Intrinsic connectivity networks (ICNs) identified through task-free fMRI (tf-fMRI) offer the opportunity to investigate human brain circuits involved in language processes without requiring participants to perform challenging cognitive tasks. In this study, we assessed the ability of tf-fMRI to isolate reproducible networks critical for specific language functions and often damaged in primary progressive aphasia (PPA). First, we performed whole-brain seed-based correlation analyses on tf-fMRI data to identify ICNs anchored in regions known for articulatory, phonological, and semantic processes in healthy male and female controls (HCs). We then evaluated the reproducibility of these ICNs in an independent cohort of HCs, and recapitulated their functional relevance with a meta-analysis on task-based fMRI. Last, we investigated whether atrophy in these ICNs could inform the differential diagnosis of nonfluent/agrammatic, semantic, and logopenic PPA variants. The identified ICNs included a dorsal articulatory-phonological network involving inferior frontal and supramarginal regions; a ventral semantic network involving anterior middle temporal and angular gyri; a speech perception network involving superior temporal and sensorimotor regions; and a network between posterior inferior temporal and intraparietal regions likely linking visual, phonological, and attentional processes for written language. These ICNs were highly reproducible across independent groups and revealed areas consistent with those emerging from task-based meta-analysis. By comparing ICNs' spatial distribution in HCs with patients' atrophy patterns, we identified ICNs associated with each PPA variant. Our findings demonstrate the potential use of tf-fMRI to investigate the functional status of language networks in patients for whom activation studies can be methodologically challenging. We showed that a single, short, task-free fMRI acquisition is able to identify four reproducible and relatively segregated intrinsic left-dominant networks associated with articulatory, phonological, semantic, and multimodal orthography-to-phonology processes, in HCs. We also showed that these intrinsic networks relate to syndrome-specific atrophy patterns in primary progressive aphasia. Collectively, our results support the application of task-free fMRI in future research to study functionality of language circuits in patients for whom tasked-based activation studies might be methodologically challenging.
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http://dx.doi.org/10.1523/JNEUROSCI.1485-19.2019 | DOI Listing |
Neuron
January 2025
Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Lentzeallee 94, 14195 Berlin, Germany and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, 10-12 Russell Square, London, WC1B 5Eh, UK. Electronic address:
The cognitive neuroscience of human aging seeks to identify neural mechanisms behind the commonalities and individual differences in age-related behavioral changes. This goal has been pursued predominantly through structural or "task-free" resting-state functional neuroimaging. The former has elucidated the material foundations of behavioral decline, and the latter has provided key insight into how functional brain networks change with age.
View Article and Find Full Text PDFSci Rep
December 2024
Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK.
Network energy has been conceptualized based on structural balance theory in the physics of complex networks. We utilized this framework to assess the energy of functional brain networks under cognitive control and to understand how energy is allocated across canonical functional networks during various cognitive control tasks. We extracted network energy from functional connectivity patterns of subjects who underwent fMRI scans during cognitive tasks involving working memory, inhibitory control, and cognitive flexibility, in addition to task-free scans.
View Article and Find Full Text PDFCerebral glucose metabolism (CMRGlc) systematically decreases with advancing age. We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task-free state. We analyzed lifespan resting-state fMRI data acquired in 455 healthy adults (ages 18-87 years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25-45 years, 65-85 years).
View Article and Find Full Text PDFImaging Neurosci (Camb)
October 2024
Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States.
NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve the temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve data quality for rodent fMRI using NORDIC PCA remains uncertain. NORDIC PCA may also be particularly beneficial for improving topological brain mapping, as conventional mapping requires precise spatiotemporal signals from large datasets (ideally ~1 hour acquisition) for individual representations.
View Article and Find Full Text PDFBrain Res
December 2024
Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; University of Science and Technology of China, Hefei 230026, China; Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei 230031, China. Electronic address:
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