Resting-state Functional Connectivity In The Dorsal And Ventral Reading Pathways Correlates With Individual Differences In Phonological Decoding And Lexical/semantic Skill. - Info and Reading Options

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Cognitive models of reading models propose that understanding written words can be accomplished via two reading pathways, one that maps from print-to-sound and then from sound-to-meaning and another that maps directly from print-to-meaning [1-3]. The print-to-sound pathway supports the phonic decoding processes necessary to read unfamiliar words in alphabetic languages, whereas the print-to-meaning pathway supports whole-word recognition and efficient comprehension. These pathways have been associated with different brain areas. Dorsal stream regions (in particular left posterior occipitotemporal cortex (OTC), inferior parietal cortex (IPC) and dorsal inferior frontal gyrus (IFG)) are primarily involved in mapping from print-to-sound. Ventral stream regions (including left occipitotemporal cortex, anterior fusiform gyrus (aFG) and middle temporal gyrus (MTG)) are involved in mapping print-to-meaning [4-6]. Diffusion tensor imaging (DTI) has shown that the major white matter tracts that underpin these pathways include the fronto-temporal and fronto-parietal segments of the arcuate fasciculus and the inferior longitudinal fasciculus [7]. One promising way to investigate the neural underpinnings of reading skill involves examination of functional networks while participants are at rest. Resting state analyses measure temporal correlations in the BOLD signal of different brain areas. Patterns of resting state functional connectivity (RSFC) are thought to reflect the brain’s functional networks [8]. Investigations of RSFC offer opportunity to probe these networks in a manner that is uncontaminated by strategies or processes associated with a specific task. Resting state fMRI studies have shown that connectivity between reading related regions relates to reading ability. For example, reading ability positively correlates with RSFC between left fusiform gyrus and left dorsal stream regions implicated in phonological output (dorsal IFG/PCG) and phonological representation/processing (left posterior superior temporal/inferior parietal regions) [9-11]. However, no previous study with adults has examined whether different reading subskills correlate with RSFC between different reading related regions. One recent study with 8- to 14-year-old children did obtain several reading and related measures including word and pseudoword reading efficiency (TOWRE), reading comprehension (WJ-III; Passage Comprehension), and rapid automatized letter naming [12]. However, these tasks are not clearly dependent on different cognitive components of reading and therefore it is challenging to interpret the observed brain-behavior relationships. Our study therefore took a different approach, starting from specific tasks thought to tap different cognitive components of reading and examining correlations between these and RSFC between left OTC and the rest of the brain. To help guide our predictions, we first established which brain regions showed significant whole-brain correlations with a seed in left OTC at well-established co-ordinates for the visual word form area [VWFA , MNI [x, y, z]: -42, -57, -15; 13]. To this end, we projected the coordinates of the VWFA seed to the nearest corresponding surface of the left hemisphere midthickness surface of each participant. Subsequently, we created a circular region of interest (ROI) with 5 mm radius around this vertex. The mean signal within the ROI was used to calculate the correlation with the signal in each vertex across the whole hemisphere controlling for confounding signals (see Methods section). Subsequently, we averaged the seed correlation maps across participants. The results of this analysis are shown in Figure 2. We also examined the correspondence between this seed correlation map and clusters in key dorsal and ventral pathway regions that showed differential activity for [pseudoword – word] or [word – pseudoword] reading in a meta-analysis [4]. These clusters are projected onto the cortical surface in Figure 2 and it can be seen that there are relatively high correlations between the VWFA seed and regions that overlap with these clusters. The behavioural tasks are described in Table 1 and comprised: nonword reading, nonword repetition, spoonerisms, word reading, word spelling, vocabulary, and a pseudomorpheme lexical decision task in which half the pseudowords were comprised