Spectral parameterization for studying neurodevelopment: How and why.
Dev Cogn Neurosci
; 54: 101073, 2022 04.
Article
en En
| MEDLINE
| ID: mdl-35074579
ABSTRACT
A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how parameterization can be readily accomplished with an automated spectral parameterization ("specparam") algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; Mage = 9.97, SD = 0.95) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, the explicit parameterization of EEG power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub as a supplement to the open-access specparam toolbox.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Cognición
/
Electroencefalografía
Límite:
Child
/
Humans
Idioma:
En
Revista:
Dev Cogn Neurosci
Año:
2022
Tipo del documento:
Article