Gravity estimation and verticality perception

Dakin, Christopher J.; Rosenberg, Ari

doi:10.1016/b978-0-444-63916-5.00003-3

Cited by 52 publications

(51 citation statements)

References 152 publications

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“…Amongst others, one of these solutions is to learn and store internal models to disambiguate sensory information and to predict forthcoming movement dynamics. On earth, a pervasive component affecting perception and motion is gravity (Bringoux et al, 2012; Dakin and Rosenberg, 2018; Elmore et al, 2014; Gaveau et al, 2011, 2016; Jorges and Lopez-Moliner, 2017; Klein et al, 2018; Lacquaniti et al, 2013; McIntyre et al, 2001; Van Pelt et al, 2005; Rosenberg and Angelaki, 2014; Saradjian et al, 2014; La Scaleia et al, 2019; Senot et al, 2005; Tajadura-Jimenez et al, 2018; De Vrijer et al, 2008). Studies in both humans and non-human primates have provided strong evidence that the brain evolved an internal representation of gravity.…”

Section: Introductionmentioning

confidence: 99%

A cross-species neural integration of gravity for motor optimisation

Gaveau

Grosprêtre

Angelaki

et al. 2019

Preprint

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15Recent kinematic results, combined with model simulations, have provided support for the 16 hypothesis that the human brain uses an internal model of gravity to shape motor patterns that 17 minimise muscle effort. Because many different muscular activation patterns can give rise to 18 the same trajectory, here we analyse muscular activation patterns during single-degree-of-19 freedom arm movements in various directions, which allow to specifically investigating 20 gravity-related movement properties. Using a well-known decomposition method of tonic and 21 phasic electromyographic activities, we demonstrate that phasic EMGs present systematic 22 negative phases. This negativity demonstrates that gravity effects are harvested to save 23 muscle effort and reveals that the brain implements an optimal motor plan using gravity to 24 accelerate downward and decelerate upward movements. Furthermore, for the first time, we 25 compare experimental findings in humans to monkeys, thereby generalising the Effort-26 optimization strategy across species. 27 the velocity and acceleration of the limb -and the gravity forces -related to the position of 51

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Section: Introductionmentioning

confidence: 99%

A cross-species neural integration of gravity for motor optimisation

Gaveau

Grosprêtre

Angelaki

et al. 2019

Preprint

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“…We further found that 567 choice activity was preferentially carried by neurons which robustly represented the task-relevant 568 sensory information, and that the strength of choice activity increased with sensory tolerance. The 569 extent to which subcortical vestibular neurons resolve the gravito-inertial acceleration ambiguity 570 necessary to represent translation independent of head tilt (Dakin and Rosenberg, 2018) similarly 571 correlates with the strength of choice activity (Liu et al, 2013). Across modalities, these results 572 reveal that neurons which have resolved fundamental ambiguities about the sensory information 573 that an animal is actively discriminating preferentially carry choice activity.…”

Section: Potential Origins Of Choice-related Activity 559mentioning

confidence: 91%

Choice activity stabilizes sensory representations and mediates sensorimotor associations in parietal cortex

