Poster C51, Wednesday, August 21, 2019, 10:45 am – 12:30 pm, Restaurant Hall
Identifying the cognitive components of the morphological fluency task through neurocognitive correlations
Galit Agmon1,2, Maya Yablonski1, Michal Ben-Shachar1;1Bar-Ilan University, 2The Hebrew University of Jerusalem
Verbal fluency tasks assess the speed of lexical access based on a predefined criterion. In a semantic fluency task, participants are given one minute to produce as many words as possible that belong to a given semantic category (e.g., animals); in a phonological fluency task, the criterion is an opening sound (e.g., words that begin with /f/). We focus here on another variant, the morphological fluency task, in which the criterion for word production is morpheme-based. Participants are presented with a spoken target word, and are requested to produce as many words as possible that share the same root morpheme as the target word. The morphological fluency task involves morphological decomposition and morpheme-guided lexical search. Other cognitive components are shared across the three fluency tasks: lexical access, retrieval, production, inhibition and switching. In this study, we combined fMRI with behavioral assessment to identify the distinct contributions of different fluency components in explaining the cortical responses during a morphological fluency task. Forty-five native Hebrew speakers (29 females, ages 20-35y) performed a covert morphological fluency task in fMRI, and completed the morphological-, semantic- and phonological-fluency tasks in a separate behavioral session. In fMRI, participants were presented with written Hebrew roots, and were asked to covertly generate words that incorporate that root (Siemens 3T, TR=2000ms, 2mm isotropic voxels). Roots were presented in blocks (4 roots in each 12s block), interleaved with fixation blocks (10s each). Baseline blocks consisted of phase scrambled words, to control for visual responses. Responses to the morphological fluency task (vs. baseline) involved multiple regions, including the left inferior frontal gyrus, left caudate nucleus and the left inferior parietal lobule (p<0.001, corrected). Next, we identified brain regions in which the activation for the morphological fluency task is modulated by individual performances on each of the behavioral fluency tasks. Significant clusters were identified based on a simulation of noise-only brain activity. One cluster in the left middle frontal gyrus (LMFG) was positively correlated with participants’ scores on the behavioral morphological fluency task (1816 cubic mm; p<0.01 corrected). This finding supports the involvement of the LMFG in morphological tasks (Bick et al., 2008). A second cluster in the right cerebellum was positively correlated with participants’ scores on the behavioral semantic fluency task (3040 cubic mm; p<0.01 corrected). This finding converges with studies showing the involvement of the right cerebellum in language production (e.g., Jansen et al., 2005). No significant correlations were found with phonological fluency scores. The results separate the contribution of shared fluency components from that of morphological fluency. At a broader level, we propose that neurocognitive correlations between general fMRI contrasts and selective cognitive measures assessed outside the scanner are a promising tool for studying the neurobiology of language. This approach capitalizes on the considerable individual variability characteristic of psycholinguistic measures, which increases the power of neurocognitive correlation analyses. By assessing behavioral sensitivity carefully and selectively in the psycholinguistics lab we can decompose complex patterns of brain activation based on the contribution of separate, well defined cognitive processes.
Themes: Language Production, Morphology
Method: Functional Imaging