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Jiang H, Zheng Y. Dissociable neural after-effects of cognitive and physical effort expenditure during reward evaluation. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2023; 23:1500-1512. [PMID: 37821754 DOI: 10.3758/s13415-023-01131-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/18/2023] [Indexed: 10/13/2023]
Abstract
The reward after-effect of effort expenditure refers to the phenomenon that previous effort investment changes the subjective value of rewards when obtained. However, the neural mechanisms underlying the after-effects of effort exertion are still not fully understood. We investigated the modulation of reward after-effects by effort type (cognitive vs. physical) through the lens of neural dynamics. Thirty-two participants performed a physically or cognitively demanding task during an effort phase and then played a simple gambling game during a subsequent reward phase to earn monetary rewards while their electroencephalogram (EEG) was recorded. We found that previous effort expenditure decreased electrocortical activity during feedback evaluation. Importantly, this effort effect occurred in a domain-general manner during the early stage (as indexed by the reward positivity) but in a domain-specific manner during the later and more elaborative stage (as indexed by the P3 and delta oscillation) of reward evaluation. Additionally, effort expenditure enhanced P3 sensitivity to feedback valence regardless of effort type. Our findings suggest that cognitive and physical effort, although bearing some surface resemblance to each other, may have dissociable neural influences on the reward after-effects.
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Affiliation(s)
- Huiping Jiang
- Department of Psychology, Guangzhou University, 230 Wai Huan Xi Road, Guangzhou Higher Education Mega Center, Guangzhou, 510006, China
- Department of Psychology, Dalian Medical University, Dalian, China
| | - Ya Zheng
- Department of Psychology, Guangzhou University, 230 Wai Huan Xi Road, Guangzhou Higher Education Mega Center, Guangzhou, 510006, China.
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Parma JO, Bacelar MFB, Cabral DAR, Recker RS, Orsholits D, Renaud O, Sander D, Krigolson OE, Miller MW, Cheval B, Boisgontier MP. Relationship between reward-related brain activity and opportunities to sit. Cortex 2023; 167:197-217. [PMID: 37572531 DOI: 10.1016/j.cortex.2023.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/23/2023] [Accepted: 06/26/2023] [Indexed: 08/14/2023]
Abstract
The present study tested whether energy-minimizing behaviors evoke reward-related brain activity that promotes the repetition of these behaviors via reinforcement learning processes. Fifty-eight healthy young adults in a standing position performed a task where they could earn a reward either by sitting down or squatting while undergoing electroencephalographic (EEG) recording. Reward-prediction errors were quantified as the amplitude of the EEG-derived reward positivity. Results showed that reward positivity was larger on reward versus no reward trials, confirming the validity of our paradigm to measure evoked reward-related brain activity. However, results showed no evidence that sitting (versus standing and squatting) trials led to larger reward positivity. Moreover, we found no evidence suggesting that this effect was moderated by typical physical activity, physical activity on the day of the study, or energy expenditure during the experiment. However, at the behavioral level, results showed that the probability of choosing the stimulus more likely to lead to sitting than standing increased as the number of trials increased. In addition, results revealed that the probability of changing the selected stimulus was higher when the previous trial was a stand trial relative to a sit trial. In sum, neural results showed no evidence supporting the theory that opportunities to minimize energy expenditure are rewarding. However, behavioral findings suggested participants tend to choose the less effortful behavioral alternative and were therefore consistent with the theory of effort minimization (TEMPA).
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Affiliation(s)
| | | | | | | | - Dan Orsholits
- Centre for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Switzerland; Swiss National Centre of Competence in Research LIVES-Overcoming Vulnerability: Life Course Perspectives, Lausanne and Geneva, Switzerland
| | - Olivier Renaud
- Methodology and Data Analysis, Department of Psychology, University of Geneva, Switzerland
| | - David Sander
- Swiss Center for Affective Sciences, University of Geneva, Switzerland; Laboratory for the Study of Emotion Elicitation and Expression (E3Lab), Department of Psychology, University of Geneva, Switzerland
| | | | - Matthew W Miller
- School of Kinesiology, Auburn University, AL, USA; Center for Neuroscience, Auburn University, USA.
| | - Boris Cheval
- Department of Sport Sciences and Physical Education, Ecole Normale Supérieure Rennes, Bruz, France; Laboratory VIPS2, University of Rennes, Rennes, France.
| | - Matthieu P Boisgontier
- School of Rehabilitation Sciences, Faculty of Health Sciences, University of Ottawa, Ottawa, Canada; Bruyère Research Institute, Ottawa, Canada.
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Using EEG to study sensorimotor adaptation. Neurosci Biobehav Rev 2022; 134:104520. [PMID: 35016897 DOI: 10.1016/j.neubiorev.2021.104520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 12/10/2021] [Accepted: 12/30/2021] [Indexed: 11/23/2022]
Abstract
Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.
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