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Aberrant Cerebellar Resting-State Functional Connectivity Related to Reading Performance in Struggling Readers

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Title: Aberrant Cerebellar Resting-State Functional Connectivity Related to Reading Performance in Struggling Readers
Language: English
Authors: Greeley, Brian (ORCID 0000-0001-5117-3866), Weber, Rachel C., Denyer, Ronan, Ferris, Jennifer K., Rubino, Cristina, White, Katherine, Boyd, Lara A.
Source: Developmental Science. Mar 2021 24(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 13
Publication Date: 2021
Document Type: Journal Articles
Reports - Research
Descriptors: Reading Processes, Brain Hemisphere Functions, Decoding (Reading), Reading Rate, Reading Comprehension, Reading Difficulties, Adolescents, Children, Correlation
DOI: 10.1111/desc.13022
ISSN: 1467-7687
Abstract: Reading is a critical neurodevelopmental skill for school-aged children, which requires a distributed network of brain regions including the cerebellum. However, we do not know how functional connectivity between the cerebellum and other brain regions contributes to reading. Here we used resting-state functional connectivity to understand the cerebellum's role in decoding, reading speed, and comprehension in a group of struggling readers (RD) and a group of adolescents and children with typical reading abilities (TD). We observed an increase in functional connectivity between the sensorimotor network and the left angular gyrus, left lateral occipital cortex, and right inferior frontal gyrus in the RD group relative to the TD group. Additionally, functional connectivity between the cerebellum network and the precentral gyrus was decreased and was related to reading fluency in the RD group. Seed-based analysis revealed increased functional connectivity between crus 1, lobule 6, and lobule 8 of the cerebellum and brain regions related to the default mode network and the motor system for the RD group. We also found associations between reading performance and the functional connectivity between lobule 8 of the cerebellum and the left angular gyrus for both groups, with stronger relationships in the TD group. Specifically, the RD group displayed a positive relationship between functional connectivity, whereas the TD group displayed the opposite relationship. These results suggest that the cerebellum is involved in multiple components of reading performance and that functional connectivity differences observed in the RD group may contribute to poor reading performance.
Abstractor: As Provided
Entry Date: 2021
Accession Number: EJ1286706
Database: ERIC
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  Value: <anid>AN0148778214;5g501mar.21;2021Feb19.05:39;v2.2.500</anid> <title id="AN0148778214-1">Aberrant Cerebellar Resting‐State Functional Connectivity Related to Reading Performance in Struggling Readers </title> <p>Reading is a critical neurodevelopmental skill for school‐aged children, which requires a distributed network of brain regions including the cerebellum. However, we do not know how functional connectivity between the cerebellum and other brain regions contributes to reading. Here we used resting‐state functional connectivity to understand the cerebellum's role in decoding, reading speed, and comprehension in a group of struggling readers (RD) and a group of adolescents and children with typical reading abilities (TD). We observed an increase in functional connectivity between the sensorimotor network and the left angular gyrus, left lateral occipital cortex, and right inferior frontal gyrus in the RD group relative to the TD group. Additionally, functional connectivity between the cerebellum network and the precentral gyrus was decreased and was related to reading fluency in the RD group. Seed‐based analysis revealed increased functional connectivity between crus 1, lobule 6, and lobule 8 of the cerebellum and brain regions related to the default mode network and the motor system for the RD group. We also found associations between reading performance and the functional connectivity between lobule 8 of the cerebellum and the left angular gyrus for both groups, with stronger relationships in the TD group. Specifically, the RD group displayed a positive relationship between functional connectivity, whereas the TD group displayed the opposite relationship. These results suggest that the cerebellum is involved in multiple components of reading performance and that functional connectivity differences observed in the RD group may contribute to poor reading performance.</p> <p>Keywords: cerebellum; motor system; reading; reading difficulties; resting‐state</p> <p>A group of struggling readers and aged‐matched controls were scanned and separately performed a battery of reading tests. We observed decreased functional connectivity between the cerebellum network and the precentral gyrus, and increased connectivity between crus 1, lobule 6 and 8 of the cerebellum and the motor system in the struggling readers. We also found several associations between reading performance (decoding, fluency, and comprehension) and functional connectivity in both groups, suggesting that the abnormal functional connectivity differences observed in the struggling readers may contribute to poor reading performance.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-toc-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-toc-0001.jpg" title="." /> </p> <p></p> <hd id="AN0148778214-3">Research Highlights</hd> <p></p> <ulist> <item> Resting‐state functional connectivity was examined in children and adolescents with and without reading difficulties.</item> <p></p> <item> Independent component analysis revealed differences in sensorimotor, salience, and cerebellar networks in the reading difficulties group.</item> <p></p> <item> Seed‐to‐voxel analysis revealed increased functional connectivity in portions of the cerebellum and brain regions associated with the motor system in the group with reading difficulties.</item> <p></p> <item> Reading performance scores and functional connectivity were associated in both groups. The direction of the associations were group dependent.</item> <p></p> <item> The differences observed in functional connectivity may contribute to poor reading in struggling readers.</item> </ulist> <hd id="AN0148778214-4">INTRODUCTION</hd> <p>Reading is a complex motor skill that requires the use of multiple brain regions (Alvarez & Fiez, 2018). Learning to read involves the acquisition and execution of a new sequence of motor, perceptual, and cognitive skills including decoding, speed (fluency), and comprehension (Pazzaglia, Cornoldi, & Tressoldi, 1993). Decoding, defined as grapheme‐phoneme (word‐sound) relationships during reading, in which graphemes are decoded into phonemes, is critical to successful reading (Gough & Tunmer, 1986). Successful reading also requires the comprehension of the content (Samuels, 2006). For reading to be fluent and successful, both decoding and comprehension must operate automatically (LaBerge & Samuels, 1974). The cerebellum plays critical role in the automaticity of practiced movements (Lang & Bastian, 2002). Because of the strong link between reading and motor control (Kulp & Schmidt, 1996; Viholainen et al., 2006), it is possible that the automatization of reading is also cerebellar dependent (Rae et al., 2002; Stoodley & Stein, 2011; Vlachos, Papathanasiou, & Andreou, 2007).</p> <p>Initially thought to exclusively support sensorimotor functions, cerebellar function has recently been linked to more "cognitive" processes, including reading (Nicolson, Fawcett, & Dean, 2001). For example, the cerebellum shows marked structural differences between individuals with reading difficulties (e.g, dyslexics) and controls (Eckert et al., 2003). Further, functional magnetic resonance imaging (fMRI) task‐based studies demonstrate that the cerebellum is involved in semantic and phonological processing (Fulbright et al., 1999), speech perception (Mathiak, Hertrich, Grodd, & Ackermann, 2002), and word production (Jansen et al., 2005). Other research linking the cerebellum to reading shows a relationship between performance on cerebellar‐mediated tasks and reading ability. Cerebellar‐mediated tasks such as the speed of completing a series of alternating oppositions of finger and thumb, and the amount of disturbance from an upright stance when pushed gently on the back were impaired in children with reading difficulties but intact in good readers (Fawcett, Nicolson, & Maclagan, 2001). These findings suggest that the cerebellum plays an important role in reading, yet which specific components of reading and regions of the cerebellum are involved are currently unknown.