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ref: Kim-2008.01 tags: PEDOT review soft date: 12-29-2017 04:34 gmt revision:4 [3] [2] [1] [0] [head]

PMID-21204405 Soft, Fuzzy, and Bioactive Conducting Polymers for Improving the Chronic Performance of Neural Prosthetic Devices.

  • lays out the soft electrode approach (obviously).
  • Extensive discussion of conductive polymer plating methods for neural electrodes.

____References____

[0] Kim DH, Richardson-Burns S, Povlich L, Abidian MR, Spanninga S, Hendricks JL, Martin DC, Soft, Fuzzy, and Bioactive Conducting Polymers for Improving the Chronic Performance of Neural Prosthetic Devicesno Source no Volume no Issue no Pages (2008)

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ref: Kim-2004.05 tags: histology electrode immune response Tresco hollow fiber membranes GFAP vimentin ED1 date: 01-28-2013 03:08 gmt revision:7 [6] [5] [4] [3] [2] [1] [head]

PMID-14741588[0] Chronic response of adult rat brain tissue to implants anchored to the skull.

  • The increase in tissue reactivity observed with transcranially implanted HFMs may be influenced by several mechanisms including chronic contact with the meninges and possibly motion of the device within brain tissue.
  • Broadly speaking, our results suggest that any biomaterial, biosensor or device that is anchored to the skull and in chronic contact with meningeal tissue will have a higher level of tissue reactivity than the same material completely implanted within brain tissue.
  • See also [1]
  • Could slice through the hollow fiber membrane for histology. (as we shall).
  • Good list of references.

____References____

[0] Kim YT, Hitchcock RW, Bridge MJ, Tresco PA, Chronic response of adult rat brain tissue to implants anchored to the skull.Biomaterials 25:12, 2229-37 (2004 May)
[1] Biran R, Martin DC, Tresco PA, The brain tissue response to implanted silicon microelectrode arrays is increased when the device is tethered to the skull.J Biomed Mater Res A 82:1, 169-78 (2007 Jul)

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ref: Kim-2009.04 tags: Utah ASIC recording 2009 date: 01-15-2012 22:08 gmt revision:1 [0] [head]

PMID-19067174[0] Integrated wireless neural interface based on the Utah electrode array

  • Describes their fully integrated 100 site Utah probe.
  • "A planar power receiving coil fabricated by patterning electroplated gold films on polyimide substrates was connected to the IC by using a custom metallized ceramic spacer and SnCu reflow soldering. The SnCu soldering was also used to assemble SMD capacitors on the UEA. "

____References____

[0] Kim S, Bhandari R, Klein M, Negi S, Rieth L, Tathireddy P, Toepper M, Oppermann H, Solzbacher F, Integrated wireless neural interface based on the Utah electrode array.Biomed Microdevices 11:2, 453-66 (2009 Apr)

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ref: Kim-2006.06 tags: Hyun Kim Carmena Nicolelis continuous shared control gripper BMI date: 01-06-2012 00:20 gmt revision:2 [1] [0] [head]

IEEE-1634510 (pdf) Continuous shared control for stabilizing reaching and grasping with brain-machine interfaces.

  • The pneumatic gripper for picking up objects.
  • 70% brain control, 30% sensor control optimal.
  • Talk about 20Hz nyquist frequency for fast human motor movements, versus the need to smooth and remove noise.
  • Method: proximity sensors
    • collision avoidance 'pain withdrawal'
    • 'infant palmar grasp reflex'
    • Potential field associated with these sensors to implement continuous shared control.
  • Not! online -- used Aurora's data.

____References____

Kim, H.K. and Biggs, J. and Schloerb, W. and Carmena, M. and Lebedev, M.A. and Nicolelis, M.A.L. and Srinivasan, M.A. Continuous shared control for stabilizing reaching and grasping with brain-machine interfaces Biomedical Engineering, IEEE Transactions on 53 6 1164 -1173 (2006)

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ref: Kim-2007.08 tags: Hyun Kim muscle activation method BMI model prediction kinarm impedance control date: 01-06-2012 00:19 gmt revision:1 [0] [head]

PMID-17694874[0] The muscle activation method: an approach to impedance control of brain-machine interfaces through a musculoskeletal model of the arm.

  • First BMI that successfully predicted interactions between the arm and a force field.
  • Previous BMIs are used to decode position, velocity, and acceleration, as each of these has been shown to be encoded in the motor cortex
  • Hyun talks about stiff tasks, like writing on paper vs . pliant tasks, like handling an egg; both require a mixture of force and position control.
  • Georgopoulous = velocity; Evarts = Force; Kalaska movement and force in an isometric task; [17-19] = joint dependence;
  • Todorov "On the role of primary motor cortex in arm movement control" [20] = muscle activation, which reproduces Georgouplous and Schwartz ("Direct cortical representation of drawing".
  • Kakei [19] "Muscle movement representations in the primary motor cortex" and Li [23] [1] show neurons correlate with both muscle activations and direction.
  • Argues that MAM is the best way to extract impedance information -- direct readout of impedance requires a supervised BMI to be trained on data where impedance is explicitly measured.
  • linear filter does not generalize to different force fields.
  • algorithm activity highly correlated with recorded EMG.
  • another interesting ref: [26] "Are complex control signals required for human arm movements?"

____References____

[0] Kim HK, Carmena JM, Biggs SJ, Hanson TL, Nicolelis MA, Srinivasan MA, The muscle activation method: an approach to impedance control of brain-machine interfaces through a musculoskeletal model of the arm.IEEE Trans Biomed Eng 54:8, 1520-9 (2007 Aug)
[1] Li CS, Padoa-Schioppa C, Bizzi E, Neuronal correlates of motor performance and motor learning in the primary motor cortex of monkeys adapting to an external force field.Neuron 30:2, 593-607 (2001 May)

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ref: Kimura-1996.12 tags: putamen globus pallidus learning basal ganglia electrophysiology projection date: 10-03-2008 17:05 gmt revision:1 [0] [head]

PMID-8985875 Neural information transferred from the putamen to the globus pallidus during learned movement in the monkey.

  • study of the physiology of the projection from the striatum to the external and internal segments of the globus pallidus.
  • Identified neurons which project from the striatum to pallidus via antridromic activation after stim to the GPe / GPi.
  • there were two classes of striatal neurons:
    • tonically active neurons (TANs, rate: 4-8hz)
      • TANs were never activated by antidromic stimulation. therefore, they probably do not project to the pallidus.
    • phasically active neurons (very low basal rate, high frequency discharge in relation to behavioral tasks
      • All PANs found projected to the globus pallidus.
      • PANs were responsive to movement or movement preparation. (or not responsive to the particular behaviors investigated)
        • the PANns that showed activity before movement initiation more frequently projected to GPi and not GPE (or both - need to look at the anatomy more).
      • PANs also show bursts of activity time-locked to the initiation of movement (e.g. time locked to a particular part of the movement).
      • no neurons with sensory response!
  • when they microstimulated in the putamen, a few pallidal neurons showed exitatory response; most showed inhibitory/supressive response.