Reference Material for Researchers
Summary of papers regarding speech prosthesis development
The most important paper describes the production of speech:
A Wireless Brain-Machine Interface for Real-time Speech Synthesis
F.H. Guenther1,2, J.S. Brumberg1,3, E.J. Wright3, A. Nieto-Castanon4, J.A. Tourville1, M. Panko1, R. Law1, S.A. Siebert3, J.L. Bartels3, D.S. Andreasen3,5, P. Ehirim6, H. Mao7, and P.R. Kennedy3
1Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02115
2Division of Health Sciences and Technology, Harvard University-Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139
3Neural Signals Inc., 3400 McClure Bridge Road, Duluth, GA 30096
4StatsANC LLC, Ayacucho 48 7A, Capital Federal 1025, Buenos Aires, Argentina
5Georgia Tech Research Institute, 5247 Forest Brook Parkway, Marietta, GA 30068
6Gwinnett Medical Center, 500 Professional Blvd, Suite 200, Lawrenceville, GA 30345
7 Emory Center for Systems Imaging, Emory Univ. Hosp., 1364 Clifton Road, NE, Atlanta, GA 30322
Corresponding Author: Prof. Frank H. Guenther, Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02215. Phone: 617-353-5765. Fax: 617-353-7755. Email: email@example.com.
Background: Brain-machine interfaces (BMIs) involving electrodes implanted into the human cerebral cortex have recently been developed in an attempt to restore function to profoundly paralyzed individuals. Current BMIs for restoring communication can provide important capabilities via a typing process, but unfortunately they are only capable of slow communication rates. In the current study we use a novel approach to speech restoration in which we decode continuous auditory parameters for a real-time speech synthesizer from neuronal activity in motor cortex during attempted speech.
Methodology/Principal Findings: Neural signals recorded by a Neurotrophic Electrode implanted in a speech-related region of the left precentral gyrus of a human volunteer suffering from locked-in syndrome, characterized by near-total paralysis with spared cognition, were transmitted wirelessly across the scalp and used to drive a speech synthesizer. A Kalman filter-based decoder translated the neural signals generated during attempted speech into continuous parameters for controlling a synthesizer that provided immediate (within 50 ms) auditory feedback of the decoded sound. Accuracy of the volunteer’s vowel productions with the synthesizer improved quickly with practice, with a 25% improvement in average hit rate (from 45% to 70%) and 46% decrease in average endpoint error from the first to the last block of a three-vowel task.
Conclusions/Significance: Our results support the feasibility of neural prostheses that may have the potential to provide near-conversational synthetic speech output for individuals with severely impaired speech motor control. They also provide an initial glimpse into the functional properties of neurons in speech motor cortical areas.
Half the phonemes in the English language have been detected in our subject:
Classification of intended phoneme production from chronic intra-cortical microelectrode recordings in speech motor cortex
Jonathan S. Brumberg1*, E. Joe Wright2, Dinal S. Andreasen2,3, Frank H. Guenther4,1,5 and Philip R. Kennedy2
1Department of Cognitive and Neural Systems, Boston University, Boston, MA, USA
2Neural Signals Inc., Duluth, GA, USA
3Georgia Tech Research Institute, Marietta, GA, USA
4Division of Health Sciences and Technology, Harvard University-Massachusetts Institute of Technology, Cambridge, MA, USA
5Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, USA
Jonathan S. Brumberg
Department of Cognitive and Neural Systems
677 Beacon St.,
Boston, MA 02215
We conducted a neurophysiological study of attempted speech production in a paralyzed human volunteer using chronic microelectrode recordings. The volunteer suffers from locked-in syndrome leaving him in a state of near-total paralysis, though he maintains good cognition and sensation. In this study, we investigated the feasibility of supervised classification techniques for prediction of intended phoneme production in the absence of any overt movements including speech. Such classification or decoding ability has the potential to greatly improve the quality-of-life of many people who are otherwise unable to speak by providing a direct communicative link to the general community. We examined the performance of three classifiers on a multi-class discrimination problem in which the items were 38 American English phonemes including mono-phthong and diphthong vowels and consonants. The three classifiers differed in performance, but averaged between 16-21% overall accuracy (chance-level is 1/38 or 2.6%). Further, the distribution of phonemes classified statistically above chance was non-uniform though 20 of 38 phonemes were classified with statistical significance for all three classifiers. These preliminary results suggest supervised classification techniques are capable of performing large scale multi-class discrimination for attempted speech production and may provide the basis for future communication prostheses.
