The concept of emotional intelligence (EI) refers to the ability to recognize and regulate emotions to appropriately guide cognition and behaviour. Unfortunately, studies on the neural bases of EI are scant, and no study so far has exhaustively investigated grey matter (GM) and white matter (WM) contributions to it. To fill this gap, we analysed trait measure of EI and structural MRI data from 128 healthy participants to shed new light on where and how EI is encoded in the brain. In addition, we explored the relationship between the neural substrates of trait EI and trait anxiety. A data fusion unsupervised machine learning approach (mCCA + jICA) was used to decompose the brain into covarying GM-WM networks and to assess their association with trait-EI. Results showed that high levels trait-EI are associated with decrease in GM-WM concentration in a network spanning from frontal to parietal and temporal regions, among which insula, cingulate, parahippocampal gyrus, cuneus and precuneus. Interestingly, we also found that the higher the GM-WM concentration in the same network, the higher the trait anxiety. These findings encouragingly highlight the neural substrates of trait EI and their relationship with anxiety. The network is discussed considering its overlaps with the Default Mode Network.
情商(EI)的概念是指识别和调节情绪以适当指导认知和行为的能力。遗憾的是,有关情商神经基础的研究还很少,迄今为止还没有一项研究详尽调查了灰质(GM)和白质(WM)对情商的贡献。为了填补这一空白,我们分析了来自 128 名健康参与者的 EI 特质测量值和结构性核磁共振成像数据,以揭示 EI 在大脑中编码的位置和方式。此外,我们还探讨了特质情绪指数的神经基质与特质焦虑之间的关系。我们采用了一种数据融合无监督机器学习方法(mCCA + jICA),将大脑分解成共变的 GM-WM 网络,并评估它们与特质 EI 之间的关联。结果表明,特质-EI 水平高与额叶、顶叶和颞叶网络中 GM-WM 浓度的降低有关,其中包括岛叶、扣带回、海马旁回、楔形回和楔前回。有趣的是,我们还发现,同一网络中 GM-WM 的浓度越高,特质焦虑就越高。这些发现令人鼓舞地强调了特质情绪智力的神经基质及其与焦虑的关系。考虑到该网络与默认模式网络的重叠,我们对其进行了讨论。
{"title":"Reduced GM-WM concentration inside the Default Mode Network in individuals with high emotional intelligence and low anxiety: a data fusion mCCA+jICA approach.","authors":"Alessandro Grecucci, Bianca Monachesi, Irene Messina","doi":"10.1093/scan/nsae018","DOIUrl":"10.1093/scan/nsae018","url":null,"abstract":"<p><p>The concept of emotional intelligence (EI) refers to the ability to recognize and regulate emotions to appropriately guide cognition and behaviour. Unfortunately, studies on the neural bases of EI are scant, and no study so far has exhaustively investigated grey matter (GM) and white matter (WM) contributions to it. To fill this gap, we analysed trait measure of EI and structural MRI data from 128 healthy participants to shed new light on where and how EI is encoded in the brain. In addition, we explored the relationship between the neural substrates of trait EI and trait anxiety. A data fusion unsupervised machine learning approach (mCCA + jICA) was used to decompose the brain into covarying GM-WM networks and to assess their association with trait-EI. Results showed that high levels trait-EI are associated with decrease in GM-WM concentration in a network spanning from frontal to parietal and temporal regions, among which insula, cingulate, parahippocampal gyrus, cuneus and precuneus. Interestingly, we also found that the higher the GM-WM concentration in the same network, the higher the trait anxiety. These findings encouragingly highlight the neural substrates of trait EI and their relationship with anxiety. The network is discussed considering its overlaps with the Default Mode Network.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10919484/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140061667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Our emotions may influence how we interact with others. Previous studies have shown an important role of emotion induction in generating empathic reactions towards others' affect. However, it remains unclear whether (and to which extent) our own emotions can influence the ability to infer people's mental states, a process associated with Theory of Mind (ToM) and implicated in the representation of both cognitive (e.g. beliefs and intentions) and affective conditions. We engaged 59 participants in two emotion-induction experiments where they saw joyful, neutral and fearful clips. Subsequently, they were asked to infer other individuals' joy, fear (affective ToM) or beliefs (cognitive ToM) from verbal scenarios. Using functional magnetic resonance imaging, we found that brain activity in the superior temporal gyrus, precuneus and sensorimotor cortices were modulated by the preceding emotional induction, with lower response when the to-be-inferred emotion was incongruent with the one induced in the observer (affective ToM). Instead, we found no effect of emotion induction on the appraisal of people's beliefs (cognitive ToM). These findings are consistent with embodied accounts of affective ToM, whereby our own emotions alter the engagement of key brain regions for social cognition, depending on the compatibility between one's own and others' affect.
