New method for fMRI investigations of language: defining ROIs functionally in individual subjects.
Ontology highlight
ABSTRACT:
SUBMITTER: Fedorenko E
PROVIDER: S-EPMC2934923 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:There is significant interest in understanding the pathophysiology of Obsessive-Compulsive Disorder (OCD) using resting-state fMRI (rsfMRI). Previous studies acknowledge abnormalities within and beyond the fronto-striato-limbic circuit in OCD that require further clarifications. However, limited information could be inferred from the conventional way of investigating the functional connectivity differences between OCD and healthy controls. Here, we identified altered brain organization in patients with OCD by applying individual-based approaches to maximize the identification of underlying network-based features specific to the OCD group. rsfMRI of 20 patients with OCD and 22 controls were preprocessed, and individual-fMRI-subspace was derived for each subject within each group. We evaluated group differences in functional connectivity using individual-fMRI-subspace and established its advantage over conventional-fMRI methodology. We applied prediction-based approaches to highlight the group differences by evaluating the differences in functional connections that predicted the clinical scores (namely, the Obsessive-Compulsive Inventory-Revised (OCI-R) and Hamilton Anxiety Rating Scale). Then, we explored the brain network organization of both groups by estimating the subject-specific communities within each group. Lastly, we evaluated associations between the inter-individual variation of nodes in the communities to clinical measures using linear regression. Functional connectivity analysis using individual-fMRI-subspace detected 83 connections that were different between OCD and control groups, compared to none found using conventional-fMRI methodology. Connectome-based prediction analysis did not show significant overlap between the two groups in the functional connections that predicted the clinical scores. This suggests that the functional architecture in patients with OCD may be different compared to controls. Seven communities were found in both groups. Interestingly, within the OCD group but not controls, we observed functional connectivity between cerebellar and visual regions, and lack of connectivity between striato-limbic and frontal areas. Inter-individual variations in the community-size of these two communities were also associated with the OCI-R score (p < .005). Due to our small sample size, we further validated our results by (i) accounting for head motion, (ii) applying global signal regression (GSR) in data processing, and (iii) using an alternate atlas for parcellation. While the main results were consistently observed with accounting for head motion and using another atlas, the key findings were not reproduced with GSR application. The study demonstrated the existence of disconnectedness in fronto-striato-limbic community and connectedness between cerebellar and visual areas in OCD patients, which was also related to the clinical symptomatology of OCD.
| S-EPMC7809273 | biostudies-literature
Project description:The extension of group-level connectivity methods to individual subjects remains a hurdle for statistical analyses of neuroimaging data. Previous group analyses of positron emission tomography data in clinically depressed patients, for example, have shown that resting-state connectivity prior to therapy predicts how patients eventually respond to pharmacological and cognitive-behavioral therapy. Such applications would be considerably more informative for clinical decision making if these connectivity methods could be extended into the individual subject domain. To test such an extension, 46 treatment-naïve depressed patients were enrolled in an fMRI study to model baseline resting-state functional connectivity. Resting-state fMRI scans were acquired and submitted to exploratory structural equation modeling (SEM) to derive the optimal group connectivity model. Jackknife and split sample tests confirm that group model was highly reproducible, and path weights were consistent across the best five group models. When this model was applied to data from individual subjects, 85% of patients fit the group model. Histogram analysis of individual subjects' paths indicate that some paths are better representative of group membership. These results suggest that exploratory SEM is a viable technique for neuroimaging connectivity analyses of individual subjects' resting-state fMRI data.
| S-EPMC2653594 | biostudies-literature
Project description:The assessment of language lateralization has become widely used when planning neurosurgery close to language areas, due to individual specificities and potential influence of brain pathology. Functional magnetic resonance imaging (fMRI) allows non-invasive and quantitative assessment of language lateralization for presurgical planning using a laterality index (LI). However, the conventional method is limited by the dependence of the LI on the chosen activation threshold. To overcome this limitation, different threshold-independent LI calculations have been reported. The purpose of this study was to propose a simplified approach to threshold-independent LI calculation and compare it with three previously reported methods on the same cohort of subjects. Fifteen healthy subjects, who performed picture naming, verb generation, and word fluency tasks, were scanned. LI values were calculated for all subjects using four methods, and considering either the whole hemisphere or an atlas-defined language area. For each method, the subjects were ranked according to the calculated LI values, and the obtained rankings were compared. All LI calculation methods agreed in differentiating strong from weak lateralization on both hemispheric and regional scales (Spearman's correlation coefficients 0.59-1.00). In general, a more lateralized activation was found in the language area than in the whole hemisphere. The new method is well suited for application in the clinical practice as it is simple to implement, fast, and robust. The good agreement between LI calculation methods suggests that the choice of method is not key. Nevertheless, it should be consistent to allow a relative comparison of language lateralization between subjects.
