Stress effects on learning and feedback‐related neural activity depend on feedback delay

Paul, Marcus; Bellebaum, Christian; Ghio, Marta; Suchan, Boris; Wolf, Oliver T.

doi:10.1111/psyp.13471

Cited by 10 publications

(5 citation statements)

References 87 publications

(149 reference statements)

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“…In addition, the main effects of both waiting time (F (1,20) = 5.422, p = 0.030, η 2 p = 0.213) and feedback (F (1,20) = 5.987, p = 0.024, η 2 p = 0.230) reached a significant level. More concretely, the long waiting time (320.082 ± 74.166 µV 2 ) elicited a larger power than that in the short waiting time (256.219 ± 56.869 µV 2 ); A large power was observed upon gain condition (346.08 ± 84.335 µV 2 ) than lose condition (230.220 ± 48.654 µV 2 ), which is similar with the previous investigations (Zhang et al, 2018;Paul et al, 2019;Höltje & Mecklinger, 2020). Then post-hoc analysis was used for further investigation.…”

Section: Proposed Approach Resultssupporting

confidence: 90%

“…3 and 4. For the actual dataset P3-delta results, similar to the results of the time domain in the previous reports (Wu & Zhou, 2009;Zhang et al, 2018;Paul et al, 2019;Höltje & Mecklinger, 2020), the loss condition reflected smaller power than by the gain one. Besides, consistent with the findings in the time domain of the paper (Höltje & Mecklinger, 2020)-that is, the interaction effect between the two factors was significant.…”

Section: Conclusion and Discussionsupporting

confidence: 85%

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Objective Extraction of Evoked Event-related Oscillations from Time-frequency Representation of Event-related Potentials

Zhang

Ristaniemi

Cong

2020

Preprint

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Evoked event-related oscillations (EROs) have been widely used to explore the mechanisms of brain activities for both normal people and neuropsychiatric disease patients. The selection of regions of evoked EROs tends to be subjectively based on the previous studies and the visual inspection of grand averaged time-frequency representations (TFRs) which causes some missing or redundant information. Meanwhile, the evoked EROs cannot be fully extracted via the conventional time-frequency analysis (TFA) method because they are sometimes overlapped with each other or with artifacts in time, frequency, and space domains to some extent. Hence, these shortcomings may pose some challenges to investigate the related neuronal processes. A data-driven approach was introduced to fill the gaps as below: extracting the temporal and spatial components of interest simultaneously by principal component analysis and Promax rotation and projecting them to the electrode field to correct their variance and polarity indeterminacy, calculating the TFRs of the back-projected components, and determining the regions of interest objectively using the edge detection algorithm. We performed this novel approach and the conventional TFA method in analyzing both a synthetic dataset and an actual ERP dataset in a two-factor simple gambling paradigm of waiting time (short/long) and feedback (loss/gain) separately. Synthetic dataset results indicated that N2-theta and P3-delta oscillations were detected using the proposed approach, but, by comparison, only one oscillation was obtained via the conventional TFA method. Furthermore, the actual ERP dataset results of P3-delta for our approach revealed that it was sensitive to the waiting time (which also was found in the previous reports) but not for that of the conventional TFA method. This study manifested that the proposed approach can objectively extract evoked EROs, which allows a better understanding of the modulations of the oscillatory responses.

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Section: Proposed Approach Resultssupporting

confidence: 90%

Section: Conclusion and Discussionsupporting

confidence: 85%

Objective Extraction of Evoked Event-related Oscillations from Time-frequency Representation of Event-related Potentials

Zhang

Ristaniemi

Cong

2020

Preprint

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“…At a first sight, however, some of the extant literature may seem equivocal, possibly due to critical methodological differences related to stress operationalization (Porcelli & Delgado, 2017). A significant number of studies have investigated the effects of stress on learning using different paradigms, such as ACUTE STRESS AND REWARD LEARNING 26 the cold pressor test (Byrne et al, 2019;Ehlers & Todd, 2017;Glienke, Wolf, & Bellebaum, 2015;Lighthall et al, 2013;Otto et al, 2013;Paul, Bellebaum, Ghio, Suchan, & Wolf, 2019) or the Trier social stress test (Boyle, Stanton, Eisenberger, Seeman, & Bower, 2019;Kruse et al, 2018;Petzold et al, 2010;Radenbach et al, 2015), in which acute stress is induced before the learning task. In these paradigms, stress induction precedes any learning processes, thus the stress-induced emotional state may be less concurrent with the cognitive processes that operate during the task.…”

