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Ludovic Bellier - Decoding a Pink Floyd song from the human brain

Date: 
Fri, 02/24/2023 - 10:30am - 12:00pm
Location: 
CCRMA Seminar Room
Event Type: 
Hearing Seminar
Can we tell the music you are listening to from brain signals?

There has been a lot of work to decode speech signals from brain signal using intracranial EEG (ECoG), MEG and EEG. But what about music? Does the brain respond the same way? Arguably speech is easier, since it is both one-dimensional and for many studies there is a single source. In addition speech is likely to engage the motor system, providing another set of neurons from which to decode the basic speech signal. Music is more challenging: multiple acoustic objects, driving the emotional centers of the brain. What does it mean to decode music? Which parts of the brain respond with a signal we can decode in real time?

Who: Ludovic Bellier
What: Decoding a Pink Floyd song from the human brain
When: Fri, 02/24/2023 - 10:30am - 12:00pm
Where: CCRMA Seminar Room, top floor of The Knoll at Stanford
Why: What is more important than music and the brain? :-)

Come to the Hearing Seminar to hear more about how our brain responds to music and what we can tell from brain signals.

- Malcolm


Decoding a Pink Floyd song from the human brain”
Ludovic Bellier (formerly UCB, now Inscopix)

Abstract: Music is core to human experience, yet many aspects of how our brain supports music perception remain unknown. We gained insights into this process by combining unique human intracranial EEG data with cutting-edge machine learning algorithms, and reconstructed a Pink Floyd song directly decoded from neural activity along the way. See this paper: Encoding and decoding analysis of music perception using intracranial EEG

Bio: Trained in biology and neuroscience, Ludovic Bellier did his PhD in Lyon, France, working on the speech-evoked Frequency Following Response (an electrophysiological marker of speech perception) and its application to hearing aid users. He then did his postdoc in the lab of Bob Knight at UC Berkeley, where he investigated music and speech perception through the use of predictive modeling applied to intracranial EEG data. He recently joined a neurotechnology company, Inscopix, where he analyzes calcium imaging neural data in the context of neuropsychiatric disorders.
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