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An open-source, ready-to-use and validated ripple detector plugin for the Open Ephys GUI.
Sousa, Bruno Monteiro de; de Oliveira, Eliezyer Fermino; Beraldo, Ikaro Jesus da Silva; Polanczyk, Rafaela Schuttenberg; Leite, João Pereira; Lopes Aguiar, Cleiton.
Afiliación
  • Sousa BM; Graduate Program in Biological Sciences: Physiology and Pharmacology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Brazil.
  • de Oliveira EF; Laboratory of Molecular and Behavioral Neuroscience (LANEC), Federal University of Minas Gerais, Belo Horizonte, Brazil.
  • Beraldo IJDS; Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, United States of America.
  • Polanczyk RS; Graduate Program in Biological Sciences: Physiology and Pharmacology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Brazil.
  • Leite JP; Laboratory of Molecular and Behavioral Neuroscience (LANEC), Federal University of Minas Gerais, Belo Horizonte, Brazil.
  • Lopes Aguiar C; Graduate Program in Biological Sciences: Physiology and Pharmacology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Brazil.
J Neural Eng ; 19(4)2022 08 12.
Article en En | MEDLINE | ID: mdl-35905709
Objective. Sharp wave-ripples (SWRs, 100-250 Hz) are oscillatory events extracellularly recorded in the CA1 subfield of the hippocampus during sleep and quiet wakefulness. Many studies employed closed-loop strategies to either detect and abolish SWRs within the hippocampus or manipulate other relevant areas upon ripple detection. However, the code and schematics necessary to replicate the detection system are not always available, which hinders the reproducibility of experiments among different research groups. Furthermore, information about performance is not usually reported. Here, we sought to provide an open-source, validated ripple detector for the scientific community.Approach. We developed and validated a ripple detection plugin integrated into the Open Ephys graphical user's interface. It contains a built-in movement detector based on accelerometer or electromyogram data that prevents false ripple events (due to chewing, grooming, or moving, for instance) from triggering the stimulation/manipulation device.Main results. To determine the accuracy of the detection algorithm, we first carried out simulations in MATLAB with real ripple recordings. Using a specific combination of detection parameters (amplitude threshold of 5 standard deviations above the mean, time threshold of 10 ms, and root mean square block size of 7 samples), we obtained a 97% true positive rate and 2.48 false positives per minute. Next, an Open Ephys plugin based on the same detection algorithm was developed, and a closed-loop system was set up to evaluate the round trip (ripple onset-to-stimulation) latency over synthetic data. The lowest latency obtained was 34.5 ± 0.5 ms. The embedded movement monitoring was effective in reducing false positives and the plugin's flexibility to detect pathological events was also verified.Significance. Besides contributing to increased reproducibility, we anticipate that the developed ripple detector plugin will be helpful for many closed-loop applications in the field of systems neuroscience.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Neurociencias Límite: Animals Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Neurociencias Límite: Animals Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido