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White Matter Correlates of Lexical Access in Aphasia

William Hula1*, Juan Carlos Fernandez-Miranda2, Michael W. Dickey1, 3, Sudhir Pathak4, Yue-Fang Chang2 and Malcolm McNeil1, 3
  • 1 VA Pittsburgh Healthcare System, Geriatric Research Education and Clinical Center, United States
  • 2 University of Pittsburgh Medical Center, Department of Neurological Surgery, United States
  • 3 University of Pittsburgh, Department of Communication Science and Disorders, United States
  • 4 University of Pittsburgh, Learning Research and Development Center, United States

INTRODUCTION Neurolinguistic models have coalesced around the view that two distinct pathways support different kinds of processing (Hickok & Poeppel ,2004; Saur et al., 2008): A ventral stream (VS) maps sound to meaning, while a dorsal stream (DS) maps sound to articulation. Dell, Schwartz, Nozari, Faseyitan, & Coslett (2013) found correspondences between this framework and the interactive two-step model of lexical access (Foygel & Dell, 2000). However, there is evidence that the arcuate fascicle (AF), a major component of the DS, also contributes to semantic processing (Glasser & Rilling, 2008; Fernandez-Miranda et al., 2014). We present preliminary results from a study applying advanced fiber mapping techniques to investigate white matter correlates of word production in aphasia. METHOD Fifteen participants with aphasia due to left hemisphere stroke were given the Philadelphia Naming Test (mean %correct = 70%, sd = 23%) and response-type counts were entered into WebFit (http://langprod.cogsci.illinois.edu/cgi-bin/webfit.cgi) to estimate the semantic (s) and phonological (p) connection weight parameters of the two-step model. Diffusion spectrum imaging data (acquired via Siemens 3T Tim Trio Scanner, 32-channel coil, 257 directions with twice-refocused spin-echo EPI sequence, TR = 9616ms, TE = 152ms, voxel size = 2.4mm3, bmax = 7000s/mm2, FOV = 231x231mm) were reconstructed by generalized q-sampling, a high angular resolution-based approach. Orientation distribution functions (directional probability of diffusion) were used to calculate quantitative anisotropy (QA) values for each tract using whole-brain seeding and defined ROIs. ROIs for the AF were the superior, middle, and inferior temporal gyri. We estimated two regression models with s and p parameters as dependent variables and QA values for the left VS (VSQA; inferior fronto-occipital fascicle, extreme capsule, uncinate fascicle) and DS (DSQA; AF, superior longitudinal fascicle) as predictors. RESULTS VSQA and DSQA were both significant positive predictors of s-weight (p < 0.05, multiple r-squared = 0.60, 95%CI: 0.07, 0.88; VSQA semi-partial r-square = 0.31, 95%CI: 0.1, 0.6; DSQA semi-partial r-squared = 0.19, 95%CI: 0.001, 0.55) DSQA was a significant negative predictor of p-weight (p = 0.009, r-squared = 0.41, 95%CI = 0.08, 0.7), with higher values predicting lower p-weights. DISCUSSION We found significant relationships between VS and DS white matter lesions and semantic word production impairments in aphasia. This is consistent with neurolinguistic models that propose a role for the AF in semantic processing (Glasser & Rilling, 2008; Fernandez-Miranda et al., 2014). They are also consistent with Dell and colleagues (2013), who found that s-weight was associated with lesions in both VS and DS cortical areas. However, when they controlled for lesion volume, relationships with DS areas were absent. Our results must be confirmed in a larger sample with control of lesion volume. We also found a counterintuitive negative relationship between phonological processing and left DS integrity. This suggests that reliance on this pathway may be maladaptive for phonological processing in aphasia. Perhaps patients with more intact dorsal pathways continue to rely on this (still damaged) network, while patients with greater damage are more successful at reorganizing function (cf. Parkinson, Raymer, Chang, FitzGerald, & Crosson, 2009).

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References

Dell, G. S., Schwartz, M. F., Nozari, N., Faseyitan, O., & Coslett, H. B. (2013). Voxel-based lesion-parameter mapping: Identifying the neural correlates of a computational model of word production. Cognition, 128(3), 380-396.

Fernández-Miranda, J. C., Wang, Y., Pathak, S., Stefaneau, L., Verstynen, T., & Yeh, F. C. (2014). Asymmetry, connectivity, and segmentation of the arcuate fascicle in the human brain. Brain Structure and Function, 1-16.

Foygel, D., & Dell, G. S. (2000). Models of impaired lexical access in speech production. Journal of Memory and Language, 43(2), 182-216.

Glasser, M. F., & Rilling, J. K. (2008). DTI tractography of the human brain's language pathways. Cerebral cortex, 18(11), 2471-2482.

Hickok, G., & Poeppel, D. (2004). Dorsal and ventral streams: a framework for understanding aspects of the functional anatomy of language. Cognition, 92(1), 67-99.

Parkinson, R. B., Raymer, A., Chang, Y. L., FitzGerald, D. B., & Crosson, B. (2009). Lesion characteristics related to treatment improvement in object and action naming for patients with chronic aphasia. Brain and language, 110(2), 61-70.

Saur, D., Kreher, B. W., Schnell, S., Kümmerer, D., Kellmeyer, P., Vry, M. S., ... & Weiller, C. (2008). Ventral and dorsal pathways for language. Proceedings of the National Academy of Sciences, 105(46), 18035-18040.

Keywords: Aphasia, Diffusion spectrum imaging, neurolinguistics, Language, naming

Conference: Academy of Aphasia -- 52nd Annual Meeting, Miami, FL, United States, 5 Oct - 7 Oct, 2014.

Presentation Type: Platform or poster presentation

Topic: Not student

Citation: Hula W, Fernandez-Miranda J, Dickey MW, Pathak S, Chang Y and McNeil M (2014). White Matter Correlates of Lexical Access in Aphasia. Front. Psychol. Conference Abstract: Academy of Aphasia -- 52nd Annual Meeting. doi: 10.3389/conf.fpsyg.2014.64.00069

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Received: 25 Apr 2014; Published Online: 04 Aug 2014.

* Correspondence: Dr. William Hula, VA Pittsburgh Healthcare System, Geriatric Research Education and Clinical Center, Pittsburgh, United States, william.hula@va.gov