A model of self-motion estimation within primate extrastriate visual cortex

Perrone, John A.; Stone, Leland S.

doi:10.1016/0042-6989(94)90060-4

Cited by 229 publications

(196 citation statements)

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“…This model provides a mathematically sound explanation for the removal of the rotational component of flow, but requires a complicated hardwired weight matrix. Beintema and van den Berg (1998) extend the template model of Perrone and Stone (1994) to incorporate eye-position gain fields as a solution to the eye rotation problem. While the STARS model also uses eye velocity gain fields, it does so at an earlier processing stage than does Beintema and van den Berg's model.…”

Section: Discussionmentioning

confidence: 99%

“…The Lappe (1998) model explains a wider range of psychophysical data, but still requires embedding the Heeger and Jepson algorithm in the weight matrix. Perrone and Stone (1994) propose a model of the MT-MSTd network in which weights from MT cells encode templates of optic flow fields corresponding to different translational heading directions. The Perrone and Stone model can account for heading perception data in the presence of eye rotations, but Crowell (1997) identified certain situations under which the Perrone and Stone model makes incorrect predictions.…”

Section: Discussionmentioning

confidence: 99%

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A neural model of visually guided steering, obstacle avoidance, and route selection.

Elder¹,

Grossberg²,

Mingolla³

2009

Journal of Experimental Psychology: Human Perception and Perfor

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A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discontinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and VIP can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.Key Words: Heading Perception, Steering, Optic Flow, Obstacle, Goal, Pursuit Eye Movement, Gain Fields, Peak Shift, V2, MT, MST, VIP, LIP 3 IntroductionMany important steering tasks are guided by visual information, including walking through a cluttered environment (Fajen & Warren, 2003), driving (Land & Horwood, 1995;Hildreth, Beusmans, Boer, & Royden, 2000;Wallis, Chatziastros, & Bülthoff, 2002), vehicle braking (Lee, 1976, piloting an aircraft (Gibson, Olum, & Rosenblatt, 1955;Beall & Loomis, 1997), and intercepting a moving target on foot (Fajen & Warren, 2004). Steering through a cluttered environment involves the selection of a path that avoids obstacles and simultaneously approaches the intended goal. Human steering is guided by visual information about the spatial layout of the environment and the direction of self-motion through the environment, as well as proprioceptive feedback and information from other sensory systems. In particular, the visual system provides information about the relative positions of the goal object and obstacles in the environment.Movement through the world creates a full-field pattern of motion on the retina, called optic flow, which contains information about the direction of self-motion, or heading (Gibson, 1950). In principle, optic flow can be used to compute heading (Longuet-Higgins & Prazdny, 1980). During translational movement of the eye, the optic flow field contains a singularity, called the focus of expansion, which specifies the direction of heading in the absence of an eye rotation.Figures 1 & 2 Whereas optic flow relates observer motion to the available visual stimuli, recent research clarifies how visual information governs the dynamics of human navigational behavior. Fajen and Warren (2003) studied the dynamics of human steering behavior in simple goal approach and obstacle avoidance tasks using an immersive virtual reality system. They found that human performa...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A neural model of visually guided steering, obstacle avoidance, and route selection.

Elder¹,

Grossberg²,

Mingolla³

2009

Journal of Experimental Psychology: Human Perception and Perfor

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show abstract

“…In this way MSTd could map out the relationship between the expansion focus and heading with relatively few neurons, each adjusting its focus preference according to the velocity of the eye. Similar models have been proposed by Perrone & Stone (1994) and by Warren (1995), but their models require separate heading maps for different combinations of eye direction and speed (rather than a smaller number of cells that are adjusted to account for eye movement).…”

Section: Visual Motion and Pursuitmentioning

confidence: 99%

“…If the flow field can be decomposed into these two contributions, then the focus of the expansion field corresponds to the direction of heading. This is not an easy computational problem, but several researchers have suggested various algorithms and explanations of how the nervous system might perform this task using retinal cues (Lounguet-Higgins & Prazdny 1980, Koenderink & van Doorn 1981, Rieger & Lawton 1985Heeger & Jepson 1990, Lappe & Rauschecker 1993, Perrone & Stone 1994. Royden et al (1992) recently showed that the eye movement itself generates a signal, presumably an efference copy of the pursuit command, that can be used to solve this problem.…”

Section: Visual Motion and Pursuitmentioning

confidence: 99%

Multimodal Representation of Space in the Posterior Parietal Cortex and Its Use in Planning Movements

Andersen

Snyder

Bradley

et al. 1997

Annu. Rev. Neurosci.

