ArticleFrontiers in neuroscience2021
Accurate Decoding of Imagined and Heard Melodies.
Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Reconstruction of Imagined Melody with Relative Pitch Decoding in Electrocorticography.eNeuro · 2026Article
- Music-selective cortex is sensitive to structure in both pitch and time.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Predicting artificial neural network representations to learn recognition model for music identification from brain recordings.Scientific reports · 2025Article
- Decoding reveals the neural representation of perceived and imagined musical sounds.PLoS biology · 2024Article
- Decoding reveals the neural representation of perceived and imagined musical sounds.bioRxiv : the preprint server for biology · 2024Article
- Exploring an EM-algorithm for banded regression in computational neuroscience.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Neural decoding of music from the EEG.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Music perception requires the human brain to process a variety of acoustic and music-related properties. Recent research used encoding models to tease apart and study the various cortical contributors to music perception. To do so, such approaches study temporal response functions that summarise the neural activity over several minutes of data. Here we tested the possibility of assessing the neural processing of individual musical units (bars) with electroencephalography (EEG). We devised a decoding methodology based on a maximum correlation metric across EEG segments (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.