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The analyses reported in this chapter aimed to determine whether cognitive mechanisms underlying inattention were different in term-born and very preterm children. It aimed to expand on previous research by comparing very preterm children to a sample of term-born children who showed similar variance in parent rated inattention. It also aimed to account for the effects of variation in lower level cognitive processes when examining the influence of executive functioning. Overall, it was found that children born very preterm displayed poorer memory and visuo- spatial processing, but better processing speed than children born at term. In both groups more severe parent-rated inattention was predicted by poorer short term memory (verbal and visuo-spatial) and poorer visuo-spatial working memory, and in children born very preterm, it was also predicted by slower processing speed. These findings are discussed in more detail below.

3.5.1 Mechanisms underlying inattention

The selection of a term-born sample with similar levels of inattention is an advantage when comparing mechanisms that underlie inattention between preterm and term- born children. Unlike previous studies, interpretations of any differences emerging between the associations observed in the two groups are not restricted by insufficient variation in inattention ratings in the term-born comparison group. Overall, it was observed that in both very preterm and term-born children, inattentive behaviour was associated with specific areas of weakness rather than with cognitive performance difficulties across the board. These findings are discussed in greater detail below.

As hypothesised, visuo-spatial working memory was associated with inattention in both term-born and very preterm children. This builds on previous findings that working memory is a key factor underlying inattention in preterm (Aarnoudse-Moens et al., 2012; Mulder et al., 2011b; Nadeau et al., 2001) and term-born children (Gathercole et al., 2008). The findings here specify the role of visuo-spatial working memory over and above verbal working memory. This fits with findings that have been relatively well established in ADHD samples (Martinussen, Hayden, Hogg-

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Johnson, & Tannock, 2005), as well as typically developing children (Gathercole et al., 2008), and preterm samples (de Kieviet et al., 2012). These findings go beyond existing research by providing evidence to show that while short term memory explains some of the variance in parent-rated inattention, even when accounting for this and for other aspects of lower level cognitive processing, visuo-spatial working memory predicts additional unique variance in inattention. Interestingly, verbal working memory did not explain sufficient variance beyond that explained by basic cognitive processing. By directly comparing term-born and very preterm samples with similar levels of inattention, it is possible to conclude that poor memory across multiple domains is common to inattention in both groups.

My results were consistent with the hypothesis that motor processing speed would predict inattention in the very preterm group, but not the term-born group, echoing the findings of Mulder et al. (2011b). Moreover, with the use of a larger term-born sample matched to the preterm group on inattention, this study confirmed that this association was restricted to the very preterm children only, a finding that emerged in the Mulder study but could not be confirmed due to the small sample size and the fact that their levels of attention were higher than that of the preterm children. Although overall processing speed was better in the children born very preterm than in the children born at term who displayed similar levels of inattention (which will be discussed below), post hoc correlations splitting the preterm children into better and poorer attenders demonstrated that the association between inattention and processing speed in this group was driven by children with poorer than average parent-rated inattention. This suggests that slower motor processing speed is a risk factor for inattention in children born very preterm. While the findings here are consistent with some prior research (Mulder et al., 2011b), other studies have failed to find an association between processing speed and behavioural difficulties, (Aarnoudse-Moens et al., 2012; de Kieviet et al., 2012). These contrary findings are likely to be due to differences in the task used to measure processing speed and differences in the outcome measures. Processing speed is a difficult concept to define, with most measures comprising the combination of a variety of different

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mental ‘processes’ (e.g. detection of stimulus, evaluation of stimulus, initiation of motor response), any of which may be impaired. Aarnoudse-Moens et al. (2012) and de Kieviet et al. (2012) used computerised response time tasks to assess processing speed, measures that are averaged over a variety of trials and susceptible to interference from lapses in attention. In contrast, Mulder et al. (2011b) used a motor processing speed task in which the child was required to circle targets as quickly as possible, and a verbal processing speed task in which they were required to read out a list of ones and twos as quickly as possible. In an attempt to reduce the number of processes required and the confounding effect of attentional lapses, I used a short (~8 seconds) finger tapping task which did not require detection of a stimulus in order for the response to be made, no require any ability to read. However, the contrary nature of findings in this area highlight the need for more sensitive measures of processing speed to be used across different samples in order to further elucidate the role of processing speed. Measures such as event-related potentials, which allow measurement of different parts of processing at the neural level with millisecond temporal resolution may be beneficial.