Our collaborators continue to decode the data
Joint Waveform and Firing Rate Spike-Sorting for Continuous Extracellular Traces
Brett Matthews, Mark Clements
Department of Electrical and Computer Engineering
Georgia Institute of Technology
Atlanta GA 30322
This paper discusses recent work in automatic spike sorting for continuous extra-cellular cortical traces. Our spike sorting framework jointly models neuronal ﬁring times and corresponding action potential waveforms as a discrete-state latent variable process. We model the likelihood of the observed ﬁring occurrence times as the aggregation of multiple hidden point processes based on inter-arrival probability distributions. We evaluate our method on two real, continuous, partially labeled recordings of extracellular traces from rat hippocampus obtaining total error rates (false positives + false negatives) of 5.60% and 1.86% in clean conditions, outperforming both a Gaussian mixture model (GMM) baseline and the state-of-the art WaveClus method. Our method continues to outperform in the presence of added noise on the same data. We then perform an empirical study of two free parameters for our method on a semi-artiﬁcial dataset. We ﬁnd that our method is more sensitive to parameter tuning in more difﬁcult data and noise conditions.
Further results with the electrode in our mute subject:
Making the lifetime connection between brain and machine for restoring and enhancing function
Philip Kennedy1,Dinal Andreasen1,2, Jess Bartels1, Princewill Ehirim4, Hui Mao5,Meel Velliste1,3, Thomas Wichmann6, Joe Wright1
1 Neural Signals Inc., 3400 McClure Bridge Road, Duluth, GA
2 Georgia Institute of Technology, Atlanta, GA
3Dept. of Neurobiology, University of Pittsburgh, Pittsburgh, PA
4 Dept. Neurosurgery, Gwinnett Medical Center, Lawrenceville, GA
5 Dept. Radiology, Emory University, Atlanta, GA
Philip Kennedy, MD, PhD
Neural Signals Inc
3400 McClure Bridge Road
Duluth, Georgia 30096.
A reliable neural interface that lasts a lifetime will lead to the development of neural prosthetic devices as well as the possibility that brain function can be enhanced. Our data demonstrate that a reliable neural interface is best achieved when the surrounding neuropil grows into the electrode tip where it is held securely, allowing myelinated axons to be recorded using implanted amplifiers. Stable single and multi-units were recorded from three implanted subjects and classified according to amplitudes and firing rates. In one paralyzed and mute subject implanted for over five years with a double electrode in the speech motor cortex, the single units allowed recognition of over half the 39 English language phonemes detected using a variety of decoding methods. These single units were used by the subject in a speech task where vowel phonemes were recognized and fed back to the subject using audio output. Weeks of training resulted in an 80% success rate in producing four vowels in an adaptation of the classic center-out task used in motor control studies. The importance of using single units was shown in a different task using pure tones that the same subject heard and then sung or hummed in his head. Feedback was associated with smoothly coordinated unit firings. The plasticity of the unit firings was demonstrated over several sessions first without, and then with, feedback. These data suggest that units can be reliably recorded over years, that there is an inverse relationship between single unit firing rate and amplitude, that pattern recognition decoding paradigms can allow phoneme recognition, that single units appear more important than multi-units when precision is important and that units are plastic in their functional relationships. These characteristics of a reliable neural interface are essential for the development of neural prostheses and also for the future enhancement of human brain function.
