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[0] Bar-Gad I, Morris G, Bergman H, Information processing, dimensionality reduction and reinforcement learning in the basal ganglia.Prog Neurobiol 71:6, 439-73 (2003 Dec)

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ref: Suner-2005.12 tags: MEA Utah reliability longevity SNR date: 01-25-2013 02:03 gmt revision:7 [6] [5] [4] [3] [2] [1] [head]

PMID-16425835[0] Reliability of signals from a chronically implanted, silicon-based electrode array

  • see {597}
  • Percutaneous connector used pressure-fitted pogo pins, as Gary was thinking of.
  • Utah array coated in parylene for this exp.
    • After implantation, array and cortex was covered in gore-tex (to prevent dura adhesion) -- they do not highlight this fact.
  • polyester insulated 25um gold wires as leads.
  • Reasonable SNR over 82, 172, 154 days.
  • One monkey had an array to 569 days -- 76 electrodes still provided good or fair waveforms.
  • ancilary (?) measure of tuning of the neurons. most neurons were not tuned.
  • SNR calculated as peak-peak of waveform divided by 2x standard deviation of signal.
  • A total of 36 implants in 16 other monkeys, which were not systematically evaluated for reliability here, provided successful recordings for up to 1264 days. Most of these studies ended because of headcap failure.
    • They no longer use dental acrylic -- only titanium bone screws.
  • 50-800K impedance
  • Improvement of the signal quality and increased yield, for which there was no clear trend in the three animals, may result from recovery produced by variations in the initial insertion injury.
  • The cortical capillary bed is densely packed, with spacing on the order of 40um in primate cortical tissue [27] ( vasculature ) -- they suppose that variance may be due to this.

____References____

[0] Suner S, Fellows MR, Vargas-Irwin C, Nakata GK, Donoghue JP, Reliability of signals from a chronically implanted, silicon-based electrode array in non-human primate primary motor cortex.IEEE Trans Neural Syst Rehabil Eng 13:4, 524-41 (2005 Dec)

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ref: Prescott-2009.02 tags: PD levodopa synaptic plasticity SNr STN DBS date: 02-22-2012 18:28 gmt revision:2 [1] [0] [head]

PMID-19050033[0] Levodopa enhances synaptic plasticity in the substantia nigra pars reticulata of Parkinson's disease patients

  • In the SNpc -> SNr.
  • High frequency stimulation (HFS--four trains of 2 s at 100 Hz) in the SNr failed to induce a lasting change in test fEPs (1 Hz) amplitudes in patients OFF medication (decayed to baseline by 160 s). Following oral L-dopa administration, HFS induced a potentiation of the fEP amplitudes (+29.3% of baseline at 160 s following a plateau).
  • Aberrant synaptic plasticity may play a role in the pathophysiology of Parkinson's disease.

____References____

[0] Prescott IA, Dostrovsky JO, Moro E, Hodaie M, Lozano AM, Hutchison WD, Levodopa enhances synaptic plasticity in the substantia nigra pars reticulata of Parkinson's disease patients.Brain 132:Pt 2, 309-18 (2009 Feb)

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ref: RodriguezOroz-2001.09 tags: STN SNr parkinsons disease single unit recording spain 2001 tremor oscillations DBS somatotopy organization date: 02-22-2012 18:24 gmt revision:12 [11] [10] [9] [8] [7] [6] [head]

PMID-11522580[0] The subthalamic nucleus in Parkinson's disease: somatotopic organization and physiological characteristics