</p> <p>While it is well established that the cerebellum and the primary motor cortex (M1) work in concert to learn and produce motor movements (Galea, Vazquez, Pasricha, Orban de Xivry, & Celnik, 2011; Spampinato, Block, & Celnik, 2017), the cerebellum and M1 also are engaged (Yarkoni, Speer, Balota, McAvoy, & Zacks, 2008) and functionally coupled during reading (Kujala et al., 2007). The functional coupling between these two brain regions may seem surprising given their distance; however, it is well established in both non‐human primates and humans that the cerebellum and M1 are linked neuroanatomically. In non‐human primates, Purkinje cells in lobules 4, 5, 6, and 9 of the cerebellum project to the arm area of M1 (Kelly & Strick, 2003). In humans, stimulation of the cerebellum using transcranial magnetic stimulation (TMS) changes both inhibitory and excitatory neurons in M1 (Daskalakis et al., 2004; Ugawa et al., 1991). This evidence suggests there is a clear anatomical link between the cerebellum and M1, while other data suggest that coupling between them is necessary for silent reading. Using magnetoencephalography while participants silently read, Kujala and colleagues (2007) found that eight interconnected brain regions emerged during reading. Out of the eight regions, the cerebellum and the face representation of M1 were a functionally coupled network during slow reading.</p> <p>Long‐range networks comprising of temporal and frontal brain regions have been identified as being involved in reading, but how the functional connectivity between these regions supports reading is not fully understood. In a meta‐analysis including 129 studies of healthy young adults, the anterior temporal cortex and the superior temporal sulcus, or the human voice area, were the only two unique clusters involved in a diverse set of tasks including phonological, semantic, and sentence processing (Vigneau et al., 2006). While these findings speak to the flexibility of the anterior temporal cortex and the human voice area in reading, they do not address how these regions are utilized across the readers of different abilities. Other work demonstrates that slower lexical readers showed greater activation in the left occipito‐temporal and left inferior frontal regions, whereas faster readers did not engage frontal regions (Seghier, Lee, Schofield, Ellis, & Price, 2008). Moreover, a recent study found that the right uncinate fasciculus, a white matter tract between the temporal lobe and the orbitofrontal cortex, was related to both reading comprehension and fluency but only in poor readers (Arrington et al., 2017). While these studies clearly demonstrate a relationship between reading and temporal and frontal brain regions, it is unknown how these brain regions are functionally connected in the absence of a task and whether functional connectivity from these brain regions are involved in or contribute to reading.</p> <p>Resting‐state fMRI (rs‐fMRI) is a neuroimaging method that investigates spontaneous blood oxygen level‐dependent (BOLD) signal alternations in spatially distinct brain regions while the participant is at rest. The default mode network (DMN), a network comprised of the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPC), inferior parietal lobule, and temporoparietal junction, is preferentially engaged in the absence of a task (Buckner, Andrews‐Hanna, & Schacter, 2008), and is engaged during reading. In addition, a meta‐analysis indicated that brain regions that comprise the DMN, such as the PCC and the anterior medial prefrontal cortex (aMPC) are important in semantic processing (Binder, Desai, Graves, & Conant, 2009). For example, better reading comprehension appears to be associated with greater functional connectivity between the PCC and the right insula (Smallwood et al., 2013). Further, increasing task focus during reading comprehension was associated with higher functional connectivity between the aMPFC and clusters in the PCC, left parietal and temporal cortex, and the cerebellum. Similarly, hyperconnectivity between reading‐related brain regions such as middle and inferior temporal gyri and the precuneus has been noted in adolescent dyslexic readers compared to controls (Schurz et al., 2015). This suggests the aMPFC and PCC, central hubs in the DMN, are related to objective measures of comprehension, whereas functional connectivity between the cerebellum and DMN are related to effort. Considering these findings, it is likely that individuals who have reading difficulties, and subsequently require more effort during reading, would show altered functional connectivity between the cerebellum and DMN.</p> <p>Evidence from a large sample rs‐fMRI study also support the idea that the DMN, or core brain regions that are parts of the DMN, interact with the cerebellum during language processing. Recently, Guell, Schmahmann, DE Gabrieli, and Ghosh (2018) used resting‐state and task‐based fMRI data from 1,000 participants to characterize the topological map of the cerebellum. The researchers found that bilateral portions of crus 1 and 2 were primarily involved in the language‐processing task (listening to stories), with activity extending to portions of lobule IX of the cerebellum. Interestingly, this same study demonstrated that the same cerebellar regions involved in language processing were also classified as belonging to the DMN. Taken together, findings from Kujala et al. (2007) and Guell (2018) show cerebro‐cerebellar functional coupling during language processing. However, because reading is a complex skill comprised of decoding, fluency, and comprehension among other processes, it is possible that the brain regions engaged during listening and silent reading differ from those that support the constituents of reading. Thus, there is currently a gap in our knowledge regarding how different components of reading are related to cerebro‐cerebellar interconnections.</p> <p>Evidence supporting abnormal cerebro‐cerebellar rs‐fMRI in struggling readers is further supported by a recent study completed in children with dyslexia (Ashburn, Flowers, Napoliello, & Eden, 2020). In this study, rs‐fMRI, but not task‐based fMRI, differences were observed in 8‐ to 10‐year‐old children with dyslexia when compared to typically developing children. Using an ROI‐to‐ROI analysis approach, Ashburn and colleagues found increased functional connectivity in the children with dyslexia between right crus 1 and left angular gyrus, posterior superior temporal gyrus, and the inferior frontal gyrus, compared to controls. While the findings of Ashburn et al. suggest individuals with reading difficulties may present with cerebro‐cerebellar functional connectivity abnormalities, it is important to note that this study confined analysis to a limited set of brain regions (ROI‐to‐ROI) that were all lateralized to the left hemisphere. It also did not relate reading performance to functional connectivity.</p> <p>However, employing ROIs data from healthy populations to understand individuals with reading difficulty leads to possibility that abnormal or compensatory brain regions are excluded. In addition ROI approaches are limited by a priori hypotheses. To counter these limitations we used an independent component analysis, which is not hypothesis driven, and ROI‐to‐voxel approach. Additionally, we considered the relationship(s) between reading performance and functional connectivity to understand brain–behavior relationships.</p> <p>In the current study we employed rs‐fMRI to study two groups of children and adolescents: one struggling with reading (RD) and one that was typically developing (TD), to understand the relationship between resting‐state cerebellar network and reading in decoding, reading fluency, and comprehension. Given the cerebellum's role in reading and the DMN, we anticipated that the RD group would display: 1) general abnormalities (hyper‐ or hypoconnectivity) in rs‐fMRI connectivity as identified by independent component analysis, and more specifically, 2) abnormalities between the cerebellum and DMN. Because individuals with reading difficulties show abnormal rs‐fMRI in the DMN, and regions within the cerebellum are functionally connected to the DMN, we anticipated there would be aberrant functional connectivity between crus 1, 2, and lobule 9 of the cerebellum and the DMN. We also anticipated that areas 1 to 6 or 8 to 10 of the cerebellum would not display rs‐fMRI connectivity differences between the two groups. Moreover, we predicted that aberrant rs‐fMRI activity in the RD group would likely be compensatory and thus relate to reading performance.