We pursued the question of LFP analysis in the frequency domain. We have discovered that beta peaks defined as being in the 14 to 20 Hz range are present prior or at onset of vocalization. This is similar to motor control studies. These data are still in preparation with confirming studies being completed on intact humans. Here is the abstract of the paper in preparation:
Detecting silent vocalizations in a locked-in subject
Elina Sarmah1, Philip Kennedy2
1Georgia Institute of Technology, Atlanta, Georgia, 30313
2Neural Signals Inc., Duluth, Georgia 30096
This paper seeks to provide evidence that beta peaks in the frequency spectrum defined as 14 to 20 Hz oscillations in the continuous neural signal were detected at vocalization onset in locked-in, mute patients. The present results were corroborated by EEG recordings in speaking persons. The data were obtained from neural recordings collected from several studies during attempts at inner speech in a mute and paralyzed subject (ER). The present off-line analysis used the continuous neural signal to (1) detect beta peaks meeting the criterion of 0.2% of the power spectrum density (PSD%) or higher, (2) determine the minimum time segments in which the beta peaks could be detected, (3) the strength of the peak and (4) their relationship, if any, to assumed speech onset. To assess the possible functional relatedness of the beta peaks, cross correlation analyses were performed on single unit data before and after beta peaks occurred. Cross correlations were found to increase after the beta peaks. Because the subject was mute, it was not possible to know when speech onset exactly occurred, if at all. Therefore, three speaking subjects were used in a similar testing paradigm but using EEG signals obtained over the speech area. Control studies to rule out EMG contamination effects were also obtained. These studies further suggested that the beta peaks were related to movement of the articulators, not to higher order speech processes.
These results indicate that the beta peak appears to be an indicator of speech onset. This raises the possibility of using these peaks in online applications to assist decoding paradigms being developed to decode speech from neural signal recordings in mute humans.
An additional paper studied the question of variability of signals when recording from humans and potentially animals. The effect of emotion was noted on our subject and this is described in a single case study paper whose abstract follows:
Changes in emotional state modulate neuronal firing rates of human speech motor cortex: A case study in long-term recording.
Neural Signals Inc., Suite D402, 3400 McClure Bridge Road, Duluth, Georgia, 30096
Philip Kennedy, MD, PhD
Neural Signals Inc
3400 McClure Bridge Road
Duluth, Georgia 30096.
In many brain areas, modulations in neuronal firing rates are thought to code information. However, in electrophysiological recording experiments, especially recordings in human patients, the type of information that is coded by a neuron’s discharge patterns is often not known, or difficult to determine. From our long experience with chronic recordings in humans, we have come to suspect that such unexplained modulations in firing rates are often due to state changes in the subject. We here present two case studies, with extensive data in one subject to illustrate the point that a change in the subject’s emotions, such as sudden fear, surprise, or happiness, may trigger substantial changes in firing rates.
Data Sharing is an important part of modern scientific effort. Neural Signals believes that all data should be shared. Thus the data is available on the website: http://migrate.speechprosthesis.org/DNN2. It is also backed up on the large hard drives attached to the main computer, our internal server network, and most of the data is also on the Boston University server. Access is restricted. To register contact us at firstname.lastname@example.org .
In addition, on our website www.neuralsignals.com there is a downloadable power point presentation with voice-over that explains the project.
Further more, the following paper describes how to assemble and implant the electrode.
Neurotrophic Electrode: Method of assembly and implantation into human motor speech cortex.
Jess Bartels1, Dinal Andreasen1,2, Princewill Ehirim3, Hui Mao4, Steven Seibert1, E Joe Wright1 and Philip Kennedy1.
