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Supplemental material, sj-docx-1-pss-10.1177_0956797621993111 for The Effects of Handwriting Experience on Literacy Learning by Robert W. Wiley and Brenda Rapp in Psychological Science

Supplemental material, sj-docx-1-pss-10.1177_0956797621993111 for The Effects of Handwriting Experience on Literacy Learning by Robert W. Wiley and Brenda Rapp in Psychological Science

Introduction. While task-based fMRI has been used extensively to study the functional neural networks that instantiate cognitive functions, there is increasing interest in analyzing the activity of the brain while it is not performing a task – in the resting state (RS). In RS-fMRI, participants lie in a relaxed awake state during fMRI scanning, and correlations of the activation time-series between their different brain areas are analyzed. These analyses have revealed many of the same networks identified in task-based fMRI, including the default-mode network (DMN), the dorsal attention network, the motor network, etc. Various network properties have been studied; for example, some networks have stronger correlations between the nodes of the same network (to which we refer as “within-network coherence”), than between nodes from different networks (“across-network coherence”), resulting in clustering of network nodes (e.g., Cole et al., 2014). There has been great interest in understanding how RS network connectivity may be affected by brain illness or injury (e.g., Finn et al., 2014, Park et al., 2011). However, one domain that has received scarce attention even in studies with neuro-typical individuals is orthographic processing (reading and spelling). We report on a study that examines the orthographic processing network (OPN) in neuro-typical individuals and in individuals with acquired dysgraphia subsequent to stroke, examining how this network can be affected by brain injury and how it responds to rehabilitation. Specifically, we examine the possibility that rehabilitation may lead to normalization of RS network connectivity such that the properties of the damaged network increasingly resemble those of intact networks. Methods. Participants are eight neuro-typical adults (NTA), and three adults with left-hemisphere stroke and acquired dysgraphia. NTAs had two RS-fMRI scans in the same session; dysgraphics had one scan, followed by 2-4 months of spelling rehabilitation, and two more scans. Regions of interest (ROIs) were identified using coordinates of the OPN (Turkeltaub et al., 2001) and the DMN (Laird et al., 2009). Within-network coherence corresponded to the average RS-fMRI correlations between every pair of ROIs within each network; across-network coherence was the average correlation between every pair of ROIs from the two different networks (Song et al., 2011). Results (Figure 1). (1) Each NTA showed stronger within-network coherence for the OPN than across-network coherence between OPN and DMN. (2) Before treatment, two of the dysgraphics showed weaker within-network coherence for the OPN than across-network coherence between OPN and DMN. Following treatment all three dysgraphics showed the same network coherence pattern as the NTAs. Discussion. The NTA findings indicate that the relationship between orthographic and default-mode networks is characterized by greater within- vs. across-network connectivity. Furthermore, we show for the first time a pattern of increasing within/across network “coherence normalization” following spelling rehabilitation. Additional dysgraphic participants and other networks (language, sensory-motor, etc.) will be analyzed to develop a better understanding of the RS orthographic network and its response to damage and recovery. Acknowledgements. The work is part of a multi-site, NIDCD-supported project examining language recovery neurobiology in aphasia (DC006740). We thank Melissa Greenberger and Xiao-Wei Song.

Introduction. While considerable research has examined the optimal intensity of aphasia treatment (Robey, 1998), there has been little work on the optimal distribution of practice within the treatment period. Research on learning and memory indicates that studied material is remembered longer when the same amount of study is distributed across multiple sessions rather than being concentrated (Pashler, et al, 2007). In this study we examine the effectiveness of distributed compared to “clustered” treatment schedules for individuals with acquired dysgraphia. Using the multiple regression approach of generalized Linear Mixed-Effects Models (LMEMs) (Barr et al., 2013) we evaluate the effectiveness of training words according to different training schedules. In addition to modeling the main effects of treatment while controlling for variables like word length and frequency, LMEMs address problems in repeated measures designs such as uneven spacing of measurements (Barr et al., 2013) and can take into account random variability in the treatment items. Thus, LMEM has a number of features that make this a promising approach to evaluating data from rehabilitation studies. Methods. Behavioral spelling treatment was administered to 5 individuals (2 female) with acquired dysgraphia resulting from a single left hemisphere stroke; ages were 46-81 and all were at least 2 years post stroke at enrollment. Study phases: pre-training evaluation, spelling training, post-training evaluation, 3 month waiting period, and follow-up evaluation. Individualized training word sets were selected for each participant depending on type and severity of dysgraphic deficit (training: n=40). Treatment used the spell-study-spell technique (Rapp, 2005) and both training schedules were applied within participant on different word subsets. In the distributed training schedule words were trained once per session (every 2-3 sessions), while in the clustered schedule, words were trained 3-4 times per session (every 6-8 sessions), for the same total number of training trials per word per schedule type (total training trials = 13-21). LMEM was used to analyze accuracy data for each individual. Predictor variables were included to evaluate the main effects of session, word type (generalization, training) , training schedule (distributed, clustered) and interactions between these predictors; by-item random intercepts and slopes were included as well. Results. 1) 5/5 individuals significantly improved their accuracy over the training period 2) 4/5 individuals showed larger training effects for distributed vs. clustered training (2 were significant or marginally so) 3) 4 /5 individuals showed significant generalization (improvement on untrained items) 4) 3 of the 4 individuals with follow-up data showed no significant learning loss for trained items at 3-month follow-up. Discussion. Using LMEM analysis techniques we analyzed a complex treatment data set for individual participants. The significant effects of training, generalization and maintenance of learning gains 3-months after training support other findings of successful dysgraphia treatment in the chronic stage. Findings also provide support for the importance of training schedule, an area that requires continued investigation. Analysis of additional participants and time points is anticipated. Acknowledgements. The work is part of a multi-site, NIDCD-supported project examining language recovery neurobiology in aphasia (DC006740). We thank Abigail Lo and Alexandra Gordon.

