Monitor yourself! Deficient error-related brain activity predicts real-life self-control failures

Krönke, Klaus-Martin; Wolff, Max; Mohr, Holger; Kräplin, Anja; Smolka, Michael N.; Bühringer, Gerhard; Goschke, Thomas

doi:10.3758/s13415-018-0593-5

Cited by 86 publications

(55 citation statements)

References 63 publications

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“…We recruited 225 young adults from a representative community sample in Dresden, Germany, for a longitudinal investigation on the onset and course of addictive disorders (for previous studies from this project, see Krönke et al, 2018; Wolff et al, 2016). This sample size is much larger than ones used in previous studies that employed a brain-as-predictor approach.…”

Section: Methodsmentioning

confidence: 99%

“…experience sampling). Although this brain-as-predictor approach (Berkman & Falk, 2013) is correlational in nature, the few recent studies that have used it yielded promising results, indicating, for instance, that individual differences in real-life self-control failures are associated with activity in brain areas involved in cognitive control and response inhibition (Berkman, Falk, & Lieberman, 2011; Krönke et al, 2018; Lopez, Hofmann, Wagner, Kelley, & Heatherton, 2014).…”

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Predicting Real-Life Self-Control From Brain Activity Encoding the Value of Anticipated Future Outcomes

et al. 2020

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Deficient self-control leads to shortsighted decisions and incurs severe personal and societal costs. Although neuroimaging has advanced our understanding of neural mechanisms underlying self-control, the ecological validity of laboratory tasks used to assess self-control remains largely unknown. To increase ecological validity and to test a specific hypothesis about the mechanisms underlying real-life self-control, we combined functional MRI during value-based decision-making with smartphone-based assessment of real-life self-control in a large community sample ( N = 194). Results showed that an increased propensity to make shortsighted decisions and commit self-control failures, both in the laboratory task as well as during real-life conflicts, was associated with a reduced modulation of neural value signals in the ventromedial prefrontal cortex in response to anticipated long-term consequences. These results constitute the first evidence that neural mechanisms mediating anticipations of future consequences not only account for self-control in laboratory tasks but also predict real-life self-control, thereby bridging the gap between laboratory research and real-life behavior.

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confidence: 99%

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Predicting Real-Life Self-Control From Brain Activity Encoding the Value of Anticipated Future Outcomes

et al. 2020

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“…Data were collected as part of a prospective-longitudinal community study within a Collaborative Research Centre (SFB 940) at the Technische Universität Dresden, Germany. At baseline, participants took part in four different test sessions including a clinical assessment, a behavioural task battery, an fMRI session, and experience sampling for daily self-control failures (for further results, see Krönke et al 2018 ; Krönke et al 2020 ; Wolff et al 2016 ). The 1-year follow-up included only a clinical assessment.…”

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confidence: 99%

Impulsive decision-making predicts the course of substance-related and addictive disorders

et al. 2020

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Background This study investigated whether patterns of impulsive decision-making (i) differ between individuals with DSM-5 substance use disorders (SUD) or non-substance-related addictive disorders (ND) and healthy controls, and (ii) predict the increase of SUD and ND severity after one year. Methods In a prospective-longitudinal community study, 338 individuals (19–27 years, 59% female) were included in one of three groups: SUD (n = 100), ND (n = 118), or healthy controls (n = 120). Group differences in four impulsive decision-making facets were analyzed with the Bayesian priors: delay discounting (mean = 0.37, variance = 0.02), probability discounting for gains and for losses (each − 0.16, 0.02), and loss aversion (− 0.44, 0.02). SUD and ND severity were assessed at baseline and after 1 year (n = 312, 92%). Predictive associations between decision-making and SUD/ND severity changes were analyzed with the Bayesian prior: mean = 0.25, variance = 0.016. Results Compared with controls, the SUD group displayed steeper delay discounting and lower probability discounting for losses; the ND group displayed lower probability discounting for losses (posterior probabilities > 98%). SUD symptom increase after 1 year was predicted by steeper delay discounting and lower loss aversion; ND symptom increase by lower probability discounting for losses and lower loss aversion (posterior probabilities > 98%). There was low evidence for predictive relations between decision-making and the quantity-frequency of addictive behaviours. Discussion Impulsive decision-making characterizes SUD and ND and predicts the course of SUD and ND symptoms but not the engagement in addictive behaviours. Strength of evidence differed between different facets of impulsive decision-making and was mostly weaker than a priori expected.

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“…For example, reward related activity in the ventral striatum during incidental food cue exposure is prospectively predictive of momentary self-control failures, as captured by ecological momentary assessment (Lopez et al, 2014(Lopez et al, , 2017, as well as long term weight gain over a six-month period (Demos et al, 2012). Activity in vlPFC/IFG (Krönke et al, 2018;Lopez et al, 2014) and the frontoparietal control network more broadly (Lopez et al, 2017) also promotes successful resistance of daily self-control challenges. Notably, patterns of brain activity predictive of real world self-control outcomes often account for variance above and beyond selfreported measures (Berkman et al, 2011;Krönke et al, 2018;Lopez et al, 2014).…”

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“…Activity in vlPFC/IFG (Krönke et al, 2018;Lopez et al, 2014) and the frontoparietal control network more broadly (Lopez et al, 2017) also promotes successful resistance of daily self-control challenges. Notably, patterns of brain activity predictive of real world self-control outcomes often account for variance above and beyond selfreported measures (Berkman et al, 2011;Krönke et al, 2018;Lopez et al, 2014). However, the predictive utility of neural indicators might be increased if they are assessed in more ecologically valid contexts.…”

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Neural indicators of food cue reactivity, regulation, and valuation and their associations with body composition and daily eating behavior

Cosme¹,

Lopez²

2020

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Exposure to food cues activates the brain’s reward system and undermines efforts to regulate impulses to eat. During explicit regulation, lateral prefrontal cortex activates and modulates activity in reward regions and decreases food cravings. However, it is unclear whether: (1) there are between-person differences in recruitment of regions associated with reward processing, subjective valuation, and regulation during food cue exposure—absent instructions to regulate; and (2) individual differences in activation patterns predict body composition and daily eating behaviors. In this preregistered study, we pooled data from several fMRI samples to examine whether regions associated with reward, valuation, and regulation, respectively, as well as whole-brain pattern expression indexing these processes, were recruited during food cue exposure and associated with body composition and real-world eating behavior. Cross-validated regression models indicated that univariate and multivariate measures of reward and valuation were associated with individual differences in BMI and enactment of daily food cravings. Specification curve analyses further revealed reliable associations between univariate and multivariate neural indicators of reactivity, regulation, and valuation, and all outcome measures. These findings highlight the utility of these methods to elucidate brain-behavior associations and suggest that multiple processes are implicated in proximal and distal markers of self-regulatory success and failure.

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Monitor yourself! Deficient error-related brain activity predicts real-life self-control failures

Cited by 86 publications

References 63 publications

Predicting Real-Life Self-Control From Brain Activity Encoding the Value of Anticipated Future Outcomes

Predicting Real-Life Self-Control From Brain Activity Encoding the Value of Anticipated Future Outcomes

Impulsive decision-making predicts the course of substance-related and addictive disorders

Neural indicators of food cue reactivity, regulation, and valuation and their associations with body composition and daily eating behavior

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