Individual differences in the language task-evoked and resting-state functional networks
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PROVIDER: S-EPMC10656779 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:The resting brain exhibits coherent patterns of spontaneous low-frequency BOLD fluctuations. These so-called resting-state functional connectivity (RSFC) networks are posited to reflect intrinsic representations of functional systems commonly implicated in cognitive function. Yet, the direct relationship between RSFC and the BOLD response induced by task performance remains unclear. Here we examine the relationship between a region's pattern of RSFC across participants and that same region's level of BOLD activation during an Eriksen Flanker task. To achieve this goal we employed a voxel-matched regression method, which assessed whether the magnitude of task-induced activity at each brain voxel could be predicted by measures of RSFC strength for the same voxel, across 26 healthy adults. We examined relationships between task-induced activation and RSFC strength for six different seed regions [Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E., 2005. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U. S. A. 102, 9673-9678.], as well as the "default mode" and "task-positive" resting-state networks in their entirety. Our results indicate that, for a number of brain regions, inter-individual differences in task-induced BOLD activity were predicted by one of two resting-state properties: (1) the region's positive connectivity strength with the task-positive network, or (2) its negative connectivity with the default mode network. Strikingly, most of the regions exhibiting a significant relationship between their RSFC properties and task-induced BOLD activity were located in transition zones between the default mode and task-positive networks. These results suggest that a common mechanism governs many brain regions' neural activity during rest and its neural activity during task performance.
| S-EPMC2839004 | biostudies-literature
Project description:Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.
| S-EPMC6462481 | biostudies-literature
Project description: Not available
| S-EPMC10933828 | biostudies-literature
Project description:ObjectivesApplication of fMRI connectivity metrics as diagnostic biomarkers at the individual level will require reliability, sensitivity and specificity to longitudinal changes in development, aging, neurocognitive, and behavioral performance and pathologies. Such metrics have not been well characterized for recent advances in BOLD acquisition.Experimental designAnalysis of multiband BOLD data from the HCP 500 Subjects Release was performed with FIX ICA and with WM, CSF and motion parameter regression. Analysis with ROIs covering the gray matter at 5 mm resolution was performed to assess functional connectivity. ROIs in key areas were used to demonstrate statistical differences between specific connections. Reproducibility of group-mean functional connectivity and for single connections for individuals was evaluated for both resting state and task acquisitions.Principal observationsSystematic differences in group-mean connectivity were demonstrated during task and rest and during different tasks, although individual differences in connectivity were maintained. Reproducibility of a single connection for a subject and across subjects for resting and task acquisition was demonstrated to be a linear function of the square root of imaging time. Randomly removing up to 50% of time points had little effect on reliability, while truncating an acquisition was associated with decreased reliability. Reliability was highest within the cortex, and lowest for deep gray nuclei, gray-white junction, and near large sulci.ConclusionsThis study found systematic differences in group-mean connectivity acquired during task and rest acquitisions and preserved individual differences in connectivity due to intrinsic differences in an individual's brain activity and structural brain architecture. We also show that longer scan times are needed to acquire data on single subjects for information on connections between specific ROIs. Longer scans may be facilitated by acquisition during task paradigms, which will systematically affect functional connectivity but may preserve individual differences in connectivity on top of task modulations.
| S-EPMC4814225 | biostudies-literature
Project description:When performing cognitively demanding tasks, people tend to experience momentary distractions or personal associations that intercept their stream of consciousness. This phenomenon is known as Mind Wandering (MW) and it has become a subject of neuroscientific investigations. Off-task thoughts can be analyzed during task performance, but currently, MW is also understood as a dimension of individual differences in cognitive processing. We wanted to recognize the intrinsically-organized functional networks that could be considered the neuronal basis for MW dispositional variability. To achieve this goal we recruited a group of normal adults, and eventually divided the group in half, based on participants’ scores on the scale measuring dispositional MW. Next, these groups were compared regarding the arrangement of preselected intrinsic functional networks, which were reconstructed based on multi-channel signal-source resting-state EEG. It appeared that subjects who tend to mind wander often exhibited decreased synchronization within the default mode network, and, simultaneously, strengthened connectivity between ‘on-task’ networks of diverse functional specificity. Such within- and between networks integrity patterns might suggest that greater Mind Wanderers present an atypical organization of resting-state brain activity, which may translate into attenuated resources needed to maintain attentional control in task-related conditions.
