1
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Sailer U, Wurm F, Pfabigan DM. Social and non-social feedback stimuli lead to comparable levels of reward learning and reward responsiveness in an online probabilistic reward task. Behav Res Methods 2024; 56:5161-5177. [PMID: 37845425 PMCID: PMC11289059 DOI: 10.3758/s13428-023-02255-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/23/2023] [Indexed: 10/18/2023]
Abstract
Social stimuli seem to be processed more easily and efficiently than non-social stimuli. The current study tested whether social feedback stimuli improve reward learning in a probabilistic reward task (PRT), in which one response option is usually rewarded more often than the other via presentation of non-social reward stimuli. In a pre-registered online study with 305 participants, 75 participants were presented with a non-social feedback stimulus (a star) and information about gains, which is typically used in published PRT studies. Three other groups (with 73-82 participants each) were presented with one of three social feedback stimuli: verbal praise, an attractive happy face, or a "thumbs up"-picture. The data were analysed based on classical signal detection theory, drift diffusion modelling, and Bayesian analyses of null effects. All PRT variants yielded the expected behavioural preference for the more frequently rewarded response. There was no processing advantage of social over non-social feedback stimuli. Bayesian analyses further supported the observation that social feedback stimuli neither increased nor decreased behavioural preferences in the PRT. The current findings suggest that the PRT is a robust experimental paradigm independent of the applied feedback stimuli. They also suggest that the occurrence of a processing advantage for social feedback stimuli is dependent on the experimental task and design.
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Affiliation(s)
- Uta Sailer
- Department of Behavioural Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Sognsvannsveien 9, 0372, Oslo, Norway
| | - Franz Wurm
- Department of Psychology, Leiden University, Leiden, 2333 AK, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, 2333 AK, The Netherlands
| | - Daniela M Pfabigan
- Department of Behavioural Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Sognsvannsveien 9, 0372, Oslo, Norway.
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Jonas Lies vei 91, 5009, Bergen, Norway.
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2
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Zhang Y, Li Y, Mai X. Fear of negative evaluation modulates the processing of social evaluative feedback with different valence and contexts. Cereb Cortex 2022; 33:4927-4938. [PMID: 36190437 DOI: 10.1093/cercor/bhac390] [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: 07/03/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
Fear of negative evaluation (FNE) is a susceptible and maintaining factor of social anxiety disorders. However, the question, how people process negative evaluation is influenced by individual differences in FNE, is poorly understood. To clarify the habitual processing characteristics of individuals with different levels of FNE, electroencephalography was recorded when two groups of participants with high FNE (hFNE) and low FNE (lFNE) performed a social evaluation perception task in which the feedback context/source (human vs. a computer) and valence (thumb-up/like vs. thumb-down/dislike) were manipulated. We found effects of feedback source and valence on N1, P2, and P3, which reflect early attention, integrated perception, and elaborative processing, respectively, as well as general reward effects on reward positivity (RewP) across contexts. Importantly, compared to the lFNE group, the hFNE group showed larger midfrontal N1 and theta oscillation in response to negative feedback indicating dislike (vs. like), and also showed larger P3. These findings suggest that individuals with hFNE are more attentional vigilance to negative (vs. positive) social feedback, implying that individuals with different levels of FNE assign different implicit threat values to social-evaluation threat stimuli.