It could be argued that the regression analysis presented in this analysis supports suggestions that processing speed is at the source of a cascade of cognitive impairment that impacts on behaviour (Mulder, Pitchford, & Marlow, 2011a). However, this would suggest that it is also at the root of executive function difficulties (Mulder, Pitchford, & Marlow, 2011a; Rose et al., 2011). Memory factors explained additional unique variance beyond the variance explained by processing speed alone however. This suggests that memory has an impact on inattention independent of that associated with processing speed. Moreover, evidence that visuo-spatial working memory explained significant unique variance supported the hypothesis that variation in specific executive functions would explain variance in inattention beyond that explained by basic cognitive processing.

No other cognitive measures explained significant unique variance in inattention in either group, and this reflects the uncertainty in my hypotheses about whether

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variance in task switching and interference control would explain unique variance. The fact that other measures didn’t predict significant unique variance in inattention is particularly interesting given that split group correlations revealed an association between poorer interference control and more severe parent-rated inattention in the very preterm children only. The only prior study of the association between interference control and inattention in preterm children did not find an association (Shum et al., 2008), and findings concerning inhibitory control are mixed, with some studies suggesting it plays an important role (Aarnoudse-Moens et al., 2012; Scott et al., 2012), while others find it to be unrelated (Mulder et al., 2011b). It is interesting and unanticipated that this association was restricted to very preterm children as it was hypothesised that the same effects would be observed in both groups. However, as the association observed was relatively small and interference control did not explain unique variance in inattention, it does not appear to be a key mechanism in the aetiology of inattention in children born preterm. These findings add further complexity to the question of how inhibitory control processes relate to inattention in children born very preterm, as well as term-born children, and suggest that a more detailed investigation of inhibitory processes and interference control in children born very preterm is warranted. Meanwhile, contrary to hypotheses, task switching was unrelated to inattention in both groups, suggesting it is not a core deficit in inattention.

It is important to note that the amount of variance in inattention explained by these cognitive predictors remains modest at 33.2%, suggesting that these cognitive processes are not the only factors involved in the aetiology of inattention in this sample of term-born and pre-term children. Given that some associations present across groups no longer met significance when groups were split, presumably due to a loss of power, this study may have benefitted from larger sample sizes to be confident that all effects were successfully detected and appropriately represented. Unfortunately, as is often the case, pragmatics took priority and further testing was not possible within the timescale of the PhD project.

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3.5.2 Patterns of strengths and weaknesses in cognitive performance in very preterm children

Performance differences between term-born and very preterm children were not specifically hypothesised in this study due to the selection of a term-born comparison group that was matched to the preterm sample on levels of inattention, and the testing of cognitive domains that were thought a priori to be associated with inattention. In spite of this, it was acknowledged that due to the wide range of cognitive impairment linked to very preterm birth, it was possible that we might see poorer performance in the very preterm group in some areas. The results of this study indicated that despite considerable overlap in performance scores of the two groups, memory is a particular area of weakness in children born very preterm, consistent with evidence showing that short term memory is impaired in preterm samples (Briscoe et al., 1998; Bull et al., 2008; Shum et al., 2008), along with the larger body of evidence documenting difficulty with working memory (including Böhm et al., 2010; Clark & Woodward, 2010; Curtis, Lindeke, Georgieff, & Nelson, 2002; Luciana, Lindeke, Georgieff, Mills, & Nelson, 1999; Luu, Ment, Allan, Schneider, & Vohr, 2011; Ni et al., 2011; Rose & Feldman, 1996; Saavalainen et al., 2007; Vicari, Caravale, Carlesimo, Casadei, & Allemand, 2004). The same is true for visuo-spatial processing, which has been repeatedly shown to be impaired in preterm populations (Foulder-Hughes & Cooke, 2003; Luciana et al., 1999; Simms et al., 2015). The absence of group differences in task switching and interference control in the present study were also in line with the results of a meta-analysis which concluded that findings relating to impaired inhibitory control and task switching in preterm samples are inconsistent (Mulder et al., 2009). It is important to remember that selection of a term-born sample with similar levels of inattention to the preterm sample makes interpretation of between-group performance differences more complex. Nonetheless, it is likely that the presence of between-group differences in the areas of memory and visuo-spatial processing, but absence in areas of task switching and interference control is likely to reflect the pattern of relative cognitive strengths and weaknesses across domains in preterm children when matched to term-born children on inattention. This could therefore identify neural processes

