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Slower visuomotor corrections with unchanged latency are consistent with optimal adaptation to increased endogenous noise in the elderly.

Sherback M, Valero-Cuevas FJ, D'Andrea R - PLoS Comput. Biol. (2010)

Bottom Line: The model reproduces the latency result from the cross-correlation method.When presented with increased noise, the computational model reproduces the experimentally observed age-related slowing and the observed lack of increased latency.The model provides a precise way to quantitatively formulate the long-standing hypothesis that age-related slowing is an adaptation to increased noise.

View Article: PubMed Central - PubMed

Affiliation: Institute for Dynamic Systems and Control, ETH-Zurich, Zurich, Switzerland. sherback@idsc.mavt.ethz.ch

ABSTRACT
We analyzed age-related changes in motor response in a visuomotor compensatory tracking task. Subjects used a manipulandum to attempt to keep a displayed cursor at the center of a screen despite random perturbations to its location. Cross-correlation analysis of the perturbation and the subject response showed no age-related increase in latency until the onset of response to the perturbation, but substantial slowing of the response itself. Results are consistent with age-related deterioration in the ratio of signal to noise in visuomotor response. The task is such that it is tractable to use Bayesian and quadratic optimality assumptions to construct a model for behavior. This model assumes that behavior resembles an optimal controller subject to noise, and parametrizes response in terms of latency, willingness to expend effort, noise intensity, and noise bandwidth. The model is consistent with the data for all young (n = 12, age 20-30) and most elderly (n = 12, age 65-92) subjects. The model reproduces the latency result from the cross-correlation method. When presented with increased noise, the computational model reproduces the experimentally observed age-related slowing and the observed lack of increased latency. The model provides a precise way to quantitatively formulate the long-standing hypothesis that age-related slowing is an adaptation to increased noise.

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Relationship of  to input velocity.The left panel shows that among a uniformly healthy young population whose multiplicative noise characteristics can be expected to be uniform, a relationship between the control cost/multiplicative noise parameter  and observed RMS  exists as expected. Data points from outlying subjects 1 and 10 are shown with triangles and omitted from the displayed empirical least-squares linear fit. The increase in this parameter at any given level of RMS  for the elderly is shown in the right frame. This is consistent with increased noise.
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pcbi-1000708-g008: Relationship of to input velocity.The left panel shows that among a uniformly healthy young population whose multiplicative noise characteristics can be expected to be uniform, a relationship between the control cost/multiplicative noise parameter and observed RMS exists as expected. Data points from outlying subjects 1 and 10 are shown with triangles and omitted from the displayed empirical least-squares linear fit. The increase in this parameter at any given level of RMS for the elderly is shown in the right frame. This is consistent with increased noise.

Mentions: Fourth, the optimal control model would be in doubt if its inferred latency values were inconsistent with the result from the cross-correlation method; this is not the case, as described in detail in the next subsection. Along similar lines, the increase in disorder visible in Fig. 5 should be captured in our model's parameters as increased multiplicative noise and therefore reflected in the fitted parameter. Specifically, direct inspection of the data in the left panel of Fig. 5 shows significant differences in RMS control input that should be correlated with age-related changes in the multiplicative noise/control cost parameter . Fig. 8 shows that the expected relationship holds for the young, where it is reasonable to assume that the effect of multiplicative noise on this parameter is relatively uniform due to uniform health, and variations in result only from altered willingness to expend effort. What is more interesting is that Fig. 7 also shows that tends to be larger for the elderly given some level of observed RMS control input . This is consistent with the empirical observation of increased multiplicative noise.


Slower visuomotor corrections with unchanged latency are consistent with optimal adaptation to increased endogenous noise in the elderly.

Sherback M, Valero-Cuevas FJ, D'Andrea R - PLoS Comput. Biol. (2010)

Relationship of  to input velocity.The left panel shows that among a uniformly healthy young population whose multiplicative noise characteristics can be expected to be uniform, a relationship between the control cost/multiplicative noise parameter  and observed RMS  exists as expected. Data points from outlying subjects 1 and 10 are shown with triangles and omitted from the displayed empirical least-squares linear fit. The increase in this parameter at any given level of RMS  for the elderly is shown in the right frame. This is consistent with increased noise.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2837393&req=5

pcbi-1000708-g008: Relationship of to input velocity.The left panel shows that among a uniformly healthy young population whose multiplicative noise characteristics can be expected to be uniform, a relationship between the control cost/multiplicative noise parameter and observed RMS exists as expected. Data points from outlying subjects 1 and 10 are shown with triangles and omitted from the displayed empirical least-squares linear fit. The increase in this parameter at any given level of RMS for the elderly is shown in the right frame. This is consistent with increased noise.
Mentions: Fourth, the optimal control model would be in doubt if its inferred latency values were inconsistent with the result from the cross-correlation method; this is not the case, as described in detail in the next subsection. Along similar lines, the increase in disorder visible in Fig. 5 should be captured in our model's parameters as increased multiplicative noise and therefore reflected in the fitted parameter. Specifically, direct inspection of the data in the left panel of Fig. 5 shows significant differences in RMS control input that should be correlated with age-related changes in the multiplicative noise/control cost parameter . Fig. 8 shows that the expected relationship holds for the young, where it is reasonable to assume that the effect of multiplicative noise on this parameter is relatively uniform due to uniform health, and variations in result only from altered willingness to expend effort. What is more interesting is that Fig. 7 also shows that tends to be larger for the elderly given some level of observed RMS control input . This is consistent with the empirical observation of increased multiplicative noise.

Bottom Line: The model reproduces the latency result from the cross-correlation method.When presented with increased noise, the computational model reproduces the experimentally observed age-related slowing and the observed lack of increased latency.The model provides a precise way to quantitatively formulate the long-standing hypothesis that age-related slowing is an adaptation to increased noise.

View Article: PubMed Central - PubMed

Affiliation: Institute for Dynamic Systems and Control, ETH-Zurich, Zurich, Switzerland. sherback@idsc.mavt.ethz.ch

ABSTRACT
We analyzed age-related changes in motor response in a visuomotor compensatory tracking task. Subjects used a manipulandum to attempt to keep a displayed cursor at the center of a screen despite random perturbations to its location. Cross-correlation analysis of the perturbation and the subject response showed no age-related increase in latency until the onset of response to the perturbation, but substantial slowing of the response itself. Results are consistent with age-related deterioration in the ratio of signal to noise in visuomotor response. The task is such that it is tractable to use Bayesian and quadratic optimality assumptions to construct a model for behavior. This model assumes that behavior resembles an optimal controller subject to noise, and parametrizes response in terms of latency, willingness to expend effort, noise intensity, and noise bandwidth. The model is consistent with the data for all young (n = 12, age 20-30) and most elderly (n = 12, age 65-92) subjects. The model reproduces the latency result from the cross-correlation method. When presented with increased noise, the computational model reproduces the experimentally observed age-related slowing and the observed lack of increased latency. The model provides a precise way to quantitatively formulate the long-standing hypothesis that age-related slowing is an adaptation to increased noise.

Show MeSH