| Autor: |
Bonetti, L., Fernández Rubio, G., Carlomagno, F., Pantazis, D., Vuust, P., Kringelbach, M.L. |
| Rok vydání: |
2022 |
| Předmět: |
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| DOI: |
10.1101/2022.11.19.517195 |
| Popis: |
The full analysis pipeline used in this study is available at the following link: https://github.com/leonardob92/HierarchicalPredictiveCoding_Music_MEG.git Additional in-house-built codes and functions used in this study are part of the LBPD repository and are available at the following link: https://github.com/leonardob92/LBPD-1.0.git. Abstract To survive the brain must extract and predict information from key spacetime features of the physical world. While neural processing of visuospatial patterns has been extensively studied, much remains to be discovered about the hierarchical brain mechanisms underlying recognition of auditory sequences with associated prediction errors. Using magnetoencephalography (MEG), we studied the temporal unfolding over milliseconds of brain activity in 83 participants recognising original melodies and systematic variations. The results showed a hierarchy of processing in networks from the auditory to the ventromedial prefrontal and inferior temporal cortices, hippocampus and medial cingulate gyrus. Both original melodies and variations engaged the pathway from auditory cortex at the bottom of the hierarchy to upstream processing in hippocampus and ventromedial prefrontal cortex, but differed in terms of temporal dynamics, where the recognition of originals elicited stronger gamma power. Our results provide detailed spacetime insights into the hierarchical brain mechanisms underlying auditory sequence recognition. The data is provided after pre-processing (Maxfilter, ICA for removing eye blink and heart beat, co-registration with the individual MRI T1) and epoching. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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