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[0] Musallam S, Corneil BD, Greger B, Scherberger H, Andersen RA, Cognitive control signals for neural prosthetics.Science 305:5681, 258-62 (2004 Jul 9)

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ref: Musallam-2004.07 tags: cognitive BMI Musallam Andersen PRR MIP date: 01-08-2012 23:13 gmt revision:5 [4] [3] [2] [1] [0] [head]

PMID-15247483[0] Cognitive control signals for Neural Prosthetics

  • decode intended target from 200 to 1100ms of memory period (reward on correct, etc).
  • got good success rates with relatively few neurons (like 8 for 8 targets) -- yet decode rates were not that good, not at all as good as Fetz or Schmidt.
  • used pareital reach region (PRR), a subsection of posterior partietal cortex PPC, which represents the goals of the reach in visual coordinates. In the experiment, the implanted in media intrapareital (MIP)
    • in encodes the intended goal rather than the trajectory to achieve that goal.
    • PMd also seems to encode planning activity, though less is known about that.
  • used an adaptive database to map neuronal activity to targets; eventually, the database contained only (correct) brain-control trials.
  • neuronal responses were recorded from parietal reach region (PRR) with 64 microwire electrodes in 4 monkeys, plus 32 microwire electrodes in PMd
  • monkeys were tained to fixate on the center of the screen dring the task, though free fixation was also tested and seemed to work ok.
  • monkeys had to press cue, fixate, observe target location, wait ~2 sec, and move to the (remembered) target location when cue disappeared.
  • they use a static or continually updated 'database' for predicting which of four targets the monkey wants to go to during the instructed delay task.
  • able to predict with moderate accuracy the expected value of the target as well as its (discrete) position.
  • predictions were made during the delay period while there was no motor movement.
  • predictions worked equally well for updated and static databases.
  • monkeys were able to increase their performance on the BMI trials over the course of training.
  • reward type or size modulated the tuning of BMI neurons in the ecpected way, though aversive stimuli did not increase the tuning - suggesting that the tuning is not a function of attention (maybe).
  • the database consisted of 900ms of spike recordings starting 200ms after cue for 30 reach trials for each target. spike trains were projected onto Haar wavelets (sorta like a binary tree), and the filter coefficients were used to describe P(r), the probability of response, and P(r|s), probability of response given the target. then they used bayes rule (P(r) and P(r|s) were approximated with histograms, i think) to find P(s|r) - a discrete function - which it is easy to find the maximum of.
  • adding more trials offline improved the decode performance.
  • supporting online material.

PMID-15491902 Cognitive neural prosthetics

  • LFPs are easier to record and may last longer (but they are not as 'sexy').
  • suggest future electrodes will move automatically, peizo-drive perhaps.
  • PRR receives direct visual projections & codes for reaches in visual coordinates relative to the current direction of gaze.
  • PRR can hold the plan for a movement in short-term memory.
  • 16 neurons peak..?
  • In area LIP of PPC Platt and Glimcher PMID-10421364 found cells that code the expected value of rewards.
    • 20Hz beta-band oscillation indicated the behavioral state of the animal. While planning for a saccade it slowly increased, whereas at the time of movement in dramatically increased in amplitude.
    • LFP was better than spikes for a state decode.


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ref: Brown-2001.11 tags: Huntingtons motor_learning intentional implicit cognitive deficits date: 0-0-2007 0:0 revision:0 [head]

PMID-11673321 http://brain.oxfordjournals.org/cgi/content/full/124/11/2188 :

  • 16 genetically-confirmed Huntington's patients (and matched controls) trained on a task using trial and error learning (intentional), and implicit learning (unintentional).
  • the task setup was simple: they had to press one of four keys arranged in a cross (with center) either in response to commands or while guessing a sequence of a few keys.
  • Within the random, commanded task there was a sequence that could/should be noticed.
  • Huntington's patients performed worse on the intentional learning segment, but comparably on the implicit learning / implicit sequence awareness, though the latter test seems rather weak to me.