The Neural Representation of a Repeated Standard Stimulus in Dyslexia
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fnhum-16-823627.pdf
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Published version
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1.76 MB
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Author(s) • • • • • •
Beach, Sara D
Ozernov-Palchik, Ola
May, Sidney C
Centanni, Tracy M
Perrachione, Tyler K
Pantazis, Dimitrios
Gabrieli, John DE
Date Issued
2022
Journal
Frontiers in Human Neuroscience
Publisher
Frontiers Media SA
Citation
Beach, Sara D, Ozernov-Palchik, Ola, May, Sidney C, Centanni, Tracy M, Perrachione, Tyler K et al. 2022. "The Neural Representation of a Repeated Standard Stimulus in Dyslexia." Frontiers in Human Neuroscience, 16.
Version
Final published version
Abstract
The neural representation of a repeated stimulus is the standard against which a deviant stimulus is measured in the brain, giving rise to the well-known mismatch response. It has been suggested that individuals with dyslexia have poor implicit memory for recently repeated stimuli, such as the train of standards in an oddball paradigm. Here, we examined how the neural representation of a standard emerges over repetitions, asking whether there is less sensitivity to repetition and/or less accrual of “standardness” over successive repetitions in dyslexia. We recorded magnetoencephalography (MEG) as adults with and without dyslexia were passively exposed to speech syllables in a roving-oddball design. We performed time-resolved multivariate decoding of the MEG sensor data to identify the neural signature of standard vs. deviant trials, independent of stimulus differences. This “multivariate mismatch” was equally robust and had a similar time course in the two groups. In both groups, standards generated by as few as two repetitions were distinct from deviants, indicating normal sensitivity to repetition in dyslexia. However, only in the control group did standards become increasingly different from deviants with repetition. These results suggest that many of the mechanisms that give rise to neural adaptation as well as mismatch responses are intact in dyslexia, with the possible exception of a putatively predictive mechanism that successively integrates recent sensory information into feedforward processing.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.3389/FNHUM.2022.823627