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[0] Churchland MM, Afshar A, Shenoy KV, A central source of movement variability.Neuron 52:6, 1085-96 (2006 Dec 21)

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ref: -0 tags: noise triboelectric implant BMI date: 05-16-2014 17:28 gmt revision:1 [0] [head]

source -- Durand

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ref: Harris-1998.08 tags: noise wolpert harris motor planning Fitt velocity variance control theory date: 01-27-2013 22:33 gmt revision:1 [0] [head]

PMID-9723616[0] Signal-dependent noise determines motor planning.

  • We present a unifying theory of eye and arm movements based on the single physiological assumption that the neural control signals are corrupted by noise whose variance increases with the size of the control signal
    • Poisson noise? (I have not read the article -- storing here for future reference.)
  • This minimum-variance theory accurately predicts the trajectories of both saccades and arm movements and the speed-accuracy trade-off described by Fitt's law.

____References____

[0] Harris CM, Wolpert DM, Signal-dependent noise determines motor planning.Nature 394:6695, 780-4 (1998 Aug 20)

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ref: Narayanan-2005.04 tags: BMI reliability noise Laubach Yale synergy date: 01-23-2013 20:50 gmt revision:1 [0] [head]

PMID-15858046[0] Redundancy and synergy of neuronal ensembles in motor cortex.

  • Reaction time task.
  • Neurons that were the best individual predictors of task performance were not necessarily the neurons that contributed the most predictive information to an ensemble of neurons.
  • Small ensembles [of neurons] could exhibit synergistic interactions (e.g., 23 +/- 9% of ensembles with two neurons were synergistic).
  • In contrast, larger ensembles exhibited mostly redundant interactions (e.g., 99 +/- 0.1% of ensembles with eight neurons were redundant).
  • Possible interpretation: redundancy enables robustness.

____References____

[0] Narayanan NS, Kimchi EY, Laubach M, Redundancy and synergy of neuronal ensembles in motor cortex.J Neurosci 25:17, 4207-16 (2005 Apr 27)

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ref: -0 tags: neural imaging recording shot noise redshirt date: 01-02-2013 02:20 gmt revision:0 [head]

http://www.redshirtimaging.com/redshirt_neuro/neuro_lib_2.htm

  • Shot Noise: The limit of accuracy with which light can be measured is set by the shot noise arising from the statistical nature of photon emission and detection.
    • If an ideal light source emits an average of N photons/ms, the RMS deviation in the number emitted is N\sqrt N .
    • At high intensities this ratio NN\frac{N}{\sqrt N} is large and thus small changes in intensity can be detected. For example, at 10^10 photons/ms a fractional intensity change of 0.1% can be measured with a signal-to-noise ratio of 100.
    • On the other hand, at low intensities this ratio of intensity divided by noise is small and only large signals can be detected. For example, at 10^4 photons/msec the same fractional change of 0.1% can be measured with a signal-to-noise ratio of 1 only after averaging 100 trials.

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ref: Holleman-2007.08 tags: amplifier recording NEF low noise original date: 01-15-2012 22:08 gmt revision:1 [0] [head]

IEEE-4353193 (pdf) A Sub-Microwatt Low-Noise Amplifier for Neural Recording

  • 0.805 uA from a 1V supply, gain of 36dB and 44db.
  • open loop amplfier, pass band between 0.3 and 4.7 kHz.
  • 3.5 uV rms input referred noise.
  • NEF 1.8

____References____

Holleman, J. and Otis, B. Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE 3930 -3933 (2007)

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ref: Churchland-2006.12 tags: motor_noise CNS Churchland execution variance motor_planning 2006 date: 12-08-2008 22:50 gmt revision:2 [1] [0] [head]

PMID-17178410[0] A central source of movement variability.

  • Small variations in preparatory neural activity were predictive of small variations in the upcoming reach
    • About half of the noise in reaching movements seems to be from variability during the preparatory phase, as estimated from regressions between preparatory neural activity and variability in performance.
  • even for a highly practiced task, the ability to repeatedly plan the same movement limits our ability to repeatedly execute the same movement.
  • when cocontraction increases, EMG variablility increases, but movement variability decreases. (This is consistent with poisson-based noise source?)
  • see the related articles!!

____References____

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ref: -0 tags: myopen EMG recordings NLMS noise date: 07-29-2008 18:32 gmt revision:2 [1] [0] [head]

Myopen amplifiers & analog/digital filters & NLMS are working properly! Below, a recording from my deltiod as I held my arm up: (only one EMG channel active, ground was my knee))

Yellow traces are raw inputs from ADC, blue are the output from the IIR / adaptive filters; hence, you only see 8 of the 16 channels. Read from bottom to top (need a -1 in some opengl matrix somewhere...) Below, the system with no input except for free wires attached to one channel (and picking up ambient noise). For this channel, NLMS could not remove the square wave - too many harmonics - but for all other channels the algorthim properly removes 60hz interference :)

Now, let me clean this EEG paste off my shoulder & leg ;)