我们的情绪可能会影响我们与他人的互动方式。以往的研究表明,情绪诱导在对他人的情绪产生移情反应方面发挥着重要作用。然而,我们自己的情绪是否(以及在多大程度上)会影响推断他人心理状态的能力(这是一个与心智理论(ToM)相关的过程,并与认知(如信念和意图)和情感条件的表征有关),目前仍不清楚。我们让 59 名参与者参加了两项情绪诱导实验,让他们观看欢乐、中性和恐惧片段。随后,他们被要求从语言情景中推断其他人的快乐、恐惧(情感 ToM)或信念(认知 ToM)。通过功能磁共振成像,我们发现颞上回、楔前区和感觉运动皮层的大脑活动受之前情绪诱导的调节,当被推断的情绪与观察者被诱导的情绪不一致时(情感性 ToM),大脑的反应较低。相反,我们发现情绪诱导对人们的信念评估(认知 ToM)没有影响。这些发现与情感性 ToM 的具身说法一致,即我们自身的情感会改变社会认知关键脑区的参与,这取决于自身情感与他人情感之间的兼容性。
{"title":"Influence of transient emotional episodes on affective and cognitive theory of mind.","authors":"Emilie Qiao-Tasserit, Corrado Corradi-Dell'Acqua, Patrik Vuilleumier","doi":"10.1093/scan/nsae016","DOIUrl":"10.1093/scan/nsae016","url":null,"abstract":"<p><p>Our emotions may influence how we interact with others. Previous studies have shown an important role of emotion induction in generating empathic reactions towards others' affect. However, it remains unclear whether (and to which extent) our own emotions can influence the ability to infer people's mental states, a process associated with Theory of Mind (ToM) and implicated in the representation of both cognitive (e.g. beliefs and intentions) and affective conditions. We engaged 59 participants in two emotion-induction experiments where they saw joyful, neutral and fearful clips. Subsequently, they were asked to infer other individuals' joy, fear (affective ToM) or beliefs (cognitive ToM) from verbal scenarios. Using functional magnetic resonance imaging, we found that brain activity in the superior temporal gyrus, precuneus and sensorimotor cortices were modulated by the preceding emotional induction, with lower response when the to-be-inferred emotion was incongruent with the one induced in the observer (affective ToM). Instead, we found no effect of emotion induction on the appraisal of people's beliefs (cognitive ToM). These findings are consistent with embodied accounts of affective ToM, whereby our own emotions alter the engagement of key brain regions for social cognition, depending on the compatibility between one's own and others' affect.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10914405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140041247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elliot Kale Edmiston, Henry W Chase, Neil Jones, Tiffany J Nhan, Mary L Phillips, Jay C Fournier
Anxiety and depression co-occur; the neural substrates of shared and unique components of these symptoms are not understood. Given emotional alterations in internalizing disorders, we hypothesized that function of regions associated with emotion processing/regulation, including the anterior cingulate cortex (ACC), amygdala and fusiform gyrus (FG), would differentiate these symptoms. Forty-three adults with depression completed an emotional functional magnetic resonance imaging task and the Hamilton Depression and Anxiety Scales. We transformed these scales to examine two orthogonal components, one representing internalizing symptom severity and the other the type of internalizing symptoms (anxiety vs depression). We extracted blood oxygen level dependent signal from FG subregions, ACC, and amygdala and performed generalized psychophysiological interaction analyses to assess relationships between symptoms and brain function. Type of internalizing symptoms was associated with FG3-FG1 coupling (F = 8.14, P = 0.007). More coupling was associated with a higher concentration of depression, demonstrating that intra-fusiform coupling is differentially associated with internalizing symptom type (anxiety vs depression). We found an interaction between task condition and internalizing symptoms and dorsal (F = 4.51, P = 0.014) and rostral ACC activity (F = 4.27, P = 0.012). Post hoc comparisons revealed that less activity was associated with greater symptom severity during emotional regulation. Functional coupling differences during emotional processing are associated with depressive relative to anxiety symptoms and internalizing symptom severity. These findings could inform future treatments for depression.