  • Looks like they discovered exactly what we have discovered ... only in 2001. This is both good and bad.
    • From the abstract: "Neurones responding to movement were of the irregular or tonic type, and were found in the dorsolateral region of the STN. Neurones with oscillatory and low frequency activity did not respond to movement and were in the ventral one-third of the nucleus. Thirty-eight tremor-related neurones were recorded."
  • Again, from the abstract: "The findings of this study indicate that the somatotopic arrangement and electrophysiological features of the STN in Parkinson's disease patients are similar to those found in monkeys."
  • It may be that we want to test differential modulation / oscillation: look for differences between rest and activity, if there is sufficient support for both these in the files we have.
  • These people were much, much more careful about localization of their single-electrode tracks. E.g. they calculated electrode location relative the DBS electrode stereotatically, and referenced this to the postoperative MRI location of the treatment electrode.
  • Many more (32% of 350 neurons) responded to active or passive movement.
  • Of this same set, 15% (31 neurons) had a firing rate with rhythmical activity; 38 neurons had rhythmic activity associated with oscillatory EMG, but most of these were responsive to passive stimulation.
  • Autocorrelation of the neuronal bursting and tremor peaked at mean 7Hz, while autocorr. of EMG peaked at mean 5Hz.
  • This whole paragraph is highly interesting: ''The neuronal response associated with active movements was studied by simultaneous recording of neuronal EMG activity of the limbs. Five tremor-related neurons, recorded while a voluntary movement was performed, were available for analysis. Voluntary activation of a particular limb segment arrested the tremor. This was associated with a change in the discharges of the recorded neuron, which fired at a slower rate and in synchrony with the voluntary movement. On occasions, freezing of the voluntary movement ensued and tremor reappeared, changing the neuronal activity back to the typical 4-5Hz tremor-related activity. The cross-correlation analysis of two such neurons showed a peak frequency of 4.63 and 4.88 Hz for tremor-related activity, and 1.5 to 1.38 Hz during voluntary movement. Whether neuronal discharges in the STN preceded or followed EMG activity of the limbs could not be precisely established under the present conditions.
  • Somatotopic representation in the STN is expected from normal and MTPT-treated monkeys. Indeed, somatotopy is enhanced int he GPm of MTPT-treated monkeys.
    • This somatotopy is likely to result from organized afferent from the primary motor cortex (M1) to dorsolateral STN; this is the target of DBS treatment. Ventral and medial STN seems to project to associative and limbic cortical regions.
    • It seems they think the STN is generally not diseased, it is just a useful target for stimulating without evoked movement as in M1. This is consistent with optogenetic studies by Deisseroth [1].
    • Supporting this: "DBS of STN in Parkinson's disease improves executive motor functions, but aggravates conditional associative learning.
  • Interesting: In Parkinson's disease patients with tremor, Levy and colleagues found synchronization and a high firing rate (>10Hz) while recording pairs of neurons >600um apart.
  • Recordings of cortical activity through EEG and STN LFP showed significant coherence in the beta and gamma frequency bands during movement - consistent with corticosubthalamic motor projection. ... and suggest that the STN neurons involved in parkinsonian tremor are the same as the ones ativated during the performance of a voluntary movement. (! -- I agree with this.)
  • More: The reciprocal inhibitory-excitatory connections tightly linking the GPe and the STN may generate self-perpetuating oscillations.

Old notes:

  • this paper concentrates on STN electrophysiology in PD.
    • has a rather excellent list of references.
  • found a somatotopic organization in the STN, with most motor-related units more irregular and in the dorsolateral STN.
  • found a substantial fraction of tremor-synchronized neurons.
  • conclude that the somatotopic organization is about the same as in monkeys (?) (!)
  • M1 projects to STN, as verified through anterograde tracing studies. [1] These neurons increase their firing rate in response to passive movements.
  • there appears to be a relatively-complete representation of the body in the dorsolateral STN.

____References____

[0] Rodriguez-Oroz MC, Rodriguez M, Guridi J, Mewes K, Chockkman V, Vitek J, DeLong MR, Obeso JA, The subthalamic nucleus in Parkinson's disease: somatotopic organization and physiological characteristics.Brain 124:Pt 9, 1777-90 (2001 Sep)
[1] Gradinaru V, Mogri M, Thompson KR, Henderson JM, Deisseroth K, Optical deconstruction of parkinsonian neural circuitry.Science 324:5925, 354-9 (2009 Apr 17)

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ref: Sato-2000.01 tags: globus_pallidus anatomy STN GPi GPe SNr substantia nigra tracing DBS date: 01-26-2012 17:20 gmt revision:6 [5] [4] [3] [2] [1] [0] [head]

PMID-10660885[0] Single-axon tracing study of neurons of the external segment of the globus pallidus in primate.

