[0] Fetz EE, Volitional control of neural activity: implications for brain-computer interfaces.J Physiol 579:Pt 3, 571-9 (2007 Mar 15)


{329} revision 7 modified: 09-07-2008 18:56 gmt

PMID-17234689[0] Volitional control of neural activity: implications for brain-computer interfaces (part of a symposium)

  • Limits in the degree of accuracy of control in the latter studies can be attributed to several possible factors. Some of these factors, particularly limited practice time, can be addressed with long-term implanted BCIs. YES.
  • Accurate device control under diverse behavioral conditions depends significantly on the degree to which the neural activity can be volitionally modulated. YES again.
  • neurons (50%) in somatosensory (post central) cortex fire prior to volitional movement. interesting.
  • It should also be noted that the monkeys activated some motor cortex cells for operant reward without ever making any observed movements See: Fetz & Finocchio, 1975, PMID-810359.
    • Motor cortex neurons that were reliably associated with EMG activity in particular forelimb muscles could be readily dissociated from EMG when the rewarded pattern involved cell activity and muscle suppression.
    • This may be realated to switching between real and imagined movements.
  • Biofeedback worked well for activating low-threshold motor units in isolation, but not high threshold units; attempts to reverse recruitment order of motor units largely failed to demonstrate violations of the size principle.
  • This (the typical BMI decoding strategy) interposes an intermediate stage that may complicate the relationship between neural activity and the final output control of the device
    • again, in other words: "First, the complex transforms of neural activity to output parameters may complicate the degree to which neural control can be learned."
    • quote: This flexibility of internal representations (e.g. to imagine moving your arm, train the BMI on that, and rapidly directly control the arm rather than gonig through the intermediate/training step) underlies the ability to cognitively incorporate external prosthetic devices in to the body image, and explains the rapid conceptual adaptation to artificial environments, such as virtual reality or video games.
      • There is a high flexibility of input (sensory) and output (motor) for purposes of imagining / simulating movements.
  • adaptive learning algorithms may create a moving target for the robust learning algorithm; does it not make more sense to allow the cortex to work it's magic?
  • Degree of independent control of cells may be inherently contrained by ensemble interactions
    • To the extent that internal representations depend on relationships between the activities of neurons in an ensemble, processing of these representations involves corresponding constraints on the independence of those activities.
  • quote: "These factors suggest that the range and reliability of neural control in BMI might increase significantly when prolonged stable recordings are acheived and the subject can practice under consistent conditions over extended periods of time.
  • Fetz agrees that the limitation is the goddamn technology. need to fix this!
  • there is evidence of favortism in his citations (friends with Miguel??)

humm.. this paper came out a month ago, and despite the fact that he is much older and more experienced than i, we have arrived at the same conclusions by looking at the same set of data/papers. so: that's good, i guess.

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