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Why overlearned sequences are special: distinct neural networks for ordinal sequences

Several observations suggest that overlearned ordinal categories (e.g., letters, numbers, weekdays, months) are processed differently than non-ordinal categories in the brain. In synesthesia, for example, anomalous perceptual experiences are most often triggered by members of ordinal categories (Ric...

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Autores principales: Pariyadath, Vani, Plitt, Mark H., Churchill, Sara J., Eagleman, David M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526771/
https://www.ncbi.nlm.nih.gov/pubmed/23267320
http://dx.doi.org/10.3389/fnhum.2012.00328
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author Pariyadath, Vani
Plitt, Mark H.
Churchill, Sara J.
Eagleman, David M.
author_facet Pariyadath, Vani
Plitt, Mark H.
Churchill, Sara J.
Eagleman, David M.
author_sort Pariyadath, Vani
collection PubMed
description Several observations suggest that overlearned ordinal categories (e.g., letters, numbers, weekdays, months) are processed differently than non-ordinal categories in the brain. In synesthesia, for example, anomalous perceptual experiences are most often triggered by members of ordinal categories (Rich et al., 2005; Eagleman, 2009). In semantic dementia (SD), the processing of ordinal stimuli appears to be preserved relative to non-ordinal ones (Cappelletti et al., 2001). Moreover, ordinal stimuli often map onto unconscious spatial representations, as observed in the SNARC effect (Dehaene et al., 1993; Fias, 1996). At present, little is known about the neural representation of ordinal categories. Using functional neuroimaging, we show that words in ordinal categories are processed in a fronto-temporo-parietal network biased toward the right hemisphere. This differs from words in non-ordinal categories (such as names of furniture, animals, cars, and fruit), which show an expected bias toward the left hemisphere. Further, we find that increased predictability of stimulus order correlates with smaller regions of BOLD activation, a phenomenon we term prediction suppression. Our results provide new insights into the processing of ordinal stimuli, and suggest a new anatomical framework for understanding the patterns seen in synesthesia, unconscious spatial representation, and SD.
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spelling pubmed-35267712012-12-24 Why overlearned sequences are special: distinct neural networks for ordinal sequences Pariyadath, Vani Plitt, Mark H. Churchill, Sara J. Eagleman, David M. Front Hum Neurosci Neuroscience Several observations suggest that overlearned ordinal categories (e.g., letters, numbers, weekdays, months) are processed differently than non-ordinal categories in the brain. In synesthesia, for example, anomalous perceptual experiences are most often triggered by members of ordinal categories (Rich et al., 2005; Eagleman, 2009). In semantic dementia (SD), the processing of ordinal stimuli appears to be preserved relative to non-ordinal ones (Cappelletti et al., 2001). Moreover, ordinal stimuli often map onto unconscious spatial representations, as observed in the SNARC effect (Dehaene et al., 1993; Fias, 1996). At present, little is known about the neural representation of ordinal categories. Using functional neuroimaging, we show that words in ordinal categories are processed in a fronto-temporo-parietal network biased toward the right hemisphere. This differs from words in non-ordinal categories (such as names of furniture, animals, cars, and fruit), which show an expected bias toward the left hemisphere. Further, we find that increased predictability of stimulus order correlates with smaller regions of BOLD activation, a phenomenon we term prediction suppression. Our results provide new insights into the processing of ordinal stimuli, and suggest a new anatomical framework for understanding the patterns seen in synesthesia, unconscious spatial representation, and SD. Frontiers Media S.A. 2012-12-20 /pmc/articles/PMC3526771/ /pubmed/23267320 http://dx.doi.org/10.3389/fnhum.2012.00328 Text en Copyright © 2012 Pariyadath, Plitt, Churchill and Eagleman. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Neuroscience
Pariyadath, Vani
Plitt, Mark H.
Churchill, Sara J.
Eagleman, David M.
Why overlearned sequences are special: distinct neural networks for ordinal sequences
title Why overlearned sequences are special: distinct neural networks for ordinal sequences
title_full Why overlearned sequences are special: distinct neural networks for ordinal sequences
title_fullStr Why overlearned sequences are special: distinct neural networks for ordinal sequences
title_full_unstemmed Why overlearned sequences are special: distinct neural networks for ordinal sequences
title_short Why overlearned sequences are special: distinct neural networks for ordinal sequences
title_sort why overlearned sequences are special: distinct neural networks for ordinal sequences
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526771/
https://www.ncbi.nlm.nih.gov/pubmed/23267320
http://dx.doi.org/10.3389/fnhum.2012.00328
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