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Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach

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Abstract
During self-control, we may resist short-term temptations in order to reach a favorable future (e.g., resisting cake to stay healthy). The neural basis of self-control is typically attributed to “cold,” unemotional cognitive control mechanisms which inhibit affect-related regions via the prefrontal cortex (PFC). Here, we investigate the neural underpinnings of regulating cravings by mentally evoking the positive consequences of resisting a temptation (e.g., being healthy) as opposed to evoking the negative consequences of giving in to a temptation (e.g., becoming overweight). It is conceivable that when using these types of strategies, regions associated with emotional processing [e.g., striatum, ventromedial prefrontal cortex (vmPFC)] are involved in addition to control-related prefrontal and parietal regions. Thirty-one participants saw pictures of unhealthy snacks in the fMRI scanner and, depending on the trial, regulated their craving by thinking of the positive consequences of resisting, or the negative consequences of not resisting. In a control condition, they anticipated the pleasure of eating and thus, allowed the craving to occur (now-condition). In line with previous studies, we found activation of a cognitive control network during self-regulation. In the negative future thinking condition, the insula was more active than in the positive condition, while there were no activations that were stronger in the positive (> negative) future thinking condition. However, additionally, multivariate pattern analysis showed that during craving regulation, information about the valence of anticipated emotions was present in the vmPFC, the posterior cingulate cortex (PCC) and the insula. Moreover, a network including vmPFC and PCC showed higher connectivity during the positive (> negative) future thinking condition. Since these regions are often associated with affective processing, these findings suggest that “hot,” affective processes may, at least in certain circumstances, play a role in self-control.
Keywords
Cognitive Neuroscience, Behavioral Neuroscience, Neuropsychology and Physiological Psychology

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Chicago
Kruschwitz, Johann D., Vera U. Ludwig, Lea Waller, David List, David Wisniewski, Uta Wolfensteller, Thomas Goschke, and Henrik Walter. 2018. “Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach.” Frontiers in Behavioral Neuroscience 12.
APA
Kruschwitz, J. D., Ludwig, V. U., Waller, L., List, D., Wisniewski, D., Wolfensteller, U., Goschke, T., et al. (2018). Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach. Frontiers in Behavioral Neuroscience, 12.
Vancouver
1.
Kruschwitz JD, Ludwig VU, Waller L, List D, Wisniewski D, Wolfensteller U, et al. Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach. Frontiers in Behavioral Neuroscience. Frontiers Media SA; 2018;12.
MLA
Kruschwitz, Johann D., Vera U. Ludwig, Lea Waller, et al. “Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach.” Frontiers in Behavioral Neuroscience 12 (2018): n. pag. Print.
@article{8584175,
  abstract     = {During self-control, we may resist short-term temptations in order to reach a favorable future (e.g., resisting cake to stay healthy). The neural basis of self-control is typically attributed to {\textquotedblleft}cold,{\textquotedblright} unemotional cognitive control mechanisms which inhibit affect-related regions via the prefrontal cortex (PFC). Here, we investigate the neural underpinnings of regulating cravings by mentally evoking the positive consequences of resisting a temptation (e.g., being healthy) as opposed to evoking the negative consequences of giving in to a temptation (e.g., becoming overweight). It is conceivable that when using these types of strategies, regions associated with emotional processing [e.g., striatum, ventromedial prefrontal cortex (vmPFC)] are involved in addition to control-related prefrontal and parietal regions. Thirty-one participants saw pictures of unhealthy snacks in the fMRI scanner and, depending on the trial, regulated their craving by thinking of the positive consequences of resisting, or the negative consequences of not resisting. In a control condition, they anticipated the pleasure of eating and thus, allowed the craving to occur (now-condition). In line with previous studies, we found activation of a cognitive control network during self-regulation. In the negative future thinking condition, the insula was more active than in the positive condition, while there were no activations that were stronger in the positive ({\textrangle} negative) future thinking condition. However, additionally, multivariate pattern analysis showed that during craving regulation, information about the valence of anticipated emotions was present in the vmPFC, the posterior cingulate cortex (PCC) and the insula. Moreover, a network including vmPFC and PCC showed higher connectivity during the positive ({\textrangle} negative) future thinking condition. Since these regions are often associated with affective processing, these findings suggest that {\textquotedblleft}hot,{\textquotedblright} affective processes may, at least in certain circumstances, play a role in self-control.},
  author       = {Kruschwitz, Johann D. and Ludwig, Vera U. and Waller, Lea and List, David and Wisniewski, David and Wolfensteller, Uta and Goschke, Thomas and Walter, Henrik},
  issn         = {1662-5153},
  journal      = {Frontiers in Behavioral Neuroscience},
  keyword      = {Cognitive Neuroscience,Behavioral Neuroscience,Neuropsychology and Physiological Psychology},
  publisher    = {Frontiers Media SA},
  title        = {Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach},
  url          = {http://dx.doi.org/10.3389/fnbeh.2018.00297},
  volume       = {12},
  year         = {2018},
}

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