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that are impaired by preterm birth irrespective of whether a child also has high inattentiveness.

The most surprising finding was that children born very preterm had faster processing speed overall than term-born children, even statistically accounting for the older age of the very preterm children. In light of prior reports of slower processing speed in preterm samples (Aarnoudse-Moens et al., 2012; Luciana et al., 1999b; Mulder et al., 2011; Rose et al., 2011), differences in this direction were entirely unexpected. It does not appear to be a finding driven by the selection of a term sample including inattentive children, as the difference in processing speed is predominantly evident in children with better than average ratings of attention. One reason could be that in preterm children, neuroplastic compensatory changes might occur to increase the speed of processing as a protective factor to reduce the impact of other impairments. Such changes may be unnecessary or less likely to occur in term-born populations with more typically developing neuroanatomy and a narrower range of impairments. Although it is not fully clear why this finding emerged, it does indicate that outcomes in children born very preterm are heterogeneous, with some children born very preterm outperforming term-born peers of similar levels of above average attention in this area. Further research is needed to understand more fully the potential role of increased processing speed as a compensatory factor in children born pre-term.

3.5.3 Conclusion

The results reported in this chapter extend the findings of previous studies by comparing associations between cognition and inattention within term and preterm children who have similar ranges of severity of inattentive symptoms, rather than using the traditional case-control approach. Aside from the unexpected difference in processing speed, the pattern of group differences in performance between term- born and preterm children corresponds well with existing literature highlighting visuo-spatial processing and memory as areas of particular weakness. It is interesting that impairments are still apparent when the term-born group includes children rated as inattentive, confirming that children born very preterm are at risk of greater

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cognitive impairment than term-born peers displaying similar levels of inattentive behaviours.

Taken together, the regressions and correlations reported above show strong evidence for the role of short term memory and visuo-spatial working memory as shared mechanisms underlying inattention in both very preterm and term-born children, while motor processing speed appears to be a mechanism relevant to inattention only in very preterm children. In both very preterm and term-born children, inattentive behaviour was associated with specific areas of weakness rather than cognitive difficulties across the board, but the results present emerging evidence to suggest that different pathways may lead to inattention in term born compared to very preterm children. This is in contrast to the conclusion drawn by van der Meere et al. (2009) from their study of children born with very low birth- weight. Moreover, the analyses reported here suggest that although some of the lower-level processes that are required for visuo-spatial working memory (i.e., short term memory) predicted inattention, difficulty at the executive level explained unique variance above and beyond that accounted for by basic cognitive processing.