| S-EPMC9731960 | biostudies-literature
Project description:BackgroundUse of functional MRI (fMRI) in pre-surgical planning is a non-invasive method for pre-operative functional mapping for patients with brain tumors, especially tumors located near eloquent cortex. Currently, this practice predominantly involves task-based fMRI (T-fMRI). Resting state fMRI (RS-fMRI) offers an alternative with several methodological advantages. Here, we compare group-level analyses of RS-fMRI vs. T-fMRI as methods for language localization.PurposeTo contrast RS-fMRI vs. T-fMRI as techniques for localization of language function.MethodsWe analyzed data obtained in 35 patients who had both T-fMRI and RS-fMRI scans during the course of pre-surgical evaluation. The RS-fMRI data were analyzed using a previously trained resting-state network classifier. The T-fMRI data were analyzed using conventional techniques. Group-level results obtained by both methods were evaluated in terms of two outcome measures: (1) inter-subject variability of response magnitude and (2) sensitivity/specificity analysis of response topography, taking as ground truth previously reported maps of the language system based on intraoperative cortical mapping as well as meta-analytic maps of language task fMRI responses.ResultsBoth fMRI methods localized major components of the language system (areas of Broca and Wernicke) although not with equal inter-subject consistency. Word-stem completion T-fMRI strongly activated Broca's area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system.ConclusionWe demonstrate several advantages of classifier-based mapping of language representation in the brain. Language T-fMRI activated task-general (i.e., not language-specific) functional systems in addition to areas of Broca and Wernicke. In contrast, classifier-based analysis of RS-fMRI data generated maps confined to language-specific regions of the brain.
| S-EPMC7394427 | biostudies-literature
Project description:A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success.
| S-EPMC4777637 | biostudies-literature
Project description:Studies on functional brain lateralization using functional magnetic resonance imaging (fMRI) have generally focused on lateralization of local brain regions. To explore the lateralization on the whole-brain level, lateralization of functional connectivity using resting-state fMRI (N=87, right handed) was analyzed and left- and right-lateralized networks were mapped. Four hundred two equally spaced regions of interest (ROI) covering the entire gray matter were divided into 358 task-positive and 44 task-negative ROIs. Lateralization of functional connectivity was analyzed separately for the task-positive and task-negative regions to prevent spuriously high lateralization indices caused by negative correlations between task-positive and task-negative regions. Lateralized functional connections were obtained using k-means clustering analysis. Within the task-positive network, the right-lateralized functional connections were between the occipital and inferior/middle frontal regions among other connections, whereas the left-lateralized functional connections were among fusiform gyrus and inferior frontal and inferior/superior parietal regions. Within the task-negative network, the left-lateralized connections were mainly between the precuneus and medial prefrontal regions. Specific brain regions exhibited different left- or right-lateralized connections with other regions, which suggest the importance of reporting lateralized connections over lateralized seed regions. The mean lateralization indices of the left- and right-lateralized connections were correlated, suggesting that the lateralization of connectivity may result from complementary processes between the lateralized networks. The potential functions of the lateralized networks were discussed.