of existing morphemes (e.g., TOWERLY). Correlations among these measures are shown in Table 2. Based on the cognitive models of reading described earlier, nonword reading, nonword repetition, and spoonerisms should index print-to-sound processes. The positive correlation among these variables supports the idea that these all tap a common underlying skill. The vocabulary task indexes print-to-meaning knowledge. The pseudomorphemic lexical decision task accuracy cost metric taps sensitivity to print-to-meaning regularities. These measures are not correlated, but this is not unexpected since they index somewhat different aspects of print-to-meaning knowledge. Word reading and spelling require both print-to-sound and print-to-meaning processes, since good print-to-sound decoding is necessary to develop good performance on these tasks, but it is not sufficient, as the tasks include irregular items that require lexical/semantic knowledge to be read/spelled accurately. It is surprising that these two measures are not correlated, particularly given that spelling correlates with all three measures thought to tap print-to-sound processes, including the nonword reading task which took the same format as the word reading task. However, the idea that spelling also indexes lexical/semantic knowledge is supported by its strong positive correlation with vocabulary knowledge. Before detailing our research questions and hypotheses it is important to consider the fact that the print-to-sound and print-to-meaning pathways are not independent. Specifically, theories of reading development suggest that good print-to-sound decoders are better equipped to self-teach and develop the print-to-meaning pathway [14]. This means that, for example, although nonword reading primarily depends on processes supported by the dorsal pathway, nonword reading skill may correlate with connectivity between left OTC and both dorsal and ventral pathway regions. The hypotheses outlined below are, therefore, somewhat tentative and we regard our analyses as exploratory and requiring replication. However, our study contributes to the literature since the dataset is relatively large and it is the first to examine the relationship between RSFC and multiple reading/language measures that are widely used to tap reading subskills in individual differences studies with both developing and skilled readers. References 1. Coltheart, M., et al., DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 2001. 108(1): p. 204-256. 2. Plaut, D.C., et al., Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review, 1996. 103(1): p. 56-115. 3. Harm, M.W. and M.S. Seidenberg, Computing the meanings of words in reading: Cooperative division of labor between visual and phonological processes. Psychological Review, 2004. 111(3): p. 662-720. 4. Taylor, J.S.H., K. Rastle, and M.H. Davis, Can cognitive models explain brain activation during word and pseudoword reading? A meta-analysis of 36 neuroimaging studies. Psychol Bull, 2013. 139(4): p. 766-791. 5. Price, C.J., A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. Neuroimage, 2012. 62(2): p. 816-47. 6. Carreiras, M., et al., The what, when, where, and how of visual word recognition. Trends Cogn Sci, 2014. 18(2): p. 90-98. 7. Yablonski, M., et al., Structural properties of the ventral reading pathways are associated with morphological processing in adult English readers. Cortex, 2019. 116: p. 268-285. 8. Fox, M.D. and M.E. Raichle, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci, 2007. 8(9): p. 700-11. 9. Koyama, M.S., et al., Resting-state functional connectivity indexes reading competence in children and adults. J Neurosci, 2011. 31(23): p. 8617-24. 10. Stevens, W.A.-O., et al., Privileged Functional Connectivity between the Visual Word Form Area and the Language System. Journal of Neuroscience, 2017. 37: p. 5288-5297. 11. Zhang, M., et al., Resting-state functional connectivity and reading abilities in first and second languages. NeuroImage, 2014. 84: p. 546-553. 12. Cross, A.M., et al., Resting-state functional connectivity and reading subskills in children. Neuroimage, 2021. 243: p. 118529. 13. Cohen, L., et al., Language-specific tuning of visual cortex functional properties of the Visual Word Form Area. Brain, 2002. 125: p. 1054-1069. 14. Share, D.L., Phonological recoding and self-teaching: sine qua non of reading acquisition. Cognition, 1995. 55(2): p. 151-218. 15. Dickie, E.W., et al., Ciftify: A framework for surface-based analysis of legacy MR acquisitions. Neuroimage, 2019. 197: p. 818-826.

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