</p> <hd id="AN0148778214-5">METHODS</hd> <p></p> <hd id="AN0148778214-6">Participants</hd> <p>All scanned participants (<emph>n</emph> = 67) were right‐hand dominant, and recruited in the lower mainland of British Columbia Canada or northern Washington State. Forty‐eight participants were recruited from schools specializing learning difficulties for children. This group will be referred to as "struggling readers" and with the acronym RD, representing a possible learning disorder in reading, or dyslexia. Participants were excluded if their overall intelligence (as measured by the Woodcock‐Johnson III Tests of Cognitive Abilities) was indicative of more global intellectual and learning challenges (e.g., IQ < 75). Demographic information about both groups are presented in Table 1. A total of 19 participants were age‐ and sex‐matched typically developing (TD) controls. The TD group was enrolled in public schools, whereas the RD group was recruited from specialized schools for students with learning challenges. Children between the ages of 8–17 years provided assent and their parent or guardian consented to their participation. Six participants with RD were excluded from analyses. Two participants were removed due to excessive head motion, two for having only one functional scan, and two had preprocessing errors. The final analysis included 61 participants (8.9 – 18.6 years old; 22 female). There were 42 participants in the RD group (8.3 – 17.2 years old; 13 female) and 19 participants in the TD group (9.4 – 18.6 years old; 9 female; Table 1). While the RD group had a smaller portion of females compared to the TD group, a chi‐squared test resulted in a non‐significant difference in sex (<emph>p </emph>= .331). All procedures were approved by the UBC Office of Research Ethics, and ethics procedures were completed in accordance with the Declaration of Helsinki.</p> <p>1 TableParticipant demographics, scan nuisance values, and reading performance for learning reading difficulty (RD) and typically developing controls (TD)</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="left">LD (<italic>n</italic> = 42; 13 female)</th><th align="left">TD (<italic>n</italic> = 19; 9 female)</th></tr></thead><tbody><tr><td align="left">Age (in years)</td><td align="left">12.9 ± 2.4</td><td align="left">12.7 ± 3.0</td></tr><tr><td align="left">Invalid Scans</td><td align="left">41.0 ± 38.3</td><td align="left">48.2 ± 52.3</td></tr><tr><td align="left">Max Motion</td><td align="left">4.0 ± 5.6</td><td align="left">3.3 ± 3.4</td></tr><tr><td align="left">Mean Motion</td><td align="left">0.32 ± 0.3</td><td align="left">0.33 ± 0.31</td></tr><tr><td align="left">Max Global Signal Change</td><td align="left">8.7 ± 6.6</td><td align="left">9.3 ± 6.6</td></tr><tr><td align="left">Mean Global Signal Change</td><td align="left">1.0 ± 0.2</td><td align="left">1.0 ± 0.23</td></tr><tr><td align="left">General Intellectual Ability</td><td align="left">506.8 ± 13.6</td><td align="left">515.9 ± 11.9</td></tr><tr><td align="left">Broad Reading Composite Score</td><td align="left">509.8 ± 17.5</td><td align="left">522.67<xref ref-type="fn" rid="tfn1" /> ± 20.2</td></tr><tr><td align="left">Letter–word Identification</td><td align="left">522.75 ± 24.7</td><td align="left">529.33 ± 20.3</td></tr><tr><td align="left">Reading Fluency</td><td align="left">503.89 ± 18.9</td><td align="left">522.67<xref ref-type="fn" rid="tfn2" /> ± 26.5</td></tr><tr><td align="left">Passage Comprehension</td><td align="left">503.26 ± 15.7</td><td align="left">516.07<xref ref-type="fn" rid="tfn2" /> ± 16.9</td></tr></tbody></table> </ephtml> </p> <p>1 * Significant at <emph>p <.05</emph></p> <p>2 ** Significant at <emph>p</emph> <.01</p> <hd id="AN0148778214-7">Behavioral testing</hd> <p>Participants completed a comprehensive test battery of the Woodcock‐Johnson III Tests of Academic Achievement (Woodcock, McGrew, & Mather, 2001). We used the broad reading score, a cluster score which measures general reading proficiency, as the main predictor of reading ability and functional connectivity. The rs‐fMRI data shown here are a part of a larger study where task‐based fMRI and multicomponent relaxation imaging were also completed; these data are reported elsewhere (Weber et al., 2019).</p> <p>Subtests of the broad reading composite score include letter–word identification, reading fluency, and passage comprehension. The letter–word identification test involves naming letters and reading words aloud from a list. The words become increasing difficult and pronunciation is assessed by the experimenter. The letter–word identification measures word recognition. The reading fluency test is a timed test where participants silently read a sentence, then circle either "yes" or "no" on an answer sheet, to decide whether each statement was true or false. The participant tries to complete as many questions as possible during a 3‐minute time period. The reading fluency test measures comprehension and speeded silent reading. The third test, passage comprehension, requires participants to orally supply a missing word removed from each sentence or passage after it is silently read; vocabulary increases throughout the test. Passage comprehension measures the integration of semantic and syntactic properties (Schrank & McGrew, 2001).</p> <p>Each subtest (letter–word identification, reading fluency, and passage comprehension) was scored and converted into a W score. The W scale is an equal‐interval scale which makes comparison between subtests within the Woodcock‐Johnson III possible.</p> <hd id="AN0148778214-8">Incomplete data</hd> <p>Twelve participants were missing a broad reading composite score, of which eight were in the RD group and four were from the TD group. Ten participants had a missing value for the letter–word identification, with six being from the RD group and four being from the TD group. Eleven participants had a missing value for reading fluency; seven of these participants were from the RD group. Eleven participants had a missing value for passage comprehension (7 = RD group).</p> <hd id="AN0148778214-9">Measures</hd> <p></p> <hd id="AN0148778214-10">MRI acquisition and data preprocessing</hd> <p>All participants were scanned at the University of British Columbia 3T Research Facility. Images were acquired on a Philips Achieva 3T MRI scanner (Philips Healthcare, Andover, MD). First, a T1 structural scan with the parameters: TR/TE = 7.7/3.5 ms, filp angle θ = 8°, field of view (FOV) = 256 x 170 x 200, 170 slices, 1 x 1 x 1 mm, for a total imaging time of 6.6 min was taken. The fMRI scans were collected for each participant using a single‐shot echo planar imaging (EPI) sequence with the parameters: TR/TE = 2000/30 ms, flip angle h = 90°, voxel dimension = 3 x 3 x 3 (mm) with 1 mm gap, 36 slices, FOV = 240 x 143 x 240 mm, for a total imaging time of 4.2 min. During the 4.2 min, participants were asked to look at a fixed target, think of nothing in particular, and to avoid closing their eyes or sleeping.</p> <p>Resting‐state functional MRI preprocessing was performed using Statistical Parametric Mapping (SPM 8, University College London, London, UK). A standard preprocessing protocol of realignment, slice‐timing correction, outlier detection, segmentation, and normalization were used. The realigned functional images were warped into the normalized Montreal Neurological Institute (MNI) EPI template, resampled into 2 x 2 x 2‐mm<sups>3</sups> resolution. Finally, the normalized images were smoothed with a Gaussian kernel at 6 mm.