Prolonged physiological reactivity and loss: Association of pupillary reactivity with negative thinking and feelings

Abstract

Prolonged psychophysiological reactions to negative information have long been associated with negative thinking and feeling. This association is operationalized in the RDoC negative affect construct of loss, which is nominally indexed by prolonged physiological reactivity, cognitive loss-related constructs such as rumination and guilt, and more feeling-related constructs such as sadness, crying, and anhedonia. These associations have not been tested explicitly. If thinking and feeling aspects of loss reflect different physiological mechanisms, as might be suggested by their putative neurobiology, different intervention pathways might be suggested. Here we examined the extent to which self-reported negative thinking and feeling constructs were associated with prolonged pupillary reactivity following negative words and a subsequent cognitive distractor in a diverse heterogeneously diagnosed sample of N = 84 participants. We also considered indices of abuse and variables associated with borderline personality disorder as possible moderators. Consistently, feeling-related negative affect constructs were related to prolonged pupillary reactivity during the distractor after a negative stimulus whereas thinking-related constructs were not. These data suggest that people who have sustained physiological reactions to emotional stimuli may be more strongly characterized by non-linguistic negative feelings than explicit cognitions related to loss. Sustained physiological reactions could reflect efforts to regulate feeling states. In contrast to cognitive and affective variables, abuse was associated with decreased physiological reactivity, consistent with decreased neural engagement. Interventions that target mechanisms underlying feelings and their regulation may be more mechanistically specific to sustained reactivity than those which directly address cognitions.

Pupil response to social-emotional material is associated with rumination and depressive symptoms in adults with autism spectrum disorder

“…Subsequent studies similarly report greater pupil dilation to dysphoric stimuli for individuals characterized by depression and greater ruminative style [ 23 , 24 ]. However, in a larger, transdiagnostic sample [ 14 ], sustained pupil dilation was associated with affective but not cognitive-ruminative features of depression. In the present study, we aim to see if pupil response course to sad stimuli in a young adult ASD sample resembles that of a TD-depressed comparison group and replicates these previous findings from the depression literature.…”

Publication guidelines and recommendations for pupillary measurement in psychophysiological studies

“…The Guthrie and Buchwald (1991) technique assesses pupillary waveform data using Monte Carlo simulations to determine the minimum number of consecutive t tests that are unlikely to occur by chance at some waveform‐wise level of significance (e.g., p = .10 or p = .05; see Figure 4). Its utility is in detecting long intervals of significance across highly autocorrelated pupillary waveforms (e.g., Aminihajibashi et al, 2020; Angulo‐Chavira et al, 2017; Gotham et al, 2018; Kvamme et al, 2019; Lasaponara et al, 2019; Siegle et al, 2015). A different method for comparing differences across large numbers of measurements (e.g., waveforms) is described by Blair and Karniski (1993) (see software by Siegle et al (2015) in Table 2, for implementation in MatLab) which is better for detecting short regions of large‐effect differences but poorer for detecting longer regions with smaller effect sizes.…”

The Use of Mathematical Statistics Methods in Modelling the Psychophysiological «Value» of Cognitive Activity of Students with Different Levels of Academic Success

“…By changing the types and complexity of tasks, analyzing the concomitant changes in physiological indicators during the study, physiological correlates of performance were obtained and reflected in the regression models of the «value» of activity mathematically. On this basis, the conclusions of other researchers on the features of physiological support for solving tasks of different types are based in [23], [24], [25]. The second approach is based on the fact that the inherent ways of human cognitive activity are reflected in physiological parameters and as a result acquire stable individual characteristics [26], [27].…”