User:AshleyHardy/Gain-field encoding

Gain-field encoding is a hypothesis about the internal storage and processing of limb motion in the brain. Specific neurons have been reported to possess this ability to integrate prior knowledge of a motor task with an internal model to produce a desired motor output.[1] Gain-field encoding also involves sensory-motor coupling, which is the sensory and motor systems working concurrently to generate purposeful motor commands. One example is that visual input is represented in eye coordinates and must be transformed into motor coordinates that your muscles use to elicit an appropriate response. [2]


Overview

edit

It has been suggested that the brain's motor system does not learn to control the dynamics of limbs by memorizing past experiences. Instead, it uses a form of dynamic adaptation in which the brain retains learned movements as a result of a change in the environment.[3]

Internal Model

edit

Research has proposed that the brain learns an internal model by associating the state of the body with forces that arise that depend on the state of the limbs.[4] Equations of muscle force vectors

Motor Primitives

edit

Research has shown that the brain learns arm movements by using a combination motor primitives. Equations


Sensorimotor Transformation

edit

The sensorimotor system is able to translate information between different coordinate systems.

Eye-Centered Coordinates

edit

Body-Part-Centered Coordinates

edit

Research

edit

Many studies have attempted to interpret how the motor system learns and adapts to a changing environment.

Models for Studying Motor Control

edit

Motor skill learning and adaptation can be studied using various experimental techniques. Two standard approaches involve applying externally applied force fields to a subject during a reaching task or testing a subject's ability to visually rotate and interpret an image.[5]

Dynamic Adaptation

edit

Applying perturbations to subjects during a motor task.

Visuomotor Adaptation

edit

Rotating images and recording how a subject responds and if they can identify how much an image has been rotated.

Computational Mechanisms

edit

Algorithms have been implemented in an attempt the model various aspects of the sensorimotor system.[6]

Nonlinearity

edit

Nonstationarity

edit

Delays

edit

Redundancy

edit

Uncertainty

edit

Noise

edit

Premotor Cortex

edit

Dorsal Premotor Cortex

edit

Ventral Premotor Cortex

edit

Parietal Cortex

edit

The parietal cortex plays a major role in the sensorimotor system.

Posterior Parietal Cortex

edit

The idea of 'gain-field encoding' was first discovered in neurons of the posterior parietal cortex.

Lateral Intraparietal Cortex (LIP)

edit

Involved in coding targets for saccadic eye movements.

Superior Colliculus

edit

Future Directions

edit

References

edit
  1. ^ Yokoi, A (2011). "Gain field encoding of the kinematics of both arms in the internal model enables flexible bimanual action". The Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 31 (47): 17058–17068. doi:10.1523/JNEUROSCI.2982-11.2011. PMID 22114275. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
  2. ^ Snyder, L.H. (2000). "Coordinate transformations for eye and arm movements in the brain". Current Opinion in Neurobiology. 10 (6): 747–754. doi:10.1016/S0959-4388(00)00152-5. PMID 11240284.
  3. ^ Conditt, MA (July 1997). "The motor system does not learn the dynamics of the arm by rote memorization of past experience". Journal of Neurophysiology. 78 (1): 554–560. doi:10.1152/jn.1997.78.1.554. PMID 9242306. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)CS1 maint: date and year (link)
  4. ^ White, O. (2008). "Motor control: from joints to objects and back". Current Biology. 18 (12): R532-3. doi:10.1016/j.cub.2008.04.055. PMID 18579100. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
  5. ^ Dayan, E. (2011). "L.G." Neuron. 72 (3): 443–454. doi:10.1016/j.neuron.2011.10.008. PMC 3217208. PMID 22078504. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
  6. ^ Franklin, D.W. (2011). "Computational mechanisms of sensorimotor control". Neuron. 72 (3): 425–442. doi:10.1016/j.neuron.2011.10.006. PMID 22078503. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
edit