</p> <hd id="AN0148778214-11">Functional connectivity analysis</hd> <p>Analysis of functional network connectivity was carried out using CONN v.18a (Whitfield‐Gabrieli & Nieto‐Castanon, 2012), a functional connectivity toolbox. The white matter and cerebrospinal fluid time series were decomposed into principal components using the CompCor method (Behzadi, Restom, Liau, & Liu, 2007), which were regressed out of the total fMRI signal. We used 10 principal components for the white matter and five for the cerebrospinal fluid. Residual head movement parameters (three rotation and three translation parameters, and another six parameters representing their first‐order temporal derivatives, outliers identified by ART) were regressed out as well. Time points with excessive motion (>0.5 mm), or where a global signal changed by above three standard deviations, were defined as outliers and "scrubbed," and removed from analysis. Groups did not differ on motion as measured by max motion displacement (t(<reflink idref="bib59" id="ref1">59</reflink>) = 0.524, <emph>p </emph>= .60) or mean motion displacement (t(<reflink idref="bib59" id="ref2">59</reflink>) = −0.225, <emph>p </emph>= .82; see Table 1). Resting‐state data were band‐pass filtered (0.008‐0.09 Hz). Age and sex were entered in CONN as covariates as well.</p> <hd id="AN0148778214-12">Independent component analysis</hd> <p>After denoising, group‐level independent component analysis (ICA) was implemented across all participants (i.e., not completed twice) through Calhoun's group‐level fast ICA approach which first performs the ICA, then those components are then back projected to individual subject ICA maps which are then entered into the second‐level analysis (Calhoun, Adali, Pearlson, & Pekar, 2001). The number of independent components was set to 20 and dimensionality reduction was set to 64 to detect resting‐state networks (Calhoun et al., 2001). Independent components corresponding to resting‐state networks were visually identified and confirmed with the spatial correlation of the independent components with the CONN functional atlas. Each group‐level spatial map was compared to CONN's default networks file. Components that were identified as representing intrinsic networks had correlation coefficients between <emph>r</emph> = 0.3 and <emph>r</emph> = 0.5. Thus, the overlap between CONN's default network maps and the ICA produced relatively high correlation coefficients. Based on the group ICA results, the DMN were split into the anterior DMN (aDMN) and posterior DMN (pDMN) which is consistent with previous research (Leech, Kamourieh, Beckmann, & Sharp, 2011). Contrasts ([−1 1]) were performed on each ICA to understand network differences between the RD group and the TD group. If multiple ICAs were identified as belonging to the same network (e.g., DMN), contrasts were performed twice, once for each component. Voxel threshold was uncorrected <emph>p </emph>< .001 and cluster threshold was FDR corrected <emph>p </emph>< .05.</p> <hd id="AN0148778214-13">Seed‐to‐voxel (regions of interest)</hd> <p>For the seed‐to‐voxel connectivity analysis, we were interested in identifying connectivity between cerebellar brain regions known to be involved in language and motor tasks. Thus, we extracted a total of 18 regions of interest (ROIs) available in the CONN toolbox. ROIs included both left and right crus 1 and crus 2, and cerebellar lobules 3, 4/5, 6, 7, 8, 9, and 10 for a total of 18 across the left and right hemispheres of the cerebellum. First‐level analysis was performed using a weighted GLM, no weighting and bivariate correlation for the seed‐to‐voxel analysis. For second‐level analysis, voxel‐wise statistics throughout the whole brain were performed at an uncorrected level (<emph>p </emph>< .001), and a false discovery rate (FDR) correction was applied at the cluster level (<emph>p </emph>< .05).</p> <hd id="AN0148778214-14">Regression</hd> <p>We performed a series of regressions for each group in order to understand the relationship between reading performance and resting‐state connectivity. Stepwise regressions using the subtests were performed only if broad reading scores showed a significant relationship between connectivity values and performance in order to determine which component of broad reading was driving the relationship. The dependent variable was mean functional connectivity values for a particular ROI and the independent variables were the three different reading component scores (reading fluency, passage comprehension, and letter–word identification scores). Mean functional connectivity values (z‐scores) were taken within the clusters of interest and extracted using the REX toolbox. As this portion of the study was exploratory, we provide both uncorrected and corrected (Benjamini–Hochberg) corrected p‐values.</p> <hd id="AN0148778214-15">RESULTS</hd> <p></p> <hd id="AN0148778214-16">Functional connectivity (ICA) networks</hd> <p>Out of the 20 components, four of the group ICA (for all participants) were found to show significant differences between the two groups (Figure 1).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-fig-0001.jpg" title="1 Group ICA (for all participants) spatial maps of four individual components identified by CONN. a) Independent component analysis (ICA) 1 identified as the cerebellar network, b) ICA component 4 identified as a sensorimotor network, c) ICA 5 identified as the salience network, and d) ICA 16 identified as a sensorimotor network" /> </p> <p></p> <hd id="AN0148778214-18">Functional connectivity (ICA) network group effects: RD greater than TD</hd> <p>The RD group displayed greater functional connectivity (hyperconnectivity) between sensorimotor and salience networks and brain regions involved in visual processing and the motor system. Contrasts revealed increased functional connectivity between the sensorimotor networks and the left angular gyrus and left lateral occipital cortex (Figure 2b) and right inferior frontal gyrus (Figure 2d). Increased functional connectivity between the salience network and bilateral supplementary motor areas (SMA) was also observed (Figure 2c, Table 2).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-fig-0002.jpg" title="2 Group differences in RD > TD contrast in a) ICA component 1, the cerebellar network, b) ICA component 4, the sensorimotor network, c) ICA component 5, the salience network, d) ICA component 16, the sensorimotor network. Warm colors (yellow) indicate positive T‐values, whereas cool colors (pink) indicate negative T‐values. The RD group displayed decreased connectivity between a) the cerebellar network and subcallosal cortex (k = 90; size p‐FDR = 0.024) and right precentral gyrus (k = 76; size p‐FDR = 0.025) and increased connectivity between b) the sensorimotor network and the left angular gyrus (k = 111; size p‐FDR = 0.015), between c) the salience network and bilateral supplementary motor cortex (k = 109; p‐FDR = 0.017), and between d) the sensorimotor network and right inferior frontal gyrus(k = 195; p‐FDR < 0.001) relative to the typically developing group" /> </p> <p></p> <p>2 TableSignificant clusters within ICA components from RD greater than TD contrast. XYZ coordinates are for maximal activity. For results where multiple brain regions comprise the significant cluster, we reported all the brain regions</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">ICA Network</th><th align="left"><p>Contrast</p><p>Direction</p></th><th align="left"><p>Cluster</p><p>p‐FDR</p></th><th align="left"><p>Height</p><p>p‐uncorrected</p></th><th align="left"><p>Cluster Size</p><p>(voxels)</p></th><th align="left">β</th><th align="left">t‐scores</th><th align="left">x y z</th><th align="left">Regions</th></tr></thead><tbody><tr><td align="left">Cerebellar ICA 1</td><td align="left">Negative</td><td align="char" char=".">0.02</td><td align="char" char="."><0.001</td><td align="char" char=".">90</td><td align="left">−2.31</td><td align="left">−5.65</td><td align="left">2, 26, −32</td><td align="left">Subcallosal Cortex</td></tr><tr><td align="left" /><td align="left">Negative</td><td align="char" char=".">0.02</td><td align="char" char=".">0.002</td><td align="char" char=".">76</td><td align="left">−1.81</td><td align="left">−5.29</td><td align="left">12, −22, 60</td><td align="left">R preCG</td></tr><tr><td align="left">Sensorimotor ICA 4</td><td align="left">Positive</td><td align="char" char=".">0.01</td><td align="char" char="."><0.001</td><td align="char" char=".">111</td><td align="left">1.57</td><td align="left">5.86</td><td align="left">−44, −56, 52</td><td align="left">L AG, L sLOC</td></tr><tr><td align="left">SalienceICA 5</td><td align="left">Positive</td><td align="char" char=".">0.02</td><td align="char" char="."