# name
How do our brainwaves perceive the passage of time? Quantifying neural correlates of time during a rhythm performance task

# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023, Director: Ignasi Cos Aguilera

# metadata.dc.description.abstract[].value
[en] The aim of this project is to establish a methodology to quantify the extent to which different brainwave signatures vary in their past data retention, and to determine how other factors interact with these variations, using previously obtained EEG recordings.  To achieve this, we quantified the amount of past values that strongly influence future values for each brainwave signature throughout different EEG time series. Specifically, we calculated the number of lags required for a univariate autoregressive computational model to predict a set of brainwave time-series with an error (RMSE) below a preset threshold. In this fashion, we could establish that a similar number of lags were required based on the brainwave signatures (alpha, beta, gamma, or unfiltered) throughout the different conditions of activities and the different EEG sets, with the number of lags required
being around 3, 4, and 6 for alpha, beta, and gamma brainwaves, respectively, when trying to achieve a minimum RMSE value of 0.001. This covariation is displayed again when using a different sets of threshold RMSE values, with gamma consistently having a greater dependency to past data, and alpha a lesser one.
Our results indicate that brainwave signatures that are more related to active states can use past data for a longer period of time than brainwave signatures related to relaxed states. Furthermore, they suggest that active-state brainwaves show a more dilated time perception than their relaxed counterparts.
In future studies, this methodology may help to establish a technique to objectively analyze time perception variation through EEG readings.

# metadata.dc.rights[].value
memòria: cc-nc-nd (c) Luca Eric Di Croce, 2023

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

# metadata.dc.title[].value
How do our brainwaves perceive the passage of time? Quantifying neural correlates of time during a rhythm performance task