COMPASS: Computations for Orientation and Motion Perception in Altered Sensorimotor States

Kravets, Victoria; Dixon, Jordan B.; Ahmed, Nisar; Clark, Torin K.

doi:10.3389/fncir.2021.757817

Cited by 11 publications

(19 citation statements)

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“…Such models have been developed in an effort to better understand how the central nervous system integrates sensory cueing ( Clark et al, 2019 ). Some models of orientation perception are built upon estimation theory concepts ( MacNeilage et al, 2008 ), such as Kalman filter ( Kalman, 1960 ) models ( Laurens and Angelaki, 2017 ), particle filter models ( Laurens and Droulez, 2007 ; Karmali and Merfeld, 2012 ; Kravets et al, 2021 ; Allred et al, 2023 ), and non-linear models ( Observer models) ( Selva and Oman, 2012 ). Observer models are non-linear models of spatial orientation perception that, as a key function, use sensory conflict to predict perception ( Luenberger, 1971 ; Oman, 1982 ; Merfeld et al, 1993 ; Merfeld and Zupan, 2002 ; Zupan et al, 2002 ; Vingerhoets et al, 2007 , 2009 ; Newman, 2009 ; Rader et al, 2009 ; Williams et al, 2021 ).…”

Section: Orientation Perception Modeling Backgroundmentioning

confidence: 99%

Humans gradually integrate sudden gain or loss of visual information into spatial orientation perception

Voros,

Kravets,

Smith

et al. 2024

Front. Neurosci.

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IntroductionVestibular and visual information is used in determining spatial orientation. Existing computational models of orientation perception focus on the integration of visual and vestibular orientation information when both are available. It is well-known, and computational models capture, differences in spatial orientation perception with visual information or without (i.e., in the dark). For example, during earth vertical yaw rotation at constant angular velocity without visual information, humans perceive their rate of rotation to decay. However, during the same sustained rotation with visual information, humans can continue to more accurately perceive self-rotation. Prior to this study, there was no existing literature on human motion perception where visual information suddenly become available or unavailable during self-motion.MethodsVia a well verified psychophysical task, we obtained perceptual reports of self-rotation during various profiles of Earth-vertical yaw rotation. The task involved transitions in the availability of visual information (and control conditions with visual information available throughout the motion or unavailable throughout).ResultsWe found that when visual orientation information suddenly became available, subjects gradually integrated the new visual information over ~10 seconds. In the opposite scenario (visual information suddenly removed), past visual information continued to impact subject perception of self-rotation for ~30 seconds. We present a novel computational model of orientation perception that is consistent with the experimental results presented in this study.DiscussionThe gradual integration of sudden loss or gain of visual information is achieved via low pass filtering in the visual angular velocity sensory conflict pathway. In conclusion, humans gradually integrate sudden gain or loss of visual information into their existing perception of self-motion.

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Section: Orientation Perception Modeling Backgroundmentioning

confidence: 99%

Humans gradually integrate sudden gain or loss of visual information into spatial orientation perception

Voros,

Kravets,

Smith

et al. 2024

Front. Neurosci.

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“…is the innovation (i.e., sensory conflict) vector for hypothesis j and S is the scaled biological noise covariance (see Supplementary Table 1 for specific values of all parameters, and Kravets et al (2021) for further discussion). Model Framework for adaptation to altered gravity incorporating short term memory (STM) and long-term memory (LTM).…”

Section: Model Framework Overviewmentioning

confidence: 99%

“…Other works suggest that vestibular sensory noise increases non-linearly with vestibular stimuli (Vingerhoets et al, 2009). We implemented vestibular noise similarly to prior works (Kravets et al, 2021(Kravets et al, , 2022 where a constant noise power (1e-8) is applied to the vestibular sensory signals (noise power is the height of the power spectral density of the white noise added to the system). A comparison of noise power to adaptation time can be found in Kravets et al (2021; see Figure 7).…”