><0.001</td><td align="char" char=".">109</td><td align="left">1.99</td><td align="left">5.49</td><td align="left">−4, −8, 66</td><td align="left">L SMA, R SMA</td></tr><tr><td align="left">SensorimotorICA 16</td><td align="left">Positive</td><td align="char" char="."><0.001</td><td align="char" char="."><0.001</td><td align="char" char=".">195</td><td align="left">2.20</td><td align="left">6.61</td><td align="left">52, 2, 18</td><td align="left">R IFG, R preCG</td></tr></tbody></table> </ephtml> </p> <ulist> <item>3 Note</item> <item>4 ICA = independent component analysis; FDR = false discovery rate; AG = angular gyrus; IFG = inferior frontal gyrus; sLOC = superior lateral occipital cortex, superior division; preCG = precentral gyrus; SMA = supplementary motor cortex; SMG = supramarginal gyrus</item> </ulist> <p>Using a negative contrast, we also observed decreased functional connectivity (hypoconnectivity) between motor‐related brain regions and the cerebellar network for the RD group. Specifically, contrasts revealed decreased functional connectivity between a portion of the subcallosal cortex and the cerebellar network as well as between the right and left precentral gyrus and the cerebellar network in the RD group relative to the TD group (Figure 2a, Table 2).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-fig-0003.jpg" title="3 Relationship between reading fluency score and mean connectivity between cerebellar network and right precentral gyrus for the RD group. Stepwise regression identified reading fluency as a significant predictor of connectivity (F(1,32) = 6.52, p = .064; r2 = 0.14)" /> </p> <p></p> <p>Two out of the 20 ICA components were identified as belonging to the DMN. Contrasts revealed no significant differences between the two groups within each of the two DMN components.</p> <hd id="AN0148778214-21">Correlation between network connectivity identified through ICA and reading</hd> <p>We found a negative relationship between broad reading and the strength of functional connectivity between the sensorimotor network and the left angular gyrus cluster (β = −0.04; <emph>p </emph>= .003; r<sups>2</sups> = 0.52) specific to the TD group (corrected <emph>p</emph> = .036). A stepwise regression with the broad reading components shows that letter–word identification (<emph>F</emph>(<reflink idref="bib1" id="ref3">1</reflink>,<reflink idref="bib13" id="ref4">13</reflink>) = 14.85, <emph>p </emph>= .002; r<sups>2</sups> = 0.53) drove this relationship (Figure 4; corrected <emph>p</emph> = .018). Higher letter–word identification scores were associated with a stronger negative correlation between the sensorimotor network and language‐related brain regions.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-fig-0004.jpg" title="4 Relationship between decoding (letter–word identification) scores and mean connectivity between sensorimotor network and left angular gyrus for the TD group. Stepwise regression identified letter–word identification scores as a significant predictor of connectivity (F(1,13) = 14.85, p = .018, r2 = 0.53)" /> </p> <p></p> <p>There was also a significant negative relationship between broad reading and strength of functional connectivity between the cerebellar network and the right precentral gyrus (β = −0.03, <emph>p</emph> = .024; r<sups>2</sups> = 0.15); this was specific to the RD group. However, there was only a trend when corrected for multiple comparisons (<emph>p</emph> = .058). We performed a stepwise regression with the broad reading components (letter–word identification, reading fluency, and passage comprehension) to determine which component of broad reading was responsible for the correlation. Only reading fluency scores were a significant predictor of the strength of functional connectivity between the cerebellar network and precentral gyrus (<emph>F</emph>(<reflink idref="bib1" id="ref5">1</reflink>,<reflink idref="bib32" id="ref6">32</reflink>) = 6.52, <emph>p</emph> = .016; r<sups>2</sups> = 0.14). After adjusting for multiple corrections, this relationship showed a trend for significance (<emph>p</emph> = .064). Higher reading fluency scores were associated with greater negative functional connectivity between the cerebellar network and the right precentral gyrus (Figure 3).</p> <hd id="AN0148778214-23">FUNCTIONAL CONNECTIVITY WITH THE CEREBELLUM (SEED‐BASED) GROUP EFFECTS</hd> <p></p> <hd id="AN0148778214-24">Increased functional connectivity: RD greater than TD</hd> <p>Positive contrasts revealed increased functional connectivity between language processing and motor regions in the RD group relative to TD. Using the right crus 1 as a seed region, we observed increased functional connectivity to the right precuneus, bilateral paracingulate gyrus, the left posterior division of the cingulate cortex, and the anterior division of the cingulate cortex for the RD group relative to controls (Table 3). Lobule 6 of the right cerebellum displayed greater functional connectivity between the right superior division of the lateral occipital cortex. Using lobule 8 of the right cerebellum as a seed region we found increased functional connectivity to the left postcentral gyrus, left precentral gyrus, right middle temporal gyrus, left inferior temporal gyrus, right frontal pole, and left angular gyrus for the RD group.</p> <p>3 TableSignificant seed‐to‐voxel RD greater than TD normal contrast. XYZ coordinates are for maximal activity. For results where multiple brain regions comprise the significant cluster, we reported all the brain regions</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">Seed ROI</th><th align="left"><p>Contrast</p><p>Direction</p></th><th align="left"><p>Cluster</p><p>p‐FDR</p></th><th align="left"><p>Height</p><p>p‐uncorrected</p></th><th align="left">Cluster size (voxels)</th><th align="left">β</th><th align="left">t‐scores</th><th align="left">x y z</th><th align="left">Regions</th></tr></thead><tbody><tr><td align="left">R. Crus I</td><td align="left">Positive</td><td align="char" char="."><0.001</td><td align="char" char="."><0.001</td><td align="char" char=".">303</td><td align="char" char=".">0.20</td><td align="char" char=".">4.89</td><td align="left">0 46 –4</td><td align="left">R & L PCG</td></tr><tr><td align="left" /><td align="left" /><td align="char" char=".">0.002</td><td align="char" char="."><0.001</td><td align="char" char=".">239</td><td align="char" char=".">0.20</td><td align="char" char=".">4.58</td><td align="left">6 –50 48</td><td align="left">R Precun</td></tr><tr><td align="left" /><td align="left">Negative</td><td align="char" char=".">0.03</td><td align="char" char=".">0.001</td><td align="char" char=".">141</td><td align="char" char=".">−0.19</td><td align="char" char=".">−5.70</td><td align="left">−38 –10 18</td><td align="left">L COC</td></tr><tr><td align="left">R. Cereb 6</td><td align="left">Positive</td><td align="char" char="."><0.001</td><td align="char" char="."><0.001</td><td align="char" char=".">319</td><td align="char" char=".">0.21</td><td align="char" char=".">5.59</td><td align="left">26 –88 36</td><td align="left">R LOC, R OP</td></tr><tr><td align="left" /><td align="left">Negative</td><td align="char" char=".">0.001</td><td align="char" char="."><0.001</td><td align="char" char=".">248</td><td align="char" char=".">−0.18</td><td align="char" char=".">−5.07</td><td align="left">−60 –24 16</td><td align="left">L PostCG, L COC, L POC</td></tr><tr><td align="left" /><td align="left">Negative</td><td align="char" char=".">0.04</td><td align="char" char=".">0.003</td><td align="char" char=".">109</td><td align="char" char=".">−0.20</td><td align="char" char=".">−4.93</td><td align="left">50 –6 –4</td><td align="left">R PP</td></tr><tr><td align="left">R. Cereb 7</td><td align="left">Positive</td><td align="char" char=".">0.007</td><td align="char" char="."><0.001</td><td align="char" char=".">213</td><td align="char" char=".">0.19</td><td align="char" char=".">4.84</td><td align="left">−16 –54 42</td><td align="left">L Precun</td></tr><tr><td align="left" /><td align="left">Positive</td><td align="char" char=".">0.02</td><td align="char" char=".">0.001</td><td align="char" char=".">145</td><td align="char" char=".">0.18</td><td align="char" char=".">4.78</td><td align="left">10 –38 46</td><td align="left">R Precun, CG</td></tr><tr><td align="left">R. Cereb 8</td><td align="left">Positive</td><td align="char" char="."><0.001</td><td align="char" char="."