  • wow, check out the computerized tracing! the neurons tend to project to multiple areas, usually. I didn't realize this. I imagine that it is relatively common in the brain.
  • complicated, tree-like axon collateral projection from GPe to GPi.
    • They look like the from through some random-walk process; paths are not at all efficient.
    • I assume these axons are mylenated? unmylenated?
  • dendritic fields in the STN seem very dense.
  • study done in cyno. rhesus

____References____

[0] Sato F, Lavallée P, Lévesque M, Parent A, Single-axon tracing study of neurons of the external segment of the globus pallidus in primate.J Comp Neurol 417:1, 17-31 (2000 Jan 31)

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ref: BarGad-2003.12 tags: information dimensionality reduction reinforcement learning basal_ganglia RDDR SNR globus pallidus date: 01-16-2012 19:18 gmt revision:3 [2] [1] [0] [head]

PMID-15013228[] Information processing, dimensionality reduction, and reinforcement learning in the basal ganglia (2003)

  • long paper! looks like they used latex.
  • they focus on a 'new model' for the basal ganglia: reinforcement driven dimensionality reduction (RDDR)
  • in order to make sense of the system - according to them - any model must ingore huge ammounts of information about the studied areas.
  • ventral striatum = nucelus accumbens!
  • striatum is broken into two, rough, parts: ventral and dorsal
    • dorsal striatum: the caudate and putamen are a part of the
    • ventral striatum: the nucelus accumbens, medial and ventral portions of the caudate and putamen, and striatal cells of the olifactory tubercle (!) and anterior perforated substance.
  • ~90 of neurons in the striatum are medium spiny neurons
    • dendrites fill 0.5mm^3
    • cells have up and down states.
      • the states are controlled by intrinsic connections
      • project to GPe GPi & SNr (primarily), using GABA.
  • 1-2% of neurons in the striatum are tonically active neurons (TANs)
    • use acetylcholine (among others)
    • fewer spines
    • more sensitive to input
    • TANs encode information relevant to reinforcement or incentive behavior

____References____

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ref: work-0 tags: gaussian random variables mutual information SNR date: 01-16-2012 03:54 gmt revision:26 [25] [24] [23] [22] [21] [20] [head]

I've recently tried to determine the bit-rate of conveyed by one gaussian random process about another in terms of the signal-to-noise ratio between the two. Assume x x is the known signal to be predicted, and y y is the prediction.

Let's define SNR(y)=Var(x)Var(err) SNR(y) = \frac{Var(x)}{Var(err)} where err=xy err = x-y . Note this is a ratio of powers; for the conventional SNR, SNR dB=10*log 10Var(x)Var(err) SNR_{dB} = 10*log_{10 } \frac{Var(x)}{Var(err)} . Var(err)Var(err) is also known as the mean-squared-error (mse).

Now, Var(err)=(xyerr¯) 2=Var(x)+Var(y)2Cov(x,y) Var(err) = \sum{ (x - y - sstrch \bar{err})^2 estrch} = Var(x) + Var(y) - 2 Cov(x,y) ; assume x and y have unit variance (or scale them so that they do), then

2SNR(y) 12=Cov(x,y) \frac{2 - SNR(y)^{-1}}{2 } = Cov(x,y)

We need the covariance because the mutual information between two jointly Gaussian zero-mean variables can be defined in terms of their covariance matrix: (see http://www.springerlink.com/content/v026617150753x6q/ ). Here Q is the covariance matrix,

Q=[Var(x) Cov(x,y) Cov(x,y) Var(y)] Q = \left[ \array{Var(x) & Cov(x,y) \\ Cov(x,y) & Var(y)} \right]

