m8ta
use https for features.
text: sort by
tags: modified
type: chronology
[0] Taylor DM, Tillery SI, Schwartz AB, Direct cortical control of 3D neuroprosthetic devices.Science 296:5574, 1829-32 (2002 Jun 7)

[0] Caminiti R, Johnson PB, Galli C, Ferraina S, Burnod Y, Making arm movements within different parts of space: the premotor and motor cortical representation of a coordinate system for reaching to visual targets.J Neurosci 11:5, 1182-97 (1991 May)

[0] Caminiti R, Johnson PB, Urbano A, Making arm movements within different parts of space: dynamic aspects in the primate motor cortex.J Neurosci 10:7, 2039-58 (1990 Jul)[1] Caminiti R, Johnson PB, Galli C, Ferraina S, Burnod Y, Making arm movements within different parts of space: the premotor and motor cortical representation of a coordinate system for reaching to visual targets.J Neurosci 11:5, 1182-97 (1991 May)

[0] Taira M, Boline J, Smyrnis N, Georgopoulos AP, Ashe J, On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional static isometric force.Exp Brain Res 109:3, 367-76 (1996 Jun)

[0] Wahnoun R, Helms Tillery S, He J, Neuron selection and visual training for population vector based cortical control.Conf Proc IEEE Eng Med Biol Soc 6no Issue 4607-10 (2004)[1] Wahnoun R, He J, Helms Tillery SI, Selection and parameterization of cortical neurons for neuroprosthetic control.J Neural Eng 3:2, 162-71 (2006 Jun)[2] Fetz EE, Operant conditioning of cortical unit activity.Science 163:870, 955-8 (1969 Feb 28)[3] Fetz EE, Finocchio DV, Operant conditioning of specific patterns of neural and muscular activity.Science 174:7, 431-5 (1971 Oct 22)[4] Fetz EE, Finocchio DV, Operant conditioning of isolated activity in specific muscles and precentral cells.Brain Res 40:1, 19-23 (1972 May 12)[5] Fetz EE, Baker MA, Operantly conditioned patterns on precentral unit activity and correlated responses in adjacent cells and contralateral muscles.J Neurophysiol 36:2, 179-204 (1973 Mar)[6] Humphrey DR, Schmidt EM, Thompson WD, Predicting measures of motor performance from multiple cortical spike trains.Science 170:959, 758-62 (1970 Nov 13)

[0] Kettner RE, Schwartz AB, Georgopoulos AP, Primate motor cortex and free arm movements to visual targets in three-dimensional space. III. Positional gradients and population coding of movement direction from various movement origins.J Neurosci 8:8, 2938-47 (1988 Aug)[1] Georgopoulos AP, Kettner RE, Schwartz AB, Primate motor cortex and free arm movements to visual targets in three-dimensional space. II. Coding of the direction of movement by a neuronal population.J Neurosci 8:8, 2928-37 (1988 Aug)[2] Schwartz AB, Kettner RE, Georgopoulos AP, Primate motor cortex and free arm movements to visual targets in three-dimensional space. I. Relations between single cell discharge and direction of movement.J Neurosci 8:8, 2913-27 (1988 Aug)[3] Georgopoulos AP, Kalaska JF, Caminiti R, Massey JT, On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex.J Neurosci 2:11, 1527-37 (1982 Nov)

{1462}
hide / / print
ref: -0 tags: 3D SHOT Alan Hillel Waller 2p photon holography date: 05-31-2019 22:19 gmt revision:4 [3] [2] [1] [0] [head]

PMID-29089483 Three-dimensional scanless holographic optogenetics with temporal focusing (3D-SHOT).

