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Stimuli by task ANOVA analyses within all stimuli-related clusters. 

Stimuli by task ANOVA analyses within all stimuli-related clusters. 

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... 1). The five components explained 15.41% of the variance in the data. The five components contained in total 31 discrete clusters distributing over the bilateral temporal and frontal regions. These clusters were used as ROIs to further examine response patterns in different regions with regard to intelligibility and task demands. As shown in Fig. 1, a large cluster in the left lateral temporal cortex and two clusters in the bilateral insular lobe showed a significant main effect of stimulus, indicating their sensitivities to sentence intelligibility (normal sentences > time-reversed sentences) in both passive and active tasks. In the bilateral superior temporal gyri including ...
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... After two EPI scans, a high-resolution 3-dimension anatomical image was acquired using MPRAGE sequence in axial plane with the following parameters: TR = 2.53 s, TE = 3.45 ms, FA = 7 ◦ , matrix size = 256 × 256, voxel size = 1 × 1 × 1 mm 3 . During the scanning, the auditory stimuli were presented binaurally via MRI-compatible headphone SereneSound (Resonance Technology Inc., Northridge, CA, USA), which reduced the background scanner noise to about 70 dB. A short pre-test scanning was administered to ensure that participants could hear the sentences clearly and the sound volume was adjusted to a comfortable level for each participant. Functional image preprocessing was conducted using the AFNI software package [4], including the correction for slice timing and head motion, alignment between functional images and struc- tural images, normalization, spatial smoothing and scaling. In order to increase the signal to noise ratio, the passive task run and active task run were concatenated together for each participant, and an average concatenated time series was calculated across all participants as the input data for the following ICA analysis. A participant-average cortical surface model was created by using Freesurfer for display and reference [5,6]. Probabilistic independent component analysis was carried out using MELODIC (Multivariate Exploratory Linear Decomposition into Independent Components) Version 3.10, part of FSL (FMRIB’s Software Library, www.fmrib.ox.ac.uk/fsl) [2]. The ICA procedure resulted in 28 independent components across the whole brain gray matter regions, each containing a temporal mode representing its temporally dynamic changes (time series) and a spatial mode which consisted of voxels having the representative time courses in its temporal mode. In order to identify the independent component activities related to the stimuli, simple correlation analyses were conducted between every temporal mode of all the 28 ICs and every ideal time series of all types of stimuli was convolved with a hypothetical hemodynamic response function. Only independent components significantly correlated ( p < 10 − 5 ) with any type of stimuli were considered as the stimuli-related components. Mean- while, the spatially discrete cortical regions were identified in the spatial map of each significantly temporally-correlated component by thresholding the amplitude of spatial map Z-score (the proba- bility of representing its temporal mode in that spatial map) at a voxel-wise threshold ( Z > 3.72, p < 10 − 4 ), corrected at cluster-wise extent (voxel size > 20, 2 × 2 × 2 mm, p < 0.005 corrected) [19,31]. These spatially discrete regions were then used as masks to extract regression coefficient for each stimulus condition from traditional individual GLM analysis. In order to analyze the effects of stimulus and task within the ROIs identified by the ICA method, repeated-measure ANOVAs were conducted on the regression coefficients with stimulus and task as fixed factors and participant as a random factor. Regres- sion coefficients were estimated using standard GLM in AFNI. Two regressors of interest for each sentence condition (normal sentence and time-reversed sentence), as well as six regressors from head motion parameters and one regressor from responses in the active task run, were modeled in GLM. The regression coefficients (beta values) of each sentence condition for every task were obtained from individual GLM analysis. A strict significance threshold ( p < 0.01) for any main effect or interaction was used to control for Type I error due to the multiple tests. In order to examine whether functional specialization of the sub-areas in the left lateral temporal cortex is modulated by tasks, the anatomical parcellation masks from Freesurfer [7] were applied in creating the sub-ROIs. Then the differences in intelligibility contrast coefficients were calculated for each sub-ROI between the passive and active tasks. For the active task runs, behavioral responses of all the participants approached ceiling-level performance (mean accu- racy = 99%), indicating that the participants maintained vigilance during the task and that the anomaly detection paradigm successfully directed participants’ attention to semantic integration of the sentences. Of the twenty-eight independent components decomposed by ICA analysis, five components were identified as stimulus- related (significantly correlated with any type of sentences), which was confirmed by t -tests on simple correlations between time modes of components and hemodynamic response function for different stimulus models (see Table 1). The five components explained 15.41% of the variance in the data. The five components contained in total 31 discrete clusters dis- tributing over the bilateral temporal and frontal regions. These clusters were used as ROIs to further examine response patterns in different regions with regard to