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Xu Q, Wang J, Li P. Willingness valued more than ability in partner choice: Insights into behavioral and ERP data. Psychophysiology 2024; 61:e14558. [PMID: 38459648 DOI: 10.1111/psyp.14558] [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: 11/30/2023] [Revised: 02/01/2024] [Accepted: 02/19/2024] [Indexed: 03/10/2024]
Abstract
In human cooperation, people prefer to choose partners with high willingness and ability-while both are valued by partners, individuals often prioritize willingness. Two event-related potential (ERP) experiments were conducted to discern the neural processes underpinning this preference. In the first experiment, participants made a choice between two potential partners and received feedback on the selected partner's willingness to cooperate. This was followed by feedback on the partner's task performance (ability) or a gambling outcome. In contrast, the second experiment first provided feedback on ability, then presented feedback on willingness or a gambling outcome. This study revealed that a potential partner's willingness trait significantly influences individuals' emotional evaluations and monetary allocations than the ability trait. Electrophysiological data indicated that low-willingness feedback elicited a diminished feedback-related negative (FRN) and an amplified P3 compared to high-willingness feedback. In contrast, no such difference was discernible between high- and low-ability feedback. Moreover, the P3 difference from high versus low willingness was considerably more pronounced than that from gambling outcomes, whereas the difference wave between high and low ability paralleled gambling outcomes. These findings bolster the novel finding that partner willingness may provide more substantial social rewards than ability. Furthermore, this study provides the first ERP evidence of willingness and ability trait perceptions in partner choice decisions.
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Affiliation(s)
- Qiang Xu
- Brain Function and Psychological Science Research Center, Shenzhen University, Shenzhen, China
- School of Psychology, Shenzhen University, Shenzhen, China
| | - Jing Wang
- School of Management, Shenzhen Polytechnic, Shenzhen, China
| | - Peng Li
- Brain Function and Psychological Science Research Center, Shenzhen University, Shenzhen, China
- School of Psychology, Shenzhen University, Shenzhen, China
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Albrecht C, van de Vijver R, Bellebaum C. Learning new words via feedback-Association between feedback-locked ERPs and recall performance-An exploratory study. Psychophysiology 2023; 60:e14324. [PMID: 37144796 DOI: 10.1111/psyp.14324] [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: 05/18/2022] [Revised: 04/13/2023] [Accepted: 04/18/2023] [Indexed: 05/06/2023]
Abstract
Feedback learning is thought to involve the dopamine system and its projection sites in the basal ganglia and anterior cingulate cortex (ACC), regions associated with procedural learning. Under certain conditions, such as when feedback is delayed, feedback-locked activation is pronounced in the medial temporal lobe (MTL), which is associated with declarative learning. In event-related potential research, the feedback-related negativity (FRN) has been linked to immediate feedback processing, while the N170, possibly reflecting MTL activity, has been related to delayed feedback processing. In the current study, we performed an exploratory investigation on the relation between N170 and FRN amplitude and memory performance in a test for declarative memory (free recall), also exploring the role of feedback delay. To this end, we adapted a paradigm in which participants learned associations between non-objects and non-words with either immediate or delayed feedback, and added a subsequent free recall test. We indeed found that N170, but not FRN amplitudes, depended on later free recall performance, with smaller amplitudes for later remembered non-words. In an additional analysis with memory performance as dependent variable, the N170, but not the FRN amplitude predicted free recall, modulated by feedback timing and valence. This finding shows that the N170 reflects an important process during feedback processing, possibly related to expectations and their violation, but is distinct from the process reflected by the FRN.
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Affiliation(s)
- Christine Albrecht
- Institute of Experimental Psychology, Heinrich Heine University, Düsseldorf, Germany
| | - Ruben van de Vijver
- Institute of Linguistics and Information Science, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Bellebaum
- Institute of Experimental Psychology, Heinrich Heine University, Düsseldorf, Germany
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Legaz A, Abrevaya S, Dottori M, Campo CG, Birba A, Caro MM, Aguirre J, Slachevsky A, Aranguiz R, Serrano C, Gillan CM, Leroi I, García AM, Fittipaldi S, Ibañez A. Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases. Brain 2021; 145:1052-1068. [PMID: 34529034 PMCID: PMC9128375 DOI: 10.1093/brain/awab345] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/17/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Social feedback can selectively enhance learning in diverse domains. Relevant
neurocognitive mechanisms have been studied mainly in healthy persons, yielding
correlational findings. Neurodegenerative lesion models, coupled with multimodal
brain measures, can complement standard approaches by revealing direct
multidimensional correlates of the phenomenon. To this end, we assessed socially reinforced and non-socially reinforced learning
in 40 healthy participants as well as persons with behavioural variant
frontotemporal dementia (n = 21), Parkinson’s
disease (n = 31) and Alzheimer’s disease
(n = 20). These conditions are typified by
predominant deficits in social cognition, feedback-based learning and
associative learning, respectively, although all three domains may be partly
compromised in the other conditions. We combined a validated behavioural task
with ongoing EEG signatures of implicit learning (medial frontal negativity) and
offline MRI measures (voxel-based morphometry). In healthy participants, learning was facilitated by social feedback relative to
non-social feedback. In comparison with controls, this effect was specifically
impaired in behavioural variant frontotemporal dementia and Parkinson’s
disease, while unspecific learning deficits (across social and non-social
conditions) were observed in Alzheimer’s disease. EEG results showed
increased medial frontal negativity in healthy controls during social feedback
and learning. Such a modulation was selectively disrupted in behavioural variant
frontotemporal dementia. Neuroanatomical results revealed extended
temporo-parietal and fronto-limbic correlates of socially reinforced learning,
with specific temporo-parietal associations in behavioural variant
frontotemporal dementia and predominantly fronto-limbic regions in
Alzheimer’s disease. In contrast, non-socially reinforced learning was
consistently linked to medial temporal/hippocampal regions. No associations with
cortical volume were found in Parkinson’s disease. Results are consistent
with core social deficits in behavioural variant frontotemporal dementia, subtle
disruptions in ongoing feedback-mechanisms and social processes in
Parkinson’s disease and generalized learning alterations in
Alzheimer’s disease. This multimodal approach highlights the impact of
different neurodegenerative profiles on learning and social feedback. Our findings inform a promising theoretical and clinical agenda in the fields of
social learning, socially reinforced learning and neurodegeneration.
