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Cited by 134Neuroscience and Music PerceptionNeurobiology of Language and BilingualismPhonetics and Phonology Research

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Specialization along the Left Superior Temporal Sulcus for Auditory Categorization

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Liebenthal, Einat, Desai, Rutvik, Ellingson, Michael M., Ramachandran, Brinda, Desai, Anjali, Binder, Jeffrey R.·2010·Cerebral Cortex
DOI 10.1093/cercor/bhq045PMC PMC2978244
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Abstract

The affinity and temporal course of functional fields in middle and posterior superior temporal cortex for the categorization of complex sounds was examined using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) recorded simultaneously. Data were compared before and after subjects were trained to categorize a continuum of unfamiliar nonphonemic auditory patterns with speech-like properties (NP) and a continuum of familiar phonemic patterns (P). fMRI activation for NP increased after training in left posterior superior temporal sulcus (pSTS). The ERP P2 response to NP also increased with training, and its scalp topography was consistent with left posterior superior temporal generators. In contrast, the left middle superior temporal sulcus (mSTS) showed fMRI activation only for P, and this response was not affected by training. The P2 response to P was also independent of training, and its estimated source was more anterior in left superior temporal cortex. Results are consistent with a role for left pSTS in short-term representation of relevant sound features that provide the basis for identifying newly acquired sound categories. Categorization of highly familiar phonemic patterns is mediated by long-term representations in left mSTS. Results provide new insight regarding the function of ventral and dorsal auditory streams.

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Crossref · 10.1093/cercor/bhq045