| S-EPMC7067428 | biostudies-literature
Project description:The purpose of this study was to gather opinions from experts via the Delphi method to inform the future development of a virtual reality based English language communication program for university level students in Korea. The participants, who consisted of a panel of experts and professors who majored in English language and multimedia education, completed three Delphi surveys based on Context, Input, Process, and Product evaluation, which is referred to as CIPP. In the first Delphi survey, the participants answered multiple choice questions and open-ended questions related to four areas relevant to the development of a virtual reality based program. Based on their answers, a second Delphi survey was designed to determine the participants' level of agreement with the appropriateness of the questions related to the four areas. In the third Delphi survey, participants were shown the results (mean, standard deviation, median, interquartile range, consensus chart, and convergence degree) and were asked to confirm or modify their answers based on the other participants' answers. According to the analysis of the Delphi survey results, need for the development of a virtual reality based English language communication program was suggested, and recommendations were made regarding the content and application of the program.
| S-EPMC8923470 | biostudies-literature
Project description:Individuals with developmental language impairment can show deficits into adulthood. This suggests that neural networks related to their language do not normalize with time. We examined the ability of 16 adults with and without impaired language to learn individual words in an unfamiliar language. Adults with impaired language were able to segment individual words from running speech, but needed more time to do so than their normal-language peers. ICA analysis of fMRI data indicated that adults with language impairment activate a neural network that is comparable to that of adults with normal language. However, a regional analysis indicated relative hyperactivation of a collection of regions associated with language processing. These results are discussed with reference to the Statistical Learning Framework and the sub-skills thought to relate to word segmentation.
| S-EPMC5295640 | biostudies-literature
Project description:BACKGROUND: Atypical language dominance is common in patients with temporal lobe epilepsy. We examined the association of left temporal hypometabolism with laterality of fMRI activation in a language task in a cross-sectional study. METHODS: Thirty patients with temporal lobe epilepsy (mean age 32.4 ± 11.0 years [range 18-55]; epilepsy onset 15.3 ± 11.3 years [range 0.8-40]; 22 left focus, 8 right focus) had (18)fluoro-deoxyglucose (FDG)-PET using noninvasive cardiac input function. After MRI-based partial volume correction, regional glucose metabolism (CMRglc) was measured and asymmetry index, AI = 2(l - R)/(L + R), calculated. fMRI language dominance was assessed with an auditory definition decision paradigm at 3 T. fMRI data were analyzed in SPM2 using regions of interest from Wake Forest PickAtlas (Wernicke area [WA], inferior frontal gyrus [IFG], middle frontal gyrus [MFG]) and bootstrap laterality index, LI = (l - R/L + R). RESULTS: Nineteen patients had ipsilateral temporal hypometabolism; 3 of 4 patients with atypical language had abnormal FDG-PET. Increasing left midtemporal hypometabolism correlated with decreased MFG LI (r = -0.41, p < 0.05) and showed trends with WA LI (r = -0.37, p = 0.055) and IFG LI (r = -0.31, p = 0.099); these relationships became more significant after controlling for age at onset. Increasing hypometabolism was associated with fewer activated voxels in WA ipsilateral to the focus and more activated voxels contralaterally, but overall, activation amount in left WA was similar to subjects without left temporal hypometabolism (t = -1.39, p > 0.10). CONCLUSIONS: We did not find evidence of impaired blood oxygenation level-dependent response in hypometabolic cortex. Regional hypometabolism appears to be a marker for the temporal lobe dysfunction that leads to displacement of language function.
| S-EPMC3090059 | biostudies-literature
Project description:Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI.