intelligibility and task demands. As shown in Fig. 1, a large cluster in the left lateral temporal cortex and two clusters in the bilateral insular lobe showed a significant main effect of stimulus, indicating their sensitivities to sentence intelligibility (normal sentences > time-reversed sentences) in both passive and active tasks. In the bilateral superior temporal gyri including Heschl’s gyri, there was only a significant stimulus by task interaction effect with time-reversed sentences eliciting stronger activation than normal sentences in the passive task and an oppo- site pattern of activation in the active task. A cluster in the dorsal part of the left inferior frontal cortex showed a significant main effect of task (active > passive) and stimulus by task interaction with normal sentences eliciting stronger activation than time-reversed sentences only in the active task. Unlike the dorsal activation pattern, a cluster in the ventral part of the left inferior frontal cortex and two clusters near the medial superior frontal region had a significant main effect of stimulus (normal sentences > time-reversed sentences) and stimulus by task interaction with active task only increasing activation of the normal sentences but not the time- reversed sentences. In a tiny cluster of the left insular cortex, there were only significant stimulus (normal sentences > time-reversed sentences) and task (active > passive) main effects, but no stimulus by task interaction. The cluster in the left lateral temporal cortex was very large covering a wide range of anterior, middle, and posterior temporal regions. In order to find out whether activation patterns of various sub-regions was modulated by task demands during auditory sentence comprehension, we created sub-ROIs by using the left STS mask from Freesurfer anatomical parcellation and anterior- posterior gradient mask along y -axis direction (Talairach standard space) [28], and then tested task by sub-ROIs interaction. The results showed that the sub-ROIs by task interaction was significant ( F (7,133) = 5.38, p < 0.001), indicating that responses to sentence intelligibility in these sub-regions were differentially modulated by passive/active task demands although all the sub-areas in the large cluster discriminate between intelligible and unintelligible sentences. Paired sample t -test further revealed that task-modulated intelligibility effect was only observed in the middle parts ( y coordinates of the sub-ROIs: − 0.5 ≤ y ≤ − 40.5; t (19) ≥ 2.564, p < 0.05), but not in either the anterior or posterior parts of the left lateral temporal cortex (anterior part, y = 9.5; t (19) = 1.598, p > 0.1; posterior parts, y = − 50.5, − 60.5; t (19) = 1.054, 0.947, p > 0.3) Fig. 2. Although multiple methodological approaches have identified the left lateral temporal cortex as one of the most important areas responsible for sentence-level speech comprehension, there remain substantial disagreements in the literature with respect to the precise functions of its sub-regions [1,12,13,23,25,30]. Specif- ically, it is unclear whether and how functions of the various sub-regions are modulated by passive/active task demands during auditory sentence comprehension. To address this issue, we combined ICA and GLM analyses of fMRI data to elucidate the sub- areas of the left lateral temporal cortex respectively involved in the passive and active processing of sentence intelligibility. Consistent with previous research, a large cluster of the left lateral temporal cortex but not the primary auditory cortex showed greater activity for intelligible relative to unintelligible sentences, reflecting its critical role in sentence comprehension. Further analyses revealed that the anterior and posterior sub-regions of the left lateral temporal cortex were equally activated during both passive and active comprehension, whereas the middle sub-regions were only activated during the active task. These findings indicate that the anterior- middle-posterior sub-areas of the left lateral temporal cortex are differentially affected by passive and active task demands during sentence comprehension. Previous studies have provided evidence implicating functional separation between the anterior and posterior sub-regions of the left lateral temporal cortex in speech intelligibility. Evidence from semantic dementia has led some researchers to emphasize the role of the anterior regions in word-level semantic processes [25,27], while other researchers have highlighted the role of posterior regions for storage of lexical representations based on functional imaging data [12,22]. Moreover, the anterior regions have been found to contribute to combinatorial semantic and syntactic com- putations because the anterior but not the posterior areas are more active when listening to sentences than to word lists and pseu- doword sentences [9,14]. While many studies have examined the anterior and posterior sub-regions, few have investigated the functional role(s) of the ...

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... Compared with the typical GLM approach ( Friston et al., 1994 ), the ICA technique has been found to detect more robust spatial maps with the advantage of not requiring prior assumptions of activation regions and the spectral distribution ( McKeown et al., 1998 ;Tie et al., 2008 ;Xu et al., 2013 ;Calhoun et al., 2001Calhoun et al., , 2008. Several identified functional networks present in healthy subjects at the resting state have been found to be modulated by language tasks such as picture naming, word generation/comprehension, semantic decision and visual/auditory sentence comprehension Karunanayaka et al., 2011 ;Tie et al., 2008 ;Ye et al., 2014 ;Zhang et al., 2015 ). In this study, we explored both the spatial and temporal information obtained from the ICA components to investigate the network dynamics related to syntactic complexity. ...
