Although this thesis provides good evidence for age differences in spatial attention asymmetries, there are likely to be a highly complex set of additional factors that contribute to the genesis of, and changes in, spatial bias. These include fluctuations in sustained attention throughout the course of an experiment, coupled with inter-individual differences in functional ability and baseline performance, with the additional influence of the cognitive load exerted by the choice of spatial attention task. These issues are highly interlinked and are, at present, underspecified with respect to precisely how they each might modulate spatial attention asymmetries. The role of baseline performance and task difficulty are paramount in the CRUNCH and HAROLD models: both models predict that difficult tasks cause a depletion of cognitive resources, which then forms the catalyst for the recruitment of alternative neural populations. In general, older adults have a lower baseline performance level for visual attention tasks (Madden, 2007; Chapter Three), they find the tasks more difficult to perform (Benwell et al., 2014a), their performance is more negatively affected by increased task difficulty (Swan et al., 2015) and they may experience a greater degree of fatigue over the course of an experiment.
Our research group, and others, have previously reported a rightward shift of spatial attention in young adults, that is driven by reduced arousal
(Benwell et al., 2013a,b; Dufour, Touzalin & Candas, 2007; Bellgrove et al., 2004; Dodds et al., 2008; Fimm, Wilmes & Spijkers, 2006; Manly et al. 2005; Matthias et al., 2010; Newman, O’Connell & Bellgrove, 2013; Perez, Garcia & Valdes-Sosa, 2008; Perez et al., 2009). This is attributed to a depletion of right-hemisphere attention resources caused by increased time-on-task, which then disrupts the balance of interhemispheric activity in favour of the left hemisphere, thus driving the rightward shift of spatial bias. For older adults, who already have a reduced neural and behavioural asymmetry, does a further depletion of right hemisphere resources via reduced sustained attention, influence spatial biases? Are older adults more negatively affected by extended time-on-task compared to young adults? Might older adults experience greater fluctuations in sustained attention over the course of an experiment? Could these effects be masked by collapsing each 5-6 minute experimental block together, as I did in Chapter Four? For example, young adults were consistently biased to the left across multiple testing sessions in both Chapter Two and Chapter Three, but the bias in older adults was less stable across days (Chapter Three), hinting that older adults might be more susceptible to the influence of these additional variables. It would be useful to perform a follow-up experiment involving single trial analysis to assess these subtle trial-by-trial fluctuations in alertness and task engagement.
Given that these issues are all of central importance, how did I attempt to control these variables in the three studies presented in this thesis? In Chapter Three I controlled the difficulty of the lateralised visual detection task by titrating stimulus size according to each participant’s ability (i.e. everyone
received stimuli that they could perceive with approximately 50% accuracy). Yet, there were clear differences in response to tDCS depending on performance (i.e. whether the participant reached this 50% threshold with larger or smaller stimuli). This concurs with our previous tDCS study which uncovered an interaction between current strength and performance, with 1mA tDCS inducing a rightward shift on the landmark task in good performers, and 2mA inducing the same rightward shift in poor performers (Benwell, Learmonth et al., 2015). Thus, it is likely that the neural substrates differ for spatial attention in good and poor performers: either different neural populations are being utilised, different strategies for undertaking the task are used, and/or neurons are closer to the action potential threshold in those with high ability.
Contrast this with Chapter Four, in which I chose not to titrate the landmark task difficulty across participants. Interestingly, and contrary to Benwell et al., (2014a), I found that older adults did in fact not perform with any less precision (as indexed by psychometric function curve width) compared to young adults. I also failed to replicate the expected shift of spatial bias into the right hemispace with short landmark lines. Due to the differences between the two studies in both behavioural asymmetry and task precision, the role of task difficulty, and performance also remain unaccounted for in this Chapter. Did the older adults in Chapter Four actively generate this high task precision by recruiting bilateral neural resources? Alternatively, were they simply a higher- functioning sample of older adults and their high precision was unrelated to the bilateral activity observed on EEG? These questions remain open at present. To test this more thoroughly, an interesting future line of enquiry would be to
replicate the EEG experiment performed in Chapter Four, but instead of presenting two different line lengths (which are perceptually very different), to instead present the same line length but with different levels of difficulty (e.g. one condition where there are relatively obvious size differences between the left and right sides of the landmark line, and another where the left vs right judgements are more difficult). This modification would allow me to disentangle the effects of line length and task difficulty in older adults, and observe how task difficulty impacts upon the spatial attention networks.