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A Spike in Entropy Precedes the Mismatch Negativity; Linking Entropy and Prediction Error

Poster Session F - Tuesday, April 1, 2025, 8:00 – 10:00 am EDT, Back Bay Ballroom/Republic Ballroom

Michael Angyus1 (michaelangyus@gmail.com), Fernando Rosas4,1, Pedro Mediano1,2, Robin Carhart-Harris3,1; 1Imperial College London, 2University of Cambridge, 3University of California San Francisco, 4University of Sussex

Predictive coding suggests that the brain minimizes free energy through the accurate prediction of sensory stimuli. While not mathematically identical, some research has suggested that information content of a brain signal can act as a proxy for free energy. Measures such as Shannon’s entropy and Shannon’s entropy rate may therefore be combined with experimental paradigms of prediction error to statistically examine the relationship in the human brain. Our study combines a recently developed measure of Shannon’s entropy rate with the auditory mismatch negativity (MMN) paradigm to explore relationships between entropy rate and event related potentials from electroencephalography (EEG) signals. Our analyses reveal a significant spike in entropy occurring prior to the onset of the MMN, providing a first direct link between neurocomputational prediction error and neural activity associated with prediction error. Mixed effects regression revealed that the magnitude of this entropy spike was associated with strength of the MMN (Adjusted R2 = 0.385, 𝛽 = 0.012, p < 0.001). Mixed effects regression was also used to see if baseline entropy (prior to a given trial) was related to MMN magnitude, finding a significant positive relationship (Adjusted R2 = 0.239, 𝛽 = 0.023, p < 0.001). These findings provide experimental evidence for the relationship between entropy and prediction error, supporting predictive coding and the free energy principle.

Topic Area: PERCEPTION & ACTION: Audition

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March 29–April 1  |  2025

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