Award Abstract # 0954243
CAREER: Consolidation of Motor Memory for Brain-Machine Interfaces

NSF Org: CBET
Div Of Chem, Bioeng, Env, & Transp Sys
Recipient: REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE
Initial Amendment Date: April 6, 2010
Latest Amendment Date: April 6, 2010
Award Number: 0954243
Award Instrument: Standard Grant
Program Manager: Athanassios Sambanis
CBET
 Div Of Chem, Bioeng, Env, & Transp Sys
ENG
 Directorate For Engineering
Start Date: April 15, 2010
End Date: March 31, 2015 (Estimated)
Total Intended Award Amount: $449,783.00
Total Awarded Amount to Date: $449,783.00
Funds Obligated to Date: FY 2010 = $449,783.00
History of Investigator:
  • Jose Carmena (Principal Investigator)
    carmena@eecs.berkeley.edu
Recipient Sponsored Research Office: University of California-Berkeley
1608 4TH ST STE 201
BERKELEY
CA  US  94710-1749
(510)643-3891
Sponsor Congressional District: 12
Primary Place of Performance: University of California-Berkeley
1608 4TH ST STE 201
BERKELEY
CA  US  94710-1749
Primary Place of Performance
Congressional District:
12
Unique Entity Identifier (UEI): GS3YEVSS12N6
Parent UEI:
NSF Program(s): Engineering of Biomed Systems
Primary Program Source: 01001011DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 004E, 1045, 1187
Program Element Code(s): 534500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

0954243
Carmena

Brain-machine interface technology has the potential of improving the quality of life for millions of patients suffering from paralysis due to lesions of the central nervous system or other neurological disorders. Our previous findings showed that monkeys can learn to reach and grasp virtual objects by controlling a robot arm through a brain-machine interface using visual feedback, even in the absence of overt arm movements. This proposal aims at bringing the field one step closer towards the ultimate control of neuroprosthetic devices through an effortless recall of a motor memory in a manner that mimics the natural process of skill acquisition and motor control. This goal will be pursued through the following specific aims: 1) To investigate the formation and stabilization of a prosthetic motor memory; 2) To investigate the neuron-behavior relationship for prosthetic function.

This project will establish a scientific basis for understanding how the brain controls movement of disembodied devices, and will drive the development of the next generation of neural prosthetics that will restore motor function in millions of neurologically impaired patients. The strong educational component of this proposal relies on brain-machine interfaces as an ideal platform for interdisciplinary education in science and engineering. The proposed efforts aim to address the nations current talent shortage of science and engineering majors which could have a severe negative impact on economic growth. This will be pursued through a mentoring program aimed at increasing the number of underrepresented and women students entering careers in engineering. The program will also involve undergraduate and graduate students, academics, and the industrial community in brain-machine interface research through teaching, collaborations, data sharing, workshops and tutorials.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Koralek A.C., Jin X., Long J.D., Costa R.M. and Carmena J.M. "Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills." Nature , v.483(738 , 2012 , p.331-335
Ganguly K., Dimitrov D.F., Wallis J.D. and Carmena J.M. "Reversible large-scale modification of cortical networks during neuroprosthetic control." Nature Neuroscience , v.14 , 2011 , p.662-667
Canolty R.T., Cadieu C.F., Koepsell K., Ganguly K., Knight R.T. and Carmena J.M. "Detecting event-related changes of multivariate phase coupling in dynamic brain networks." Journal of Neurophysiology , v.107(7) , 2012 , p.2020-203
Canolty R.T., Cadieu C.F., Koepsell K., Knight R.T. and Carmena J.M. "Multivariate phase-amplitude cross-frequency coupling in neurophysiological signals." IEEE Transactions on Biomedical Engineering , v.59(1) , 2012 , p.8-11
Orsborn A.L., Dangi S., Moorman H.G. and Carmena J.M. "Closed-loop decoder adaptation on intermediate time-scales facilitates rapid BMI performance improvements independent of decoder initialization conditions." IEEE Transactions on Neural Systems and Rehabilitation Engineering , v.20(4) , 2012 , p.468-77
Canolty R.T., Ganguly K. and Carmena J.M. "Task-dependent changes in cross-level coupling between single neurons and multi-scale network activity" PLoS Computational Biology , 2012 10.1371/journal.pcbi.1002809.
Koralek A.C., Costa R.M. and Carmena J.M. "Temporally precise cell-specific coherence develops in corticostriatal networks during learning." Neuron , v.79(5) , 2013
Dangi D.*, Orsborn A.L.*, Moorman H.G. and Carmena J.M. "Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces" Neural Computation , v.25 , 2013
Orsborn A.L. and Carmena J.M. "Creating new functional circuits for action via brain-machine interfaces" Frontiers in Computational Neuroscience , v.7 , 2013
Krishna V. Shenoy and Jose M. Carmena "Combining Decoder Design and Neural Adaptation in Brain-Machine Interfaces" Neuron , v.84 , 2014

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