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Affiliation(s)
- Agustina Legaz
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Universidad Nacional de Córdoba. Facultad de Psicología, Córdoba, CU320, Argentina
| | - Sofía Abrevaya
- National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, CONICET, Buenos Aires, C1021, Argentina
| | - Martín Dottori
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina
| | - Cecilia González Campo
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | - Agustina Birba
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | - Miguel Martorell Caro
- National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, CONICET, Buenos Aires, C1021, Argentina
| | - Julieta Aguirre
- Instituto de Investigaciones Psicológicas (IIPsi), CONICET, Universidad Nacional de Córdoba, Córdoba, CB5000, Argentina
| | - Andrea Slachevsky
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital delSalvador, SSMO & Faculty of Medicine, University of Chile, Santiago, Chile.,Gerosciences Center for Brain Health and Metabolism, Santiago, Chile.,Neuropsychology and Clinical Neuroscience Laboratory, Physiopathology Department, ICBM, Neurosciences Department, Faculty of Medicine, University of Chile, Chile.,Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Chile
| | | | - Cecilia Serrano
- Neurología Cognitiva, Hospital Cesar Milstein, Buenos Aires, C1221, Argentina
| | - Claire M Gillan
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA.,Department of Psychology, Trinity College Dublin, Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Iracema Leroi
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA
| | - Adolfo M García
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA.,Global Brain Health Institute (GBHI), Trinity College Dublin (TCD), Dublin, Dublin 2, Ireland.,Faculty of Education, National University of Cuyo, Mendoza, M5502JMA, Argentina.,Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Sol Fittipaldi
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Universidad Nacional de Córdoba. Facultad de Psicología, Córdoba, CU320, Argentina
| | - Agustín Ibañez
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
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Chen X, Zhang L, Yang D, Li C, An G, Wang J, Shao Y, Fan R, Ma Q. Effects of Caffeine on Event-Related Potentials and Neuropsychological Indices After Sleep Deprivation. Front Behav Neurosci 2020; 14:108. [PMID: 32714162 PMCID: PMC7347038 DOI: 10.3389/fnbeh.2020.00108] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 05/28/2020] [Indexed: 11/13/2022] Open
Abstract
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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Affiliation(s)
- Xuewei Chen
- Department of Operational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Liwei Zhang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Danfeng Yang
- Department of Operational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Chao Li
- Department of Operational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Gaihong An
- Department of Operational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Jing Wang
- Department of Operational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
| | - Rong Fan
- Central Laboratory, Xi Qing Hospital, Tianjin, China
| | - Qiang Ma
- Department of Operational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
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de Bruijn ERA, Mars RB, Hester R. Processing of performance errors predicts memory formation: Enhanced feedback-related negativities for corrected versus repeated errors in an associative learning paradigm. Eur J Neurosci 2019; 51:881-890. [PMID: 31494976 PMCID: PMC7079158 DOI: 10.1111/ejn.14566] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 08/20/2019] [Accepted: 08/27/2019] [Indexed: 11/27/2022]
Abstract
Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demonstrated enhanced anterior cingulate cortex activity for errors that were later corrected versus repeated errors even when a substantial delay between the error and the opportunity to correct was introduced. We aimed at identifying the electrophysiological correlates of these processes by investigating the feedback‐related negativity (FRN) and stimulus‐locked P3. Participants had to learn and recall the location of 2‐digit targets over consecutive rounds. Feedback was provided in two steps, first a color change indicated a correct or incorrect response (feedback phase) followed by presentation of the correct digit information (re‐encoding phase). Behaviorally, participants improved performance from the first to the third round. FRN amplitudes time‐locked to feedback were enhanced for corrected compared to repeated errors. The P3 in response to re‐encoding did not differ between the two error types. The finding that FRN amplitudes positively predicted memory performance is consistent with the idea that the FRN reflects prediction errors and the need for enhanced cognitive control. Interestingly, this happens early during feedback processing and not at a later time point when re‐encoding of correct information takes place. The prediction error signal reflected in the FRN is usually elicited by performance errors, but may thus also play a role in preparing/optimizing the system for memory formation. This supports the existence of a close link between action control and memory processes even when there is a substantial delay between error feedback and the opportunity to correct the error.
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Affiliation(s)
- Ellen R A de Bruijn
- Department of Clinical Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition (LIBC), Leiden, The Netherlands
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Rob Hester
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Vic., Australia
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