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Wang W, Yan X, He X, Qian J. Evidence for the Beneficial Effect of Reward on Working Memory: A Meta-Analytic Study. J Intell 2024; 12:88. [PMID: 39330467 PMCID: PMC11433210 DOI: 10.3390/jintelligence12090088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 09/01/2024] [Accepted: 09/05/2024] [Indexed: 09/28/2024] Open
Abstract
Rewards act as external motivators and can improve performance in various cognitive tasks. However, previous research demonstrated mixed findings regarding the effect of reward on working memory (WM) performance, and the question of whether reward enhances WM performance is arguable. It remains unclear how the effect of reward on WM can be influenced by various factors, such as types of reward and experimental paradigms. In this meta-analytic study, we systematically investigated the effect of reward on WM by analyzing data from 51 eligible studies involving a total of 1767 participants. Our results showed that reward robustly enhanced WM performance, with non-monetary rewards inducing more benefits than monetary rewards. This may be because, while both types of reward could induce extrinsic motivation, non-monetary rewards enhanced intrinsic motivation while monetary rewards reduced it. Notably, all three reward methods-reward binding, reward expectation, and subliminal reward-effectively improved WM performance, with the reward binding paradigm exhibiting the greatest effects. This finding suggests that the reward effect can be attributed to both increasing the total amount of WM resources and improving the flexibility of resource reallocation. Moreover, the type of WM, the experimental paradigms, and the outcome measures are three moderators that should be jointly considered when assessing the reward effects on WM. Overall, this meta-analytic study provides solid evidence that reward improves WM performance and reveals possible mechanisms underlying these improvements.
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Affiliation(s)
- Weiyu Wang
- Department of Psychology, Sun Yat-sen University, #132 Waihuan Dong Road, Panyu District, Guangzhou 510006, China
| | - Xin Yan
- Department of Psychology, Sun Yat-sen University, #132 Waihuan Dong Road, Panyu District, Guangzhou 510006, China
| | - Xinyu He
- Department of Psychology, Sun Yat-sen University, #132 Waihuan Dong Road, Panyu District, Guangzhou 510006, China
| | - Jiehui Qian
- Department of Psychology, Sun Yat-sen University, #132 Waihuan Dong Road, Panyu District, Guangzhou 510006, China
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Master SL, Li S, Curtis CE. Trying Harder: How Cognitive Effort Sculpts Neural Representations during Working Memory. J Neurosci 2024; 44:e0060242024. [PMID: 38769009 PMCID: PMC11236589 DOI: 10.1523/jneurosci.0060-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 05/22/2024] Open
Abstract
While the exertion of mental effort improves performance on cognitive tasks, the neural mechanisms by which motivational factors impact cognition remain unknown. Here, we used fMRI to test how changes in cognitive effort, induced by changes in task difficulty, impact neural representations of working memory (WM). Participants (both sexes) were precued whether WM difficulty would be hard or easy. We hypothesized that hard trials demanded more effort as a later decision required finer mnemonic precision. Behaviorally, pupil size was larger and response times were slower on hard compared with easy trials suggesting our manipulation of effort succeeded. Neurally, we observed robust persistent activity during delay periods in the prefrontal cortex (PFC), especially during hard trials. Yet, details of the memoranda could not be decoded from patterns in prefrontal activity. In the patterns of activity in the visual cortex, however, we found strong decoding of memorized targets, where accuracy was higher on hard trials. To potentially link these across-region effects, we hypothesized that effort, carried by persistent activity in the PFC, impacts the quality of WM representations encoded in the visual cortex. Indeed, we found that the amplitude of delay period activity in the frontal cortex predicted decoded accuracy in the visual cortex on a trial-wise basis. These results indicate that effort-related feedback signals sculpt population activity in the visual cortex, improving mnemonic fidelity.
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Affiliation(s)
- Sarah L Master
- Department of Psychology, New York University, New York, New York 10003
| | - Shanshan Li
- Department of Psychology, New York University, New York, New York 10003
- Program in Psychology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Clayton E Curtis
- Department of Psychology, New York University, New York, New York 10003
- Center for Neural Science, New York University, New York, New York 10003
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Zhozhikashvili N, Protopova M, Shkurenko T, Arsalidou M, Zakharov I, Kotchoubey B, Malykh S, Pavlov YG. Working memory processes and intrinsic motivation: An EEG study. Int J Psychophysiol 2024; 201:112355. [PMID: 38718899 DOI: 10.1016/j.ijpsycho.2024.112355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/21/2024] [Accepted: 04/30/2024] [Indexed: 06/11/2024]
Abstract
Processes typically encompassed by working memory (WM) include encoding, retention, and retrieval of information. Previous research has demonstrated that motivation can influence WM performance, although the specific WM processes affected by motivation are not yet fully understood. In this study, we investigated the effects of motivation on different WM processes, examining how task difficulty modulates these effects. We hypothesized that motivation level and personality traits of the participants (N = 48, 32 females; mean age = 21) would modulate the parietal alpha and frontal theta electroencephalography (EEG) correlates of WM encoding, retention, and retrieval phases of the Sternberg task. This effect was expected to be more pronounced under conditions of very high task difficulty. We found that increasing difficulty led to reduced accuracy and increased response time, but no significant relationship was found between motivation and accuracy. However, EEG data revealed that motivation influenced WM processes, as indicated by changes in alpha and theta oscillations. Specifically, higher levels of the Resilience trait-associated with mental toughness, hardiness, self-efficacy, achievement motivation, and low anxiety-were related to increased alpha desynchronization during encoding and retrieval. Increased scores of Subjective Motivation to perform well in the task were related to enhanced frontal midline theta during retention. Additionally, these effects were significantly stronger under conditions of high difficulty. These findings provide insights into the specific WM processes that are influenced by motivation, and underscore the importance of considering both task difficulty and intrinsic motivation in WM research.
