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Tone-grammar association within words: Concurrent ERP and fMRI show rapid neural pre-activation and involvement of left inferior frontal gyrus in pseudoword processing

Söderström, Pelle LU ; Horne, Merle LU ; Mannfolk, Peter LU ; van Westen, Danielle LU and Roll, Mikael LU (2017) In Brain and Language 174. p.119-126
Abstract
© 2017 The Authors Using a concurrent ERP/fMRI paradigm, we investigated how listeners take advantage of morphologically relevant tonal information at the beginning of words to predict and pre-activate likely word endings. More predictive, low tone word stems gave rise to a ‘pre-activation negativity’ (PrAN) in the ERPs, a brain potential which has previously been found to increase along with the degree of predictive certainty as regards how a word is going to end. It is suggested that more predictive, low tone stems lead to rapid access to word endings with processing subserved by the left primary auditory cortex as well as the supramarginal gyrus, while high tone stems – which are less predictive – decrease predictive certainty, leading... (More)
© 2017 The Authors Using a concurrent ERP/fMRI paradigm, we investigated how listeners take advantage of morphologically relevant tonal information at the beginning of words to predict and pre-activate likely word endings. More predictive, low tone word stems gave rise to a ‘pre-activation negativity’ (PrAN) in the ERPs, a brain potential which has previously been found to increase along with the degree of predictive certainty as regards how a word is going to end. It is suggested that more predictive, low tone stems lead to rapid access to word endings with processing subserved by the left primary auditory cortex as well as the supramarginal gyrus, while high tone stems – which are less predictive – decrease predictive certainty, leading to increased competition between activated word endings, which needs to be resolved by the left inferior frontal gyrus. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
ERP, fMRI, Morphology, Pre-activation, Prosody, Word tone
in
Brain and Language
volume
174
pages
8 pages
publisher
Academic Press
external identifiers
  • scopus:85028361667
ISSN
0093-934X
DOI
10.1016/j.bandl.2017.08.004
language
English
LU publication?
yes
id
b09212d1-1a0f-43a5-8ea1-c02d2c2b46be
date added to LUP
2017-09-05 13:36:51
date last changed
2017-09-05 14:02:25
@article{b09212d1-1a0f-43a5-8ea1-c02d2c2b46be,
  abstract     = {© 2017 The Authors Using a concurrent ERP/fMRI paradigm, we investigated how listeners take advantage of morphologically relevant tonal information at the beginning of words to predict and pre-activate likely word endings.  More predictive, low tone word stems gave rise to a ‘pre-activation negativity’ (PrAN) in the ERPs, a brain potential which has previously been found to increase along with the degree of predictive certainty as regards how a word is going to end. It is suggested that more predictive, low tone stems lead to rapid access to word endings with processing subserved by the left primary auditory cortex as well as the supramarginal gyrus, while high tone stems – which are less predictive – decrease predictive certainty, leading to increased competition between activated word endings, which needs to be resolved by the left inferior frontal gyrus.},
  author       = {Söderström, Pelle and Horne, Merle and Mannfolk, Peter and van Westen, Danielle and Roll, Mikael},
  issn         = {0093-934X},
  keyword      = {ERP,fMRI,Morphology,Pre-activation,Prosody,Word tone},
  language     = {eng},
  month        = {11},
  pages        = {119--126},
  publisher    = {Academic Press},
  series       = {Brain and Language},
  title        = {Tone-grammar association within words: Concurrent ERP and fMRI show rapid neural pre-activation and involvement of left inferior frontal gyrus in pseudoword processing},
  url          = {http://dx.doi.org/10.1016/j.bandl.2017.08.004},
  volume       = {174},
  year         = {2017},
}