MI=12logVar(x)Var(y)det(Q) MI = \frac{1 }{2 } log \frac{Var(x) Var(y)}{det(Q)}

Det(Q)=1Cov(x,y) 2 Det(Q) = 1 - Cov(x,y)^2

Then MI=12log 2[1Cov(x,y) 2] MI = - \frac{1 }{2 } log_2 \left[ 1 - Cov(x,y)^2 \right]

or MI=12log 2[SNR(y) 114SNR(y) 2] MI = - \frac{1 }{2 } log_2 \left[ SNR(y)^{-1} - \frac{1 }{4 } SNR(y)^{-2} \right]

This agrees with intuition. If we have a SNR of 10db, or 10 (power ratio), then we would expect to be able to break a random variable into about 10 different categories or bins (recall stdev is the sqrt of the variance), with the probability of the variable being in the estimated bin to be 1/2. (This, at least in my mind, is where the 1/2 constant comes from - if there is gaussian noise, you won't be able to determine exactly which bin the random variable is in, hence log_2 is an overestimator.)

Here is a table with the respective values, including the amplitude (not power) ratio representations of SNR. "

SNRAmp. ratioMI (bits)
103.11.6
20103.3
30315.0
401006.6
9031e315
Note that at 90dB, you get about 15 bits of resolution. This makes sense, as 16-bit DACs and ADCs have (typically) 96dB SNR. good.

Now, to get the bitrate, you take the SNR, calculate the mutual information, and multiply it by the bandwidth (not the sampling rate in a discrete time system) of the signals. In our particular application, I think the bandwidth is between 1 and 2 Hz, hence we're getting 1.6-3.2 bits/second/axis, hence 3.2-6.4 bits/second for our normal 2D tasks. If you read this blog regularly, you'll notice that others have achieved 4bits/sec with one neuron and 6.5 bits/sec with dozens {271}.

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ref: notes-0 tags: sorting SNR correlation coefficient expectation maximization tlh24 date: 01-06-2012 03:07 gmt revision:5 [4] [3] [2] [1] [0] [head]

Description: red is the per-channel cross-validated correlation coeifficent of prediction. Blue is the corresponding number of clusters that the unit was sorted into, divided by 10 to fit on the same axis. The variable being predicted is cartesian X position. note 32 channels were dead (from PP). The last four (most rpedictive) channels were: 71 (1 unit), 64 (5 units), 73 (6 units), 67 (1 unit). data from sql entry: clem 2007-03-08 18:59:27 timarm_log_20070308_185706.out ;Looks like this data came from PMD region.

Description: same as above, but for the y-axis.

Description: same as above, but for the z-axis.

Conclusion: sorting seems to matter & have a non-negligible positive effect on predictive ability.

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ref: bookmark-0 tags: EMG SNR bits delsys differential amplifier bandwidth date: 12-07-2011 03:15 gmt revision:4 [3] [2] [1] [0] [head]

http://delsys.com/KnowledgeCenter/FAQ_EMGSensor.html

  • on a very good EMG recording the signal-to-noise is 65db ~= 11 bits
  • dynamic range of 5uv to 10mv.
  • differential measurement essential.
  • googling 'EMG bandwidth' yields something around 20-500hz. study of this question
  • delsys wireless EMG system & logger - uses WLAN to transmit the data (up to 16 channels) passband 20-450hz, has QVGA screen, 1GB removable storage.
  • also see "grasp recognition from myoelectric signals" images/474_1.pdf

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ref: notes-0 tags: SNR MSE error multidimensional mutual information date: 03-08-2007 22:33 gmt revision:2 [1] [0] [head]

http://ieeexplore.ieee.org/iel5/516/3389/00116771.pdf or http://hardm.ath.cx:88/pdf/MultidimensionalSNR.pdf

  • the signal-to-noise ratio between two vectors is the ratio of the determinants of the correlation matrices. Just see equation 14.

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ref: neuro notes-0 tags: SNr SNc substantia nigra anatomy tracing date: 02-06-2007 05:40 gmt revision:0 [head]

Patterns of axonal branching of neurons of the substantia nigra pars reticulata and pars lateralis in the rat.