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Two distinct ipsilateral cortical representations for individuated finger movements.

Diedrichsen J, Wiestler T, Krakauer JW - Cereb. Cortex (2012)

Bottom Line: A second type of representation becomes evident in caudal premotor and anterior parietal cortices during bimanual actions.In these regions, ipsilateral actions are represented as nonlinear modulation of activity patterns related to contralateral actions, an encoding scheme that may provide the neural substrate for coordinating bimanual movements.We conclude that ipsilateral cortical representations change their informational content and functional role, depending on the behavioral context.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cognitive Neuroscience, University College London, London, UK. j.diedrichsen@ucl.ac.uk

ABSTRACT
Movements of the upper limb are controlled mostly through the contralateral hemisphere. Although overall activity changes in the ipsilateral motor cortex have been reported, their functional significance remains unclear. Using human functional imaging, we analyzed neural finger representations by studying differences in fine-grained activation patterns for single isometric finger presses. We demonstrate that cortical motor areas encode ipsilateral movements in 2 fundamentally different ways. During unimanual ipsilateral finger presses, primary sensory and motor cortices show, underneath global suppression, finger-specific activity patterns that are nearly identical to those elicited by contralateral mirror-symmetric action. This component vanishes when both motor cortices are functionally engaged during bimanual actions. We suggest that the ipsilateral representation present during unimanual presses arises because otherwise functionally idle circuits are driven by input from the opposite hemisphere. A second type of representation becomes evident in caudal premotor and anterior parietal cortices during bimanual actions. In these regions, ipsilateral actions are represented as nonlinear modulation of activity patterns related to contralateral actions, an encoding scheme that may provide the neural substrate for coordinating bimanual movements. We conclude that ipsilateral cortical representations change their informational content and functional role, depending on the behavioral context.

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Nonlinear tuning of voxels for bimanual actions. (A) Tuning function of a hypothetical neural unit for the 9 task conditions of a bimanual task. The activity of this unit (indicated by the gray shading) is determined by a linear combination of a tuning function for the ipsi- and contralateral fingers. Any change in the units output would influence task condition A mostly, but would generalize to conditions C and D. A system that has only linear units could, therefore, not learn a task in which a different output has to be produced for combinations A and B than for bimanual finger combinations C and D. (B) Instead, the control of such a task requires cortical circuits with nonlinear combinations of contra- and ipsilateral actions. (C) Average tuning functions of the voxels in the functional bimanual ROI in precentral gyrus, averaged across hemispheres and participants. Each 3 × 3 matrix indicates the activity of 9 groups of voxels, which were selected based on the bimanual combination for which they are most highly activated (black cross). The activity in the other conditions can then be averaged across the contralateral or ipsilateral finger to reveal the presence of consistent tuning across the bimanual actions. For the contralateral finger, this tuning is highly similar to the one observed for unimanual actions. For the ipsilateral finger, no tuning is apparent. Nonlinear tuning would be apparent as an interaction effect in this 2-factorial design.
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BHS120F6: Nonlinear tuning of voxels for bimanual actions. (A) Tuning function of a hypothetical neural unit for the 9 task conditions of a bimanual task. The activity of this unit (indicated by the gray shading) is determined by a linear combination of a tuning function for the ipsi- and contralateral fingers. Any change in the units output would influence task condition A mostly, but would generalize to conditions C and D. A system that has only linear units could, therefore, not learn a task in which a different output has to be produced for combinations A and B than for bimanual finger combinations C and D. (B) Instead, the control of such a task requires cortical circuits with nonlinear combinations of contra- and ipsilateral actions. (C) Average tuning functions of the voxels in the functional bimanual ROI in precentral gyrus, averaged across hemispheres and participants. Each 3 × 3 matrix indicates the activity of 9 groups of voxels, which were selected based on the bimanual combination for which they are most highly activated (black cross). The activity in the other conditions can then be averaged across the contralateral or ipsilateral finger to reveal the presence of consistent tuning across the bimanual actions. For the contralateral finger, this tuning is highly similar to the one observed for unimanual actions. For the ipsilateral finger, no tuning is apparent. Nonlinear tuning would be apparent as an interaction effect in this 2-factorial design.

Mentions: If the identified ipsilateral region is functionally engaged in the control of coordinated bimanual movements, we hypothesize that it should represent bimanual finger presses jointly. Consider the example of playing a tune on the piano. Imagine that you need to accentuate a combination of notes played jointly with the left thumb and the right middle finger (Fig. 6A,B, cell A) and another combination of notes played by the left middle finger and right little finger (cell B). All other combinations of the same fingers (cells C and D) should not receive the same stress. If the motor system had only neural units with tuning functions reflecting a linear combination of the left- and right-hand actions, such a task could not be learned. For example, any change to the output of a unit that is mostly activated during bimanual combination A would generalize to bimanual actions C and D (Fig. 6A). To produce different amounts of force for arbitrary combinations of bimanual movements, the motor system, therefore, needs neural circuits that show nonlinear tuning for bimanual actions (Fig. 6B; Yokoi et al. 2011). One example would be patches of cortex that responded preferentially to a single specific bimanual combination. However, any sufficient set of arbitrary nonlinear tuning functions would allow the nervous system to learn arbitrary functions of 2 variables (Zipser and Andersen 1988; Pouget and Sejnowski 1997).Figure 6.


