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BOARD-FTD-PACC: a graphical user interface for the synaptic and cross-frequency analysis derived from neural signals

Research output: Contribution to Journal › Research Article › peer-review

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Abstract

In order to understand the link between brain functional states and behavioral/cognitive processes, the information carried in neural oscillations can be retrieved using different analytic techniques. Processing these different bio-signals is a complex, time-consuming, and often non-automatized process that requires customization, due to the type of signal acquired, acquisition method implemented, and the objectives of each individual research group. To this end, a new graphical user interface (GUI), named BOARD-FTD-PACC, was developed and designed to facilitate the visualization, quantification, and analysis of neurophysiological recordings. BOARD-FTD-PACC provides different and customizable tools that facilitate the task of analyzing post-synaptic activity and complex neural oscillatory data, mainly cross-frequency analysis. It is a flexible and user-friendly software that can be used by a wide range of users to extract valuable information from neurophysiological signals such as phase-amplitude coupling and relative power spectral density, among others. BOARD-FTD-PACC allows researchers to select, in the same open-source GUI, different approaches and techniques that will help promote a better understanding of synaptic and oscillatory activity in specific brain structures with or without stimulation.
Translated title of the contributionBOARD-FTD-PACC: una interfaz gráfica de usuario para el análisis sináptico y de frecuencia cruzada derivado de señales neuronales
Original languageEnglish (US)
Article number12
Pages (from-to)1-17
Number of pages17
JournalBrain Informatics
Volume10
Issue number12
DOIs
StatePublished - May 8 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Neuroscience (miscellaneous)
  • General Computer Science

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