{"title":"Differential role of fusiform gyrus coupling in depressive and anxiety symptoms during emotion perception.","authors":"Elliot Kale Edmiston, Henry W Chase, Neil Jones, Tiffany J Nhan, Mary L Phillips, Jay C Fournier","doi":"10.1093/scan/nsae009","DOIUrl":"10.1093/scan/nsae009","url":null,"abstract":"<p><p>Anxiety and depression co-occur; the neural substrates of shared and unique components of these symptoms are not understood. Given emotional alterations in internalizing disorders, we hypothesized that function of regions associated with emotion processing/regulation, including the anterior cingulate cortex (ACC), amygdala and fusiform gyrus (FG), would differentiate these symptoms. Forty-three adults with depression completed an emotional functional magnetic resonance imaging task and the Hamilton Depression and Anxiety Scales. We transformed these scales to examine two orthogonal components, one representing internalizing symptom severity and the other the type of internalizing symptoms (anxiety vs depression). We extracted blood oxygen level dependent signal from FG subregions, ACC, and amygdala and performed generalized psychophysiological interaction analyses to assess relationships between symptoms and brain function. Type of internalizing symptoms was associated with FG3-FG1 coupling (F = 8.14, P = 0.007). More coupling was associated with a higher concentration of depression, demonstrating that intra-fusiform coupling is differentially associated with internalizing symptom type (anxiety vs depression). We found an interaction between task condition and internalizing symptoms and dorsal (F = 4.51, P = 0.014) and rostral ACC activity (F = 4.27, P = 0.012). Post hoc comparisons revealed that less activity was associated with greater symptom severity during emotional regulation. Functional coupling differences during emotional processing are associated with depressive relative to anxiety symptoms and internalizing symptom severity. These findings could inform future treatments for depression.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10908550/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139708913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The cerebellum causally supports social processing by generating internal models of social events based on statistical learning of behavioral regularities. However, whether the cerebellum is only involved in forming or also in using internal models for the prediction of forthcoming actions is still unclear. We used cerebellar transcranial Direct Current Stimulation (ctDCS) to modulate the performance of healthy adults in using previously learned expectations in an action prediction task. In a first learning phase of this task, participants were exposed to different levels of associations between specific actions and contextual elements, to induce the formation of either strongly or moderately informative expectations. In a following testing phase, which assessed the use of these expectations for predicting ambiguous (i.e. temporally occluded) actions, we delivered ctDCS. Results showed that anodic, compared to sham, ctDCS boosted the prediction of actions embedded in moderately, but not strongly, informative contexts. Since ctDCS was delivered during the testing phase, that is after expectations were established, our findings suggest that the cerebellum is causally involved in using internal models (and not just in generating them). This encourages the exploration of the clinical effects of ctDCS to compensate poor use of predictive internal models for social perception.