1Neural Signals Inc., 3400 McClure Bridge Rd. Building D Suite B, Duluth, GA 30096, USA
2Georgia Institute of Technology, Cobb Co. Atlanta, GA, USA
3Dept. Neurosurgery, Gwinnett Medical Center, Lawrenceville, GA 30350
4Dept. Radiology, Emory University Hospital, Atlanta, GA 30332
The Neurotrophic Electrode (NE) is designed for longevity and stability of recorded signals. To achieve this aim it induces neurites to grow through its glass tip, thus anchoring it in neuropil. The glass tip contains insulated gold wires for recording the activity of the myelinated neurites that grow into the tip. Neural signals inside the tip are insulated from surrounding neural activity by the glass. The most recent version of the electrode has four wires inside its tip to maximize the number of discriminable signals recorded from ingrown neurites, and has a miniature connector. Flexible coiled, insulated gold wires connect to electronics on the skull that remain subcutaneous. The implanted electronics consist of differential amplifiers, FM transmitters, and a sine wave at power up for tuning and calibration. Inclusion criteria for selecting locked-in subjects include medical stability, normal cognition, and strong caregiver support. The implant target is localized via an fMRI-naming task. Final localization at surgery is achieved by 3D stereotaxic localization. During recording, implanted electronics are powered by magnetic induction across an air gap. Coiled antennas placed on the scalp over the implanted transmitters receive the amplified FM transmitter outputs. Data is processed as described in the companion paper where stability and longevity issues are addressed. Five subjects have been successfully implanted with the NE. Recorded signals persisted for over four years in two subjects who died from underlying illnesses, and continue for over three years in our present subject.
To help decide which electrode to use, the following updated paper should be helpful:
Comparing Electrodes for use as Cortical Control Signals: Tines, Wires or Cones on Wires: Which is best?
Philip R. Kennedy, MD, PhD
In the fields of Neural Prosthetics and Neural Engineering there are several viable contenders for the prize of best long-term electrode to access cortical control signals for restoration of communication and movement in humans. These contenders can be classified into three main groups. The first group includes those who have developed millimeter-sized tines or pins that are driven into the cortex and provide signals for months and sometimes years [1,11,13,14]. The second group produces flexible wires that are inserted into the cortex and provide signals also for months and sometimes years . The third type of electrode is also a wire configuration but allows for growth of the brain’s neuropil into the hollow glass tip of the electrode that envelops the wires. Robust signals have been recorded for years from this Neurotrophic Electrode [5,11,13,14]. Thus, these electrodes can be classified into (a) those that protrude towards neurons (tines and wires) and (b) the Neurotrophic Electrode that welcomes the neurites into its tip and thus fuses with the neuropil.
The above nine publications are detailed here:
1) Sarmah E. and Kennedy P.R. Detection of beta peaks during silent speech in a mute subject. In preparation. 2011.
2) Kennedy, P.R., Andreasen D.S., Bartels, J., Ehirim P., Mao H., Velliste M.,Wichmann T.,Wright, E.J. (2011) Making the lifetime connection between brain and machine for restoring and enhancing function. Proceedings in Brain Research, Ch.1, August 2011.
3) Brumberg J., Wright EJ, Andersen D, Guenther FH and Kennedy PR. Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech motor cortex. 2011. Frontiers in Neuroscience 5(65)1-14.
4) Kennedy, PR. Changes in emotional state modulate neuronal firing rates of human speech motor cortex: A case study in long-term recording. Neurocase 2011 17(5), 381-393.
5) Brumberg JS, Nieto-Castanon A, Kennedy PR, Guenther FH. Brain-Computer Interfaces for Speech Communication. Speech Commun. 2010 Apr 1;52(4):367-379.
6) Guenther, F.H., Brumberg, J.S., Wright, E.J., Nieto-Castanon, A., Tourville, J.A., Panko, M., Law, R., Siebert, S.A., Bartels, J.L., Andreasen, D.S., Ehirim, P., Mao, H., and Kennedy, P.R. A wireless brain-machine interface for real-time speech synthesis. PLoS ONE. (2009) 9;4(12):e8218
7) Bartels J, Andreasen D, Ehirim P, Mao H, Seibert S, Wright EJ, Kennedy PR. Neurotrophic electrode: Method of assembly and implantation into human motor speech cortex. J Neurosci Methods. 2008 Sep 30;174(2):168-76. Epub 2008 Jul 10.
8) Kennedy PR. Comparing Electrodes for use as Cortical Control Signals: Tiny Tines, Tiny Wires or Tiny Cones on Wires: Which is best? . The Biomedical Engineering Handbook, Third Edition. Ed.: Joe Brazino, 32-1 to 32-14, 2006, revised 2011.
