Modified ANT behavioural analysis

3.2.1 Participants

For details regarding the participant recruitment and initial screening procedure please see chapter 2. The final experimental cohort comprised 63 healthy participants, 32 LBD patients and 27 AD patients. As discussed in chapter 2, for the purposes of the behavioural analyses DLB and PDD patients were grouped together; the LBD patient group comprised 18 DLB and 14 PDD patients. Preliminary analyses showed that there were no differences between the DLB and PDD patients in terms of the key behavioural effects and interactions. The dementia patients (aged 62-89 years) and 21 healthy elderly individuals (aged 62-83) were recruited from the CATFieLD study. An additional 42 healthy participants (aged 19-94) were recruited in order to validate the modified ANT in young healthy controls (section 3.3), and to aid characterisation of attentional network changes with healthy ageing (section 3.4). These additional healthy controls underwent the same recruitment and initial screening procedure as the CATFieLD study participants.

To ensure any group differences in reaction time data were not due to a lack of task comprehension amongst the dementia patients, individuals with a response rate < 60 %, and those with a response rate > 60% but < 60% of responses correct, were also excluded. The same cut-off value was used for the EEG analyses; this cut-off value ensured that there was sufficient data for both the behavioural and EEG analyses (as described in chapter 4). Using this cut off rate, 3 AD and 3 LBD potential participants were excluded from the behavioural

analyses, leaving 27 AD and 32 LBD patients. Demographic details of the participant cohorts used for each of the analyses are described in the following results sections (sections 3.3-3.5).

3.2.2 Procedure

For participants recruited from the CATFieLD study all testing sessions were conducted in the Clinical Ageing Research Unit (CARU), Institute for Ageing and Health, Newcastle University (see chapter 2). These participants completed the modified ANT whilst simultaneously undergoing EEG recordings. The additional healthy participants (not recruited as part of the CATFieLD study) were recruited by William Solyom, an undergraduate student who conducted a validation study of the modified ANT with Dr John-Paul Taylor. These participants underwent the same ANT testing procedure as the CATFieLD participants but the testing was conducted by William Solyom in the participants’ homes, and without

simultaneous EEG recordings.

3.2.3 Analysis method

A MATLAB script, written by Dr Michael Firbank,was used to convert the raw data from the ANT output files to reaction times and standard deviations for each cue (no cue, neutral, spatial) by target (congruent, incongruent) condition. These values were calculated for each task trial (for each participant). Using only the trials in which the participants gave correct responses, the mean reaction times (RT) (across all trials) and standard deviations were calculated for each cue and target condition. The attentional networks were calculated using the network calculations as devised by Fan et al (2002):

Alerting effect = no cue trials mean RT - neutral cue trials mean RT

Orienting effect = neutral cue trials mean RT - spatial cue trials mean RT

Executive conflict effect = incongruent target trials mean RT- congruent target trials mean RT

To calculate the alerting and orienting effects, the mean RTs were calculated by averaging the across the congruent and incongruent target trials. Similarly, the mean RTs for the target trials used to calculate the executive conflict effect were calculated by averaging across all of the cue conditions.

Error rates were also calculated for each task condition (cue and target) and each of the attentional networks (using the subtraction approach described above). Error rates were calculated for each participant by dividing the total number of incorrect and missed response trials by the total number of trials. Note error rates are not reported for the validation analyses (section 3.3) given error rates were minimal in the young healthy cohort used for these

analyses, and were comparable across task conditions.

3.2.4 Statistical analysis

All of the analyses (sections 3.3-3.5) were conducted using SPSS 19.0 (SPSS Inc, Chicago), and an alpha value of 0.05. For each of the ANOVA analyses discussed below, Mauchly's sphericity test was used and F values adjusted accordingly, and post-hoc pairwise comparisons were performed using Bonferroni correction for family-wise errors.

Validation of the modified ANT (section 3.3)

For the mean RT data, repeated measures (cue x target) ANOVAs were conducted to investigate the cue and target interactions, and post-hoc pairwise comparisons were used to investigate the RT differences between the cue and target conditions; thus determining whether the attentional network effects were significant. To investigate the independence of the attentional networks, Pearson’s r bivariate correlations were used to investigate the associations between each of the attentional network effects (alerting, orienting and executive conflict). Person’s r correlations were also used to determine the association between each of the attentional network effects and the overall mean RT (RT averaged across all task

conditions, correct responses only).

Attentional networks in healthy ageing (section 3.4)

In order to investigate how the overall mean RT changed with healthy ageing, a linear regression analysis was conducted. Linearity of the data is an assumption of this ANOVA analysis approach, however when plotting the data (see section 3.4.2) it was apparent that the best fit to the data was a quadratic relationship between overall mean RT in the healthy controls and age. However, when age was modelled as age2 the relationship between overall mean RT and age was linear, hence age2 (as opposed to age) was used for the healthy ageing

analyses (see section 3.4.2 for further details). For the regression analyses, the independent variable was age2, and the dependent variable was overall mean RT (averaged across all task conditions).

To investigate the mean RT data for each task condition, repeated measures (cue x target) ANOVAs were conducted with age2 as a covariate to determine the cue and target interactions, and post-hoc pairwise comparisons were used to calculate the attentional network effects. Comparable cue x target repeated measures ANOVAs, with age2 as a covariate, were conducted for the error rate data. For each of the attentional networks, separate regression analyses were conducted with age2 as the independent variable, and the network effect (alerting, orienting, or executive conflict) as the dependent variable.

To investigate the independence of the attentional networks, Pearson’s r partial correlations were conducted using age2 as a covariate. Partial correlations (with age2 as a covariate) were also used to determine the association between each of the attentional network effects and overall mean RT (across all task conditions).

Attentional networks in dementia and age-matched healthy controls (section 3.5)

To determine whether the healthy controls and dementia groups differed in terms of overall mean RT, a univariate ANOVA analysis was conducted with overall mean RT as the dependent variable and group (AD, LBD, age-matched controls) as the fixed factor.

For the mean RT data for each task condition, repeated measures (cue x target) ANOVAs were conducted with a between-subject factor of group (AD, LBD, age-matched controls). For each group, post-hoc pairwise comparisons were used to calculate RT

differences between the cue and target conditions, in order to determine whether each of the attentional network effects were significant. Comparable cue x target repeated measures ANOVAs, with group as a between-subject factor, were also conducted for the error rate data. Given that cholinesterase inhibitor usage has been found to enhance attentional function in dementia cohorts (Emre et al., 2004; McKeith et al., 2000a), medication usage was initially considered as a covariate in the mean RT and error rate analyses models (cholinesterase and dopaminergic medication usage were considered), but was subsequently removed due to an absence of main effects and interactions.

To investigate the independence of the attentional networks, for each group Pearson’s

r bivariate correlations were conducted to determine the association between each of the

attentional network effects. For each group, correlations were also conducted between each of the attentional network effects and the overall mean RT (across all task conditions).

Correlation analyses (using Pearson’s r) were also conducted to investigate associations between the behavioural data (overall mean RT, attentional network effects and error rates) and clinical variables in the dementia groups. Clinical variables investigated included: measures of global cognitive functioning (CAMCOG and MMSE total score), clinical measures of cognitive fluctuations (CAF, MFS, ODFAS), and UPDRS motor subscale total score (details of these clinical assessments are given in chapter 2). For the purposes of clarity, for the clinical correlation analyses, only the correlations which yielded significant results are reported in this chapter. Due to the exploratory nature of these analyses, relationships are reported uncorrected for family-wise errors.