><0.001</td><td align="char" char=".">520</td><td align="char" char=".">0.18</td><td align="char" char=".">6.92</td><td align="left">−8 –28 72</td><td align="left">L PostCG, L PreCG, L Precun</td></tr><tr><td align="left" /><td align="left">Positive</td><td align="char" char=".">0.001</td><td align="char" char="."><0.001</td><td align="char" char=".">279</td><td align="char" char=".">0.17</td><td align="char" char=".">6.24</td><td align="left">66 –42 8</td><td align="left">R MTG, R SMG</td></tr><tr><td align="left" /><td align="left">Positive</td><td align="char" char=".">0.002</td><td align="char" char="."><0.001</td><td align="char" char=".">238</td><td align="char" char=".">0.21</td><td align="char" char=".">5.88</td><td align="left">−66 –36 –20</td><td align="left">L ITG, L MTG</td></tr><tr><td align="left" /><td align="left">Positive</td><td align="char" char=".">0.02</td><td align="char" char="."><0.001</td><td align="char" char=".">149</td><td align="char" char=".">0.19</td><td align="char" char=".">5.29</td><td align="left">16 54 42</td><td align="left">R FP</td></tr><tr><td align="left" /><td align="left">Positive</td><td align="char" char=".">0.02</td><td align="char" char="."><0.001</td><td align="char" char=".">147</td><td align="char" char=".">0.19</td><td align="char" char=".">4.62</td><td align="left">−48 –50 25</td><td align="left">L AG</td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 Note</item> <item>6 FDR = false discovery rate; ROI = region of interest; AG = angular gyrus, COC = central opercular cortex, ICC = intracalcarine cortex, ITG = inferior temporal gyrus, LOC = lateral occipital cortex, MTG = middle temporal gyrus, OP = occipital pole, PCG = paracingulate gyrus, POC = parietal operculum cortex, PostCG = postcentral gyrus, PreCG = precentral gyrus, Precun = precuneous SMG = supramarginal gyrus</item> </ulist> <hd id="AN0148778214-25">Correlation in seed‐based analysis</hd> <p>We found a significant positive relationship between broad reading scores and the strength of functional connectivity between lobule 8 of the right cerebellum and the right frontal pole limited to the RD group (<emph>F</emph>(<reflink idref="bib1" id="ref7">1</reflink>,<reflink idref="bib32" id="ref8">32</reflink>) = 5.59, <emph>p</emph> = .024, r<sups>2</sups> = 0.15). However, this only trended toward significance after correction for multiple comparisons (<emph>p</emph> = .056). A stepwise regression revealed a positive relationship between letter–word identification scores and the strength of functional connectivity between the right lobule 8 of the cerebellum and the right frontal pole (<emph>F</emph>(<reflink idref="bib1" id="ref9">1</reflink>,<reflink idref="bib32" id="ref10">32</reflink>) = 7.89, <emph>p</emph> = .008, r<sups>2</sups> = .20; Figure 5), which trended towards significance after correction (<emph>p</emph> = .056).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-fig-0005.jpg" title="5 Relationship between decoding (letter–word identification) scores and mean connectivity between right lobule 8 and the right frontal pole for the RD group. Stepwise regression identified letter–word identification scores as a significant predictor of connectivity (F(1,32) = 7.89, p = .056, r2 = 20)" /> </p> <p></p> <p>Significant associations between broad reading scores and the strength of functional connectivity between lobule 8 of the right cerebellum and the left angular gyrus were found. The RD group (<emph>F</emph>(<reflink idref="bib1" id="ref11">1</reflink>,<reflink idref="bib32" id="ref12">32</reflink>) = 5.33, <emph>p</emph> = .028, r<sups>2</sups> = 0.14; corrected <emph>p</emph> = .049) and the TD group (<emph>F</emph>(<reflink idref="bib1" id="ref13">1</reflink>,<reflink idref="bib13" id="ref14">13</reflink>) = 5.32, <emph>p </emph>= .038, r<sups>2</sups> = 0.29; corrected <emph>p</emph> = .053) displayed a relationship between both broad reading scores and functional connectivity. Stepwise regression revealed that reading fluency scores were positively correlated with greater mean functional connectivity between lobule 8 of the right cerebellum and the left angular gyrus for the RD group (<emph>F</emph>(<reflink idref="bib1" id="ref15">1</reflink>,<reflink idref="bib32" id="ref16">32</reflink>) = 5.72, <emph>p</emph> = .023, r<sups>2</sups> = 15; corrected <emph>p</emph> = .081; Figure 6 left panel), whereas stepwise regression revealed a negative relationship between passage comprehension scores and mean functional connectivity values between the right cerebellum 8 and the left angular gyrus for the TD group (<emph>F</emph>(<reflink idref="bib1" id="ref17">1</reflink>,<reflink idref="bib13" id="ref18">13</reflink>) = 5.01, <emph>p</emph> = .042, r<sups>2</sups> = 0.28; corrected <emph>p</emph> = .049; Figure 6 right panel).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/5G5/01mar21/desc13022-fig-0006.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="desc13022-fig-0006.jpg" title="6 Relationship between reading performance and connectivity. Relationship between reading speed (fluency) scores and mean connectivity between the right lobule 8 and left angular gyrus for the RD group (F(1,32) = 5.72, p = .081, r2 = 15; left panel) and comprehension scores and mean connectivity between right lobule 8 and left angular gyrus for the TD group (F(1,13) = 5.01, p = .049, r2 = 0.28; right panel)" /> </p> <p></p> <hd id="AN0148778214-28">Decreased functional connectivity: RD greater than TD</hd> <p>There was decreased functional connectivity between the right crus 1 seed region and the left central opercular cortex and the left insular cortex for the RD group. Additionally, we observed decreased functional connectivity between the right cerebellum 6 seed region and the left central opercular cortex, the right planum polare and the left postcentral gyrus (Table 3). No other seed regions displayed decreased functional connectivity.</p> <hd id="AN0148778214-29">DISCUSSION</hd> <p>The primary aim of the current study was to investigate whether cerebellar and DMN functional connectivity as shown by rs‐fMRI differed in children and adolescents with reading challenges from their typically developing peers. The secondary aim of the study was to understand how functional connectivity relates to reading within the two groups. Independent component analysis revealed that the RD group exhibited abnormal functional connectivity in sensorimotor (Figure 2b,d), salience (Figure 2c), and cerebellar networks (Figure 2a) but not in the DMN. In partial support of our hypothesis, seed‐based analyses revealed differences in functional connectivity between language‐related regions within the cerebellum, and brain regions involved in sensorimotor and motor function. Moreover, children with RD had different patterns of functional connectivity in the cerebellar network, relative to the TD group, that were weakly associated with reading performance.</p> <p>Functional connectivity between the cerebellum, motor and language‐related brain regions was marginally related to reading performance scores in the RD group. We observed that better reading performance scores were related to a more <emph>negative</emph> functional connectivity between the cerebellar network and the right precentral gyrus (Figure 3), whereas a more <emph>positive</emph> functional connectivity between the right lobule 8, the left angular gyrus, and right frontal pole was related to better reading scores in this same group (Figure 6 left panel). However, these relationships only trended toward significance after correction for multiple corrections. In contrast, we observed the inverse relationship, more <emph>negative</emph> functional connectivity between the right lobule 8 and the left angular gyrus was associated with better reading performance scores, in the TD group (Figure 6 right panel). This is consistent with the general pattern of decreased functional specialization in the cerebellum observed in less proficient readers (Baillieux et al., 2009; Cullum, Hodgetts, Milburn, & Cummine, 2019); these individuals tend to show more widespread cerebellar activation during reading tasks rather than the discrete regional recruitment evident in typical readers. In addition, individuals with dyslexia maintain a pattern of right cerebral hemisphere recruitment when reading in fMRI‐based tasks (Hoeft et al., 2011; Waldie, Haigh, Badzakova‐Trajkov, Buckley, & Kirk, 2013). The present study builds on these findings by demonstrating that, in addition to unusual patterns of cerebellar and cerebral activation, reading difficulties are also associated with abnormal cerebro‐cerebellar functional connectivity.