9) Brett Matthews, Mark Clements. Joint Waveform and Firing Rate Spike-Sorting for Continuous Extracellular Traces. Presented at Asilomar conference, Asilomar, CA, November 2011.
20. Sarmah E. and Kennedy P.R. Detecting silent vocalizations in a locked-in subject. In preparation 2011.
19. Kennedy, P.R., Andreasen D.S., Bartels, J., Ehirim P., Mao H., Velliste M.,Wichmann T.,Wright, E.J. (2011) Making the lifetime connection between brain and machine for restoring and enhancing function. Proceedings in Brain Research, Ch.1, August 2011.
18. Brumberg J., Wright EJ, Andersen D, Guenther FH and Kennedy PR. Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech motor cortex. 2011. Frontiers in Neuroscience 5(65)1-14.
17. Brumberg JS, Nieto-Castanon A, Kennedy PR, Guenther FH. Brain-Computer Interfaces for Speech Communication. Speech Commun. 2010 Apr 1;52(4):367-379.
16. Kennedy, PR. Changes in emotional state modulate neuronal firing rates of human speech motor cortex: A case study in long-term recording. Neurocase 2011 17(5), 381-393.
15. Guenther, F.H., Brumberg, J.S., Wright, E.J., Nieto-Castanon, A., Tourville, J.A., Panko, M., Law, R., Siebert, S.A., Bartels, J.L., Andreasen, D.S., Ehirim, P., Mao, H., and Kennedy, P.R. A wireless brain-machine interface for real-time speech synthesis. PLoS ONE. (2009) 9;4(12):e8218
14. Bartels J, Andreasen D, Ehirim P, Mao H, Seibert S, Wright EJ, Kennedy PR. Neurotrophic electrode: Method of assembly and implantation into human motor speech cortex. J Neurosci Methods. 2008 Sep 30;174(2):168-76. Epub 2008 Jul 10.
13. Comparing Electrodes for use as Cortical Control Signals: Tiny Tines, Tiny Wires or Tiny Cones on Wires: Which is best? Kennedy PR. The Biomedical Engineering Handbook, Third Edition. Ed.: Joe Brazino, 32-1 to 32-14, 2006, revised 2011.
12. Comparing Electrodes for use as Cortical Control Signals: Tiny Tines, Tiny Wires or Tiny Cones on Wires: Which is best? Kennedy PR. The Biomedical Engineering Handbook, Third edition. Ed.: Joe Brazino, pp. 32-1 to 32.14, 2006.
11. Using Human Extra-cortical Local Field Potentials to Control a Switch. Kennedy PR, Dinal Andreasen, Princewill Ehirim, Brandon King, Todd Kirby, Hui Mao, Melody Moore. J. of Neural Technology, June 2004.
10. Correlations between human motor cortical local field potentials, action potentials, contralateral arm EMG activity and digit movements. Kennedy PR, Dinal Andeasen, Brandon King, Todd Kirby, Hui Mao, Melody Moore, Princewill Ehirim. Submitted to J. Neural Engineering 2005.
9. Computer Control Using Human Cortical Local Field Potentials. Kennedy PR, Kirby MT, Moore MM, King B & Mallory A. IEEE Trans on Neural Systems and Rehabilitation Eng. 12(3), 339-344, 2004.
8. A Decision tree for Brain-Computer Interface Devices. Kennedy PR and Adams K. IEEE Trans on Neural Sys. & Rehab Eng. 11(2), 2003.
7. Dynamic interplay of neural signals during the emergence of cursor related cursor in a human implanted with the Neurotrophic electrode. Kennedy PR and King B. CH 7 in Neural Prostheses for Restoration of Sensory and Motor Function. Eds. Chapin J and Moxon, K. CRC Press, 2001.
6. Direct control of a computer from the human central nervous system. Kennedy PR, Bakay RAE, Adams K, Goldthwaite J, and M. Moore. IEEE Trans. Rehab. Eng., 8(2), 198-202, 2000.