1,280

637

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Recent experiments are reviewed that indicate that sensory signals from many modalities, as well as efference copy signals from motor structures, converge in the posterior parietal cortex in order to code the spatial locations of goals for movement. These signals are combined using a specific gain mechanism that enables the different coordinate frames of the various input signals to be combined into common, distributed spatial representations. These distributed representations can be used to convert the sensory locations of stimuli into the appropriate motor coordinates required for making directed movements. Within these spatial representations of the posterior parietal cortex are neural activities related to higher cognitive functions, including attention. We review recent studies showing that the encoding of intentions to make movements is also among the cognitive functions of this area.

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“…Indeed, this would be sensible if robust perception of self-motion ultimately relies on neural representations in which visual and vestibular cues are integrated. MSTd neurons have large visual receptive fields 18 , respond selectively to large-field optic flow stimuli 16,17 , and are thought to constitute a population code for representing heading from optic flow [19][20][21][22] . Electrical microstimulation of MSTd biases monkeys' reports of heading based on optic flow 23, 24 , indicating that MSTd carries visual signals used to judge heading.…”

mentioning

confidence: 99%

A functional link between area MSTd and heading perception based on vestibular signals

2007

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Recent findings of vestibular responses in visual cortex -the dorsal medial superior temporal area (MSTd) -suggest that vestibular signals might contribute to cortical processes mediating selfmotion perception. We tested this hypothesis in monkeys trained to perform a fine heading discrimination task based solely on inertial motion cues. Neuronal sensitivity was typically lower than psychophysical sensitivity, and only the most sensitive neurons rivaled behavioral performance. MSTd responses were significantly correlated with perceptual decisions, with correlations being strongest for the most sensitive neurons. These results support a functional link between MSTd and heading perception based on inertial motion cues. These cues are mainly of vestibular origin, since labyrinthectomy produced dramatic elevation of psychophysical thresholds and abolished MSTd responses. This study provides the first evidence that links single-unit activity to spatial perception mediated by vestibular signals, and suggests that the role of MSTd in self-motion perception extends beyond optic flow processing. The vestibular apparatus provides sensory information about the angular velocity (semicircular canals) and linear acceleration (otolith organs) of the head 1, 2 . Lesion studies demonstrate that vestibular signals play critical roles in several reflexive processes, including compensatory eye movements (vestibulo-ocular reflex, VOR) 3, 4 , maintenance of balance, and control of posture 5 . The neural circuits that mediate these automatic processes-especially the VORhave been explored extensively 6, 7 .The vestibular system should also contribute to processes that are under cognitive control, such as perception of spatial orientation and self-motion 8-10 . To investigate this, we trained rhesus monkeys to report their perceived direction of heading (leftward vs. rightward relative to straight ahead) based solely on inertial motion cues. We show that trained animals discriminate differences in heading as small as 1-2° (comparable to human performance 11 ), and that damage to the vestibular labyrinth dramatically impairs performance. This establishes the heading discrimination task as a sensitive probe of vestibular function relevant to self-motion perception.Where in the brain can one find neurons that mediate heading perception based on inertial motion cues? Unlike in other sensory systems, relatively little is known about the cortical processing of vestibular signals. Whereas neural activity has been linked to perception in other

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A model of self-motion estimation within primate extrastriate visual cortex

Cited by 229 publications

References 114 publications

A neural model of visually guided steering, obstacle avoidance, and route selection.

A neural model of visually guided steering, obstacle avoidance, and route selection.

Multimodal Representation of Space in the Posterior Parietal Cortex and Its Use in Planning Movements

A functional link between area MSTd and heading perception based on vestibular signals

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