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[0] Sergio LE, Kalaska JF, Systematic changes in directional tuning of motor cortex cell activity with hand location in the workspace during generation of static isometric forces in constant spatial directions.J Neurophysiol 78:2, 1170-4 (1997 Aug)

[0] Cheney PD, Fetz EE, Functional classes of primate corticomotoneuronal cells and their relation to active force.J Neurophysiol 44:4, 773-91 (1980 Oct)

[0] Kawato M, Internal models for motor control and trajectory planning.Curr Opin Neurobiol 9:6, 718-27 (1999 Dec)

[0] Scott SH, Optimal feedback control and the neural basis of volitional motor control.Nat Rev Neurosci 5:7, 532-46 (2004 Jul)

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ref: Deco-2009.05 tags: stochastic dynamics Romo memory computation date: 01-16-2012 18:54 gmt revision:1 [0] [head]

PMID-19428958[0] Stochastic dynamics as a principle of brain function

  • Noise produces a 'probabalistic choice'.
  • Used simulated integrate and fire neurons.
  • justification: "and the taking of probabilistic decisions that on an individual trial may be non-optimal, but that may be adaptive by providing evidence about whether the probability of opportunities is changing in the world". So, a broader optimality in an uncertain world?
  • I'm skimming this, but looks like they largely are focused on frequency discrimination tasks.
  • Lots of text.

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[0] Deco G, Rolls ET, Romo R, Stochastic dynamics as a principle of brain function.Prog Neurobiol 88:1, 1-16 (2009 May)

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ref: Sergio-1997.08 tags: M1 force tuning kinematics dynamics Kalaska date: 01-03-2012 02:31 gmt revision:1 [0] [head]

PMID-9307146[0] Systematic changes in directional tuning of motor cortex cell activity with hand location in the workspace during generation of static isometric forces in constant spatial directions.

  • The discharge rate of all proximal-arm M1 cells was affected by both hand location and by the direction of static force. w/ interaction between force direction and hand location.
    • this is consistent with cortical units controlling muscle activity directly or through the spinal cord.
  • conclusion: M1 controls muscles directly and contributes to the transformation from extrinsic coordinates to muscle activations while coordinating limb movements.

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ref: Cheney-1980.1 tags: M1 kinematics dynamics tuning STA EMG Fetz date: 01-03-2012 02:30 gmt revision:3 [2] [1] [0] [head]

PMID-6253605[0] Functional classes of primate corticomotoneuronal cells and their relation to active force

  • monkeys made ramp and hold torque wrist movements/contractions.
  • corticomotoneuronal cells identified by clear postspike facilitation of rectified EMG activity.
  • all CM cells or PTNs were related to force - with a mixture/diversity of phasic, tonic, and ramp discharge rate profiles.
  • torque trajectory rather than velocity signal seems to be the primnary determinant of cell firing rate...
  • cells appear to be recruited at low force levels..with increasing rates as the torque increases.
  • high firing rates observed > 100!
    • and really low firing rate when there was no torque.

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ref: notes-0 tags: CSV blog article group dynamics steinberg date: 07-05-2010 15:30 gmt revision:1 [0] [head]

Another excellent post from Steinberg regarding treating people as predictable nonlinear fluids. "The system works far better when a column is introduced off-center in front of the door,as demonstrated Mr. Torrens. "It's counterintuitive, but the column sends shock waves through the crowds to break up the congestion patterns." (...) Most traffic jams are emergent phenomena that begin with mistakes from just one or two drivers. According to Horvitz's models, they can actually "un-jam" traffic by calling drivers at a particular location, and giving them very specific instructions: "Move to the left-most lane, and then speed-up to 65."

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ref: Kawato-1999.12 tags: kawato inverse dynamics cerebellum motor control learning date: 04-09-2007 22:45 gmt revision:1 [0] [head]

PMID-10607637[0] Internal models for motor control and trajectory planning

  • in this review, I will discuss evidence supporting the existence of internal models.
  • fast coordinated arm movement canot be executed under feedback control, as biological feedback loops are slow and have low gains. hence, the brain mostly needs to control things in a pure feedforward manner.
    • visual feedback delay is about 150-200ms.
    • fast spinal reflexes still require 30-50ms; large compared to fast movements (150ms).
    • muscle intrinsic mechanical properties produce proportional (stiffness) and derivative (viscosity) gains without delay.
    • inverse models are required for fast robotics, too. http://www.erato.atr.co.jp/DB/
  • talk about switching external force field to gauge the nature of the internal model - these types of experiments verily prove that feedforward / model-based control is happening. has anyone shown what happens neuronally during the course of this learning? I guess it might be in my datar.

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ref: Scott-2004.07 tags: Scott motor control optimal feedback cortex reaching dynamics review date: 04-09-2007 22:40 gmt revision:1 [0] [head]

PMID-15208695[0] PDF HTML summary Optimal feedback control and the neural basis of volitional motor control by Stephen S. Scott

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ref: bookmark-0 tags: robot kinematics lagrangian dynamics date: 0-0-2007 0:0 revision:0 [head]

http://virtual.cvut.cz/odl/partners/fuh/course_main/node27.html