5. Restoration of neural output from a paralyzed patient using a direct brain connection. P.R.Kennedy and R.A.E.Bakay. NeuroReport 9,1707-11, 1998.
4. Activity of single action potentials in monkey motor cortex during long-term task learning. Kennedy PR & Bakay RAE. Brain Research 760:251-4 (1997).
3. Behavioral correlates of action potentials recorded chronically inside the Cone Electrode. P.R. Kennedy, R.A.E. Bakay and S.M. Sharpe. NeuroReport, 3:605-608, (1992).
2. The Cone Electrode: Ultrastructural Studies Following Long-Term Recording. P.R. Kennedy, S.Mirra and R.A.E. Bakay. Neuroscience Letters, 142:89-94, (1992).
1. A long-term electrode that records from neurites grown onto its recording surface. P.R. Kennedy, J. Neuroscience Methods, 29 (1989) 181-193.
47. M. Panko, S. Brincat, J. Brumberg, A. Salazar-gomez, J. Roy, S. Overduin, P. Kennedy, E. K. Miller, F. Guenther. Signal stability in chronic invasive brain-machine interfaces
46. T. H. Sanders, T. Wichmann, M. A. Clements, P. R. Kennedy. Speech phoneme detection and recognition from chronically recorded human motor cortex neurons.
45. Using cross correlation analysis of recorded units to detect phonemes in human speech cortex. Phil Kennedy, Neural Signals Inc, Duluth, GA, Thomas Wichmann, Emory Univ. Dept Neurology, Atlanta GA, Joe Wright, Neural Signals Inc, Duluth, GA. SFN Abstr. 2010.
44. Modular Software Architecture for Neural Prosthetic Control. Velliste, M 1., Brumberg J2 and Kennedy P1 Neural Signals Inc., Duluth, GA 3Department of Cognitive and Neural Systems, Boston University, Boston, MA SFN 2009
43. Human speech cortex : Stability, variability, emotionality and multimodality of units recorded via the Neurotrophic Electrode. PR Kennedy1 D Andreasen1,2 J Brumberg3 J Bartels 1, D Felice1, EJ Wright1 . 1 Neural Signals Inc., Duluth, GA; 2 Georgia Tech, Atlanta, GA; 3 Boston Univ. MA SFN 2009.
42. Human speech cortex : Tuning of single units during listening and imagined singing of tones and musical notes using feedback. P. Kennedy1, D. Andeasen1,2, J. Brumberg1,3a, M. Clements2, F. Guenther3, J. Kim2, B. Mathews2, C. Ramos1, M. Velliste1,4, *E. J. Wright1. 1Neural Signals, Inc, Atlanta, GA; 2Georgia Tech., Atlanta, GA; 3Boston Univ., Boston, MA; 3Univ. of Pittsburgh, Pittsburgh, PA SFN 2009
41. Advances in the development of the Neurotrophic Electrode. Siebert SA, Bartels J, Shire D, Kennedy PR, Andreasen A. SFN Abstr. 2008
40. Detecting patterns of neural signals from Broca’s area to produce speech in a locked-in subject. P.R.Kennedy, D.Andreasen,S.Seibert, E.J.Wright. SFN 2006.
39. Towards conversational speech restoration in a locked-in patient by recording from Broca’s area with the Neurotrophic Electrode. P.R.Kennedy1., D. Andreasen1,2., E.J.Wright1., H. Mao3.,. P.Ehirim 4. SfN 2005.
38.Speech Prosthesis: Initial recordings from Broca’s area with the Neurotrophic Electrode in a locked-in patient. P.R.Kennedy, D.Andreasen,S.Seibert, E.J.Wright, H. Mao,. P.Ehirim. NIW, NIH, September 2005
37.Wright EJ, Kennedy PR. BCI Control for Locked-in Patients in Real World Environments. Presented at the BCI Conference, Rensellaerville NY 2005.