  • Pégard NC1,2, Mardinly AR1, Oldenburg IA1, Sridharan S1, Waller L2, Adesnik H3,4
  • Combines computer-generated holography and temporal focusing for single-shot (no scanning) two-photon photo-activation of opsins.
  • The beam intensity profile determines the dimensions of the custom temporal focusing pattern (CTFP), while phase, a previously unused degree of freedom, is engineered to make 3D holograph and temporal focusing compatible.
  • "To ensure good diffraction efficiency of all spectral components by the SLM, we used a lens Lc to apply a small spherical phase pattern. The focal length was adjusted so that each spectral component of the pulse spans across the short axis of the SLM in the Fourier domain".
    • That is, they spatially and temporally defocus the pulse to better fill the SLM. The short axis of the SLM in this case is Y, per supplementary figure 2.
  • The image of the diffraction grating determines the plane of temporal focusing (with lenses L1 and L2); there is a secondary geometric focus due to Lc behind the temporal plane, which serves as an aberration.
  • The diffraction grating causes the temporal pattern to scan to produce a semi-spherical stimulated area ('disc').
  • Rather than creating a custom 3D holographic shape for each neuron, the SLM is after the diffraction grating -- it imposes phase and space modulation to the CTFP, effectively convolving it with a holograph of a cloud of points & hence replicating at each point.

{1419}
hide / / print
ref: -0 tags: diffraction terahertz 3d print ucla deep learning optical neural networks date: 02-13-2019 23:16 gmt revision:1 [0] [head]

All-optical machine learning using diffractive deep neural networks

  • Pretty clever: use 3D printed plastic as diffractive media in a 0.4 THz all-optical all-interference (some attenuation) linear convolutional multi-layer 'neural network'.
  • In the arxive publication there are few details on how they calculated or optimized given diffractive layers.
  • Absence of nonlinearity will limit things greatly.
  • Actual observed performance (where thy had to print out the handwritten digits) rather poor, ~ 60%.

{1349}
hide / / print
ref: -0 tags: bone regrowth hyperelastic 3d print implant hydroxyapatite polycaptolactone date: 09-30-2016 18:27 gmt revision:0 [head]

Hyperelastic “bone”: A highly versatile, growth factor–free, osteoregenerative, scalable, and surgically friendly biomaterial

  • (From the abstract): hyperelastic “bone” is composed of 90 weight % (wt %) hydroxyapatite and 10 wt % polycaprolactone or poly(lactic-co-glycolic acid),
  • Can be rapidly three-dimensionally (3D) printed (up to 275 cm3/hour) from room temperature extruded liquid inks.
  • Mechanical properties: ~32 to 67% strain to failure, ~4 to 11 MPa elastic modulus & was highly absorbent (50% material porosity)
  • Supported cell viability and proliferation, and induced osteogenic differentiation of bone marrow–derived human mesenchymal stem cells cultured in vitro over 4 weeks without any osteo-inducing factors in the medium.
  • HB did not elicit a negative immune response, became vascularized, quickly integrated with surrounding tissues, and rapidly ossified and supported new bone growth without the need for added biological factors.

{1025}
hide / / print
ref: Hoogerwerf-1994.12 tags: Wise Michigan array MEA recording 3D date: 01-15-2012 07:12 gmt revision:4 [3] [2] [1] [0] [head]

IEEE-335862 (pdf) A three-dimensional microelectrode array for chronic neural recording.

  • see {995} for reasonable photos (they don't show up in the black and white IEEE scan).
  • 16-channel, 4 shanks.
  • 3D : 16 shanks, 64 channels, includes a 16:1 MNOS mux on the attached micromachined silicon platform.
  • Nickel plated lead stransfers (90 deg) see figure 6 electroplating current.
    • This was a point of difficulty, it seems.

____References____

Hoogerwerf, A.C. and Wise, K.D. A three-dimensional microelectrode array for chronic neural recording Biomedical Engineering, IEEE Transactions on 41 12 1136 -1146 (1994)

{334}
hide / / print
ref: Taylor-2002.06 tags: Taylor Schwartz 3D BMI coadaptive date: 01-08-2012 04:29 gmt revision:7 [6] [5] [4] [3] [2] [1] [head]

