D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 46 Citations 10,667 169 World Ranking 2445 National Ranking 913
Neuroscience D-index 51 Citations 12,590 167 World Ranking 3216 National Ranking 1485

Research.com Recognitions

Awards & Achievements

2009 - Fellow of Alfred P. Sloan Foundation

2007 - Hellman Fellow

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Artificial intelligence
  • Electrical engineering

His primary scientific interests are in Neuroscience, Motor cortex, Brain–computer interface, Neuroplasticity and Motor skill. His research on Neuroscience frequently links to adjacent areas such as Anatomy. The Motor cortex study combines topics in areas such as Neuronal tuning, Neuron, Brain mapping and Motor learning.

His research investigates the connection between Neuronal tuning and topics such as Cortical map that intersect with issues in Neural ensemble. His Brain–computer interface research includes themes of Ultrasonic sensor, Interfacing, Bandwidth and Neuroprosthetics. His Neuroplasticity study incorporates themes from Neural activity, Closed loop and Adaptation.

His most cited work include:

  • Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates (1444 citations)
  • Chronic, multisite, multielectrode recordings in macaque monkeys (643 citations)
  • Emergence of a Stable Cortical Map for Neuroprosthetic Control (417 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Neuroscience, Brain–computer interface, Artificial intelligence, Motor cortex and Ultrasonic sensor. His is doing research in Macaque, Local field potential, Microstimulation, Neuroplasticity and Primary motor cortex, both of which are found in Neuroscience. As a member of one scientific family, Jose M. Carmena mostly works in the field of Brain–computer interface, focusing on Kalman filter and, on occasion, Decoding methods.

His study looks at the relationship between Artificial intelligence and topics such as Machine learning, which overlap with Adaptation. His studies in Motor cortex integrate themes in fields like Motor skill, Movement, Neuron, Neural activity and Brain mapping. While the research belongs to areas of Ultrasonic sensor, Jose M. Carmena spends his time largely on the problem of Wireless, intersecting his research to questions surrounding Electrical engineering, Electronic engineering and Computer hardware.

He most often published in these fields:

  • Neuroscience (64.84%)
  • Brain–computer interface (38.36%)
  • Artificial intelligence (20.55%)

What were the highlights of his more recent work (between 2017-2021)?

  • Neuroscience (64.84%)
  • Ultrasonic sensor (15.53%)
  • Brain–computer interface (38.36%)

In recent papers he was focusing on the following fields of study:

Jose M. Carmena mainly focuses on Neuroscience, Ultrasonic sensor, Brain–computer interface, Motor cortex and Neural activity. When carried out as part of a general Neuroscience research project, his work on Optogenetics, Stimulation and Macaque is frequently linked to work in Control and Calcium imaging, therefore connecting diverse disciplines of study. His Ultrasonic sensor research integrates issues from Wireless, Transducer, Biomedical engineering and Integrated circuit.

The concepts of his Brain–computer interface study are interwoven with issues in Motor unit, Neurofeedback and Biceps, Physical medicine and rehabilitation. His biological study spans a wide range of topics, including Contralateral hemisphere, Motor planning and Cortical network. His research in Neural activity focuses on subjects like Pulse, which are connected to Electrophysiology, Closed loop and Neuromodulation.

Between 2017 and 2021, his most popular works were:

  • A wireless and artefact-free 128-channel neuromodulation device for closed-loop stimulation and recording in non-human primates (68 citations)
  • A wireless and artefact-free 128-channel neuromodulation device for closed-loop stimulation and recording in non-human primates (68 citations)
  • A wireless millimetre-scale implantable neural stimulator with ultrasonically powered bidirectional communication. (55 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Neuroscience
  • Electrical engineering

His primary areas of study are Neuroscience, Stimulation, Ultrasonic sensor, Brain–computer interface and Optogenetics. His Stimulation study combines topics from a wide range of disciplines, such as Biosignal, Distortion, Local field potential and Communication channel. The various areas that Jose M. Carmena examines in his Ultrasonic sensor study include Wireless, Transducer, Biomedical engineering and Integrated circuit.

Jose M. Carmena interconnects Computer hardware, Interfacing and Neural Prosthesis in the investigation of issues within Wireless. His research in Brain–computer interface tackles topics such as Neuromodulation which are related to areas like Chip. His Optogenetics research incorporates elements of Motor cortex and Neural activity.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates

Jose M Carmena;Mikhail A Lebedev;Roy E Crist;Joseph E O'Doherty.
PLOS Biology (2003)

2185 Citations

Chronic, multisite, multielectrode recordings in macaque monkeys

Miguel A. L. Nicolelis;Dragan Dimitrov;Jose M. Carmena;Roy Crist.
Proceedings of the National Academy of Sciences of the United States of America (2003)

911 Citations

Cortical Ensemble Adaptation to Represent Velocity of an Artificial Actuator Controlled by a Brain-Machine Interface

Mikhail A. Lebedev;Jose M. Carmena;Joseph E. O'Doherty;Miriam Zacksenhouse.
The Journal of Neuroscience (2005)

688 Citations

Emergence of a Stable Cortical Map for Neuroprosthetic Control

Karunesh Ganguly;Jose M. Carmena;Jose M. Carmena.
PLOS Biology (2009)

580 Citations

Wireless Recording in the Peripheral Nervous System with Ultrasonic Neural Dust

Dongjin Seo;Ryan M. Neely;Konlin Shen;Utkarsh Singhal.
Neuron (2016)

386 Citations

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

Aaron C. Koralek;Xin Jin;John D. Long;Rui M. Costa.
Nature (2012)

375 Citations

Oscillatory phase coupling coordinates anatomically dispersed functional cell assemblies

Ryan T. Canolty;Karunesh Ganguly;Steven W. Kennerley;Charles F. Cadieu.
Proceedings of the National Academy of Sciences of the United States of America (2010)

310 Citations

A Minimally Invasive 64-Channel Wireless μECoG Implant

Rikky Muller;Hanh-Phuc Le;Wen Li;Peter Ledochowitsch.
IEEE Journal of Solid-state Circuits (2015)

303 Citations

Reversible large-scale modification of cortical networks during neuroprosthetic control

Karunesh Ganguly;Dragan F Dimitrov;Jonathan D Wallis;Jonathan D Wallis;Jose M Carmena.
Nature Neuroscience (2011)

269 Citations

Microstimulation Activates a Handful of Muscle Synergies

Simon A. Overduin;Andrea d’Avella;Jose M. Carmena;Jose M. Carmena;Emilio Bizzi.
Neuron (2012)

268 Citations

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