Abstract:The functional organization of the perisylvian language network was examined using a functional MRI (fMRI) adaptation paradigm with spoken sentences. In Experiment 1, a given sentence was presented every 14.4 s and repeated two, three, or four times in a row. The study of the temporal properties of the BOLD response revealed a temporal gradient along the dorsal-ventral and rostral-caudal directions: From Heschl's gyrus, where the fastest responses were recorded, responses became increasingly slower toward the posterior part of the superior temporal gyrus and toward the temporal poles and the left inferior frontal gyrus, where the slowest responses were observed. Repetition induced a decrease in amplitude and a speeding up of the BOLD response in the superior temporal sulcus (STS), while the most superior temporal regions were not affected. In Experiment 2, small blocks of six sentences were presented in which either the speaker voice or the linguistic content of the sentence, or both, were repeated. Data analyses revealed a clear asymmetry: While two clusters in the left superior temporal sulcus showed identical repetition suppression whether the sentences were produced by the same speaker or different speakers, the homologous right regions were sensitive to sentence repetition only when the speaker voice remained constant. Thus, hemispheric left regions encode linguistic content while homologous right regions encode more details about extralinguistic features like speaker voice. The results demonstrate the feasibility of using sentence-level adaptation to probe the functional organization of cortical language areas.
The hippocampus is the brain structure of highest and earliest structural alteration in Alzheimer's disease (AD). New developments in neuroimaging methods recently made it possible to assess the respective involvement of the different hippocampal subfields by mapping atrophy on a 3D hippocampal surface view. In this longitudinal study on patients with mild cognitive impairment (MCI), we used such an approach to map the profile of hippocampal atrophy and its progression over an 18-month follow-up period in rapid converters to AD and "non-converters" compared to age-matched controls. For the sake of comparison, we also assessed the profile of hippocampal atrophy associated with AD and with increasing age in a healthy control population ranging from young adult to elderly. We found major involvement of the lateral part of the superior hippocampus mainly corresponding to the CA1 subfield in MCI and AD while increasing age was mainly associated with subiculum atrophy in the healthy population. Moreover, the CA1 subfield also showed highest atrophy rates during follow-up, in both rapid converters and "non-converters" although increased effects were observed in the former group. This study emphasizes the differences between normal aging and AD processes leading to hippocampal atrophy, pointing to a specific AD-related CA1 involvement while subiculum atrophy would represent a normal aging process. Our findings also suggest that the degree of hippocampal atrophy, more than its spatial localization, predicts rapid conversion to AD in patients with MCI.
Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.
Diffusion tensor imaging can be used in vivo to assess the longitudinal and regional microstructural changes occurring after middle cerebral artery (MCA) infarcts in humans. Nine patients were investigated 1 week (D7), 1 (M1), 3 (M3), and 6 months (M6) after the occurrence of an isolated MCA infarction. First, an overall analysis was performed using histograms of mean diffusivity (MD) and fractional anisotropy (FA) in each hemisphere. Thereafter, the regional pattern of diffusion changes was investigated voxel by voxel with statistical parametric mapping 99. In the hemisphere ipsilateral to the infarction, histogram analysis revealed a significant decrease in FA between D7 and M6 associated with a progressive increase in MD from D7 to M3. Remote from the MCA territory, the voxel by voxel analyses detected a significant increase in MD within the thalamus at M3 and M6 and a reduction in FA along the pyramidal tract at M6. In the contralateral hemisphere, between D7 and M6, a significant hemispheric atrophy was observed in association with a global reduction in anisotropy, in the absence of distinctive regional diffusion changes. These results suggest that micro-and macrostructural tissue modifications can be detected with diffusion tensor imaging in regions remote from the ischemic area in both hemispheres.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.