36. Accurate Localization of Implant Targets in the Cerebral Cortices of Locked-in Subjects undergoing BCI Applications. P.R.Kennedy, Hui Mao, SFN 2004
35. Different potential roles of Fast Transients and Local Field Potentials recorded through the Neurotrophic Electrode in humans. P.R. Kennedy, Dinal Andreasen, Neural Prostheses Workshop, submitted, 2003.
34. Different potential roles of Fast Transients and Local Field Potentials recorded through the Neurotrophic Electrode in humans. P.R. Kennedy, Dinal Andreasen, Soc. Neurosci. Abstr. 2003.
33. A comparison of Fast Transients and Local Field Potentials recorded through the Neurotrophic Electrode. P.R. Kennedy, Dinal Andreasen, Neural Control of Movement meeting, 2003.
32. Directionality may be inherent in the Local Field Potentials (LFPs) recorded via the Neurotrophic Electrode in human cortex. P.R. Kennedy, B. King; M.T. Kirby; K. Adams. Soc. Neurosci. Abstr. 2002.
31. Brain-Machine Interfaces: Can they teach us something? S. Mussa-Ivaldi, N.Hatsopoulos, P.R.Kennedy, M.Nicholelis, A.Schwartz and J.Wolpaw. Neural Control of Movement Meeting, Naples, FL, April 2002.
30. Adams, KD, Goldthwaite, J, Plummer, T, Moore, MM and Kennedy, PR, (2001). Computer Control Using Surface EMG Signals”, RESNA Proceedings, Reno, NV, pp. 80-82.
29. Motor Cortical control of a cyber digit by patient implanted with the Neurotrophic Electrode. P.R.Kennedy, B.King, M.T.Kirby, M.Blankowski and M.M.Moore*. Soc. for Neuroscience Abstr., 2001.
28. The role of tactile feedback in the control of cortical neural signals two years after implantation in patient TT with mitochondrial myopathy. P.R .Kennedy, T .Kirby, K. Adams, B. King and A. Mallory. Neural Prostheses Workshop, NINDS, NIH, Oct. 2001.
27. Directionality coding in human cortical area 4: Role of phase relationships of individual action potentials. P.R.Kennedy King B, Moore MM SFN Abstracts 2000.
26. A Surface EMG Connection for Cursor Control and Morse Code. Adams, KD, Goldthwaite, J, Moore, MM and Kennedy, PR, (2000). RESNA Proceedings, Orlando, FL, pp 101-103.
25. Direct control of a computer from the human central nervous system. Kennedy P.R., Adams K, Bakay RAE, Goldthwaite J, Montgomery G and Moore M. BCI Conference New York, June 16th to 20th 1999.
24. A direct brain connection for computer control. K. Adams, J. Goldthwaite, P.R. Kennedy, RESNA-99, June 25-29 1999.
23. Neural Activity during acquisition of cursor control in a locked-in patient. P.R.Kennedy, R.A.E.Bakay, M.Moore, K,Adams, G.Montgomery. Soc. Neurosci. Abstracts, 1999.
22. Cognitive Engineering: Early attempts to control a computer by directly interfacing with the CNS of a locked-in patient. P.R.Kennedy, R.A.E.Bakay, C.Russell & G. Montgomery. Neural Prostheses Workshop, 1998.
21. Cognitive Engineering: Continuing experiences with implantation of the Neurotrophic Electrode in Locked-in patients. P.R.Kennedy and R.A.E.Bakay. Soc. Neurosci. Abstr., 1998.
20. Cognitive Engineering: Using the Neurotrophic Electrode to access neural signals in locked-in patients: Experiences with initial human implantation. P.R.Kennedy and R.A.E.Bakay. International Meeting on Regeneration, Asilomar, CA 1997.
19. Cognitive Engineering: Using the Neurotrophic Electrode to access neural signals in locked-in patients: Experiences with initial human implantation. P.R.Kennedy and R.A.E.Bakay. Soc. Neurosci. Abstr., 24(1)193, 1997.
18. Plasticity of motor cortex action potentials during task learning in monkeys. P.R.Kennedy and R.A.E.Bakay. Soc. Neurosci. Abstr., 21(1)28, 1995.