| S-EPMC2819173 | biostudies-literature
Project description:Functional magnetic resonance imaging (fMRI) is widely used in clinical applications to highlight brain areas involved in specific cognitive processes. Brain impairments, such as tumors, suppress the fMRI activation of the anatomical areas they invade and, thus, brain-damaged functional networks present missing links/areas of activation. The identification of the missing circuitry components is of crucial importance to estimate the damage extent. The study of functional networks associated with clinical tasks but performed by healthy individuals becomes, therefore, of paramount concern. These "healthy" networks can, indeed, be used as control networks for clinical studies. In this work we investigate the functional architecture of 20 healthy individuals performing a language task designed for clinical purposes. We unveil a common architecture persistent across all subjects under study, that we call "core" network, which involves Broca's area, Wernicke's area, the premotor area, and the pre-supplementary motor area. We study the connectivity of this circuitry by using the k-core centrality measure, and we find that three of these areas belong to the most robust structure of the functional language network for the specific task under study. Our results provide useful insights on primarily important functional connections.
| S-EPMC7006870 | biostudies-literature
Project description:At the earliest break of ancient hominins from their primate relatives in vocal communication, we propose a selection pressure on vocal fitness signaling by hominin infants. Exploratory vocalizations, not tied to expression of distress or immediate need, could have helped persuade parents of the wellness and viability of the infants who produced them. We hypothesize that hominin parents invested more in infants who produced such signals of fitness plentifully, neglecting or abandoning them less often than infants who produced the sounds less frequently. Selection for such exploratory vocalization provided a critically important inclination and capability relevant to language, we reason, because the system that encouraged spontaneous vocalization also made vocalization functionally flexible to an extent that has not been observed in any other animal. Although this vocal flexibility did not by itself create language, it provided an essential foundation upon which language would evolve through a variety of additional steps. In evaluating this speculation, we consider presumable barriers to evolving language that are thought to be implications of Darwinian Theory. It has been claimed that communication always involves sender self-interest and that self-interest leads to deceit, which is countered through clever detection by receivers. The constant battle of senders and receivers has been thought to pose an insuperable challenge to honest communication, which has been viewed as a requirement of language. To make communication honest, it has been proposed that stable signaling requires costly handicaps for the sender, and since language cannot entail high cost, the reasoning has suggested an insurmountable obstacle to the evolution of language. We think this presumed honesty barrier is an illusion that can be revealed by recognition of the fact that language is not inherently honest and in light of the distinction between illocutionary force and semantics. Our paper also considers barriers to the evolution of language (not having to do with honesty) that we think may have actually played important roles in preventing species other than humans from evolving language.
| S-EPMC7870697 | biostudies-literature
Project description:In terms of its soluble precursors, the coagulation proteome varies quantitatively among apparently healthy individuals. The significance of this variability remains obscure, in part because it is the backdrop against which the hemostatic consequences of more dramatic composition differences are studied. In this study we have defined the consequences of normal range variation of components of the coagulation proteome by using a mechanism-based computational approach that translates coagulation factor concentration data into a representation of an individual's thrombin generation potential. A novel graphical method is used to integrate standard measures that characterize thrombin generation in both empirical and computational models (e.g max rate, max level, total thrombin, time to 2 nM thrombin ("clot time")) to visualize how normal range variation in coagulation factors results in unique thrombin generation phenotypes. Unique ensembles of the 8 coagulation factors encompassing the limits of normal range variation were used as initial conditions for the computational modeling, each ensemble representing "an individual" in a theoretical healthy population. These "individuals" with unremarkable proteome composition was then compared to actual normal and "abnormal" individuals, i.e. factor ensembles measured in apparently healthy individuals, actual coagulopathic individuals or artificially constructed factor ensembles representing individuals with specific factor deficiencies. A sensitivity analysis was performed to rank either individual factors or all possible pairs of factors in terms of their contribution to the overall distribution of thrombin generation phenotypes. Key findings of these analyses include: normal range variation of coagulation factors yields thrombin generation phenotypes indistinguishable from individuals with some, but not all, coagulopathies examined; coordinate variation of certain pairs of factors within their normal ranges disproportionately results in extreme thrombin generation phenotypes, implying that measurement of a smaller set of factors may be sufficient to identify individuals with aberrant thrombin generation potential despite normal coagulation proteome composition.
| S-EPMC3271084 | biostudies-literature