Lexical orthographic information provides the basis for recovering the meanings of words in reading and for generating correct word spellings in writing. Research has provided evidence that an area of the left ventral temporal cortex, a subregion of what is often referred to as the visual word form area (VWFA), plays a significant role specifically in lexical orthographic processing. The current investigation goes beyond this previous work by examining the neurotopography of the interface of lexical orthography with semantics. We apply a novel lesion mapping approach with three individuals with acquired dysgraphia and dyslexia who suffered lesions to left ventral temporal cortex. To map cognitive processes to their neural substrates, this lesion mapping approach applies similar logical constraints to those used in cognitive neuropsychological research. Using this approach, this investigation: (a) identifies a region anterior to the VWFA that is important in the interface of orthographic information with semantics for reading and spelling; (b) determines that, within this orthography-semantics interface region (OSIR), access to orthography from semantics (spelling) is topographically distinct from access to semantics from orthography (reading); (c) provides evidence that, within this region, there is modality-specific access to and from lexical semantics for both spoken and written modalities, in both word production and comprehension. Overall, this study contributes to our understanding of the neural architecture at the lexical orthography-semantic-phonological interface within left ventral temporal cortex.

Introduction: There is a fundamental distinction in memory systems between long-term memory and working memory. This distinction is prominent in virtually every cognitive domain including written (and spoken) word production, where the long-term storage and retrieval of lexical information is distinguished from working memory processes deployed during production. These latter processes are responsible for maintaining the activation level of the representations retrieved from long-term memory, serial selection of segments, inhibition of produced segments, etc. In the orthographic domain, evidence regarding the processes and representations involved in orthographic working memory (OWM) has come primarily from investigations of acquired dysgraphia subsequent to brain injury (Buchwald & Rapp, 2009; Caramazza & Miceli, 1990; Costa, et al, 2011). However, the neural bases of OWM (also referred to as the graphemic buffer) has not been extensively examined. In this research we present findings from the first evaluation of brain lesion overlap in a set of individuals with well-documented OWM impairments. Methods: The lesions of 9 right-handed individuals with left-hemisphere strokes and well-documented OWM deficits were examined. All individuals had deficits affecting OWM and not orthographic lexical or sublexical processes. There were 6 males, 6 native English speakers, and 3 native Italian speakers. Neuroimaging modalities included 3 CT scans and 6 T1-weighted MRI scans. MRIcron was used to map each lesion. Normalization was carried out in SPM8 with non-linear normalization parameters derived from the intact tissue, not the lesion volume (Brett, Leff, Rorden, & Ashburner, 2001). Normalized lesion maps were overlaid on a template brain, and regions of high density lesion overlap were defined as regions with 4 or more overlapping lesions. Results: The analysis (see Figure 1) revealed three left hemisphere regions of high density lesion overlap (geometric centers in MNI coordinates): (1) along the intraparietal sulcus (IPS), with primary concentration in the anterior region (-36, -49, 39); (2) the inferior frontal junction (IFJ;-44, -11, 38) and (3) the insula (-43, 5, 0). Eight of the nine individuals had lesions affecting the IPS region, while both the IFJ and the insula regions were affected by 4 of the lesions; there was one individual whose lesion only impacted the insula region. General Discussion: First, these results reveal a neurotopography of OWM lesion sites that is well-aligned with results from neuroimaging of orthographic working memory in neurally intact participants (Rapp & Dufor, 2011). Second, the dorsal neurotopography of the OWM lesion overlap is clearly distinct from what has been reported for lesions associated with either lexical or sublexical deficits (e.g., Henry, Beeson, Stark, & Rapcsak, 2007; Rapcsak & Beeson, 2004); these have, respectively, been identified with the inferior occipital/temporal and superior temporal/inferior parietal regions. These neurotopographic distinctions support the claims of the computational distinctiveness of long-term vs. working memory operations. The specific lesion loci raise a number of questions to be discussed regarding: (a) the selectivity of these regions and associated deficits to orthographic working memory vs. working memory more generally (b) the possibility that different lesion sub-regions may correspond to different components of the OWM system.