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Hand Shape Representations in the Human Posterior Parietal Cortex.

Christian Klaes1, Spencer Kellis1, Tyson Aflalo1

  • 1Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|November 21, 2015
PubMed
Summary
This summary is machine-generated.

Scientists decoded imagined hand shapes from the human posterior parietal cortex (PPC). This brain region processes hand movements, even when not grasping objects, paving the way for advanced neuroprosthetics.

Keywords:
audio processingbrain–machine interfacegraspinghand shapingmotor imageryposterior parietal cortex

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Area of Science:

  • Neuroscience
  • Human Motor Control
  • Brain-Computer Interfaces

Background:

  • The posterior parietal cortex (PPC) is known to process visual and motor information for grasping in nonhuman primates.
  • It remains unclear how non-grasp-related hand shapes are represented in the human PPC.

Purpose of the Study:

  • To investigate neuronal selectivity for imagined hand shapes in the human PPC, independent of graspable objects.
  • To determine if motor imagery for hand shapes can be decoded from PPC activity.
  • To explore differences in auditory and visual information processing within the PPC.

Main Methods:

  • Utilized a modified Rock-Paper-Scissors game with visual and auditory cues to elicit imagined hand shapes.
  • Recorded neural signals from the human PPC during the task.
  • Applied decoding techniques to analyze PPC activity related to motor imagery and sensory input.

Main Results:

  • Demonstrated, for the first time, the ability to decode specific imagined hand shapes from single neurons in the human PPC.
  • Showed that distinct neuronal populations are activated by visual cues versus the imagined hand shape.
  • Found differential processing of auditory and visual cues, with visual information decoded earlier than auditory information.

Conclusions:

  • Successfully decoded hand-shape imagery from the human PPC, independent of object interaction.
  • Highlighted differences in sensory processing within the PPC for auditory and visual cues.
  • Established the potential of human PPC neural signals for driving dexterous cortical neuroprostheses.