A sensory source for motor variation

Osborne, Leslie C.; Lisberger, Stephen G.; Bialek, William

doi:10.1038/nature03961

Cited by 278 publications

(321 citation statements)

References 27 publications

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“…The basis for this recommendation has received little attention, even though it was shown that humans in a manual interception task naturally use smooth pursuit eye movements (Brenner & Smeets, 2009Mrotek & Soechting, 2007). It also has been shown convincingly that the visual system is extremely fast at figuring out in which direction a stimulus moves (de Bruyn & Orban, 1988), and that this information is readily available to guide smooth pursuit eye movements (Osborne, Lisberger, & Bialek, 2005;Stone & Krauzlis, 2003).…”

Section: Directional Selectivity During Pursuitmentioning

confidence: 99%

The Interaction Between Vision and Eye Movements

Gegenfurtner

2016

Perception

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The existence of a central fovea, the small retinal region with high analytical performance, is arguably the most prominent design feature of the primate visual system. This centralization comes along with the corresponding capability to move the eyes to reposition the fovea continuously. Past research on visual perception was mainly concerned with foveal vision while the observers kept their eyes stationary. Research on the role of eye movements in visual perception emphasized their negative aspects, for example, the active suppression of vision before and during the execution of saccades. But is the only benefit of our precise eye movement system to provide high acuity of the small foveal region, at the cost of retinal blur during their execution? In this review, I will compare human visual perception with and without saccadic and smooth pursuit eye movements to emphasize different aspects and functions of eye movements. I will show that the interaction between eye movements and visual perception is optimized for the active sampling of information across the visual field and for the calibration of different parts of the visual field. The movements of our eyes and visual information uptake are intricately intertwined. The two processes interact to enable an optimal perception of the world, one that we cannot fully grasp by doing experiments where observers are fixating a small spot on a display.

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Section: Directional Selectivity During Pursuitmentioning

confidence: 99%

The Interaction Between Vision and Eye Movements

Gegenfurtner

2016

Perception

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“…Whereas Gordon et al (1994) and Churchland et al (2006) concluded that the variability in arm movements originates mostly in central movement planning, van Beers et al (2004) demonstrated that movement execution is the major source. Moreover, Osborne et al (2005Osborne et al ( , 2007 showed that sensory information is the major source of variability in smooth pursuit eye movements. Although the major source could be different for movements of different body parts, the conflicting results for arm movements demonstrate how poorly the origin of movement variability is understood.…”

Section: Introductionmentioning

confidence: 99%

The Sources of Variability in Saccadic Eye Movements

Beers¹

2007

J. Neurosci.

156

146

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Our movements are variable, but the origin of this variability is poorly understood. We examined the sources of variability in human saccadic eye movements. In two experiments, we measured the spatiotemporal variability in saccade trajectories as a function of movement direction and amplitude. One of our new observations is that the variability in movement direction is smaller for purely horizontal and vertical saccades than for saccades in oblique directions. We also found that saccade amplitude, duration, and peak velocity are all correlated with one another. To determine the origin of the observed variability, we estimated the noise in motor commands from the observed spatiotemporal variability, while taking into account the variability resulting from uncertainty in localization of the target. This analysis revealed that uncertainty in target localization is the major source of variability in saccade endpoints, whereas noise in the magnitude of the motor commands explains a slightly smaller fraction. In addition, there is temporal variability such that saccades with a longer than average duration have a smaller than average peak velocity. This noise model has a large generality because it correctly predicts the variability in other data sets, which contain saccades starting from very different initial locations. Because the temporal noise most likely originates in movement planning, and the motor command noise in movement execution, we conclude that uncertainty in sensory signals and noise in movement planning and execution all contribute to the variability in saccade trajectories. These results are important for understanding how the brain controls movement.

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“…Although earlier work focused on the deterministic properties of dynamical systems such as bifurcations and attractors, the important role of noise in the motor system is also increasingly recognized, either as a limitation that the system must overcome (17,18) or as an imprint of the inherent uncertainties in estimates of the input stimuli (19). In movement science, there is thus increased attention to learning stochastic dynamical systems from data (20).…”

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confidence: 99%

Emergence of long timescales and stereotyped behaviors in Caenorhabditis elegans

Stephens

Mesquita

Ryu

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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Animal behaviors often are decomposable into discrete, stereotyped elements, well separated in time. In one model, such behaviors are triggered by specific commands; in the extreme case, the discreteness of behavior is traced to the discreteness of action potentials in the individual command neurons. Here, we use the crawling behavior of the nematode Caenorhabditis elegans to demonstrate the opposite view, in which discreteness, stereotypy, and long timescales emerge from the collective dynamics of the behavior itself. In previous work, we found that as C. elegans crawls, its body moves through a "shape space" in which four dimensions capture approximately 95% of the variance in body shape. Here we show that stochastic dynamics within this shape space predicts transitions between attractors corresponding to abrupt reversals in crawling direction. With no free parameters, our inferred stochastic dynamical system generates reversal timescales and stereotyped trajectories in close agreement with experimental observations. We use the stochastic dynamics to show that the noise amplitude decreases systematically with increasing time away from food, resulting in longer bouts of forward crawling and suggesting that worms can use noise to modify their locomotory behavior.motor behavior | stochastic transitions | adaptation M any organisms, from bacteria to humans, exhibit discrete, stereotyped motor behaviors. A common model is that these behaviors are stereotyped because they are triggered by specific commands, and in some cases we can identify "command neurons" whose activity provides the trigger (1). In the extreme, discreteness and stereotypy of the behavior reduces to the discreteness and stereotypy of the action potentials generated by the command neurons, as with the escape behaviors in fish triggered by spiking of the Mauthner cell (2). But the stereotypy of spikes itself emerges from the continuous dynamics of currents, voltages, and ion channel populations (3, 4). Is it possible that, in more complex systems, stereotypy emerges not from the dynamics of single neurons, but from the dynamics of larger circuits of neurons, perhaps coupled to the mechanics of the behavior itself? Here we explore this question in the context of abrupt reversals in the crawling direction of the nematode Caenorhabditis elegans (5-7).Reversal behaviors of C. elegans are particularly interesting as the underlying neural circuitry includes a nominal command neuron, AVA (8), whose activity is correlated with forward vs. backward crawling (9). On the other hand, AVA is an interneuron in a network, and it is unknown whether the decision to reverse direction can be traced to a single cell. Even when AVA is ablated, reversals occur, although the distribution of times spent in the backward crawling state shifts (7). Further, most neurons in C. elegans do not generate action potentials, so even if a single neuron dominates the decision it is not obvious why the trajectory of a reversal would be stereotyped. As a complement to probing further in...

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A sensory source for motor variation

Cited by 278 publications

References 27 publications

The Interaction Between Vision and Eye Movements

The Interaction Between Vision and Eye Movements

The Sources of Variability in Saccadic Eye Movements

Emergence of long timescales and stereotyped behaviors in Caenorhabditis elegans

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