Neural correlates of verb argument structure characteristics
Svetlana Malyutina ([email protected]) & Dirk-Bart den Ouden
(Department of Communication Sciences and Disorders, University of South Carolina)
Introduction
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•
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fMRI results: whole-brain analysis
Verbs are central to language production and comprehension,
determining sentence structure (Anna gave a book to her son)
People with aphasia have difficulty producing verbs (Bastiaanse & van
Zonneveld, 2004); more complex verb argument structure (VAS) parameters
render verb processing more difficult for both people with aphasia and
healthy controls (Kegl, 1995; Kim & Thompson, 2000; Thompson, 2003)
However, investigations of the neural correlates of VAS processing/
representation have mostly focused on one VAS characteristic:
o Number of arguments:
John runs (1 arg = intransitive) vs. John reads a book (2 args = transitive) vs. John
gives a gift to his son (3 args = ditransitive)
- (den Ouden et al., 2009): left supramarginal and angular gyri, Broca’s area;
(Thompson et al., 2010): left angular gyrus; etc.
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Fig. 1
• Greater complexity (break-verbs > sing-verbs):
Left cingulum, WM underlying pars orbitalis and triangularis of IFG (Fig. 2, red)
• Lower complexity (sing-verbs > break-verbs):
Right angular gyrus (Fig. 2, green)
Max number of
arguments
Nr of number-ofargument options
Nr of thematic
options
Nr of
subcategorization
options
2
1
1
1
The buyer demanded a refund;
The guard concealed the weapon
2
1
1
≥2
sing-verbs
The choir sang a carol;
The suspect obeyed the orders
2
2
1
(≥2, across frames)
break-verbs
The thief broke the lock;
The rain worsened the situation
2
2
2
(≥2, across frames)
complete-verbs The user completed the survey;
Task:
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Sentences balanced for linguistic frequency, length, imageability, animacy
Sentences (see examples in the table) presented for 3 sec
Judging the well-formedness of sentences; pressing a button only for fillers (semantically
and syntactically non-well-formed sentences: e.g., The group arrived the village, The
experiment hated the flowers)
Experiment 1: fMRI
The army abandoned the city
demand-verbs
Fig. 3
Methods (cont.)
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(3) Number of number-of-argument options: lower ling complexity ~ greater
processing load (complete-verbs slower than sing-verbs, p = .002)
Two investigated verb argument structure parameters beyond the number of
arguments contribute to processing load:
o Number of subcategorization options
• Greater complexity (sing-verbs > complete-verbs):
No significant activation
• Lower complexity (complete-verbs > sing-verbs):
Left SFG (Fig. 3)
(break-verbs slower, p = .004, and, as a trend, less accurate, p = .094, than sing-verbs)
Discussion & Future Directions
(3) Number of number-of-argument options
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(1) Number of subcategorization options: no significant effects
(2) Number of thematic options: greater ling complexity ~ greater processing load
(2) Number of thematic options
o Number of number-of-argument options:
Sentence examples
Significant comparisons
n/s
n/s
↑ for greater subcategorization options complexity (p = .005)
↑ for greater subcategorization options complexity (p = .001)
n/s
↑ for greater subcategorization options complexity (p = .094)
n/s
Selection of integration vs. storage retrieval ROIs was based on (Bookheimer, 2002; Gold & Buckner, 2002; Binder et al., 2009;
Meyer et al., 2012; Thompson & Meltzer-Asscher, 2014)
Fig. 2
John ran (agent) vs. John fell (patient)
- (Meltzer-Asscher et al., 2015): LIFG, precentral gyrus fore more complex verbs
Verb group
ROI
Pars triangularis of LIFG
Pars opercularis of LIFG
Pars orbitalis of LIFG
LpMTG
LpSTG
L angular gyrus
L supramarginal gyrus
Behavioral results
o Thematic options:
Methods
• Greater complexity
(demand-verbs > complete-verbs):
Left SFG, MTG, temporo-parietal junction (Fig. 1)
• Lower complexity:
(complete-verbs > demand-verbs):
No significant activation
John completed the task (1 SO) vs. John ordered a pizza / John ordered that they
leave (2 SO’s)
- (Shetreet et al., 2007): left STG, IFG for more complex verbs
Research questions:
(1) Do these parameters contribute to processing load, reflected in
increased regional BOLD signal measured with fMRI?
(2) If yes, what is the nature of the processing load they place?
- Semantic storage/retrieval vs. semantic integration
Function
Semantic
integration
Semantic
storage/retrieval
1) Number of subcategorization options:
Our goal is to investigate three less extensively studied VAS parameters:
o Number of subcategorization options:
John smiles (only one option: use with one argument) vs. John reads / John reads
a book (two options: use with one argument or two arguments)
- (Meltzer-Asscher et al., 2015): no specific brain activation
fMRI results: ROI analysis
17 healthy right-handed volunteers (mean age 23.4, SD 2.8 years; 10 females)
3T Siemens MRI scanner; multi-band sequence (TR = 1550 ms, TE = 34 ms)
Event-related design; 40 sentences per condition; 4 runs of ~7.5 seconds
Analysis in SPM8:
o Preprocessing: slice timing correction, motion correction, co-registration, segmentationbased normalization, smoothing (8 mm FWHM)
o GLM (paired t-tests):
• Number of subcategorization options: demand-verbs > complete-verbs
• Number of thematic options: break-verbs > sing-verbs
• Number of number-of-argument options: sing-verbs > complete-verbs
o Multiple comparison correction: cluster threshold determined with AlphaSim (17 voxels
for α = .05)
o Labeling of activation using AAL toolbox for SPM
• VAS complexity effect found (at the neural level); activation location consistent with
(Shetreet et al., 2007)
• The processing load likely pertains to semantic storage/retrieval
o Number of thematic options
• VAS complexity effect found (at the neural and behav level); activation location
consistent with (Meltzer-Asscher et al., 2015)
• The processing load likely pertains to semantic integration
• However, there was also neural recruitment (right AG) specific to less complex verbs:
less “robust” lexical representations?
For one parameter, there was no evidence of greater complexity being
associated with increased processing load:
o Number of number-of-argument options
• No VAS complexity effect found; consistent with (Meltzer-Asscher et al., 2015)
• In contrasts, we found poorer behavioral performance and additional neural
recruitment for less complex verbs: less “robust” lexical representations?
Further research:
o Single-word level (as opposed to sentence-level) processing:
• Sentence task is affected by grammatical and semantic integration & prediction
demands, whereas single-word level tasks may isolate lexical characteristics
o Potential implications for aphasia treatment:
• Characterizing verbs on complexity for complexity-based behavioral treatments;
• Determining potential targets for brain stimulation treatments
Experiment 2: behavioral
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20 healthy right-handed volunteers (mean age 22.4, SD 3.2 years; 14 females)
Planned paired t-tests performed on RT and log-transformed accuracy
References: References available upon request. Acknowledgements: The study was supported by
SPARC Graduate Research Grant of the Office of the Vice President for Research of the University of
South Carolina. The authors would like to thank Brett Bankson for his help with stimuli development.