Internal Consistency of Functional Magnetic Resonance Imaging and Electroencephalography Measures of Reward in Late Childhood and Early Adolescence

Abstract

Background Abnormal neural response to reward is increasingly thought to function as a biological correlate of emerging psychopathology during adolescence. However, this view assumes such responses have good psychometric properties—especially internal consistency—an assumption that is rarely tested. Methods Internal consistency (i.e., spilt-half reliability) was calculated for event-related potentials (ERPs) and Blood Oxygen Level Dependent (BOLD) responses to monetary gain and loss feedback from the same sample of 8–14 year-old females (n=177). Internal consistency for ERPs (i.e. feedback negativity) and BOLD responses within the ventral striatum and medial/lateral prefrontal cortex to gain, loss, difference scores (gain-loss), and residual scores (gain controlling for loss) were compared. Moderation analyses were conducted to investigate whether internal consistency differed by age. Results ERP and BOLD responses to gain and loss feedback showed high internal consistency in all regions (Spearman Brown Coefficients (SB) ≥ 0.70). When considering difference and residual scores, however, responses showed lower internal consistency (SBs ≤ 0.50), with particularly low internal consistency for subtraction-based scores (SB ≤ 0.36). Age was not a significant moderator of split-half relationships, indicating similar internal consistency across late childhood to early adolescence. Conclusions Within the same subjects, high internal consistency was observed for both ERP and fMRI measures of response to gains and losses, which did not vary as a function of age. Moreover, excellent psychometric properties were evident even within the first half of the experiment. Difference scores were characterized by lower internal consistency, although regression-based approaches outperformed subtraction-based difference scores.

Cognitive loading via mental arithmetic modulates effects of blink‐related oscillations on precuneus and ventral attention network regions

“…The overall behavioral characteristics in each task were deemed to be consistent across individuals if the mean correlation coefficient exceeded 0.8 in accordance with previous literature (Luking, Nelson, Infantolino, Sauder, & Hajcak, 2017;Raz, Bar-Haim, Sadeh, & Dan, 2014). The overall behavioral characteristics in each task were deemed to be consistent across individuals if the mean correlation coefficient exceeded 0.8 in accordance with previous literature (Luking, Nelson, Infantolino, Sauder, & Hajcak, 2017;Raz, Bar-Haim, Sadeh, & Dan, 2014).…”

“…This process was repeated 1,000 times following randomized group divisions, and the mean correlation coefficient was computed. The overall behavioral characteristics in each task were deemed to be consistent across individuals if the mean correlation coefficient exceeded 0.8 in accordance with previous literature (Luking, Nelson, Infantolino, Sauder, & Hajcak, 2017;Raz, Bar-Haim, Sadeh, & Dan, 2014).…”

Time of day differences in neural reward responsiveness in children

“…EEG was segmented for each trial, beginning 200 ms before onset of the feedback stimulus and ending 1,000 ms after onset of the feedback stimulus. Based on the findings of a recent comprehensive study on internal consistency of fMRI and EEG measures of reward in late childhood and early adolescence demonstrating that internally consistent measure of response to gain and loss can be obtained using just 14 gain and 14 loss trials of the Doors task (Luking, Nelson, Infantolino, Sauder, & Hajcak, ), we focused only on children who had at least 14 trials per condition. In our sample, the average number of gain trials remaining following artifact rejection was 23.28 ( SD = 2.03; range of 16–25) and the average number of loss trials was 23.04 ( SD = 2.39; range of 15–25).…”

Age‐typical changes in neural reward response are moderated by maternal anhedonia

“…Details regarding the doors task, a monetary guessing task, including patterns of activation and internal consistency, have been published previously for a larger overlapping sample (Luking, Nelson, Infantolino, Sauder, & Hajcak, 2017). See Figure S2 for a schematic of the doors task timing.…”

“…Participants were excluded from analyses if over 20% of data were discarded (n = 6). This motion correction strategy had been used in our previous work (Infantolino, Luking, Sauder, Curtin, & Hajcak, 2018;Luking et al, 2017). On average, 1.05% of volumes were interpolated (SD = 2.41).…”