Section: Effect Of Acute Stress On Reward Learningmentioning

confidence: 99%

Acute stress impairs reward learning in men

Carvalheiro

Conceição

Mesquita

et al. 2020

Preprint

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Acute stress is ubiquitous in everyday life, but the extent to which acute stress affects how people learn from the outcomes of their choices is still poorly understood. Here, we investigate how acute stress impacts reward and punishment learning in men using a reinforcement-learning task. Sixty-two male participants performed the task whilst under stress and control conditions. We observed that acute stress impaired participants' choice performance towards monetary gains, but not losses. To unravel the mechanism(s) underlying such impairment, we fitted a reinforcement-learning model to participants' trial-by-trial choices. Computational modeling indicated that under acute stress participants learned more slowly from positive prediction errors - when the outcomes were better than expected - consistent with stress-induced dopamine disruptions. Such mechanistic understanding of how acute stress impairs reward learning is particularly important given the pervasiveness of stress in our daily life and the impact that stress can have on our wellbeing and mental health.

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“…P300 amplitude and latency are thought to reflect cognitive processing, such as stimulus identification and evaluation (Feng et al, 2019;Wang et al, 2019;Gao et al, 2020;Khedr et al, 2020). Studies have also suggested that higher-order cognitive stimulielicited P300 components are generated from the anterior cortex, and these components reflect the response inhibition process (de Bruijn et al, 2020;Paul et al, 2020). However, Deslandes et al (2006) and Tieges et al (2009) have found no significant alteration of ERP indices or other neuropsychomotor results following caffeine administration after TSD, indicating that there is still a lack of knowledge of caffeine's effects on the human brain.…”

Section: Introductionmentioning

confidence: 99%

Effects of Caffeine on Event-Related Potentials and Neuropsychological Indices After Sleep Deprivation

Chen

Zhang

Yang

et al. 2020

Front. Behav. Neurosci.

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Objective: Caffeine is a central nervous system stimulant that can effectively alleviate brain fatigue and low cognitive efficiency induced by total sleep deprivation (TSD). Recent studies have demonstrated that caffeine can improve subjective attention and objective behavioral metrics, such as arousal level, reaction time, and memory efficiency. However, only a few studies have examined the electrophysiological changes caused by the caffeine in humans following sleep disturbance. In this study, an event-related potential (ERP) technique was employed to measure the behavioral, cognitive, and electrophysiological changes produced by caffeine administration after TSD. Methods: Sixteen healthy subjects within-subject design performed a visual Go/No-Go task with simultaneous electroencephalogram recording. Behavioral and ERP data were evaluated after 36 h of TSD, and the effects of ingestion of either 400 mg of caffeine or placebo were compared in a double-blind randomized design. Results: Compared with placebo administration, the Go hit rates were significantly enhanced in the caffeine condition. A simple effect analysis revealed that, compared with baseline, the Go-P2 amplitude was significantly enhanced after TSD in the caffeine consumption condition. A significant main effect of the drug was found on No-Go-P2, No-Go-N2 amplitude, and Go-P2 latency before and after TSD. Conclusion: Our findings indicate that caffeine administration has acute effects on improving the efficiency of individual automatic reactions and early cognitive processes. Caffeine was related to the preservation of an individual's arousal level and accelerated response-related decisions, while subjects' higher-level recognition had limited improvement with prolonged awareness.

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Stress effects on learning and feedback‐related neural activity depend on feedback delay

Cited by 10 publications

References 87 publications

Objective Extraction of Evoked Event-related Oscillations from Time-frequency Representation of Event-related Potentials

Objective Extraction of Evoked Event-related Oscillations from Time-frequency Representation of Event-related Potentials

Acute stress impairs reward learning in men

Effects of Caffeine on Event-Related Potentials and Neuropsychological Indices After Sleep Deprivation

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