Event Abstract

Back to Event

Is resting state fMRI activity sensitive to the severity of acquired language impairments?

Nicole Dickerson1*, Robert Wiley1, James P. Higgins2, Kristin Grunewald2, David Caplan3, Swathi Kiran4, Todd Parrish2, Richard Zinbarg2, Cynthia K. Thompson2 and Brenda Rapp1
  • 1 Johns Hopkins University, Cognitive Science, United States
  • 2 Northwestern University, United States
  • 3 Harvard Medical School, United States
  • 4 Boston University, United States

Measures that can improve prediction of responsiveness to language therapy for aphasia are of considerable clinical importance. Functional MRI (fMRI) constitutes one potential source of relevant information but strokes often produce comorbidities causing difficulties in using task-based fMRI. In contrast, in resting state fMRI (RS-fMRI) participants have only to remain awake and stationary during scanning, allowing data collection from a wider range of individuals. One measure obtained from RS-fMRI is the Fractional Amplitude of Low Frequency Fluctuations (fALFF). For any given brain region, fALFF is the proportion of the BOLD signal within the low frequency range of .01-.08 Hz (Zou et. al, 2008). We specifically investigated if there are brain areas in which there is a relationship between fALFF values and severity of deficits affecting syntactic processing, spoken naming and spelling. Methods and Results. Sixty-eight individuals, recruited from three laboratories (sites), who suffered language impairment subsequent to a single left-hemisphere stroke received language, cognitive and neuroimaging evaluations both before and after behavioral therapy. Pre-treatment language-domain severity was indexed for syntactic processing, spoken naming and spelling based on: scores from the Northwestern Assessment of Verbs and Sentences (Thompson, 2011), Northwestern Naming Battery (Thompson, & Weintraub, 2014), and PALPA 40 (Lesser & Coltheart, 1992), respectively. For RS-fMRI, 210 3D image volumes were collected, consisting of 41 slices (voxel size 1.7x1.7x3mm), with a TR of 2.4s. FALLF values were computed for each voxel (all lesioned voxels were excluded from analysis). Using Linear mixed effects modelling (LMEM), the dependent variable corresponded to the fALFF values of each voxel from the 96 parcels (ROIs) from the Harvard/Oxford atlas (Desikan et al., 2006). Fixed effects were: site, language-domain severity score, zero voxels, mean surrounding voxel fALFF, age, education, and months post-stroke, and also: site x language-domain severity score and zero voxels x language-domain severity score; random effects were included both by-subjects and by-voxels. The analyses revealed a set of 8 left-lateralized clusters of ROIs that showed a systematic relationship between fALFF and language-domain severity within: left inferior frontal cortex, left superior temporal gyrus, bilateral middle frontal cortex, bilateral posterior MTG, and bilateral occipito-temporal cortex. In most ROIs, greater severity of impairment was associated with lower fALFF values, but the reverse relationship was also observed in certain ROIs. While some regions showed sensitivity to deficit severity for multiple language domains, the neurotopographic distribution of regional sensitivities differed across the language deficit types. Conclusions This research identified brain regions, including areas within the language network and their right hemisphere homologues, in which BOLD response at rest shows sensitivity to language deficit severity. Given the relative feasibility of collecting RS-FMRI, these findings provide important foundations for subsequent evaluations of the role that RS-fMRI might play in the assessment of language deficits and the prediction of response to treatment.

Acknowledgements

Acknowledgements
The research reported here is part of a multi-site NIH-funded P50 project examining the neurobiology of language recovery in people with aphasia (DC 012283). The authors wish to thank Dr. Elena Barbieri for data analysis assistance.

References

References

Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., ... & Albert, M. S. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31(3), 968-980.

Kay, J., Lesser, R., Coltheart, M. (1992). PALPA: Psycholinguistic Assessments of Language Processing in Aphasia. Lawrence Erlbaum Associates, Hove, UK.

Thompson, C.K. (2011). Northwestern Assessment of Verbs and Sentences (NAVS). Evanston, IL, US: Northwestern University, www.flintbox.northwestern.com.

Thompson, C.K., & Weintruab, S. (2014). Northwestern Naming Battery. Evanston, IL, US: Northwestern University, https://northwestern.flintbox.com/public/project/22014/.

Zou, Q. H., Zhu, C. Z., Yang, Y., Zuo, X. N., Long, X. Y., Cao, Q. J., ... & Zang, Y. F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. Journal of neuroscience methods, 172(1), 137-141.

Keywords: resting state, fALFF, dysgraphia, Anomia, agrammatism

Conference: Academy of Aphasia 56th Annual Meeting, Montreal, Canada, 21 Oct - 23 Oct, 2018.

Presentation Type: poster presentation

Topic: Eligible for a student award

Citation: Dickerson N, Wiley R, Higgins JP, Grunewald K, Caplan D, Kiran S, Parrish T, Zinbarg R, Thompson CK and Rapp B (2019). Is resting state fMRI activity sensitive to the severity of acquired language impairments?. Conference Abstract: Academy of Aphasia 56th Annual Meeting. doi: 10.3389/conf.fnhum.2018.228.00098

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 01 May 2018; Published Online: 22 Jan 2019.

* Correspondence: Ms. Nicole Dickerson, Johns Hopkins University, Cognitive Science, Baltimore, United States, ndicker3@jhu.edu