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Learning course adjustments during arm movements with reversed sensitivity derivatives.

Abdelghani MN, Tweed DB - BMC Neurosci (2010)

Bottom Line: Here we test a recent theory that the brain's estimates of sensitivity derivatives are revisable based on sensory feedback.The target jumped once during each movement.It is consistent with the idea of a single, all-purpose estimate of those derivatives; and it suggests that the estimate is a function of context, as one would expect given that the true sensitivity derivatives may vary with the state of the controlled system, the target, and the motor commands.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physiology, University of Toronto, Toronto, Canada.

ABSTRACT

Background: To learn, a motor system needs to know its sensitivity derivatives, which quantify how its neural commands affect motor error. But are these derivatives themselves learned, or are they known solely innately? Here we test a recent theory that the brain's estimates of sensitivity derivatives are revisable based on sensory feedback. In its simplest form, the theory says that each control system has a single, adjustable estimate of its sensitivity derivatives which affects all aspects of its task, e.g. if you learn to reach to mirror-reversed targets then your revised estimate should reverse not only your initial aiming but also your online course adjustments when the target jumps in mid-movement.

Methods: Human subjects bent a joystick to move a cursor to a target on a computer screen, but the cursor's motion was reversed relative to the joystick's. The target jumped once during each movement. Subjects had up to 4000 trials to practice aiming and responding to target jumps.

Results: All subjects learned to reverse both initial aiming and course adjustments.

Conclusions: Our study confirms that sensitivity derivatives can be relearned. It is consistent with the idea of a single, all-purpose estimate of those derivatives; and it suggests that the estimate is a function of context, as one would expect given that the true sensitivity derivatives may vary with the state of the controlled system, the target, and the motor commands.

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All 5 subjects learned. (a) On the ordinate are means and standard errors of launch error (LE) for the 1000 initial control trials. On the abscissa are the same measures for first 200 reversed trials (5 gray symbols for the 5 subjects) and for the last 1000 reversed trials (black symbols). Across all subjects, launch error improved significantly by t-test (p = 0.025) and in late reversed trials was not significantly different from control (p = 0.35). (b) Adjustment (AE) error also improved (p = 0.025) to control levels (p = 0.47). (c, d) Similarly for launch latency (LL) (p = 0.035 and 0.26) and adjustment latency (AL) (p = 0.004 and 0.43).
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Figure 5: All 5 subjects learned. (a) On the ordinate are means and standard errors of launch error (LE) for the 1000 initial control trials. On the abscissa are the same measures for first 200 reversed trials (5 gray symbols for the 5 subjects) and for the last 1000 reversed trials (black symbols). Across all subjects, launch error improved significantly by t-test (p = 0.025) and in late reversed trials was not significantly different from control (p = 0.35). (b) Adjustment (AE) error also improved (p = 0.025) to control levels (p = 0.47). (c, d) Similarly for launch latency (LL) (p = 0.035 and 0.26) and adjustment latency (AL) (p = 0.004 and 0.43).

Mentions: In test blocks, both dimensions of cursor motion were reversed from control, flipping the signs of all components of ∂e/∂u (Figure 1e). Five subjects took part -- one female, four males, all healthy, aged 21-48. Three of them knew the experiment involved a reversed relation between joystick and cursor. One of these three had experience with joystick experiments, and one with joystick computer games. All our single-person data plots (Figure 2, 3, and 4) are of subjects who were unfamiliar both with joysticks and with the idea of motor adaptation to reversals, but the key findings were the same for all subjects, as shown in Figure 5.


Learning course adjustments during arm movements with reversed sensitivity derivatives.

Abdelghani MN, Tweed DB - BMC Neurosci (2010)

All 5 subjects learned. (a) On the ordinate are means and standard errors of launch error (LE) for the 1000 initial control trials. On the abscissa are the same measures for first 200 reversed trials (5 gray symbols for the 5 subjects) and for the last 1000 reversed trials (black symbols). Across all subjects, launch error improved significantly by t-test (p = 0.025) and in late reversed trials was not significantly different from control (p = 0.35). (b) Adjustment (AE) error also improved (p = 0.025) to control levels (p = 0.47). (c, d) Similarly for launch latency (LL) (p = 0.035 and 0.26) and adjustment latency (AL) (p = 0.004 and 0.43).
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3008695&req=5

Figure 5: All 5 subjects learned. (a) On the ordinate are means and standard errors of launch error (LE) for the 1000 initial control trials. On the abscissa are the same measures for first 200 reversed trials (5 gray symbols for the 5 subjects) and for the last 1000 reversed trials (black symbols). Across all subjects, launch error improved significantly by t-test (p = 0.025) and in late reversed trials was not significantly different from control (p = 0.35). (b) Adjustment (AE) error also improved (p = 0.025) to control levels (p = 0.47). (c, d) Similarly for launch latency (LL) (p = 0.035 and 0.26) and adjustment latency (AL) (p = 0.004 and 0.43).
Mentions: In test blocks, both dimensions of cursor motion were reversed from control, flipping the signs of all components of ∂e/∂u (Figure 1e). Five subjects took part -- one female, four males, all healthy, aged 21-48. Three of them knew the experiment involved a reversed relation between joystick and cursor. One of these three had experience with joystick experiments, and one with joystick computer games. All our single-person data plots (Figure 2, 3, and 4) are of subjects who were unfamiliar both with joysticks and with the idea of motor adaptation to reversals, but the key findings were the same for all subjects, as shown in Figure 5.

Bottom Line: Here we test a recent theory that the brain's estimates of sensitivity derivatives are revisable based on sensory feedback.The target jumped once during each movement.It is consistent with the idea of a single, all-purpose estimate of those derivatives; and it suggests that the estimate is a function of context, as one would expect given that the true sensitivity derivatives may vary with the state of the controlled system, the target, and the motor commands.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physiology, University of Toronto, Toronto, Canada.

ABSTRACT

Background: To learn, a motor system needs to know its sensitivity derivatives, which quantify how its neural commands affect motor error. But are these derivatives themselves learned, or are they known solely innately? Here we test a recent theory that the brain's estimates of sensitivity derivatives are revisable based on sensory feedback. In its simplest form, the theory says that each control system has a single, adjustable estimate of its sensitivity derivatives which affects all aspects of its task, e.g. if you learn to reach to mirror-reversed targets then your revised estimate should reverse not only your initial aiming but also your online course adjustments when the target jumps in mid-movement.

Methods: Human subjects bent a joystick to move a cursor to a target on a computer screen, but the cursor's motion was reversed relative to the joystick's. The target jumped once during each movement. Subjects had up to 4000 trials to practice aiming and responding to target jumps.

Results: All subjects learned to reverse both initial aiming and course adjustments.

Conclusions: Our study confirms that sensitivity derivatives can be relearned. It is consistent with the idea of a single, all-purpose estimate of those derivatives; and it suggests that the estimate is a function of context, as one would expect given that the true sensitivity derivatives may vary with the state of the controlled system, the target, and the motor commands.

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