Eric A Pohlmeyer
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Explore the profile of Eric A Pohlmeyer including associated specialties, affiliations and a list of published articles.
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21
Citations
355
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Recent Articles
1.
Fifer M, McMullen D, Osborn L, Thomas T, Christie B, Nickl R, et al.
Neurology
. 2021 Dec;
98(7):e679-e687.
PMID: 34880087
Background And Objectives: The restoration of touch to fingers and fingertips is critical to achieving dexterous neuroprosthetic control for individuals with sensorimotor dysfunction. However, localized fingertip sensations have not been...
2.
Mylavarapu R, Prins N, Pohlmeyer E, Shoup A, Debnath S, Geng S, et al.
J Neural Eng
. 2021 Jul;
18(4).
PMID: 34225263
The common marmoset has been increasingly used in neural interfacing studies due to its smaller size, easier handling, and faster breeding compared to Old World non-human primate (NHP) species. While...
3.
McMullen D, Thomas T, Fifer M, Candrea D, Tenore F, Nickl R, et al.
J Neurosurg
. 2021 Mar;
135(5):1493-1500.
PMID: 33770760
Defining eloquent cortex intraoperatively, traditionally performed by neurosurgeons to preserve patient function, can now help target electrode implantation for restoring function. Brain-machine interfaces (BMIs) have the potential to restore upper-limb...
4.
Prins N, Pohlmeyer E, Debnath S, Mylavarapu R, Geng S, Sanchez J, et al.
J Neurosci Methods
. 2017 Apr;
284:35-46.
PMID: 28400103
Background: The common marmoset (Callithrix jacchus) has been proposed as a suitable bridge between rodents and larger primates. They have been used in several types of research including auditory, vocal,...
5.
Scholl C, Chi Y, Elconin M, Gray W, Chevillet M, Pohlmeyer E
Annu Int Conf IEEE Eng Med Biol Soc
. 2017 Mar;
2016:4467-4470.
PMID: 28269270
Pilot-Induced Oscillations (PIOs) are potentially hazardous piloting phenomena in which a pilot's control-inputs and the aircraft control-responses have (for any of a number of possible reasons) become out of phase....
6.
Kryger M, Wester B, Pohlmeyer E, Rich M, John B, Beaty J, et al.
Exp Neurol
. 2016 May;
287(Pt 4):473-478.
PMID: 27196543
As Brain-Computer Interface (BCI) systems advance for uses such as robotic arm control it is postulated that the control paradigms could apply to other scenarios, such as control of video...
7.
Bae J, Sanchez Giraldo L, Pohlmeyer E, Francis J, Sanchez J, Principe J
Comput Intell Neurosci
. 2015 Apr;
2015:481375.
PMID: 25866504
We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value...
8.
Pohlmeyer E, Mahmoudi B, Geng S, Prins N, Sanchez J
PLoS One
. 2014 Feb;
9(1):e87253.
PMID: 24498055
Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living,...
9.
Bae J, Sanchez Giraldo L, Pohlmeyer E, Sanchez J, Principe J
Annu Int Conf IEEE Eng Med Biol Soc
. 2013 Oct;
2013:5402-5.
PMID: 24110957
This paper presents the first attempt to quantify the individual performance of the subject and of the computer agent on a closed loop Reinforcement Learning Brain Machine Interface (RLBMI). The...
10.
Prins N, Geng S, Pohlmeyer E, Mahmoudi B, Sanchez J
Annu Int Conf IEEE Eng Med Biol Soc
. 2013 Oct;
2013:5250-3.
PMID: 24110920
New reinforcement based paradigms for building adaptive decoders for Brain-Machine Interfaces involve using feedback directly from the brain. In this work, we investigated neuromodulation in the Nucleus Accumbens (reward center)...