</p> <p>In partial support of our hypothesis, functional connectivity differences were observed but limited to the right side of crus 1, lobules 6, 7, and 8 of the cerebellum in the RD group. Considering there is an overlap between language‐related regions of the cerebellum and the DMN (Guell et al., 2018), we anticipated abnormal functional connectivity in crus 1 and 2 in the RD group. Instead we found aberrant functional connectivity between motor and working memory‐related areas of the cerebellum (lobules 6, 7, and 8). Specifically, lobules 6, 7, and 8 of the cerebellum showed increased functional connectivity with the precuneus, and pre‐ and postcentral gyrus. This finding is consistent with the notion that less efficient readers show decreased specialization in the cerebellum during reading (Baillieux et al., 2009; Cullum et al., 2019) and may recruit additional or task unrelated regions. Further, lobules 6 and 8 of the cerebellum are also a part of the sensorimotor resting‐state network (Guell et al., 2018), a network we observed to be increased in the RD group. Considering that reading involves a distributed and complex system of brain regions involved in motor, sensory, and language function, it is not surprising that functional connectivity differences were observed throughout the cerebellum.</p> <p>All seed‐based functional connectivity differences observed in the RD group were localized to the right cerebellum. This is consistent with previous results showing a right cerebellar hemisphere dominance in language‐related tasks and is also the focus of recent meta‐analytic work on the functional connectivity between the cerebellum and the cerebral network involved in reading (Alvarez & Fiez, 2018). For example, individuals with infarcts of the right cerebellum show impaired error detection and learning of a verb generation task (Fiez, Petersen, Cheney, & Raichle, 1992; Silveri, Leggio, & Molinari, 2012). Moreover, children with right cerebellar tumors show poor verbal and literacy performance compared to children with left cerebellar tumors (Scott et al., 2010). More recently, children with dyslexia showed an increase in rs‐fMRI between the right crus 1 of the cerebellum and the left angular gyrus, posterior superior temporal gyrus, and inferior frontal gyrus, compared to controls (Ashburn et al., 2020). Additionally, we found that reading performance as assessed by letter–word identification (decoding/ sight‐word recognition) and reading fluency (speed) scores were associated with increased functional connectivity between in the right lobule 8 and right frontal pole and left angular gyrus, respectively. These results are consistent with the cerebellar deficit hypothesis (Nicolson et al., 2001), which theorizes that the cerebellar procedural learning system is crucial for the automaticity involved in fluent reading and rapid word recognition by sight. Interestingly, passage comprehension did not account for a significant portion of the variance except in one (Figure 6 right panel) of the stepwise regressions. At least one other study investigated reading and comprehension in children and adolescents who were treated for benign cerebellar tumors. In this work, participants had to first silently read a list of instructions, then act them out. While the patient group displayed a marked difficultly in silent reading, they had no differences in comprehension as scored by miming the instructions they had to silently read (Ait Khelifa‐Gallois et al., 2015). Thus, our findings provide more support for a right cerebellum hemisphere dominance in the automatization of reading but not necessarily in comprehension.</p> <p>In contrast to our hypothesis, we found no difference between the DMN between the two groups. Abnormalities in the DMN have been shown across a variety of healthy and clinical populations. For example, aberrant patterns of rs‐fMRI in the DMN has been shown in Alzheimer's disease (Ferreira & Busatto, 2013), Parkinson's disease (Hacker, Perlmutter, Criswell, Ances, & Snyder, 2012; Wu et al., 2009), and in older adults (Wang et al., 2013). It has been proposed that the DMN is sensitive and the first network to show aberrant functional connectivity (Chen et al., 2015; Greicius, Krasnow, Reiss, & Menon, 2003; Wang et al., 2013). These data have led to the suggestion that the DMN might be used as a diagnostic measure in patient populations, showing changes in activity even before the onset of behavioral symptoms. However, in the current study, there were no group differences in the DMN. This null result indicates that the integrity of higher order brain networks, at least in the context of the DMN, was not compromised in our RD group.</p> <p>The RD group in the current study displayed increased functional connectivity between the salience network and bilateral supplementary motor areas (SMAs) relative to controls. The salience network is thought to be an integral hub (Menon & Uddin, 2010), exerting its influence on the DMN and the dorsal attention network (Zhou et al., 2018). Despite not observing aberrant functional connectivity between the salience network and brain regions involved in the DMN and dorsal attentional network, we observed increased functional connectivity to the SMA limited to the RD group, which has been implicated in attention. For example, an increase in activation in the SMA was observed during a concurrent counting and a motor task, but not during the motor task alone (Johansen‐Berg & Matthews, 2002). Moreover, using subdural recordings in humans, it was shown that the SMA is involved in anticipation of and attention to upcoming stimuli in a GO/NOGO task (Ikeda et al., 1999). Our findings suggest that the salience network does not influence the DMN and dorsal attention networks, at least not in this current population. Instead, the salience network may shift functional connectivity to other brain regions outside the DMN and dorsal attentional networks also involved in attention, potentially increasing attentional demands in the RD group. Whether unconventional brain regions associated with attention show increased functional connectivity similar to the salience network needs to be investigated in future studies.</p> <p>Relative to the TD group, the RD group displayed increased functional connectivity strength between the sensorimotor network and angular gyrus. However, a negative relationship was observed between performance on letter–word identification and functional connectivity strength limited to the TD group. Specifically, better performance scores were associated with weaker functional connectivity strength between the angular gyrus and the sensorimotor network (Figure 4). In task‐based fMRI studies, the angular gyrus has been implicated as an area that receives multisensory inputs and is involved in language‐based tasks including semantic processing, word reading (Horwitz, Rumsey, & Donohue, 1998; Vigneau et al., 2006), and verbal working memory (Vigneau et al., 2006; Yang et al., 2015). In a meta‐analysis, the left and right angular gyrus were part of a language‐related network which also included the right superior parietal lobe, right supramarginal gyrus, the left superior temporal lobe, bilateral premotor and left prefrontal cortex (Rosselli, Ardila, & Bernal, 2015). However, the precise role of the left angular gyrus is unknown. One study suggests that it is not specialized for language but given its long‐range functional connectivity to other brain regions, that it is instead specialized in a role of information transmission (Chai, Mattar, Blank, Fedorenko, & Bassett, 2016). Thus, in the context of our data, the angular gyrus may be related to decoding.</p> <p>The current study is not without limitations. One limitation was the number of correlations performed between mean rs‐fMRI connectivity values and reading performance, which increases the possibility of spurious findings. Understanding the relationship between brain region, network, and function in humans has proven to be a difficult endeavor in neuroscience (Pessoa, 2014). When corrected for multiple comparisons, many of these relationships trended toward significance, especially in the RD group. However, the associations found between functional connectivity and reading performance here complement previous casual relationships between the cerebellum and reading (Fiez et al., 1992; Scott et al., 2010; Silveri et al., 2012), suggesting that the associations that emerged were not type I errors. Moreover, we limited the regressions to the significant resting‐state clusters that emerged between the two groups and choose not to explore other, unrelated behavioral measures.