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4

Chapter 4: ERP Predictors of Inattention

4.1 Background

Neuroimaging allows for non-invasive investigation of the neural mechanisms that operate during cognitive functioning, and can reveal the ways in which atypical brain structure and/or function relates to the atypical behaviour that defines disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD; Gabrieli et al., 2015). Inattention difficulties in preterm children and ADHD populations are attributed to atypical neurobiological development, thus it is important to assess whether the causes of inattention in preterm and term-born children differ at the neural level. EEG detects the voltage produced by neural activity that is measurable on the scalp, and as such it has millisecond temporal resolution and reflects true neuronal activation, rather than secondary biophysical processes such as blood-oxygen level (as often used in functional MRI). Event-related potentials (ERPs) are derived from continuous electroencephalography (EEG) recordings by time-locking epochs to events of interest such as stimulus onset, and averaging across multiple trials of the same type to reduce interference from noise. Use of the event-related potentials (ERP) technique also allows the separation of a behavioural response into different processing components such as stimulus detection, categorisation, and evaluation as well as response preparation (Luck, Woodman, & Vogel, 2000) which are often compared on the basis of amplitude and latency. The amplitude of an ERP component is thought to represent the amount of neural resources recruited for that stage of processing, while latency measures the speed of each stage of processing. These characteristics can be compared for each neural component that contributes to the behavioural response. In spite of a growing body of magnetic resonance imaging-based (MRI) research showing links between atypical brain function or anatomy and behavioural difficulties in those born very preterm (Ment et al., 2009), to date only a single electroencephalography (EEG) study has been conducted investigating how neural activity relates to ADHD symptoms in children born preterm (Potgieter, Vervisch, & Lagae, 2003).

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In light of the importance of processing speed as a mechanism underlying inattention in children born very preterm described in Chapter 3 (see also Mulder, Pitchford, & Marlow, 2011b), investigation of ERPs, with their high temporal resolution, may be particularly useful to measure processing speed at a neural level. Further, use of ERPs may help ameliorate problems associated with task dependency of behavioural measures of processing speed. Such detail has the potential to help elucidate which stages of processing are linked to inattention, and further define the role of processing speed as a mediator of inattention in preterm children. Not only could the finer temporal detail provided by ERP analysis produce a greater understanding of the mechanisms underlying inattention, but ERPs also have the potential to reveal biomarkers that are able to explain individual differences in symptoms beyond those that can be explained or detected using behavioural data alone. In this way, ERPs could have functional benefit for diagnosis and treatment. Moreover, it has been argued that if biomarkers of inattention can be established, particularly those using relatively inexpensive and non-invasive techniques such as ERPs, these may be of use during diagnosis to aid the assessment of symptoms and predict symptom-associated outcomes (Loo, Lenartowicz, & Makeig, 2016).

4.1.1 ERPs and inattention in preterm children: What we know so far

As mentioned above, to date only one published study has utilised ERPs in order to assess ADHD behaviour in children born very preterm. Potgieter et al. (2003) recorded ERPs in school-aged children born with very low birth weight (VLBW; <1500g) and at less than 34 weeks gestation in an attempt to identify a neural marker that might explain the increased risk for ADHD in this population. They compared groups of VLBW children with and without an ADHD diagnosis with groups of normal birth weight (NBW; >2500g) children with and without an ADHD diagnosis on a visual oddball task. Children were required to respond to infrequent oddball targets among more frequent presentations of a single non-target stimulus. They found that, compared to children without ADHD, children with ADHD (VLBW and NBW) had slower and more variable response times, and had a lower hit rate (responded on fewer target trials), suggesting poorer attention. They also made

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more commission errors (responded on non-target trials) suggesting poorer inhibitory control. However, there were no differences between VLBW and NBW children with ADHD, or between VLBW and NBW children without ADHD. These behavioural findings were coupled with larger N2 ERP components (a component that is thought to reflect inhibitory processing) and reduced positivity at around 500ms (a component the authors thought reflected specific attention to the stimulus) to non-targets in the two ADHD groups compared to the non ADHD groups, suggestive of atypical neural processing during inhibitory control. However, again, there were no differences in ERP measures between VLBW and NBW children with ADHD, nor between VLBW and NBW children without ADHD, suggesting that any differences resulted from ADHD status as opposed to LBW. Both ERP findings were related to inhibitory processing of the non-target stimulus as opposed to more general attentional processing of target stimuli, with any other comparisons revealing no group differences in spite of behavioural findings of lower hit rates in