Zobrazeno 1 - 10
of 27
pro vyhledávání: '"John S. Choi"'
Autor:
Eric H. Pollmann, Heyu Yin, Ilke Uguz, Agrita Dubey, Katie Elizabeth Wingel, John S Choi, Sajjad Moazeni, Yatin Gilhotra, Victoria A. Pavlovsky, Adam Banees, Vivek Boominathan, Jacob Robinson, Ashok Veeraraghavan, Vincent A. Pieribone, Bijan Pesaran, Kenneth L. Shepard
Publikováno v:
bioRxiv
Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical extents. While there has been significant progress in miniaturizing microscope for h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9459a8c17d41f75f0b8adcf275f63c1
https://doi.org/10.1101/2023.02.07.527500
https://doi.org/10.1101/2023.02.07.527500
Publikováno v:
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 29
Non-parametric regression has been shown to be useful in extracting relevant features from Local Field Potential (LFP) signals for decoding motor intentions. Yet, in many instances, brain-computer interfaces (BCIs) rely on simple classification metho
Autor:
Krishan Kumar, John S. Choi, Mohammad Khazali, Mahdi Choudhury, Katie E. Wingel, Bijan Pesaran, Adam S. Charles
Neural-Matrix style, high-density electrode arrays for brain-machine interfaces (BMIs) and neuroscientific research require the use of multiplexing: Each recording channel can be routed to one of several electrode sites on the array. This capability
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::706264e08dfad4778396fc5ea9f22f11
https://doi.org/10.1101/2020.10.06.328526
https://doi.org/10.1101/2020.10.06.328526
Publikováno v:
ICASSP
Nonparametric regression has proven to be successful in extracting features from limited data in neurological applications. However, due to data scarcity, most brain-computer interfaces still rely on linear classifiers. This work leverages the robust
Objective We consider the cross-subject decoding problem from local field potential (LFP) signals, where training data collected from the prefrontal cortex (PFC) of a source subject is used to decode intended motor actions in a destination subject. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbd96358d600d8cc24f2da6494edca25
http://arxiv.org/abs/1911.03540
http://arxiv.org/abs/1911.03540
We consider the problem of predicting eye movement goals from local field potentials (LFP) recorded through a multielectrode array in the macaque prefrontal cortex. The monkey is tasked with performing memory-guided saccades to one of eight targets d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1c7a059f0fe5c6104196b389d807b12
Autor:
Jonathan Viventi, Amy L. Orsborn, Bijan Pesaran, John S. Choi, Charles Wang, Jessica E. Kleinbart, Shaoyu Qiao
Publikováno v:
Conf Proc IEEE Eng Med Biol Soc
EMBC
EMBC
Neural circuitry can be investigated and manipulated using a variety of techniques, including electrical and optical recording and stimulation. At present, most neural interfaces are designed to accommodate a single mode of neural recording and/or ma
Publikováno v:
EMBC
Conf Proc IEEE Eng Med Biol Soc
Conf Proc IEEE Eng Med Biol Soc
The size and curvature of the macaque brain present challenges for two photon laser scanning microscopy (2P-LSM). General access to the cortex requires 5-axis positioning over a range of motion wider than existing designs offer. In addition, movement
Publikováno v:
SSP
A problem of classification of local field potentials (LFPs), recorded from the prefrontal cortex of a macaque monkey, is considered. An adult macaque monkey is trained to perform a memory-based saccade. The objective is to decode the eye movement go
Publikováno v:
ICASSP
A macaque monkey is trained to perform two different kinds of tasks, memory aided and visually aided. In each task, the monkey saccades to eight possible target locations. A classifier is proposed for direction decoding and task decoding based on loc