Poster E16, Thursday, August 22, 2019, 3:45 – 5:30 pm, Restaurant Hall
Do different language impairments have distinctive patterns of RS-fMRI as indexed by fALFF?
Nicole Dickerson1, Robert Wiley1, James Higgins2, David Caplan3, Swathi Kiran4, Todd Parrish2, Cynthia Thompson2, Brenda Rapp1;1Johns Hopkins University, 2Northwestern University, 3Harvard Medical School, 4Boston University
Although most RS-fMRI studies examine functional connectivity, local activation strength in specific brain areas can also be investigated with measurements of local Fractional Amplitude of Low Frequency Fluctuations (fALFF) -the proportion of the total BOLD signal in a given brain region that falls within the low frequency range of .01-.08 Hz, (Zou et. al, 2008). Relatively little research has been directed at understanding these local properties of the RS-fMRI signal, although recent work (DeMarco & Turkeltaub, 2018) indicates this information may be used to distinguish lesioned from healthy tissue and index language deficits. The current investigation aimed to determine if fALFF values within the functional language networks used for spoken naming, syntactic processing and spelling reflect the severity of language deficits affecting these specific functions. Methods: Participants were 68 individuals (21 females) who suffered language impairment subsequent to a single left-hemisphere stroke. Participants were recruited from three sites (Johns Hopkins, Northwestern and Boston University). Language-domain severity was measured for syntactic processing (Northwestern Assessment of Verbs and Sentences; Thompson, 2011), spoken naming (Northwestern Naming Battery; Thompson, & Weintraub, 2014), and spelling (PALPA 40; Lesser & Coltheart, 1992). For RS-fMRI, 210 or 175 3D image volumes were collected, consisting of 41 slices (voxel size 1.7x1.7x3mm), with a TR of 2.4s. Preprocessing of the images was performed using the NUNDA “Robust fMRI preprocessing pipeline”. FALLF values were calculated for each voxel (all lesioned voxels and voxels with fALFF values under .098 were excluded from analysis). Voxels were grouped into ROIs (Harvard/Oxford atlas; Desikan et al., 2006) constituting the three functional language networks (ROIs: spoken naming =13, syntactic processing=12, spelling =13). Using Linear Modeling (RStudio Software), 3 models were evaluated. For each, the dependent variable corresponded to the language-domain severity scores; fixed effects were: average fALFF for each ROI of the respective functional language network, months post-stroke, and lesion volume. Results: First, with regard to overall model fits, the three language networks resulted in the following Syntax: R2= 0.51, Naming: R2= 0.42, Spelling: R2 = 0.37. Second, the following specific ROIs predicted language deficit severity: 1) Syntactic processing: left inferior frontal gyrus pars opercularis (t=-2.1, p <0.04), 2) Spoken naming: left angular gyrus / left supramarginal gyrus(posterior division) (t=-1.9, p<0.07), right inferior frontal gyrus pars opercularis /middle frontal gyrus (t=1.9, p <0.07), and the right frontal orbital cortex (t=-1.7, p<0.1), 3) Spelling: left supramarginal gyrus (posterior division) (t=-2.7, p <0.02). Conclusions: This study identified specific brain regions in which BOLD response at rest shows sensitivity to language deficit severity. Overall, we found that lower fALFF values were associated with greater deficit severity. These findings help to advance our understanding of the consequences of lesions to the networks that support language processing and provide foundations for future research using the properties of the brain’s activity at rest to predict treatment outcomes and evaluate neural changes that support recovery of function.
Themes: Disorders: Acquired, Language Production
Method: Functional Imaging