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Figure 1. Experimental paradigm: Sound stimuli were presented in 4 runs alternating between the phonemic and nonphonemic conditions, in each of the 2 scanning sessions (pre- and posttraining). Image acquisition was clustered to 2 s at 7-s periods. Electroencephalograph was acquired continuously. Sounds were presented during the intervals between image acquisitions.
Figure 1. Experimental paradigm: Sound stimuli were presented in 4 runs alternating between the phonemic and nonphonemic conditions, in each of the 2 scanning sessions (pre- and posttraining). Image acquisition was clustered to 2 s at 7-s periods. Electroencephalograph was acquired continuously. Sounds were presented during the intervals between image acquisitions.CC BY-NC · PubMed Central
Figure 2. (a) Tokenwise categorization and RT curves for the phonemic and nonphonemic continua prior to training (PreP and PreNP, respectively) and following training (PostP and PostNP, respectively). RT was calculated from the onset of the sound. (b) Effect of training on the CI for P and NP.
Figure 2. (a) Tokenwise categorization and RT curves for the phonemic and nonphonemic continua prior to training (PreP and PreNP, respectively) and following training (PostP and PostNP, respectively). RT was calculated from the onset of the sound. (b) Effect of training on the CI for P and NP.CC BY-NC · PubMed Central
Figure 3. Group fMRI contrast maps showing the effects of stimulus type before and after training (a), the effects of training status for P and NP (b), and the interaction between stimulus and training (c), overlaid over an inflated template of the N27 brain. *The interaction map was masked to show only voxels displaying positive activation (P < 0.05) in PostNP–PreNP.
Figure 3. Group fMRI contrast maps showing the effects of stimulus type before and after training (a), the effects of training status for P and NP (b), and the interaction between stimulus and training (c), overlaid over an inflated template of the N27 brain. *The interaction map was masked to show only voxels displaying positive activation (P < 0.05) in PostNP–PreNP.CC BY-NC · PubMed Central
Figure 4. Mean activation relative to baseline in left middle superior temporal sulcus (LmSTS) and left posterior superior temporal sulcus (LpSTS) before (Pre) and after (Post) training to categorize the P and the NP continua.
Figure 4. Mean activation relative to baseline in left middle superior temporal sulcus (LmSTS) and left posterior superior temporal sulcus (LpSTS) before (Pre) and after (Post) training to categorize the P and the NP continua.CC BY-NC · PubMed Central
Figure 5. Binary fMRI conjunction map of areas showing a positive correlation between the level of activation in PostP and the phonemic CIP and a positive correlation between the level of activation in PostNP and the nonphonemic CINP. Both the PostP–CIP and PostNP–CINP correlation maps, which were used to construct the conjunction map, were thresholded at P < 0.05.
Figure 5. Binary fMRI conjunction map of areas showing a positive correlation between the level of activation in PostP and the phonemic CIP and a positive correlation between the level of activation in PostNP and the nonphonemic CINP. Both the PostP–CIP and PostNP–CINP correlation maps, which were used to construct the conjunction map, were thresholded at P < 0.05.CC BY-NC · PubMed Central
Figure 6. Grand-average ERPs (N = 17) at left (FC3), midline (FZ), and right (FC4) frontal electrode sites, during identification of phonemic and nonphonemic tokens before (PreP and PreNP, respectively) and after (PostP and PostNP, respectively) training.
Figure 6. Grand-average ERPs (N = 17) at left (FC3), midline (FZ), and right (FC4) frontal electrode sites, during identification of phonemic and nonphonemic tokens before (PreP and PreNP, respectively) and after (PostP and PostNP, respectively) training.CC BY-NC · PubMed Central
Figure 7. Pointwise t-score maps from 60 electrodes showing the effect of stimulus pretraining (PreP–PreNP; left panel) and the effect of training on nonphonemic categorization (PostNP–PreNP; right panel). The electrodes are grouped according to their anterior–posterior position on the scalp from frontal (top third) to central (middle third) and parieto-occipital (bottom third) sites. Within each group of sites, electrodes are sorted according to their lateral position from left (L, upper half) to right (R, lower half). The midline electrode in each group is also indicated (Fz, Cz, Pz). Maps are thresholded at t-scores corresponding to P < 0.05 sustained for at least 11 consecutive data points (see Materials and Methods for further details).
Figure 7. Pointwise t-score maps from 60 electrodes showing the effect of stimulus pretraining (PreP–PreNP; left panel) and the effect of training on nonphonemic categorization (PostNP–PreNP; right panel). The electrodes are grouped according to their anterior–posterior position on the scalp from frontal (top third) to central (middle third) and parieto-occipital (bottom third) sites. Within each group of sites, electrodes are sorted according to their lateral position from left (L, upper half) to right (R, lower half). The midline electrode in each group is also indicated (Fz, Cz, Pz). Maps are thresholded at t-scores corresponding to P < 0.05 sustained for at least 11 consecutive data points (see Materials and Methods for further details).CC BY-NC · PubMed Central
Figure 8. Current density reconstruction (CDR) of grand-average ERPs in PostP (a) and PostNP (b) at 230 ms, displayed on coronal, sagittal, and axial slices of the MNI ICBM152 template brain (upper quadrants and left lower quadrant) as implemented in Curry 5 (Compumedics Neuroscan). The cursor is positioned near the peak of the activation in the left superior temporal cortex. Bottom right quadrant: CDR shown within the standardized boundary element model volume conductor computed from the template brain (top view, transparent rendering). Activation below 75% of the maximum is clipped.
Figure 8. Current density reconstruction (CDR) of grand-average ERPs in PostP (a) and PostNP (b) at 230 ms, displayed on coronal, sagittal, and axial slices of the MNI ICBM152 template brain (upper quadrants and left lower quadrant) as implemented in Curry 5 (Compumedics Neuroscan). The cursor is positioned near the peak of the activation in the left superior temporal cortex. Bottom right quadrant: CDR shown within the standardized boundary element model volume conductor computed from the template brain (top view, transparent rendering). Activation below 75% of the maximum is clipped.CC BY-NC · PubMed Central

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  1. Ward, 2000, Simultaneous inference for fMRI data

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Metadata

Authors
Liebenthal, E., Desai, R., Ellingson, M. M., Ramachandran, B., Desai, A., & Binder, J. R.
Affiliations
Medical College of Wisconsin (US)
Corresponding author
Liebenthal, Einat
ORCID
Venue
Cerebral Cortex
Publisher
Oxford University Press (OUP)
Published
2010-04-09
Volume
20
Issue
12
Pages
2958-2970
ISSN
  • 1047-3211 (ISSN-L)
  • 1460-2199
DOI
10.1093/cercor/bhq045
PMC
PMC2978244
OpenAlex
W2117381528
Cited by
134
References
91
Citations by year
2026: 2 · 2025: 2 · 2024: 5 · 2023: 5 · 2022: 6 · 2021: 10 · 2020: 12 · 2019: 8 · 2018: 8 · 2017: 6 · 2016: 6 · 2015: 11 · 2014: 14 · 2013: 16 · 2012: 9
FWCI
7.35
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Cerebral Cortex (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Scholar Commons (University of South Carolina) (submittedVersion, cc-by-nc)
Funders
  • National Institute on Deafness and Other Communication Disorders (R01DC006287)
  • National Center for Research Resources (M01-RR00058, M01RR000058)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
Keywords
auditory categorization
MeSH terms
Acoustic Stimulation, Adult, Auditory Perception, Brain Mapping, Cerebral Cortex, Evoked Potentials, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult

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