PMID-12052948[0] Direct Cortical Control of 3D Neuroprosthetic Devices

  • actually not a bad paper... reasonable and short. they adapted the target size to maintain a 70% hit rate, and one monkey was able to floor this (reach and stay at the minimum)
  • coadaptive algorithm removed noise units based on (effectively) cross-validation.
    • both arms were restrained during performance & co-adaptation. Monkeys initially strained to move the cursor, but eventually relaxed.
  • Changes from hand control to brain control random but apparently somewhat consistent between days.
  • continually increasing performance in brain-control for both monkeys, arguably due to the presence of feedback and learning. They emphasize the difference between open-loop (Wessberg) and closed-loop control. (42 ± 5% versus 12 ± 5% of targets hit)
    • still, the percentage of correct trials is low - ~50% for the 8 target 3D task.
    • monkeys improved target hit rate by 7% from the first to the third block of 8 closed-loop movements each day.
  • claim that they were able to record some units for up to 2 months ?? ! In their other monkey, with teflon/polymide coated stainless electrodes, the neural recordings changed nearly every day, and eventually went away.
  • quote: Cell-tuning functions obtained during normal arm movements were not good predictors of intended movement once both arms were restrained. interesting.
  • coadaptive algorithm:
    • Raw PV yielded poor predictions.
    • first, effectively z-score the firing rate of each neuron.
    • junk / hash neurons were not removed.
    • Two different weights per neuron per axis (hence 6 weights altogether), one if firing rate was above the mean value, another if it was below. corrected for resulting drift. Sum (neuronal firing rates * weights) controlled velocity on each of the axes. (Hence, it is not surprising that the brain-control tuning was significantly different from the hand control - the output model is vastly different).
    • restarted the coadaptive algorithm every day?
    • coadaptive algorithm appears to be something like stochastic gradient descent with a step-size that decreases with increasing performance.
      • From her Case-western website, Dawn Taylor still seems to be on the coadaptive kick. Seems like it's bad to get stuck on one idea all your life ... though perhaps that is the best way to complete something.
    • Their movies in supplementary materials look rather good, better than most of the stuff that we have done. She did not quantify SNR or correlation coefficient.

____References____

{938}
hide / / print
ref: -0 tags: Georgopoulos 1988 M1 population vector tuning 3D single unit date: 12-20-2011 00:58 gmt revision:2 [1] [0] [head]

PMID-3411363[0] Primate motor cortex and free arm movements to visual targets in three-dimensional space. III. Positional gradients and population coding of movement direction from various movement origins.

  • In comparison to the first experiment, where they showed that movement direction was encoded by single units within M1, here they varied the starting position of the movements.
  • tonic discharge of many cells varied in and orderly fashion with the position at which the hand was actively maintained in space.
  • however, cell activity changes were the same independent of movement onset and dependent on movement direction.
    • similar but not that similar -- vary based on tonic firing rate. See figure 9.

____References____

[0] Kettner RE, Schwartz AB, Georgopoulos AP, Primate motor cortex and free arm movements to visual targets in three-dimensional space. III. Positional gradients and population coding of movement direction from various movement origins.J Neurosci 8:8, 2938-47 (1988 Aug)

{344}
hide / / print
ref: Caminiti-1991.05 tags: transform motor control M1 3D population_vector premotor Caminiti date: 04-09-2007 20:10 gmt revision:2 [1] [0] [head]

PMID-2027042[0] Making arm movements within different parts of space: the premotor and motor cortical representation of a coordinate system for reaching to visual targets.

  • trained monkeys to make similar movements in different parts of external/extrinsic 3D space.
  • change of preferred direction was graded in an orderly manner across extrinsic space.
  • virtually no correlations found to endpoint static position: "virtually all cells were related to the direction and not to the end point of movement" - compare to Graziano!
  • yet the population vector remained an accurate predictor of movement: "Unlike the individual cell preferred directions upon which they are based, movement population vectors did not change their spatial orientation across the work space, suggesting that they remain good predictors of movement direction regardless of the region of space in which movements are made"

____References____

{294}
hide / / print
ref: Caminiti-1990.07 tags: transform motor control M1 3D population_vector premotor Caminiti date: 04-09-2007 20:07 gmt revision:4 [3] [2] [1] [0] [head]