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Affiliation(s)
- Natalia Zhozhikashvili
- Faculty of Social Sciences, HSE University, Moscow, Russia; Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany.
| | - Maria Protopova
- Center for Language and Brain, HSE University, Moscow, Russia
| | | | | | - Ilya Zakharov
- Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg, Russia
| | - Boris Kotchoubey
- Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany
| | - Sergey Malykh
- Developmental Behavioral Genetics Lab, Psychological Institute of Russian Academy of Education, Moscow, Russia
| | - Yuri G Pavlov
- Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany
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Souza AS, Frischkorn GT. A diffusion model analysis of age and individual differences in the retro-cue benefit. Sci Rep 2023; 13:17356. [PMID: 37833420 PMCID: PMC10575881 DOI: 10.1038/s41598-023-44080-z] [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: 03/03/2023] [Accepted: 10/03/2023] [Indexed: 10/15/2023] Open
Abstract
The limited capacity of working memory (WM) constrains how well we can think and act. WM capacity is reduced in old age, with one explanation for this decline being a deficit in using attention to control WM contents. The retro-cue paradigm has been used to examine the ability to focus attention in WM. So far, there are conflicting findings regarding an aging deficit in the retro-cue effect. The present study evaluated age-related changes and individual differences in the retro-cue effect through a well-established computational model that combines speed and accuracy to extract underlying psychological parameters. We applied the drift-diffusion model to the data from a large sample of younger and older adults (total N = 346) that completed four retro-cue tasks. Retro-cues increased the quality of the evidence entering the decision process, reduced the time taken for memory retrieval, and changed response conservativeness for younger and older adults. An age-related decline was observed only in the retro-cue boost for evidence quality, and this was the only parameter capturing individual differences in focusing efficiency. Our results suggest that people differ in how well they can strengthen and protect a focused representation to boost evidence-quality accumulation, and this ability declines with aging.
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Affiliation(s)
- Alessandra S Souza
- Center for Psychology, Faculty of Psychology and Education Sciences, University of Porto, Rua Alfredo Allen S/N, 4200-135, Porto, Portugal.
- University of Zurich, Zürich, Switzerland.
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Sun Y, Kang P, Huang L, Wang H, Ku Y. Reward advantage over punishment for incentivizing visual working memory. Psychophysiology 2023; 60:e14300. [PMID: 36966450 DOI: 10.1111/psyp.14300] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 01/26/2023] [Accepted: 03/01/2023] [Indexed: 03/27/2023]
Abstract
The prospects of gaining reward and avoiding punishment widely influence human behavior. Despite of numerous attempts to investigate the influence of motivational signals on working memory (WM), whether the valence and the magnitude of motivational signals interactively influence WM performance remains unclear. To investigate this, the present study used a free-recall working memory task with EEG recording to compare the effect of incentive valence (reward or punishment), as well as the magnitude of incentives on visual WM. Behavioral results revealed that the presence of incentive signals improved WM precision when compared with no-incentive condition, and compared with punishing cues, rewarding cues led to greater facilitation in WM precision, as well as confidence ratings afterward. Moreover, event related potential (ERP) results suggested that compared with punishment, reward led to an earlier latency of late positive component (LPC), a larger amplitude of contingent negative variation (CNV) during the expectation period, and a larger P300 amplitude during the sample and delay periods. Furthermore, reward advantage over punishment in behavioral and neural results were correlated, such that individuals with larger CNV difference between reward and punishment conditions also report greater distinction in confidence ratings between the two conditions. In sum, our results demonstrate what and how rewarding cues cause more beneficial effects than punishing cues when incentivizing visual WM.
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Affiliation(s)
- Yurong Sun
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Center for Brain and Mental Well-Being, Department of Psychology, Sun Yat-sen University, Guangzhou, China
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Pyungwon Kang
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Leyu Huang
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Huimin Wang
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Yixuan Ku
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Center for Brain and Mental Well-Being, Department of Psychology, Sun Yat-sen University, Guangzhou, China
- Peng Cheng Laboratory, Shenzhen, China
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Task prioritization modulates alpha, theta and beta EEG dynamics reflecting proactive cognitive control. Sci Rep 2022; 12:15072. [PMID: 36064572 PMCID: PMC9445103 DOI: 10.1038/s41598-022-19158-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 08/24/2022] [Indexed: 11/09/2022] Open
Abstract
Most neuroscientific studies investigating mental effort apply unspecific effort allocation paradigms. In contrast, the present EEG study targets specific effort allocation during task prioritization. Twenty-eight participants performed a cued number classification task during the retention interval of a working memory task including retrospective cues. One of two possible number classifications was done per trial. Each trial started with a cue indicating which of the two tasks would be more important in the upcoming trial. Subjects were told to engage in both tasks, but to concentrate on the important one. Feedback given at the end of each trial was calculated based on task performance, with scores obtained from the relevant task being tripled. Participants performed significantly better in either task when it was important compared to when not. Task prioritization modulates theta, alpha and beta oscillations, predominantly during task preparation. Multivariate pattern analysis revealed that the exact type of the two possible number classifications was decodable, however, decoding accuracy did not depend on task importance. Hemispheric alpha power asymmetries indicating attentional orienting between working memory representations also did not depend on task importance. The findings suggest that task prioritization primarily affects proactive cognitive control on a superordinate level.
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