Spontaneous neuronal activity is correlated to statistical learning performance: computation of ALFF and fALFF indices on resting-state fMRI
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Sanahuja Irene, Sandra
- dc.date.accessioned 2019-08-01T09:29:30Z
- dc.date.available 2019-08-01T09:29:30Z
- dc.date.issued 2019
- dc.description Treball de fi de grau en Biologia Humanaca
- dc.description 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.ca
- dc.format.mimetype application/pdf*
- dc.identifier.uri http://hdl.handle.net/10230/42224
- dc.language.iso engca
- dc.rights Reconeixement-NoComercial-CompartirIgual 4.0 Internacional*
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/deed.ca*
- dc.subject.other Neurologia
- dc.subject.other Estadística
- dc.title Spontaneous neuronal activity is correlated to statistical learning performance: computation of ALFF and fALFF indices on resting-state fMRIca
- dc.type info:eu-repo/semantics/bachelorThesisca