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Somatosensation

Somatosensation

The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.

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Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand

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Bimanual proprioception: are two hands better than one?

Jeremy D Wong¹, Elizabeth T Wilson, Dinant A Kistemaker

¹Brain and Mind Institute, Department Psychology, Western University, London, Ontario, Canada;

Journal of Neurophysiology

|January 2, 2014

Summary

The brain integrates limb proprioception by favoring the limb with better sensory information, rather than optimally combining signals. This suggests a rudimentary use of sensory acuity data for bimanual tasks.

Keywords:

bimanual human maximum likelihood proprioception sensory integration

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Area of Science:

Neuroscience
Human motor control
Sensory integration

Background:

Proprioception, the sense of limb position, is crucial for controlling objects held in both hands.
The human brain must integrate proprioceptive signals from both the left and right arms for effective bimanual tasks.
Understanding how the brain combines these sensory inputs is key to understanding motor control.

Purpose of the Study:

To investigate how the human brain combines proprioceptive information from two limbs during bimanual object manipulation.
To compare empirical bimanual proprioception with models of sensory integration, including optimal Bayesian combination and unimanual dominance.
To determine if the nervous system utilizes knowledge of individual limb proprioceptive acuity in bimanual tasks.

Main Methods:

Utilized a robotic system to move participants' passive limbs, assessing proprioceptive function independently for each limb.
Measured psychophysical estimates of proprioception when participants grasped the robot handle with both arms (bimanual condition).
Compared experimental bimanual proprioception data against established sensory integration models.

Main Results:

Empirical results align with the hypothesis that the nervous system selects the limb with superior proprioceptive acuity for bimanual tasks.
A Bayesian model predicting optimal sensory signal combination failed to accurately predict the observed bimanual proprioceptive acuity.
Participants' bimanual proprioception primarily relied on the more accurate limb, with limited integration of information from the less accurate limb.

Conclusions:

The central nervous system possesses awareness of individual limb proprioceptive acuity.
This awareness is applied in a simplified manner, predominantly using the more reliable limb's sensory data for bimanual proprioception.
The brain does not perform an optimal, weighted combination of sensory signals from both limbs as predicted by some models.