dc.contributor.author |
Sanahuja Irene, Sandra |
dc.date |
2019-08-01 |
dc.identifier.uri |
http://hdl.handle.net/10230/42224 |
dc.format |
application/pdf |
dc.language.iso |
eng |
dc.rights |
Reconeixement-NoComercial-CompartirIgual 4.0 Internacional |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by-nc-sa/4.0/deed.ca |
dc.subject |
Neurologia |
dc.subject |
Estadística |
dc.title |
Spontaneous neuronal activity is correlated to statistical learning performance: computation of ALFF and fALFF indices on resting-state fMRI |
dc.type |
info:eu-repo/semantics/bachelorThesis |
dc.description.abstract |
Treball de fi de grau en Biologia Humana |
dc.description.abstract |
Tutor: Miguel Burgaleta Díaz |
dc.description.abstract |
Statistical learning (SL) is a mechanism that enables us to detect and learn probabilistic regularities and patterns from the environment. Previous studies have explored the role of SL in resting-state functional connectivity, but none of them has focused on spontaneous neuronal activity (SNA) and whether it can predict performance at a word segmentation task. Here we compute the functional segregation indices, ALFF and fALFF, on resting-state functional MRI (rs-fMRI) data and correlate them to statistical learning performance after listening to an artificial language stream. Our results show that there is a significant negative correlation between fALFF index and SL performance after a 4-minute exposure at bilateral temporo-occipital junction. This region seems to play a role in auditory attention and speech perception and, according to our results, is relevant for statistical learning when SNA is taken into account. |