Chang

Doudlah

Kim

et al. 2020

Preprint

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33Selecting actions which achieve desired goals often requires three-dimensional (3D) 34representations of the environment. Because the sensory epithelia cannot directly encode the 35 world's 3D spatial features, sensory signals must be converted into 3D representations. Here we 36 investigated the relationships between the quality of 3D visual representations, choice-related 37 activity, and motor-related activity in the parietal cortex of macaque monkeys using an eight-38 alternative 3D orientation discrimination task, visually guided saccade task, and laminar probe 39 recordings. We found that choice activity was preferentially carried by caudal intraparietal area 40 neurons with more robust 3D representations. Choice activity further stabilized the 3D 41representations, rather than attenuating information not directly relevant to the behavioral task 42 (nuisance variables). An experience-dependent, sensorimotor association additionally aligned 43 sensory and saccade direction preferences, particularly for neurons with choice activity. These 44 findings reveal novel roles for choice activity in improving the fidelity of ecologically relevant object 45 representations and mediating sensorimotor associations. 46 (Tsutsui et al., 2001;Van Dromme et al., 2016). 67 47The anatomical projections and effective connectivity of CIP suggest that it may also 68 contribute to goal-directed sensorimotor transformations (Nakamura et al., 2001; Premereur et 69 al., 2015;Van Dromme et al., 2016; Lanzilotto et al., 2019). In particular, CIP projects to areas 70 involved in motor planning and execution, including the lateral intraparietal area (LIP) (Andersen 71 et al., 1992;Bennur and Gold, 2011;Shushruth et al., 2018), anterior intraparietal area (Murata 72 et al., 2000;Baumann et al., 2009;Pani et al., 2014), and V6A (Fattori et al., 2010; Fattori et al., 73 2012;Breveglieri et al., 2016). However, it is untested if CIP carries motor-related signals, or if its 74 output only contains 3D sensory information. 75Here we investigated the relationships between sensory representations, choice-related 76 activity, and motor-related activity in CIP. Neuronal activity was recorded while macaque monkeys 77 performed an eight-alternative forced choice (8AFC) tilt discrimination task with planar surfaces 78 presented at different slants and distances . The neurons differed in the extent 79 to which their 3D orientation selectivity depended on distance. Choice activity was preferentially 80 carried by neurons with more robust 3D representations, and further stabilized 3D selectivity. 81Choice tuning was parametric, and the choice and tilt preferences aligned. Motor-related activity 82 was assessed using a visually guided saccade task (Munoz and Wurtz, 1995; Hanes and Schall, 83 1996). We found that many CIP neurons had saccade direction tuning. Moreover, the surface tilt 84 and saccade direction preferences were mapped onto one another, reflecting a sensorimotor 85 association that was strongest for neurons with choice acti...

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“…The mean () and concentration () parameters describe the accuracy and precision of perception, respectively (Murray and Morgenstern, 2010;Seilheimer et al, 2014;Dakin and Rosenberg, 2018). The closer is to 0, the more accurate (less biased) the judgments.…”

Section: Quantifying Tilt Perceptionmentioning

confidence: 99%

Optimized but Not Maximized Cue Integration for 3D Visual Perception

Chang

Thompson

Doudlah

et al. 2019

eNeuro

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Reconstructing three-dimensional (3D) scenes from two-dimensional (2D) retinal images is an ill-posed problem. Despite this, 3D perception of the world based on 2D retinal images is seemingly accurate and precise. The integration of distinct visual cues is essential for robust 3D perception in humans, but it is unclear whether this is true for non-human primates (NHPs). Here, we assessed 3D perception in macaque monkeys using a planar surface orientation discrimination task. Perception was accurate across a wide range of spatial poses (orientations and distances), but precision was highly dependent on the plane's pose. The monkeys achieved robust 3D perception by dynamically reweighting the integration of stereoscopic and perspective cues according to their pose-dependent reliabilities. Errors in performance could be explained by a prior resembling the 3D orientation statistics of natural scenes. We used neural network simulations based on 3D orientation-selective neurons recorded from the same monkeys to assess how neural computation might constrain perception. The perceptual data were consistent with a model in which the responses of two independent neuronal populations representing stereoscopic cues and perspective cues (with perspective signals from the two eyes combined using nonlinear canonical computations) were optimally integrated through linear summation. Perception of combined-cue stimuli was optimal given this architecture. However, an alternative architecture in which stereoscopic cues, left eye perspective cues, and right eye perspective cues were represented by three independent populations yielded two times greater precision than the monkeys. This result suggests that, due to canonical computations, cue integration for 3D perception is optimized but not maximized. Significance StatementOur eyes sense two-dimensional (2D) projections of the world, like a movie on a screen, but we perceive the world as three-dimensional (3D). Here, we show that non-human primates (NHPs), like humans, achieve more precise 3D vision by perceptually integrating distinct 3D cues. We also present evidence that perception is influenced by 3D natural scene statistics, and that priors over 3D orientation are subjectively encoded. Using simulations, we examine how neural computation can constrain 3D perception and estimate that perception is half as precise as theoretically possible. Our findings suggest that the concurrence of multiple canonical computations simultaneously optimizes and curbs 3D visual perception, and highlight that what constitutes optimal task performance depends on the underlying neural architecture.

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Gravity estimation and verticality perception

Cited by 52 publications

References 152 publications

A cross-species neural integration of gravity for motor optimisation

A cross-species neural integration of gravity for motor optimisation

Choice activity stabilizes sensory representations and mediates sensorimotor associations in parietal cortex

Optimized but Not Maximized Cue Integration for 3D Visual Perception

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