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

Pitzalis, Sabrina; Serra, Chiara; Sulpizio, Valentina; Committeri, Giorgia; Pasquale, Francesco de; Fattori, Patrizia; Galletti, Claudio; Sepe, Rosamaria; Galati, Gaspare

doi:10.1002/hbm.24862

Cited by 47 publications

(79 citation statements)

References 185 publications

(469 reference statements)

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“…3 a). These results go along the same direction of our previous studies showing different functional responses in V6+ and MT+ (Pitzalis et al 2010 , 2013b , 2020 ).…”

Section: Resultssupporting

confidence: 91%

“…3a). These results go along the same direction of our previous studies showing different functional responses in V6+ and MT+ (Pitzalis et al 2010(Pitzalis et al , 2013b(Pitzalis et al , 2020. Figure 5 shows the results of a conjunction null analysis showing the cortical regions activated by both scenes/places and flow fields on a flattened cortical surface reconstruction of the left and right hemisphere of a standard brain.…”

Section: Scene-and Egomotion-related Responses In Mt+supporting

confidence: 80%

“…The general assumption behind this dynamic interaction is that motion information is a dominant cue for scene reconstruction and spatial updating (Britten 2008;Frenz et al 2003;Medendorp et al 2003). Consequently, the neural activity in scene-selective regions is modulated by visual motion cues, either when these are constituted by realistic environment (Korkmaz Hacialihafiz and Bartels 2015; Schindler and Bartels 2016; Pitzalis et al 2020) or by coherently moving dot fields (present study). This points to a dynamic interplay between the dorsal and ventral visual pathways likely aimed at combining egomotion-related dynamic cues and scene-related static cues to coordinate visually guided navigation in real environments.…”

Section: Resultsmentioning

confidence: 70%

“…The retinotopic area V3A (Tootell et al 1997 ), which is strongly and directly connected with V6 in monkeys (Galletti et al 2001 ) and humans (Tosoni et al 2015 ; Serra et al 2019 ), responds to changes of heading directions (Huang et al 2012 ; Furlan et al 2014 ) and, together with V6, is specialized in discounting extraretinal signals (coming from eye and head movements) from retinal visual motion in order to infer what is actually moving in the scene, in monkeys (Galletti et al 1990 ; Galletti and Fattori 2003 , 2018 ) and humans (Schindler and Bartels 2018a , b ; Fischer et al 2012 ; Nau et al 2018 ). Interestingly, both V6 and V3A have been recently described in humans as involved in the “flow parsing mechanism” in a realistic virtual environment, being able to extract object motion information by subtracting out self-induced optical flow components (Pitzalis et al 2020 ). In addition, the direct involvement of V6 and V3A in navigational tasks has been also suggested by anatomical (Kravitz et al 2011 ) and resting-state functional connectivity data (Boccia et al 2017a ; Tosoni et al 2015 ; Serra et al 2019 ) and by functional connectivity analysis (Sherrill et al 2015 ).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

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Neuroimaging studies have revealed two separate classes of category-selective regions specialized in optic flow (egomotioncompatible) 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 egomotionselective 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.

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“…3 a). These results go along the same direction of our previous studies showing different functional responses in V6+ and MT+ (Pitzalis et al 2010 , 2013b , 2020 ).…”

Section: Resultssupporting

confidence: 91%

Section: Scene-and Egomotion-related Responses In Mt+supporting

confidence: 80%

Section: Resultsmentioning

confidence: 70%

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

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“…A. Warren, Rushton, & Foulkes, 2012), but we know very little about the neural mechanisms underlying this process. While some recent human neuroimaging studies have reported neural correlates of flow parsing (Field, Biagi, & Inman, 2020;Pitzalis et al, 2020), nothing is currently known about how flow parsing is implemented at the level of individual neurons or neural populations. To investigate the neurophysiology of flow parsing, we must first develop an animal model of flow-parsing behavior.…”

Section: Introductionmentioning

confidence: 99%

Optic flow parsing in the macaque monkey

2020

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During self-motion, an independently moving object generates retinal motion that is the vector sum of its world-relative motion and the optic flow caused by the observer's self-motion. A hypothesized mechanism for the computation of an object's world-relative motion is flow parsing, in which the optic flow field due to self-motion is globally subtracted from the retinal flow field. This subtraction generates a bias in perceived object direction (in retinal coordinates) away from the optic flow vector at the object's location. Despite psychophysical evidence for flow parsing in humans, the neural mechanisms underlying the process are unknown. To build the framework for investigation of the neural basis of flow parsing, we trained macaque monkeys to discriminate the direction of a moving object in the presence of optic flow simulating self-motion. Like humans, monkeys showed biases in object direction perception consistent with subtraction of background optic flow attributable to self-motion. The size of perceptual biases generally depended on the magnitude of the expected optic flow vector at the location of the object, which was contingent on object position and self-motion velocity. There was a modest effect of an object's depth on flow-parsing biases, which reached significance in only one of two subjects. Adding vestibular self-motion signals to optic flow facilitated flow parsing, increasing biases in direction perception. Our findings indicate that monkeys exhibit perceptual hallmarks of flow parsing, setting the stage for the examination of the neural mechanisms underlying this phenomenon.

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Neural sensitivity to translational self‐ and object‐motion velocities

Sulpizio,

von Gal,

Galati

et al. 2024

Human Brain Mapping

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The ability to detect and assess world‐relative object‐motion is a critical computation performed by the visual system. This computation, however, is greatly complicated by the observer's movements, which generate a global pattern of motion on the observer's retina. How the visual system implements this computation is poorly understood. Since we are potentially able to detect a moving object if its motion differs in velocity (or direction) from the expected optic flow generated by our own motion, here we manipulated the relative motion velocity between the observer and the object within a stationary scene as a strategy to test how the brain accomplishes object‐motion detection. Specifically, we tested the neural sensitivity of brain regions that are known to respond to egomotion‐compatible visual motion (i.e., egomotion areas: cingulate sulcus visual area, posterior cingulate sulcus area, posterior insular cortex [PIC], V6+, V3A, IPSmot/VIP, and MT+) to a combination of different velocities of visually induced translational self‐ and object‐motion within a virtual scene while participants were instructed to detect object‐motion. To this aim, we combined individual surface‐based brain mapping, task‐evoked activity by functional magnetic resonance imaging, and parametric and representational similarity analyses. We found that all the egomotion regions (except area PIC) responded to all the possible combinations of self‐ and object‐motion and were modulated by the self‐motion velocity. Interestingly, we found that, among all the egomotion areas, only MT+, V6+, and V3A were further modulated by object‐motion velocities, hence reflecting their possible role in discriminating between distinct velocities of self‐ and object‐motion. We suggest that these egomotion regions may be involved in the complex computation required for detecting scene‐relative object‐motion during self‐motion.

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

Cited by 47 publications

References 185 publications

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

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

Optic flow parsing in the macaque monkey

Neural sensitivity to translational self‐ and object‐motion velocities

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