Two distinct ipsilateral cortical representations for individuated finger movements.

Diedrichsen J, Wiestler T, Krakauer JW - Cereb. Cortex (2012)

Nonlinear tuning of voxels for bimanual actions. (A) Tuning function of a hypothetical neural unit for the 9 task conditions of a bimanual task. The activity of this unit (indicated by the gray shading) is determined by a linear combination of a tuning function for the ipsi- and contralateral fingers. Any change in the units output would influence task condition A mostly, but would generalize to conditions C and D. A system that has only linear units could, therefore, not learn a task in which a different output has to be produced for combinations A and B than for bimanual finger combinations C and D. (B) Instead, the control of such a task requires cortical circuits with nonlinear combinations of contra- and ipsilateral actions. (C) Average tuning functions of the voxels in the functional bimanual ROI in precentral gyrus, averaged across hemispheres and participants. Each 3 × 3 matrix indicates the activity of 9 groups of voxels, which were selected based on the bimanual combination for which they are most highly activated (black cross). The activity in the other conditions can then be averaged across the contralateral or ipsilateral finger to reveal the presence of consistent tuning across the bimanual actions. For the contralateral finger, this tuning is highly similar to the one observed for unimanual actions. For the ipsilateral finger, no tuning is apparent. Nonlinear tuning would be apparent as an interaction effect in this 2-factorial design.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3643717&req=5

BHS120F6: Nonlinear tuning of voxels for bimanual actions. (A) Tuning function of a hypothetical neural unit for the 9 task conditions of a bimanual task. The activity of this unit (indicated by the gray shading) is determined by a linear combination of a tuning function for the ipsi- and contralateral fingers. Any change in the units output would influence task condition A mostly, but would generalize to conditions C and D. A system that has only linear units could, therefore, not learn a task in which a different output has to be produced for combinations A and B than for bimanual finger combinations C and D. (B) Instead, the control of such a task requires cortical circuits with nonlinear combinations of contra- and ipsilateral actions. (C) Average tuning functions of the voxels in the functional bimanual ROI in precentral gyrus, averaged across hemispheres and participants. Each 3 × 3 matrix indicates the activity of 9 groups of voxels, which were selected based on the bimanual combination for which they are most highly activated (black cross). The activity in the other conditions can then be averaged across the contralateral or ipsilateral finger to reveal the presence of consistent tuning across the bimanual actions. For the contralateral finger, this tuning is highly similar to the one observed for unimanual actions. For the ipsilateral finger, no tuning is apparent. Nonlinear tuning would be apparent as an interaction effect in this 2-factorial design.
Mentions: If the identified ipsilateral region is functionally engaged in the control of coordinated bimanual movements, we hypothesize that it should represent bimanual finger presses jointly. Consider the example of playing a tune on the piano. Imagine that you need to accentuate a combination of notes played jointly with the left thumb and the right middle finger (Fig. 6A,B, cell A) and another combination of notes played by the left middle finger and right little finger (cell B). All other combinations of the same fingers (cells C and D) should not receive the same stress. If the motor system had only neural units with tuning functions reflecting a linear combination of the left- and right-hand actions, such a task could not be learned. For example, any change to the output of a unit that is mostly activated during bimanual combination A would generalize to bimanual actions C and D (Fig. 6A). To produce different amounts of force for arbitrary combinations of bimanual movements, the motor system, therefore, needs neural circuits that show nonlinear tuning for bimanual actions (Fig. 6B; Yokoi et al. 2011). One example would be patches of cortex that responded preferentially to a single specific bimanual combination. However, any sufficient set of arbitrary nonlinear tuning functions would allow the nervous system to learn arbitrary functions of 2 variables (Zipser and Andersen 1988; Pouget and Sejnowski 1997).Figure 6.

Bottom Line: A second type of representation becomes evident in caudal premotor and anterior parietal cortices during bimanual actions.In these regions, ipsilateral actions are represented as nonlinear modulation of activity patterns related to contralateral actions, an encoding scheme that may provide the neural substrate for coordinating bimanual movements.We conclude that ipsilateral cortical representations change their informational content and functional role, depending on the behavioral context.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cognitive Neuroscience, University College London, London, UK. j.diedrichsen@ucl.ac.uk

ABSTRACT
Movements of the upper limb are controlled mostly through the contralateral hemisphere. Although overall activity changes in the ipsilateral motor cortex have been reported, their functional significance remains unclear. Using human functional imaging, we analyzed neural finger representations by studying differences in fine-grained activation patterns for single isometric finger presses. We demonstrate that cortical motor areas encode ipsilateral movements in 2 fundamentally different ways. During unimanual ipsilateral finger presses, primary sensory and motor cortices show, underneath global suppression, finger-specific activity patterns that are nearly identical to those elicited by contralateral mirror-symmetric action. This component vanishes when both motor cortices are functionally engaged during bimanual actions. We suggest that the ipsilateral representation present during unimanual presses arises because otherwise functionally idle circuits are driven by input from the opposite hemisphere. A second type of representation becomes evident in caudal premotor and anterior parietal cortices during bimanual actions. In these regions, ipsilateral actions are represented as nonlinear modulation of activity patterns related to contralateral actions, an encoding scheme that may provide the neural substrate for coordinating bimanual movements. We conclude that ipsilateral cortical representations change their informational content and functional role, depending on the behavioral context.

Show MeSH
Related in: MedlinePlus