Look Out! Examining Children's Immediate Neural Responses to Threat Stimuli
Restricted (Penn State Only)
- Author:
- Wise, Shane
- Graduate Program:
- Psychology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- June 15, 2023
- Committee Members:
- Koraly Perez-Edgar, Major Field Member
Carol Miller, Outside Unit & Field Member
Cynthia Huang-Pollock, Chair & Dissertation Advisor
Peter Arnett, Major Field Member
Kristin Buss, Program Head/Chair - Keywords:
- Electroencephalogram
diffusion model
anxiety
ADHD - Abstract:
- Over the past several decades, electroencephalography (EEG) recording has emerged as a prolific research tool for measuring neural activity associated with emotional processing, both at rest and during cognitive activity (Dietrich & Kanso, 2010; Klimesch, 1999; Soroush, Maghooli, Setarehdan, & Nasrabadi, 2017). Much of this research has examined brain wave activity and Event Related Potentials (ERPs) to offer insights into emotion formation (Harmon‐Jones & Gable, 2018), processing of emotional stimuli (Suhaimi, Mountstephens, & Teo, 2020), and even distinguishing between groups based on psychopathology (Al-Ezzi, Kamel, Faye, & Gunaseli, 2020; de Aguiar Neto & Rosa, 2019). Such work is crucial for understanding, preventing, and treating psychological disorders (Insel et al., 2010). However, accurate measurement techniques are critical for understanding the associations between neural representations and behavioral presentations of anxiety. One domain of study in which methodology is being improved is power data analysis. One prominent example of this is with delta-beta coherence (DBC), the correlation between activity in the delta and beta EEG frequency bands. Greater resting state DBC is positively associated with heightened trait and state anxiety (Miskovic et al., 2010; Poppelaars, Harrewijn, Westenberg, & van der Molen, 2018), as well as with emotion regulation capability (Myruski, Bagrodia, & Dennis-Tiwary, 2022; Tortella-Feliu et al., 2014). A related variable, the ratio of relative theta and beta wave activity (theta-beta ratio; TBR) has been associated with attentional dysfunction (Morillas-Romero, Tortella-Feliu, Bornas, & Putman, 2015; van Son, de Rover, et al., 2019). However, this research has primarily examined only long periods of resting state data to assess for differences between pre-determined groups and has not as extensively studied changes in power in response to rapidly shifting environmental cues. It is therefore unclear whether DBC fluctuates actively in response to emotional information or whether it is a more stable byproduct of affective state. The first paper presented here employs a novel approach to assess for second-by-second changes in delta-beta coherence in response to emotionally evocative stimuli in children ages 8-12. It also evaluates whether these changes are influenced by inattention or anxiety as trait-based factors. If DBC or TBR respond to brief, single image presentations of evocative stimuli, that would serve as evidence that EEG power bands can serve as a neural representation of individual emotional and related attentional processing. A second area of research with shifting methodology concerns improving the behavioral measurement of bottom-up reactivity to stimuli. Anxious participants demonstrate enhanced attentional bias toward threatening stimuli in their environment (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & Van Ijzendoorn, 2007). However, accruing evidence has documented poor reliability of the RT difference score used to index threat bias in the most commonly used tasks (Kappenman, Farrens, Luck, & Proudfit, 2014; MacLeod, Grafton, & Notebaert, 2019). The second paper presented here explores a novel method of assessing for threat bias. It combines a novel two-choice threat labeling task with a well-validated computational modeling technique (i.e., the diffusion model) to better specify where in the flow of information processing that the threat bias occurs (C. N. White, Ratcliff, Vasey, & McKoon, 2010). Several different ERPs have been shown to be associated with early attentional orienting and cognitive processing of emotional information, and are thus relevant to attentional bias to threat (Gupta, Kujawa, & Vago, 2019). This paper assesses how well diffusion model (DM) performance parameters on a threat identification task predict ERP indices of attentional orienting to emotional information to determine whether it may offer a more efficient behavioral method of determining threat bias in children. Together, these papers offer complimentary perspectives on the neural and behavioral correlates of anxiety development by exploring novel methodological techniques for EEG signals and behavioral performance during a threat identification paradigm in a sample of school-aged children.