and in recent studies (which also seem largely independent of age), the current results again highlight the importance of task choice, especially when testing for age related differences in older adults. In addition, it has been found that
spatial attention asymmetries are modulated by non-spatial factors such as changes in sustained attention likely driven by time on task and reduced alertness, increased task difficulty or participant dependent variables (for a review see Chandrakumar et al., 2019).Therefore, an observed spatial bias might not simply reflect a fixed measure of asymmetrically spatial attention per se but might change across tasks and testing time, reflecting changes in other non- spatial components. The leftward spatial bias that is often observed in young adults has long been interpreted as a healthy norm and any deviation from it suggested to imply deficits, especially with older age. However, in view of the findings of other modulating factors, this view is too rigid and age per se might in fact not be influencing the shifts of attention.
The absence of inter- task correlations in Chapter 2 also reveals the limitation of making predictions for the natural environment, as a particular bias in one task does not predict the same behaviour for a different task. Moreover, while I found that older adults were similarly able to perform the tasks across different days I could not estimate which task, in comparison to the other 4, was more taxing on the participants as I did not control for task difficulty. Differences in task difficulty across the spatial tasks could account for the absence or presence of leftward biases in spatial attention. This complicates generalisation and comparability of pseudoneglect effects across different tasks, age-groups and studies.
The experiments in Chapters 3 and 4 attempted to address this issue and
investigated the influence of attentional load on spatial attention in a dual task paradigm, while employing EEG (see Chapter 4). The design was adapted from O’ Connell et al. (2011), who found modulating effects of attentional load on both spatial bias and early visual processing, as indexed in the P1 and N1 components. With the three experiments of Chapters 3 and 4, I extended their research by investigating if such modulations would be more pronounced in older adults.
Moreover, in contrast to the experiment in Chapter 2, this design allowed me to increase attentional load systematically from a baseline visual detection task in which participants did not monitor a RSVP steam for a target, to an increased attentional impact design. Attentional load was increased via an alphanumerical central target that participants were required to detect in a RSVP stream of red numbers while simultaneously reacting to lateralized peripheral targets.
Attentional load was defined as either low: a green number as central target required low attentional resources due to it being a pop out task or high: a red letter within a stream of red numbers, as additional discrimination between central target and distracters became necessary (O’Connell et al., 2011; Treisman & Gelade, 1980) (see Methods in Chapters 3 and 4 ).
The behavioural results of experiments 2 and 3 (see Chapter 3) served as pilot studies and informed the design of the EEG experiment, were EEG was employed in addition, and the obtained results allowed a refinement of the testing
parameters (see method section Chapter 3). In short, they deviated in
methodology from the final study, as only low and high attentional loads were measured and the viewing distance was decreased to a closer peri- personal space (80 to 50cm), which was identical to the viewing distance of the study design by O’Connell et al.(2011) and enhancing comparability to the results of the previous study. Finally for the EEG study, hand response was limited to the right hand only. Spatial preferences between left and right targets shifted between experiments 1 and 2 (Chapter 3) based on the changes in viewing distance, supporting the argument that spatial biases become stronger at closer range (see Dellatolas et al., 1996; A. Varnava et al., 2002). Moreover, this finding also ties into the earlier argument that changes in non-spatial factors have a strong influence on the spatial biases observed.
Interestingly, as mentioned above, across experiments 2 (Chapter 3) and the EEG experiment (Chapter 4), older and younger adults showed similar behavioural results in terms of reaction times and accuracy detection towards the central targets in the attentional load manipulation conditions. This suggests that older adults were suitably engaged in the task and were able to perform it similarly well when compared to young controls. Focussing on the EEG study in particular (see Chapter 4), I found supporting evidence that changes in attentional load
modulated spatial attention, as indexed by increased reaction times with
increased attentional load. However, against my predictions this effect was not more pronounced in older adults but independent of age. Moreover, in view of spatial asymmetry, I found no separation by age but instead all participants showed faster reaction times to right over left targets. The observed preference of the right visual target is perhaps one of the more surprising results and I have discussed possible influencing factors in Chapter 4. Yet, as I did not find a
decline with age in either visual field, and both reaction times and accuracy were good for both target types, this preference does not suggest a decline in ability with age. The electrophysiological data suggest instead that during early visual processing, left targets were processed better with increased additional attentional load (low and high load) as indexed by the greater lateralization and enhanced peak amplitudes over the contralateral RH for the N1 component. However, this advantage attenuated in the later processing stages, possibly driving the behavioural response for the faster right targets. I conclude that there was an absence of age related differences, specific to increased attentional load, in both the behavioural data and during the early spatial processing stages as indexed in P1 and N1 components.