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The research on the neural correlates underlying the language system has gradually moved away from the traditional Broca-Wernicke framework to a network perspective in the past 15 years. Language processing is found to be supported by the co-activation of both core and peripheral brain regions. However, the dynamic co-activation patterns of these brain regions serving different language functions remain to be fully revealed. The present functional magnetic resonance imaging (fMRI) study focused on sentence processing at different syntactic complexity levels to examine how the co-activation of different brain networks will be modulated by increased processing costs. Chinese relative clauses were used to probe the two dimensions of syntactic complexity: embeddedness (left-branching vs. center-embedded) and gap-filler dependency (subject-gap vs. object-gap) using the general linear model (GLM) approach, independent component analysis (ICA) and graph theoretical analysis. In contrast to localized activation revealed by the GLM approach, ICA identified more extensive networks both positively and negatively correlated with the task. We found that the posterior default mode network was anti-correlated to the gap-filler integration costs with increased deactivation for the left-branching object relative clauses compared to subject relative clauses, suggesting the involvement of this network in leveraging the cognitive resources based on the complexity level of the language task. Concurrent activation and deactivation of networks were found to be associated with the higher costs induced by center-embedding and its interaction with gap-filler integration. The graph theoretical analysis further unveiled that center-embeddedness imposed more attentional demand on the subject relative clause, as characterized by its higher degree and strength in the ventral attention network, and higher processing costs of syntactic reanalysis on the object relative clause, as characterized by increased intermodular connections of the language network with other networks. The results suggest that network activation and deactivation profiles are modulated by different dimensions of syntactic complexity to serve the higher demand of creating a coherent semantic representation.
... Brain structures whose normal functioning in healthy right-handed people is critical for one or another speech function (so-called nuclear zones) are traditionally identifi ed as the anterior speech zone of Broca (the triangular and opercular part of the inferior frontal gyrus) and the posterior speech zone of Wernicke (the posterior third of the superior temporal gyrus, the angular and supramarginal gyri) of the dominant hemisphere [16,17]. fMRI results have yielded convincing evidence that the cerebral cortex in adult humans can undergo signifi cant functional reorganization during the processing of various speech stimuli [18][19][20]. In addition, the pattern of activation of the left frontal and temporal-parietal areas on speech stimulus has a distribution similar to that of the classical Wernicke-Geschwind model of speech activity [21]. ...
... Experimental cognitive tasks associated with syntactic, semantic, and phonological analysis of speech activate large territories of the brain: the cerebral cortex, subcortical structures, and the cerebellar hemispheres [19,20,26,27]. Most fMRI studies have provided evidence that presentation of these cognitive tasks produces elevated activity in the classical dominant "nuclear" speech zones and low activity in their subdominant homologs, and bilateral activation of the supramarginal and angular gyri and the cerebellum is generally seen [18][19][20][26][27][28][29]. fMRI data show that speech stimuli, in contrast to nonspeech stimuli, evoke specifi c activation of the superior temporal gyri of both hemispheres [30]. ...
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... The ILF connects the posterior temporal lobe with anterior temporal cortex, which has been implicated in both semantic (30) and syntactic processing (40). Evidence from fMRI studies of healthy participants has indicated that auditory sentence comprehension simultaneously activates both posterior and anterior temporal regions (41), implying involvement of anterior/ posterior connections via the ILF. However, the exact nature of the processing supported by the ILF remains unclear. ...
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... Экспериментальные когнитивные задачи, связанные с синтаксическим, семантическим и фонологическим анализом речи, активируют большие территории мозга: кору больших полушарий, подкорковые структуры и полушария мозжечка [19,20,26,27]. Большинство фМРТ-исследований свидетельствует, что при предъявлении этих когнитивных задач отмечаются высокая активность классических доминантных, «ядерных» речевых зон и низкая активность их субдоминантных гомологов, при этом, как правило, наблюдается билатеральная активация надкраевой и угловой извилин и мозжечка [18][19][20][26][27][28][29]. По данным фМРТ, речевые стимулы, в отличие от неречевых, вызывают специфическую активацию верхней височной извилины обоих полушарий [30]. ...
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The introduction of non-invasive functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), in the practice of scientific and clinical research can increase our knowledge about the organization of cognitive processes, including language, in normal and reorganization of these cognitive functions in post-stroke aphasia. The article discusses the results of fMRI studies of functional organization of the cortex of a healthy adult’s brain in the processing of various voice information as well as the main types of speech reorganization after post-stroke aphasia in different stroke periods. The concepts of «effective» and «ineffective» brain plasticity in post-stroke aphasia were considered. It was concluded that there was an urgent need for further comprehensive studies, including neuropsychological testing and several complementary methods of functional neuroimaging, to develop a phased treatment plan and neurorehabilitation of patients with post-stroke aphasia.
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