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. 2014 Feb 3:5:50.
doi: 10.3389/fpsyg.2014.00050. eCollection 2014.

The role of differential delays in integrating transient visual and proprioceptive information

Brendan D Cameron  1 , Cristina de la Malla  1 , Joan López-Moliner  1
Affiliations

The role of differential delays in integrating transient visual and proprioceptive information

Brendan D Cameron et al. Front Psychol. .

Abstract

Many actions involve limb movements toward a target. Visual and proprioceptive estimates are available online, and by optimally combining (Ernst and Banks, 2002) both modalities during the movement, the system can increase the precision of the hand estimate. The notion that both sensory modalities are integrated is also motivated by the intuition that we do not consciously perceive any discrepancy between the felt and seen hand's positions. This coherence as a result of integration does not necessarily imply realignment between the two modalities (Smeets et al., 2006). For example, the two estimates (visual and proprioceptive) might be different without either of them (e.g., proprioception) ever being adjusted after recovering the other (e.g., vision). The implication that the felt and seen positions might be different has a temporal analog. Because the actual feedback from the hand at a given instantaneous position reaches brain areas at different times for proprioception and vision (shorter for proprioception), the corresponding instantaneous unisensory position estimates will be different, with the proprioceptive one being ahead of the visual one. Based on the assumption that the system integrates optimally and online the available evidence from both senses, we introduce a temporal mechanism that explains the reported overestimation of hand positions when vision is occluded for active and passive movements (Gritsenko et al., 2007) without the need to resort to initial feedforward estimates (Wolpert et al., 1995). We set up hypotheses to test the validity of the model, and we contrast simulation-based predictions with empirical data.

Keywords: perceptual judgments; position estimates; proprioception; reaching; vision.

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Figures

Figure 1
Figure 1
Sketch to illustrate our rationale. (A) The gray curve denotes the actual path traveled by a hand: the changing position in one dimensional space is plotted against time. The slope of the curve at any given point describes the tangential velocity at this particular time. The green and red points therefore correspond to moments at which the hand moves slowly early in the path (green) and when it moves at the highest speed half way to the target (red). See text for details. (B) Sketch of the position estimate based on integrated information. The dashed curve denotes the integrated estimate based on visual feedback (red) and proprioceptive feedback (blue). A constant shift is assumed to correct for the sensory delays. (C) The same as (B) but without visual information. The visual estimate (red) has a larger uncertainty.
Figure 2
Figure 2
(A) Velocity profile of a hand movement in a pursuit task (adapted from Rodríguez-Herreros and López-Moliner, 2008). (B) The expected perceptual bias across time would be determined by the velocity profile and the differential delay (color coded) between vision and proprioception. Inset: The expected bias as a function of tangential velocity for the four possible differential delays used in the simulation. See text for more details.
Figure 3
Figure 3
Bias as a function of angular velocity adapted from Gritsenko et al. (2007), (Figure 7A) for the different active movement conditions. Different colors code the angles at which the probe was shown while moving the arm (60, 75, 90, and 105° in blue, black, orange, and red respectively). The black line denotes the expected bias assuming a differential delay of 60 ms between vision and proprioception. The blue solid line denotes the best fit (slope 0.066 s and zero intercept) including the data points that fall within the gray rectangle. The dashed solid line (slope 0.133 s and zero intercept) denotes the fit to all data points.
Figure 4
Figure 4
The nine different movements used in the simulation of under-reaching bias. (A) Changing position of the finger for the different movements. The movement time was always 0.7 s and the peak velocity varied from 10 cm/s (the slowest movement) until 200 cm/s (the fastest movement). (B) The corresponding velocity profiles with signal-dependent noise. Note that in (A) the noise is not noticeable after integrating the tangential velocity.
Figure 5
Figure 5
The expected values for a bias in under-reaching static visual targets with the unseen hand as a function of peak velocity in simulated movements. Different colors and symbols denote differential delays between visual and proprioceptive feedback. Inset: illustration of the estimation of the felt position of the hand (dashed red Gaussian) and the estimation of the static target (solid black Gaussian). A running distance (denoted by d) between both Gaussian was computed to determine the final end point based on unisensory estimates of the hand. See text for details.
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