</p> <p>Similarly, another potential limitation is the lack of a significant relationship between reading performance and rs‐fMRI connectivity values in the RD group. Our data suggest that individuals in the RD group may be using different networks and brain regions to support their reading. Given the amount of variance between each individual's connectivity measures, it is possible that we were unable to identify any single network or brain region responsible for reading in the RD group. An example of a variable, compensatory connectivity network comes from previous work in individuals with stroke (Wadden et al., 2015). Wadden et al. (2015) found differences in the motor network engaged between controls and individuals who have had a stroke during an implicit motor learning task. Taken together, it is possible that the altered networks employed by those in the RD group reflect a less efficient attempt to support reading, which leads to the poorer behavior of the RD group.</p> <hd id="AN0148778214-30">Conclusion</hd> <p>The current results demonstrate that relative to age‐matched healthy controls, child and adolescent struggling readers show rs‐fMRI connectivity abnormalities in cerebellar, sensorimotor, and salience networks as well as in specific cerebellar regions. Moreover, functional connectivity was associated with reading performance for both groups; however, the direction of the association was group dependent suggesting that resting‐state abnormalities observed in the RD group may contribute to poor reading performance. These finding have implications for potentially identifying biomarkers in children and adolescents with reading difficulties. Overall, our work advances knowledge of how functional brain connectivity supports reading.</p> <hd id="AN0148778214-31">CONFLICT OF INTERESTS</hd> <p>The authors declare of conflict of interests.</p> <hd id="AN0148778214-32">DATA AVAILABILITY STATEMENT</hd> <p>The data that support the findings of this study are available from the corresponding author upon reasonable request.</p> <ref id="AN0148778214-33"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref3" type="bt">1</bibl> <bibtext> Ait Khelifa‐Gallois, N., Puget, S., Longaud, A., Laroussinie, F., Soria, C., Sainte‐Rose, C., & Dellatolas, G. (2015). Clinical evidence of the role of the cerebellum in the suppression of overt articulatory movements during reading. A study of reading in children and adolescents treated for cerebellar Pilocytic Astrocytoma. Cerebellum, 14 (2), 97 – 105, https://doi.org/10.1007/s12311‐014‐0612‐1</bibtext> </blist> <blist> <bibl id="bib2" type="bt">2</bibl> <bibtext> Alvarez, T. 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  Data: <searchLink fieldCode="AR" term="%22Greeley%2C+Brian%22">Greeley, Brian</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5117-3866">0000-0001-5117-3866</externalLink>)<br /><searchLink fieldCode="AR" term="%22Weber%2C+Rachel+C%2E%22">Weber, Rachel C.</searchLink><br /><searchLink fieldCode="AR" term="%22Denyer%2C+Ronan%22">Denyer, Ronan</searchLink><br /><searchLink fieldCode="AR" term="%22Ferris%2C+Jennifer+K%2E%22">Ferris, Jennifer K.</searchLink><br /><searchLink fieldCode="AR" term="%22Rubino%2C+Cristina%22">Rubino, Cristina</searchLink><br /><searchLink fieldCode="AR" term="%22White%2C+Katherine%22">White, Katherine</searchLink><br /><searchLink fieldCode="AR" term="%22Boyd%2C+Lara+A%2E%22">Boyd, Lara A.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Developmental+Science%22"><i>Developmental Science</i></searchLink>. Mar 2021 24(2).
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 13
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2021
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Reading+Processes%22">Reading Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+Hemisphere+Functions%22">Brain Hemisphere Functions</searchLink><br /><searchLink fieldCode="DE" term="%22Decoding+%28Reading%29%22">Decoding (Reading)</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Rate%22">Reading Rate</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Comprehension%22">Reading Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Difficulties%22">Reading Difficulties</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescents%22">Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/desc.13022
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1467-7687
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Reading is a critical neurodevelopmental skill for school-aged children, which requires a distributed network of brain regions including the cerebellum. However, we do not know how functional connectivity between the cerebellum and other brain regions contributes to reading. Here we used resting-state functional connectivity to understand the cerebellum's role in decoding, reading speed, and comprehension in a group of struggling readers (RD) and a group of adolescents and children with typical reading abilities (TD). We observed an increase in functional connectivity between the sensorimotor network and the left angular gyrus, left lateral occipital cortex, and right inferior frontal gyrus in the RD group relative to the TD group. Additionally, functional connectivity between the cerebellum network and the precentral gyrus was decreased and was related to reading fluency in the RD group. Seed-based analysis revealed increased functional connectivity between crus 1, lobule 6, and lobule 8 of the cerebellum and brain regions related to the default mode network and the motor system for the RD group. We also found associations between reading performance and the functional connectivity between lobule 8 of the cerebellum and the left angular gyrus for both groups, with stronger relationships in the TD group. Specifically, the RD group displayed a positive relationship between functional connectivity, whereas the TD group displayed the opposite relationship. These results suggest that the cerebellum is involved in multiple components of reading performance and that functional connectivity differences observed in the RD group may contribute to poor reading performance.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2021
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1286706
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1286706
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/desc.13022
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
    Subjects:
      – SubjectFull: Reading Processes
        Type: general
      – SubjectFull: Brain Hemisphere Functions
        Type: general
      – SubjectFull: Decoding (Reading)
        Type: general
      – SubjectFull: Reading Rate
        Type: general
      – SubjectFull: Reading Comprehension
        Type: general
      – SubjectFull: Reading Difficulties
        Type: general
      – SubjectFull: Adolescents
        Type: general
      – SubjectFull: Children
        Type: general
      – SubjectFull: Correlation
        Type: general
    Titles:
      – TitleFull: Aberrant Cerebellar Resting-State Functional Connectivity Related to Reading Performance in Struggling Readers
        Type: main
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            NameFull: Greeley, Brian
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            NameFull: Weber, Rachel C.
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            NameFull: White, Katherine
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            NameFull: Boyd, Lara A.
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            – D: 01
              M: 03
              Type: published
              Y: 2021
          Identifiers:
            – Type: issn-electronic
              Value: 1467-7687
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              Value: 24
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            – TitleFull: Developmental Science
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