| S-EPMC4238260 | biostudies-literature
Project description:ImportanceAnhedonia can present in children and predict detrimental clinical outcomes.ObjectiveTo map anhedonia in children onto changes in intrinsic large-scale connectivity and task-evoked activation and to probe the specificity of these changes in anhedonia against other clinical phenotypes (low mood, anxiety, and attention-deficit/hyperactivity disorder [ADHD]).Design, setting, and participantsFunctional magnetic resonance imaging (fMRI) data were from the first annual release of the Adolescent Brain Cognitive Development study, collected between September 2016 and September 2017 and analyzed between April and September 2018. Cross-sectional data of children aged 9 to 10 years from unreferred, community samples during rest (n?=?2878) and during reward anticipation (n?=?2874) and working memory (n?=?2745) were analyzed.Main outcomes and measuresAlterations in fMRI data during rest, reward anticipation, and working memory were examined, using both frequentist and Bayesian approaches. Functional MRI connectivity within large-scale networks, between networks, and between networks and subcortical regions were examined during rest. Functional MRI activation were examined during reward anticipation and working memory using the monetary incentive delayed and N-back tasks, respectively.ResultsAmong 2878 children with adequate-quality resting-state fMRI data (mean [SD] age, 10.03 [0.62] years; 1400 girls [48.6%]), children with anhedonia (261 [9.1%]), compared with those without anhedonia (2617 [90.9%]), showed hypoconnectivity among various large-scale networks and subcortical regions, including between the arousal-related cingulo-opercular network and reward-related ventral striatum area (mean [SD] with anhedonia, 0.08 [0.10] vs without anhedonia,?0.10 [0.10]; t2,876?=?3.33; P?<?.001; q[false discovery rate]?=?0.03; ln[Bayes factor10]?=?2.85). Such hypoconnectivity did not manifest among children with low mood (277 of 2878 [9.62%]), anxiety (109 of 2878 [3.79%]), or ADHD (459 of 2878 [15.95%]), suggesting specificity. Similarly, among 2874 children (mean [SD] age, 10.03 [0.62] years; 1414 girls?[49.2%]) with high-quality task-evoked fMRI data, children with anhedonia (248 of 2874 [8.63%]) demonstrated hypoactivation during reward anticipation in various areas, including the dorsal striatum and areas of the cingulo-opercular network. This hypoactivity was not found among children with low mood (268 of 2874 [9.32%]), anxiety (90 of 2874 [3.13%]), or ADHD (473 of 2874 [16.46%]). Moreover, we also found context- and phenotype-specific double dissociations; while children with anhedonia showed altered activation during reward anticipation (but not working memory), those with ADHD showed altered activation during working memory (but not reward anticipation).Conclusions and relevanceUsing the Adolescent Brain Cognitive Development study data set, phenotype-specific alterations were found in intrinsic large-scale connectivity and task-evoked activation in children with anhedonia. The hypoconnectivity at rest and hypoactivation during reward anticipation complementarily map anhedonia onto aberrations in neural-cognitive processes: lack of intrinsic reward-arousal integration during rest and diminishment of extrinsic reward-arousal activity during reward anticipation. These findings help delineate the pathophysiological underpinnings of anhedonia in children.
| S-EPMC6552295 | biostudies-literature
Project description:We compared resting state (RS) functional connectivity and task-based fMRI to lateralize language dominance in 30 epilepsy patients (mean age = 33; SD = 11; 12 female), a measure used for presurgical planning. Language laterality index (LI) was calculated from task fMRI in frontal, temporal, and frontal + temporal regional masks using LI bootstrap method from SPM12. RS language LI was assessed using two novel methods of calculating RS language LI from bilateral Broca's area seed based connectivity maps across regional masks and multiple thresholds (p < .05, p < .01, p < .001, top 10% connections). We compared LI from task and RS fMRI continuous values and dominance classifications. We found significant positive correlations between task LI and RS LI when functional connectivity thresholds were set to the top 10% of connections. Concordance of dominance classifications ranged from 20% to 30% for the intrahemispheric resting state LI method and 50% to 63% for the resting state LI intra- minus interhemispheric difference method. Approximately 40% of patients left dominant on task showed RS bilateral dominance. There was no difference in LI concordance between patients with right-sided and left-sided resections. Early seizure onset (<6 years old) was not associated with atypical language dominance during task-based or RS fMRI. While a relationship between task LI and RS LI exists in patients with epilepsy, language dominance is less lateralized on RS than task fMRI. Concordance of language dominance classifications between task and resting state fMRI depends on brain regions surveyed and RS LI calculation method.
| S-EPMC7336139 | biostudies-literature