Making sense of the DtD task

In the remaining sections of the discussion, the author will address the following points. First, what is the putative nature of the DtD task measures that were found to be unique contributors to the model explaining variance in reading? What difficulties these measures could reflect and the potential causal link between these measures will be discussed. In this section, speculations as to why the DtD task seems to be helping in predicting reading will be provided trying to link with the alternative to phonological processing deficit theories in the literature, which will lead to further research questions. From the correlations between the DtD measures and the established dyslexia screening tests shown in Chapter 4, that were revisited in the current chapter, one cannot conclude univocally what does the DtD measure, but current study shows that its components play a unique role in reading. Possible explanations for the DtD measures will be now discussed.

Initially, at the pilot study stage, when the author considered the nature, cognitive and motor requirements of the task, it was suggested that the task requires visual attention, perhaps divided attention between the two panels on the screen and the graphics tablet requiring participant to dissociate the eye and hand gaze in line with automaticity and visual defictis. Also, it was expected that the task measures motor skills in line with the cerebellar theory (Nicolson et al., 1995).

As the DtD task is novel, it is difficult to pin point precisely what it measures. However, there have been some tasks reported in the literature that are somewhat similar to the DtD task (Fawcett & Nicolson, 1994; Stoodley et al., 2006) and could aid the understanding of the DtD task. Such tasks are speeded motor tasks created in line with the cerebellar deficit hypothesis first proposed by Nicolson et al. (1995). The cerebellum, as previously discussed in Chapter 2, is vital for smooth coordination of rapid movements. Children and adolescents with dyslexia were slower than their age- and IQ-matched peers on the Annett peg-moving task (Fawcett & Nicolson, 1994). In this task, children were required to move pegs, which were

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previously placed in the top row of a board by the experimenters, with the dominant hand as quickly as possible, jumping over the empty row into the third row of holes, while holding the board steady with the non-dominant hand. Similarly to the DtD task, this task required a novel, speeded hand movement. The peg-moving task showed group differences in time taken to complete the series of movements. There were no significant differences between the poor and typical readers in the time they took to complete the DtD task; however there were differences in the measure taking into account the speed-accuracy trade-offs (TimeTotal for dominant hand) which indicates that poor children were compromised when drawing the entire pattern and the time they took was considered. The TimeTotal measure also was a significant predictor of reading scores (explaining 4.4% of variance) on its own. Stoodley et al.’s (2006) study, using a rapid pointing task, showed that the pointing scores combining speed and accuracy contributed significantly to the variance in literacy skills. Although the tasks differed on some key aspects, unlike the DtD task the peg- moving task did not require one to dissociate between eye and the hand gaze, the similarity of those tasks and the findings obtained may point one to the assumption that the DtD task can be construed under the cerebellar deficit theory.

Drawing on the last point, the current investigation did not reveal significant relationships between any of the DtD measures and the Bead Threading task associated with fine motor skills and thus the cerebellar functioning. It is unlikely that the DtD task represents a purely “motor” task, then. Another explanation may be that the Bead Threading task may not be a reliable dyslexia indicator. Performance on the Bead Threading task was not correlated with reading scores which resonates with Barth et al.'s (2010) findings also indicating no association between the Bead Threading performance and academic performance. Similarly, Carroll et al.’s (2016) study did not find motor skills to be predictive of reading level group membership but did find significant group differences (exactly the same pattern of results was found here). Poor readers in the present study were also compromised on the Bead Threading task comparing to typical readers. Also, in the current study there was not a single poor reader whose only deficit was in the Bead Threading task. There were children who showed this deficit along with another deficit, such as DtD, RAN and memory, however. It is possible that the Bead Threading task may not be the best proxy of cerebellar functioning or that individuals with dyslexia may have deficits

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in a range of cerebellum – related functions and this task may not reflect that. Studies using a range of different motor tasks, such as toe tapping, arm shaking and postural stability (Fawcett & Nicolson, 1999), eye-blink conditioning (Nicolson, Daum, Schugens, Fawcett & Schulz, 200) and time estimation (Nicolson et al, 1995) showed deficits in children with dyslexia. The current investigation would, therefore, benefit from adding more measures of cerebellum – dependent abilities.

The DtD measures compromised in poor readers could reflect a deficit in motor skill learning which would also be in line with the cerebellum deficit theory. Cerebellar impairment may also affect automatisation of skills; the greater its impairment the greater the range of deficits displayed by the poor readers (Nicolson & Fawcett, 1999). Sela and Karni (2012) showed evidence for language-independent deficits in dyslexia that are related to recruitment of motor systems to perform a task requiring learning a new movement sequence. The authors distinguished between a so-called ‘on-line’ learning that can be observed within a session, and an ‘off-line’ learning that reflects between-session gains. The latter gains require time and sleep to be expressd, reflecting procedural memory consolidation processes (e.g., Karni et al., 1998), and could not be investigated in the current study as children completed the DtD task only once. It could be argued, however, that the significantly greater total errors made by children identified as poor readers were due to their poor on-line motor skill learning. The task consisted of six trials per each hand so the children would be expected to show improvement with each trial that would lead to better overall score as the total score represents the mean of all six trials. The significantly better score of typical readers may be a reflection of these volitional skills learning processes as being more effective than in children with dyslexia. This only relates to the motor skills acquisition that was arguably measured by the Total Error and Time measures.

