to leg movements (visuomotor areas), while V6+, V3A, and IPSmot/VIP did not (visual areas). Functional connectivity analysis showed that visuomotor areas are connected to the cingulate motor areas, the supplementary motor area, and notably to the medial portion of the somatosensory cortex, which represents legs and feet. We suggest that CSv, pCi, and PIC perform the visual analysis of egomotion-like signals to provide sensory information to the motor system with the aim of guiding locomotion.

The occipital place area represents first-person perspective motion information through scenes

Neuroimaging studies have identified multiple scene-selective regions in human cortex, but the precise role each region plays in scene processing is not yet clear. It was recently hypothesized that two regions, the occipital place area (OPA) and the retrosplenial complex (RSC), play a direct role in navigation, while a third region, the parahippocampal place area (PPA), does not. Some evidence suggests a further division of labor even among regions involved in navigation: While RSC is thought to support navigation through the broader environment, OPA may be involved in navigation through the immediately visible environment, although this role for OPA has never been tested. Here we predict that OPA represents first-person perspective motion information through scenes, a critical cue for such "visually-guided navigation", consistent with the hypothesized role for OPA. Response magnitudes were measured in OPA (as well as RSC and PPA) to i) video clips of first-person perspective motion through scenes ("Dynamic Scenes"), and ii) static images taken from these same movies, rearranged such that first-person perspective motion could not be inferred ("Static Scenes"). As predicted, OPA responded significantly more to the Dynamic than Static Scenes, relative to both RSC and PPA. The selective response in OPA to Dynamic Scenes was not due to domain-general motion sensitivity or to low-level information inherited from early visual regions. Taken together, these findings suggest the novel hypothesis that OPA may support visually-guided navigation, insofar as first-person perspective motion information is useful for such navigation, while RSC and PPA support other aspects of navigation and scene recognition.

Visual high-level regions respond to high-level stimulus content in the absence of low-level confounds

High-level regions of the ventral stream exhibit strong category selectivity to stimuli such as faces, houses, or objects. However, recent studies suggest that at least part of this selectivity stems from low-level differences inherent to images of the different categories. For example, visual outdoor and indoor scenes as well as houses differ in spatial frequency, rectilinearity and obliqueness when compared to face or object images. Correspondingly, scene responsive para-hippocampal place area (PPA) showed strong preference to low-level properties of visual scenes also in the absence of high-level scene content. This raises the question whether all high-level responses in PPA, the fusiform face area (FFA), or the object-responsive lateral occipital compex (LOC) may actually be explained by systematic differences in low-level features. In the present study we contrasted two classes of simple stimuli consisting of ten rectangles each. While both were matched in visual low-level features only one class of rectangle arrangements gave rise to a percept compatible with a high-level 3D layout such as a scene or an object. We found that areas PPA, transverse occipital sulcus (TOS, also referred to as occipital place area, OPA), as well as FFA and LOC showed robust responses to the visual scene class compared to the low-level matched control. Our results suggest that visual category responsive regions are not purely driven by low-level visual features but also by the high-level perceptual stimulus interpretation.