Section: Model Implementationmentioning

confidence: 99%

“…This model CNS recursively estimates gravity's magnitude through Bayesian inference, as previously proposed in Kravets et al (2021). However we differ from the Kravets et al (2021) implementation (which considered a static set of gravity hypotheses at each time step), and instead utilize methods proposed in Kravets et al (2022) by modeling the evolution of potential Model simulation of tilt perceptions associated with adaptation to gravity transition. (A) highlights the adaptation trajectory surrounding the gravity transition from 1 to 4 g at timepoint T1 in Figure 5, with a roll tilt motion profile.…”

Section: A B Figurementioning

confidence: 99%

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Modeling orientation perception adaptation to altered gravity environments with memory of past sensorimotor states

Allred

Kravets

Ahmed

et al. 2023

Front. Neural Circuits

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Transitioning between gravitational environments results in a central reinterpretation of sensory information, producing an adapted sensorimotor state suitable for motor actions and perceptions in the new environment. Critically, this central adaptation is not instantaneous, and complete adaptation may require weeks of prolonged exposure to novel environments. To mitigate risks associated with the lagging time course of adaptation (e.g., spatial orientation misperceptions, alterations in locomotor and postural control, and motion sickness), it is critical that we better understand sensorimotor states during adaptation. Recently, efforts have emerged to model human perception of orientation and self-motion during sensorimotor adaptation to new gravity stimuli. While these nascent computational frameworks are well suited for modeling exposure to novel gravitational stimuli, they have yet to distinguish how the central nervous system (CNS) reinterprets sensory information from familiar environmental stimuli (i.e., readaptation). Here, we present a theoretical framework and resulting computational model of vestibular adaptation to gravity transitions which captures the role of implicit memory. This advancement enables faster readaptation to familiar gravitational stimuli, which has been observed in repeat flyers, by considering vestibular signals dependent on the new gravity environment, through Bayesian inference. The evolution and weighting of hypotheses considered by the CNS is modeled via a Rao-Blackwellized particle filter algorithm. Sensorimotor adaptation learning is facilitated by retaining a memory of past harmonious states, represented by a conditional state transition probability density function, which allows the model to consider previously experienced gravity levels (while also dynamically learning new states) when formulating new alternative hypotheses of gravity. In order to demonstrate our theoretical framework and motivate future experiments, we perform a variety of simulations. These simulations demonstrate the effectiveness of this model and its potential to advance our understanding of transitory states during which central reinterpretation occurs, ultimately mitigating the risks associated with the lagging time course of adaptation to gravitational environments.

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“…2012 ; Kravets et al. 2021 ). The choice of the PFM is aimed at including probabilistic modelling to study motion perception and sickness.…”

Section: Introductionmentioning

confidence: 99%

Validating models of sensory conflict and perception for motion sickness prediction

et al. 2023

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The human motion perception system has long been linked to motion sickness through state estimation conflict terms. However, to date, the extent to which available perception models are able to predict motion sickness, or which of the employed perceptual mechanisms are of most relevance to sickness prediction, has not been studied. In this study, the subjective vertical model, the multi-sensory observer model and the probabilistic particle filter model were all validated for their ability to predict motion perception and sickness, across a large set of motion paradigms of varying complexity from literature. It was found that even though the models provided a good match for the perception paradigms studied, they could not be made to capture the full range of motion sickness observations. The resolution of the gravito-inertial ambiguity has been identified to require further attention, as key model parameters selected to match perception data did not optimally match motion sickness data. Two additional mechanisms that may enable better future predictive models of sickness have, however, been identified. Firstly, active estimation of the magnitude of gravity appears to be instrumental for predicting motion sickness induced by vertical accelerations. Secondly, the model analysis showed that the influence of the semicircular canals on the somatogravic effect may explain the differences in the dynamics observed for motion sickness induced by vertical and horizontal plane accelerations.

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COMPASS: Computations for Orientation and Motion Perception in Altered Sensorimotor States

Cited by 11 publications

References 70 publications

Humans gradually integrate sudden gain or loss of visual information into spatial orientation perception

Humans gradually integrate sudden gain or loss of visual information into spatial orientation perception

Modeling orientation perception adaptation to altered gravity environments with memory of past sensorimotor states

Validating models of sensory conflict and perception for motion sickness prediction

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