Limits...
Effect of reinforcement history on hand choice in an unconstrained reaching task.

Stoloff RH, Taylor JA, Xu J, Ridderikhoff A, Ivry RB - Front Neurosci (2011)

Bottom Line: We modeled the shift in hand use using a Q-learning model of reinforcement learning.The results provided a good fit of the data and indicate that the effects of increasing and decreasing the rate of positive reinforcement are additive.These experiments emphasize the role of decision processes for effector selection, and may point to a novel approach for physical rehabilitation based on intrinsic reinforcement.

View Article: PubMed Central - PubMed

Affiliation: UCSF Joint Graduate Group in Bioengineering, University of California Berkeley Berkeley, CA, USA.

ABSTRACT
Choosing which hand to use for an action is one of the most frequent decisions people make in everyday behavior. We developed a simple reaching task in which we vary the lateral position of a target and the participant is free to reach to it with either the right or left hand. While people exhibit a strong preference to use the hand ipsilateral to the target, there is a region of uncertainty within which hand choice varies across trials. We manipulated the reinforcement rates for the two hands, either by increasing the likelihood that a reach with the non-dominant hand would successfully intersect the target or decreasing the likelihood that a reach with the dominant hand would be successful. While participants had minimal awareness of these manipulations, we observed an increase in the use of the non-dominant hand for targets presented in the region of uncertainty. We modeled the shift in hand use using a Q-learning model of reinforcement learning. The results provided a good fit of the data and indicate that the effects of increasing and decreasing the rate of positive reinforcement are additive. These experiments emphasize the role of decision processes for effector selection, and may point to a novel approach for physical rehabilitation based on intrinsic reinforcement.

No MeSH data available.


Hand choice results for Experiment 2 for participants who were tested on BOOST in day 1 (left side) or TAX on day 1 (right side). BOOST is shown in green and TAX in cyan. (A) Mean probability of right hand use as a function of target location. Solid lines are for data from the last two blocks of the manipulation phase (Blocks 7–8) and dotted lines are for data from the last two blocks of the baseline phase (Blocks 3–4). (B) Percent right hand use across all targets as a function of block number. (C) PSE values, calculated from the data for the last two blocks of each phase (B, baseline; M, manipulation; P, post manipulation).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3066466&req=5

Figure 6: Hand choice results for Experiment 2 for participants who were tested on BOOST in day 1 (left side) or TAX on day 1 (right side). BOOST is shown in green and TAX in cyan. (A) Mean probability of right hand use as a function of target location. Solid lines are for data from the last two blocks of the manipulation phase (Blocks 7–8) and dotted lines are for data from the last two blocks of the baseline phase (Blocks 3–4). (B) Percent right hand use across all targets as a function of block number. (C) PSE values, calculated from the data for the last two blocks of each phase (B, baseline; M, manipulation; P, post manipulation).

Mentions: As in Experiment 1, the psychometric functions were very steep, with participants overwhelmingly preferring to use the ipsilateral hand when reaching to peripheral targets (Figure 6A). A right-hand bias was again observed at the center location (71.5 ± 2.6%), although there were a significant number of left hand reaches to this location during the baseline phase. The inclusion of target locations just off-center (±8.6°) increased the occurrence of off-center ambiguity, with the right-hand being used to cross the midline on 20.2 ± 1.8% of the trials during the baseline phase. Interestingly, the inclusion of these locations may have reduced participants’ willingness to use the right hand to reach to the −17.4° target (left of midline): The percentage of right hand reaches to this location during the baseline phase was only 5.8 ± 1.3%, compared to 16.1 ± 1.7% in Experiment 1. We did not analyze this effect given the various methodological differences between the two experiments.


Effect of reinforcement history on hand choice in an unconstrained reaching task.

Stoloff RH, Taylor JA, Xu J, Ridderikhoff A, Ivry RB - Front Neurosci (2011)

Hand choice results for Experiment 2 for participants who were tested on BOOST in day 1 (left side) or TAX on day 1 (right side). BOOST is shown in green and TAX in cyan. (A) Mean probability of right hand use as a function of target location. Solid lines are for data from the last two blocks of the manipulation phase (Blocks 7–8) and dotted lines are for data from the last two blocks of the baseline phase (Blocks 3–4). (B) Percent right hand use across all targets as a function of block number. (C) PSE values, calculated from the data for the last two blocks of each phase (B, baseline; M, manipulation; P, post manipulation).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3066466&req=5

Figure 6: Hand choice results for Experiment 2 for participants who were tested on BOOST in day 1 (left side) or TAX on day 1 (right side). BOOST is shown in green and TAX in cyan. (A) Mean probability of right hand use as a function of target location. Solid lines are for data from the last two blocks of the manipulation phase (Blocks 7–8) and dotted lines are for data from the last two blocks of the baseline phase (Blocks 3–4). (B) Percent right hand use across all targets as a function of block number. (C) PSE values, calculated from the data for the last two blocks of each phase (B, baseline; M, manipulation; P, post manipulation).
Mentions: As in Experiment 1, the psychometric functions were very steep, with participants overwhelmingly preferring to use the ipsilateral hand when reaching to peripheral targets (Figure 6A). A right-hand bias was again observed at the center location (71.5 ± 2.6%), although there were a significant number of left hand reaches to this location during the baseline phase. The inclusion of target locations just off-center (±8.6°) increased the occurrence of off-center ambiguity, with the right-hand being used to cross the midline on 20.2 ± 1.8% of the trials during the baseline phase. Interestingly, the inclusion of these locations may have reduced participants’ willingness to use the right hand to reach to the −17.4° target (left of midline): The percentage of right hand reaches to this location during the baseline phase was only 5.8 ± 1.3%, compared to 16.1 ± 1.7% in Experiment 1. We did not analyze this effect given the various methodological differences between the two experiments.

Bottom Line: We modeled the shift in hand use using a Q-learning model of reinforcement learning.The results provided a good fit of the data and indicate that the effects of increasing and decreasing the rate of positive reinforcement are additive.These experiments emphasize the role of decision processes for effector selection, and may point to a novel approach for physical rehabilitation based on intrinsic reinforcement.

View Article: PubMed Central - PubMed

Affiliation: UCSF Joint Graduate Group in Bioengineering, University of California Berkeley Berkeley, CA, USA.

ABSTRACT
Choosing which hand to use for an action is one of the most frequent decisions people make in everyday behavior. We developed a simple reaching task in which we vary the lateral position of a target and the participant is free to reach to it with either the right or left hand. While people exhibit a strong preference to use the hand ipsilateral to the target, there is a region of uncertainty within which hand choice varies across trials. We manipulated the reinforcement rates for the two hands, either by increasing the likelihood that a reach with the non-dominant hand would successfully intersect the target or decreasing the likelihood that a reach with the dominant hand would be successful. While participants had minimal awareness of these manipulations, we observed an increase in the use of the non-dominant hand for targets presented in the region of uncertainty. We modeled the shift in hand use using a Q-learning model of reinforcement learning. The results provided a good fit of the data and indicate that the effects of increasing and decreasing the rate of positive reinforcement are additive. These experiments emphasize the role of decision processes for effector selection, and may point to a novel approach for physical rehabilitation based on intrinsic reinforcement.

No MeSH data available.