The meaning of different results shown on scores obtained while using dominant vs non-dominant hand could be interpreted in the context of the already mentioned ‘on- line’ learning, but only to some extent. The Total Error and Time measures did not differ between groups when the non-dominant hand was used (performance using this hand was always measured after the dominant hand was used). This may indicate that the task could have been too difficult as it required the use of a hand that was

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less often practiced hence there might have been more noise, more variability within each of the groups, and the comparisons did not reveal any differences. The ‘on-line’ learning of these completely new motor skills would require a lot more practice. Beyond the motor skills, however, an interesting cognitive mechanisms may be drawn upon when it comes to the Direction Ratio measure. The lack of group differences in this measure in trials where the dominant hand was used may be fairly easily explained by the fact that all children needed some time to adjust to the rules of a new task and both groups of readers struggled equally. However, when they switched to the non-dominant hand the group differences were found. Children who were indicated as typical readers did not confuse the direction of the first line as much as those identified as poor readers. As the patterns of the dots were repeated (in random order) it is possible that implicit learning of the sequences by the time children saw six patterns took place. This learning was not as effective in poor readers though.

It can be assumed that different DtD measures reflect different skills as they are not strongly correlated with each other. One of the most interesting measures in the DtD task that seemed to be important from the onset of the pilot study were the measures related to the first sector. Similarly to the Touch Sequence Task (TST), developed by Sosnik, Hauptmann, Karni, and Flash (2004) and Sosnik, Shemesh, and Abeles (2007), in which participants were asked to perform rapid and accurate trajectories with their hand, the DtD task required a number of pre-motor processes that perhaps are reflected in the first sector measures. These pre-motor processes could include visual perception, decision making, initiation of a movement and recruitment of motor systems engaging complex feed-forward processes and sensorimotor loops (Sosnik et al., 2004). The first sector measures may also reflect processes such as hand-eye coordination which would be partially supported by its significant correlation with the block design task also requiring such a coordination (Wechsler, 1993, 2004, 2013). What is more, Sela and Karni (2012) suggested that the same parameters may correspond to different sub-systems at different stages of a task practice. This notion was also supported by studies showing different neural representations depending on the level of experience (Bock & Schneider, 2001; Hikosaka, et al. 1999; Karni et al., 1998; Korman, Raz, Flash, & Karni, 2003). Researchers indicated chunking and co-articulation processes that may change

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movement routine with practice (Engel, Flanders, & Soechting, 1997; Hikosaka, et al. 1999; Sosnik et al., 2004).

Another aspect that could have affected children’s performance on the DtD task was their visual attention. This was not tested empirically in the current study. However, further exploration of this would be an important future research direction. In line with a multifactorial view of dyslexia, difficulties of individuals with dyslexia in processing multi-element strings have been shown in the literature (Bednarek et al., 2004; Hawelka & Wimmer, 2005; Pammer et al., 2004; Valdois et al., 2003). Such difficulties might reflect the allocation of attention deficits which could perhaps explain difficulties in the first sector of the DtD task.

Another potential theoretical framework in the context of which the DtD can be interpreted is one of the biological explanations of dyslexia, as discussed in chapter 2, focusing around the visual aspects. The magnocellular-dorsal (MD) deficit hypothesis suggests that cognitive mechanisms controlled by the MD pathway may precede the orthographic-to-phonological mapping that is crucial for successful reading. The MD pathway also is believed to provide a mechanism for the early selection of features in space (e.g., Vidyasagar, 1998) therefore it is possible that it may be related to the DtD’s first sector error measures. This hypothesis will be further tested in the following chapter.

5.5 Limitations and directions for further research

Children were categorised as poor readers on the basis of only two readings tests measuring the speed accuracy of non-word and real words reading. This identification, although practised by many researchers (e.g., Carroll et al., 2016; Gori et al., 2016) is not as accurate as a professional diagnosis would be. Also, the reading tests were administered either one, two or three years after the baseline measure and the scores were combined. Data analysis did not allow distinguishing between the long and short term predictors: some studies suggest that some predictors may be more or less stable over time (Rose, 2009). Although the baseline sample size was suitable, not all children took part in all follow-up session, and some children did not complete some of the tasks leading to a fairly substantial loss of participants. As the sample was unselected, the number of children identified as poor

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readers was not sufficient for some analyses to achieve adequate power. These results then need to be considered with caution.

Further studies should explore the above mentioned explanations for the DtD task in order to find out what is the nature of this task’s measures and whether the contribution of these measures to the model predicting reading is due to motor skill acquisition, attentional aspects or low- and high-level visual processing. The importance of the latter processes is addressed in the following chapter.

In term of causality, often researchers conduct a comparison of performance between poor readers and younger reading-level-matched children which can reveal any discrepancies found between the groups that cannot be attributed to their differing reading experience (Bryant & Goswami, 1986; Goswami & Bryant, 1989). The current study did not incorporate such a design due to a small number of children indicated as poor readers who could be matched for reading level. Future studies should, however, include such an analysis.

5.6 Conclusion

The study presented in the current chapter seems to provide some evidence for the DtD task helping to identify reading problems in the long term but little evidence for the DtD being a reliable stand-alone screener. An encouraging finding was that there were three children who displayed single deficit that was in the DtD task. This

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indicates that there may be a subgroup of poor readers who do not show any of the phonological or reasoning problems but can be identified by means of the DtD task. At this point, it is clear that the DtD measures are associated with some abilities that are important for reading, as one of the DtD measures added to the prediction model; however, the results did not reveal what those skills are. The implications of the current study are that focusing solely on phonological and language related difficulties may not be enough to screen reliably for dyslexia in young children. These are practical implications suggesting a need of a broad range of tests required in order to capture all of the at risk children. The next chapter will explore visual aspects of poor and typical readers and it will aim to investigate if the DtD measure is related to them.