PMID-2376768[0] Making arm movements within different parts of space: dynamic aspects in the primate motor cortex

  • monkeys made similar movements in different parts of external/extrinsic 3D space.
  • change of preferred direction was graded in an orderly manner across extrinsic space.
    • this change closely followed the changes in muscle activation required to effect the observed movements.
  • motor cortical cells can code direction of movement in a way which is dependent on the position of the arm in space
  • implies existence of mechanisms which facilitate the transformation between extrinsic (visual targets) and intrinsic coordinates
  • also see [1]

____References____

{339}
hide / / print
ref: Taira-1996.06 tags: 3D Georgopoulos SUA M1 force motor control direction tuning date: 04-09-2007 15:16 gmt revision:1 [0] [head]

PMID-8817266[0] On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional static isometric force.

  • 3D isometric joystick.
  • stepwise multiple linear regression.
  • direction of force is a signal especially prominent in the motor cortex.
    • the pure directional effect was 1.8 times more prevalent in the cells than in the muscles studied (!)

____References____

{302}
hide / / print
ref: Wahnoun-2004.01 tags: BMI population_vector neural selection Brown 3D arizona ASU date: 04-06-2007 23:28 gmt revision:3 [2] [1] [0] [head]

PMID-17271333[0] Neuron selection and visual training for population vector based cortical control.

  • M1 and Pmd (not visual areas), bilateral.
  • a series of experiments designed to parameterize a cortical control algorithm without an animal having to move its arm.
  • a highly motivated animal observes as the computer drives a cursor move towards a set of targets once each in a center-out task.
    • how motivated? how did they do this? (primate working for its daily water rations)
  • I do not think this is the way to go. it is better to stimulate in the proper afferents and let the brain learn the control algorithm, the same as when a baby learns to crawl.
    • however, the method described here may be a good way to bootstrap., definitely.
  • want to generate an algorithm that 'tunes-up' control with a few tens of neurons, not hundreds as Miguel estimates.
  • estimate the tuning from 12 seconds of visual following (1.5 seconds per each of the 8 corners of a cube)
  • optimize over the subset of neurons (by dropping them) & computing the individual residual error.
  • their paper seems to be more of an analysis of this neuron-removal method.
  • neurons seem to maintain their tuning between visual following and brain-control.
  • they never actually did brain control

PMID-16705272[1] Selection and parameterization of cortical neurons for neuroprosthetic control

  • here they actually did neuroprosthetic control.
  • most units add noise to the control signal, a few actually improve it -> they emphasize cautious unit selection leaning to simpler computational/electrical systems.
  • point out that the idea of using chronically recorded neural signals has a very long history.. [2,3,4,5] [6] etc.
  • look like it took the monkeys about 1.6-1.8 seconds to reach the target.
    • minimum summed path length / distance to target = 3.5. is that good?

____References____

{296}
hide / / print
ref: Kettner-1988.08 tags: 3D motor control population_vector Schwartz Georgopoulos date: 04-05-2007 17:09 gmt revision:1 [0] [head]

A triptych of papers (good job increasing your publication count, guys!):

  • PMID-3411363[0] Primate motor cortex and free arm movements to visual targets in three-dimensional space. III. Positional gradients and population coding of movement direction from various movement origins.
    • propose multilinear model to predict firing rate of nneuron (a regression that is the same direction as the kalman filter)
    • i don't see how this is that much different from below (?)
  • PMID-3411362[1] Primate motor cortex and free arm movements to visual targets in three-dimensional space. II. Coding of the direction of movement by a neuronal population.
    • they show, basically, that they can predict movement direction (note this is different from actual movement!) using the poulation vector scheme.
  • PMID-3411361[2] Primate motor cortex and free arm movements to visual targets in three-dimensional space. I. Relations between single cell discharge and direction of movement.
    • 568 cells!!
    • 8 directional targets, again -- not sure how they were aranged; they say 'in approximately equal angular intervals'
    • these findings generalize the previous 2D results [3] (tuning to external space) to 3D

____References____