17. The quietude of primate cerebral cortex is interrupted by microstimulation plus caffeine administration during chronic Cone Electrode recordings. P.R.Kennedy, L.L.Howell, R.A.E.Bakay, R.Verellan and J.Echard. Soc. Neurosci. Abstr., 19(1)777, 1993.
16. An implantable FM transmitter and amplifier powered by transcutaneous RF coupling for use in long-term prosthetic controllers. P.R.Kennedy, A.Hopper, C.Linker, R.Verellen, H.Yun and S.M.Sharpe. Neural Prosthesis Workshop Abstr., NIH, October, 1992.
15. The Cone Electrode: Chronic Recording Techniques. P.R.Kennedy, A.Hopper, C.Linker, S.M.Sharpe and R.A.E.Bakay. Soc. Neurosci. Abstr., 18(1)217, 1992.
14. A system for real time processing of neural signals for use as prosthetic controllers. P.R. Kennedy, A. Hopper, C. Linker and S.M. Sharpe. 14th. International Conference of the IEEE Engineering in Medicine and Biology Society meeting, Paris Oct. 29th. to Nov. 1st., 1992.
13. The Cone Electrode: Ultrastructural analysis of recorded tissue, behavioral correlates of neural activity, and development of a totally implantable system using transcutaneous power induction. P.R. Kennedy, A. Hopper, R.A.E. Bakay and S. Mirra. Poster presentation at the Neural Prosthesis Workshop, NIH, October 22-24, 1991.
12. The Cone Electrode: Ultrastructural study following long-term recording. P.R. Kennedy, S. Mirra and R.A.E. Bakay. Soc. Neuroscience Abstr., 17(2):1018, 1991.
11. Long-term recording of cortical units using the cone electrode in monkeys. Bakay R.A.E., Kennedy P.R. and Banks D.M. American Association of Neurological Surgeons Annual Meeting, 1991.
10. Long-term recording of the same cortical units in monkeys using the cone electrode. Kennedy, P.R., Banks, D.M. and Bakay R.A.E. 21st Annual Neural Prosthesis Workshop, National Institutes of Health, October 1990.
9. Long-term recording of cortical units using the cone electrode in monkeys. P.R.Kennedy, R.A.E.Bakay, N.Oyesiku and D.M.Banks. Soc. Neuroscience Abstracts, 16(2):1134, 1990.
8. Dynamic aspects of receptive fields of neurons chronically recorded in rat vibrissa cortex. D.Banks and P.R.Kennedy. Soc. Neurosci. Abstr. 15(1):962, 1989, and poster presentation at the Barrels Symposium, Phoenix Az, Oct.28-29 1989.
7. The Cone Electrode: New concepts in long-term recording. Results in rat and monkey. P.R.Kennedy, 20th Annual Neural Prosthesis Workshop, NIH, Oct. 1989.
6. Ion Assisted Ir and IrOxide Coating of Neural Electrodes. K.O.Legg, P.R.Kennedy and H. Solnick-Legg, 20th Annual Neural Prosthesis Workshop, NIH, Oct 1989.
5. Robust Noise Suppression Techniques for Neural Signals. J.L.Lansford, P.R.Kennedy and J.E.Schroeder, IEEE Proceedings, 11(2/6) (1989) 681.
4. The cone electrode: A Long-term Electrode that Records from Neurites. P.R. Kennedy. Society for Neuroscience Abstract, 14(2):1261, 1988.
3. A new long-term recording electrode. P.R. Kennedy. Symposium: Spotlight on Research at Emory and Georgia Tech, Proceedings. April 11-13, 1988.
2. Telemetry systems for high and low frequency biological signals. John Fanguy, Neal Hollenbeck, Philip Kennedy, Ann Patterson, Steve Sharpe. Symposium: Spotlight on Research at Emory and Georgia Tech, Proceedings. April 11-13, 1988.
1. An Electrode that Records from Regenerated Neurites. Kennedy PR. International Symposium on Neural Regeneration. Asilomar, Ca. Dec. 6-l0, l987.