Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Carlos A. Loza"'
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Here the authors compare place cell sequence coding during correct and error trials in a spatial memory task. Sequences coded paths that were longer and more temporally compressed during correct trials and developed a bias to replay paths to a goal l
Externí odkaz:
https://doaj.org/article/f6dd9f5d9ec44f769f44ebb1cec88b68
Publikováno v:
Frontiers in Neuroscience, Vol 13 (2019)
Brain–Computer Interfaces (BCI) aim to bypass the peripheral nervous system to link the brain to external devices via successful modeling of decoding mechanisms. BCI based on electrocorticogram or ECoG represent a viable compromise between clinical
Externí odkaz:
https://doaj.org/article/d8bef48f0fc3452d952b7a20082db5f2
Autor:
Carlos A. Loza
Publikováno v:
PeerJ Computer Science, Vol 5, p e192 (2019)
Sparse coding aims to find a parsimonious representation of an example given an observation matrix or dictionary. In this regard, Orthogonal Matching Pursuit (OMP) provides an intuitive, simple and fast approximation of the optimal solution. However,
Externí odkaz:
https://doaj.org/article/d1a1730a8a784afbb52737a32cf3c5ec
Publikováno v:
Frontiers in Systems Neuroscience, Vol 11 (2017)
Neuromodulations are an important component of extracellular electrical potentials (EEP), such as the Electroencephalogram (EEG), Electrocorticogram (ECoG) and Local Field Potentials (LFP). This spatially temporal organized multi-frequency transient
Externí odkaz:
https://doaj.org/article/45ab0a0c191e44f4bf275b35865762f7
Autor:
Carlos A. Loza, Jose C. Principe
Publikováno v:
Handbook of Neuroengineering ISBN: 9789811655395
Handbook of Neuroengineering ISBN: 9789811528484
Handbook of Neuroengineering
Handbook of Neuroengineering ISBN: 9789811528484
Handbook of Neuroengineering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b16f676a65387e65469e6ba97a339d24
https://doi.org/10.1007/978-981-16-5540-1_65
https://doi.org/10.1007/978-981-16-5540-1_65
Autor:
Ricardo Ignacio Audiffred Jaramillo, Javier Eduardo García de Alba García, Ivonne García Monzón, Carlos Isaac Loza Salazar, Leticia Limón Cervantes
Publikováno v:
Salud mental. 44:277-285
Introduction. Schizophrenia is a mental disorder that affects 21 million people worldwide, and it brings about environments with high Expressed Emotion (EE) in the families of these individuals. High EE is characterized by negative evaluations, criti
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Nature Communications
Nature Communications
Theta rhythms temporally coordinate sequences of hippocampal place cell ensembles during active behaviors, while sharp wave-ripples coordinate place cell sequences during rest. We investigated whether such coordination of hippocampal place cell seque
Autor:
Olga Gloria Barbón-Pérez, Ángela del Rocío Calderón-Tobar, Carlos Augusto Loza-Cevallos, Lenin Garcés-Viteri, Jorge Washington Fernández-Pino
Publikováno v:
Actualidades Investigativas en Educación, Vol 17, Iss 1 (2017)
Actualmente, la mayor parte de las investigaciones sobre la producción científica de los docentes de la educación superior aborda el problema desde perspectivas ajenas a los procesos formativos universitarios, mediante los cuales estos sujetos des
Externí odkaz:
https://doaj.org/article/961ac89d0ab74e34af5b55c33eb6e0ba
Autor:
Laura Lee Colgin, Carlos A. Loza
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872397
MICCAI (5)
MICCAI (5)
We propose a generative model for single–channel EEG that incorporates the constraints experts actively enforce during visual scoring. The framework takes the form of a dynamic Bayesian network with depth in both the latent variables and the observ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94121429a3c3a3259672bc5a20c978ce
https://doi.org/10.1007/978-3-030-87240-3_53
https://doi.org/10.1007/978-3-030-87240-3_53
Autor:
Carlos A. Loza
Publikováno v:
2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON).
We propose a robust alternative the well known dictionary learning technique K-SVD. Specifically, we exploit the theory behind M-Estimators to incorporate robustness into the sparse coding stage of K-SVD, and hence, decrease the estimation bias that