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Affiliation(s)
- Yinling Zhang
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Yanju Li
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Xiaoqin Mai
- Department of Psychology, Renmin University of China, Beijing 100872, China.,Laboratory of Department of Psychology, Renmin University of China, Beijing 100872, China.,Interdisciplinary Platform of Philosophy and Cognitive Science, Renmin University of China, Beijing 100872, China
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4
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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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5
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Severo MC, Paul K, Walentowska W, Moors A, Pourtois G. Neurophysiological evidence for evaluative feedback processing depending on goal relevance. Neuroimage 2020; 215:116857. [PMID: 32304885 DOI: 10.1016/j.neuroimage.2020.116857] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/18/2020] [Accepted: 04/11/2020] [Indexed: 12/31/2022] Open
Abstract
Feedback signaling the success or failure of actions is readily exploited to implement goal-directed behavior. Two event-related brain potentials (ERPs) have been identified as reliable markers of evaluative feedback processing: the Feedback-Related Negativity (FRN) and the P3. Recent ERP studies have shown a substantial reduction of these components when the feedback's goal relevance (in terms of goal informativeness) was decreased. However, it remains unclear whether this lowering of evaluative feedback processing at the FRN and P3 levels (i) reflects a common regulation process operating across them or (ii) indirectly and mostly depends on valence processing. To address these questions, 44 participants performed a time estimation task wherein the perceived goal relevance of the feedback following each decision was manipulated via instructions in different blocks. We recorded 64-channel EEG and collected subjective ratings of feedback valence and relevance, separately for goal-relevant and irrelevant conditions. ERP results showed a substantial reduction of the FRN and P3 components for irrelevant than relevant feedback, despite the balanced task relevance between them. Moreover, a Principal Component Analysis (PCA) showed that these two successive ERP effects had dissociable spatiotemporal properties. Crucially, a multivariate multiple regression analysis revealed that goal relevance per se, but not valence, was the unique significant predictor of the amplitude reduction of the FRN and P3 when the feedback was goal irrelevant. Our results suggest that although these ERP components exhibit non-overlapping spatiotemporal properties and performance monitoring effects, they can both be modulated by a common, valence-unspecific process related to goal relevance.
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Affiliation(s)
- Mario Carlo Severo
- Cognitive & Affective Psychophysiology Laboratory, Department of Experimental Clinical and Health Psychology, Ghent University, Belgium.
| | - Katharina Paul
- Cognitive & Affective Psychophysiology Laboratory, Department of Experimental Clinical and Health Psychology, Ghent University, Belgium
| | - Wioleta Walentowska
- Cognitive & Affective Psychophysiology Laboratory, Department of Experimental Clinical and Health Psychology, Ghent University, Belgium; Psychophysiology Laboratory, Institute of Psychology, Jagiellonian University in Krakow, Poland
| | - Agnes Moors
- Research Group of Quantitative Psychology and Individual Differences, Center for Social and Cultural Psychology, KU Leuven, Belgium
| | - Gilles Pourtois
- Cognitive & Affective Psychophysiology Laboratory, Department of Experimental Clinical and Health Psychology, Ghent University, Belgium
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7
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Matyjek M, Meliss S, Dziobek I, Murayama K. A Multidimensional View on Social and Non-Social Rewards. Front Psychiatry 2020; 11:818. [PMID: 32973574 PMCID: PMC7466643 DOI: 10.3389/fpsyt.2020.00818] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 07/29/2020] [Indexed: 01/08/2023] Open
Abstract
Social rewards are a broad and heterogeneous set of stimuli including for instance smiling faces, gestures, or praise. They have been widely investigated in cognitive and social neuroscience as well as psychology. Research often contrasts the neural processing of social rewards with non-social ones, with the aim to demonstrate the privileged and unique nature of social rewards or to examine shared neural processing underlying them. However, such comparisons mostly neglect other important dimensions of rewards that are conflated in those types of rewards: primacy, temporal proximity, duration, familiarity, source, tangibility, naturalness, and magnitude. We identify how commonly used rewards in both social and non-social domains may differ in respect to these dimensions and how their interaction calls for careful consideration of alternative interpretations of observed effects. Additionally, we propose potential solutions on how to adapt the multidimensional view to experimental research. Altogether, these methodological considerations aim to inform and improve future experimental designs in research utilizing rewarding stimuli, especially in the social domain.
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Affiliation(s)
- Magdalena Matyjek
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefanie Meliss
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom
| | - Isabel Dziobek
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Kou Murayama
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom.,Research Institute, Kochi University of Technology, Kochi, Japan
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