{"title":"Excitatory cerebellar transcranial direct current stimulation boosts the leverage of prior knowledge for predicting actions.","authors":"Viola Oldrati, Niccolò Butti, Elisabetta Ferrari, Zaira Cattaneo, Cosimo Urgesi, Alessandra Finisguerra","doi":"10.1093/scan/nsae019","DOIUrl":"10.1093/scan/nsae019","url":null,"abstract":"<p><p>The cerebellum causally supports social processing by generating internal models of social events based on statistical learning of behavioral regularities. However, whether the cerebellum is only involved in forming or also in using internal models for the prediction of forthcoming actions is still unclear. We used cerebellar transcranial Direct Current Stimulation (ctDCS) to modulate the performance of healthy adults in using previously learned expectations in an action prediction task. In a first learning phase of this task, participants were exposed to different levels of associations between specific actions and contextual elements, to induce the formation of either strongly or moderately informative expectations. In a following testing phase, which assessed the use of these expectations for predicting ambiguous (i.e. temporally occluded) actions, we delivered ctDCS. Results showed that anodic, compared to sham, ctDCS boosted the prediction of actions embedded in moderately, but not strongly, informative contexts. Since ctDCS was delivered during the testing phase, that is after expectations were established, our findings suggest that the cerebellum is causally involved in using internal models (and not just in generating them). This encourages the exploration of the clinical effects of ctDCS to compensate poor use of predictive internal models for social perception.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11227954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140308436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This review offers an accessible primer to social neuroscientists interested in neural networks. It begins by providing an overview of key concepts in deep learning. It then discusses three ways neural networks can be useful to social neuroscientists: (i) building statistical models to predict behavior from brain activity; (ii) quantifying naturalistic stimuli and social interactions; and (iii) generating cognitive models of social brain function. These applications have the potential to enhance the clinical value of neuroimaging and improve the generalizability of social neuroscience research. We also discuss the significant practical challenges, theoretical limitations and ethical issues faced by deep learning. If the field can successfully navigate these hazards, we believe that artificial neural networks may prove indispensable for the next stage of the field's development: deep social neuroscience.
{"title":"Deep social neuroscience: the promise and peril of using artificial neural networks to study the social brain.","authors":"Beau Sievers, Mark A Thornton","doi":"10.1093/scan/nsae014","DOIUrl":"10.1093/scan/nsae014","url":null,"abstract":"<p><p>This review offers an accessible primer to social neuroscientists interested in neural networks. It begins by providing an overview of key concepts in deep learning. It then discusses three ways neural networks can be useful to social neuroscientists: (i) building statistical models to predict behavior from brain activity; (ii) quantifying naturalistic stimuli and social interactions; and (iii) generating cognitive models of social brain function. These applications have the potential to enhance the clinical value of neuroimaging and improve the generalizability of social neuroscience research. We also discuss the significant practical challenges, theoretical limitations and ethical issues faced by deep learning. If the field can successfully navigate these hazards, we believe that artificial neural networks may prove indispensable for the next stage of the field's development: deep social neuroscience.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10880882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139708938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mia Anthony, Adam Turnbull, Duje Tadin, F Vankee Lin
Cognitive training for older adults varies in efficacy, but it is unclear why some older adults benefit more than others. Positive affective experience (PAE), referring to high positive valence and/or stable arousal states across everyday scenarios, and associated functional networks can protect plasticity mechanisms against Alzheimer's disease neurodegeneration, which may contribute to training outcome variability. The objective of this study is to investigate whether PAE explains variability in cognitive training outcomes by disrupting the adverse effect of neurodegeneration on plasticity. The study's design is a secondary analysis of a randomized control trial of cognitive training with concurrent real or sham brain stimulation (39 older adults with mild cognitive impairment; mean age, 71). Moderation analyses, with change in episodic memory or executive function as the outcome, PAE or baseline resting-state connectivity as the moderator and baseline neurodegeneration as the predictor are the methods used in the study. The result of the study is that PAE stability and baseline default mode network (DMN) connectivity disrupted the effect of neurodegeneration on plasticity in executive function but not episodic memory. The study concludes that PAE stability and degree of DMN integrity both explained cognitive training outcome variability, by reducing the adverse effect of neurodegeneration on cognitive plasticity. We highlight the need to account for PAE, brain aging factors and their interactions with plasticity in cognitive training.
{"title":"Positive affect disrupts neurodegeneration effects on cognitive training plasticity in older adults.","authors":"Mia Anthony, Adam Turnbull, Duje Tadin, F Vankee Lin","doi":"10.1093/scan/nsae004","DOIUrl":"10.1093/scan/nsae004","url":null,"abstract":"<p><p>Cognitive training for older adults varies in efficacy, but it is unclear why some older adults benefit more than others. Positive affective experience (PAE), referring to high positive valence and/or stable arousal states across everyday scenarios, and associated functional networks can protect plasticity mechanisms against Alzheimer's disease neurodegeneration, which may contribute to training outcome variability. The objective of this study is to investigate whether PAE explains variability in cognitive training outcomes by disrupting the adverse effect of neurodegeneration on plasticity. The study's design is a secondary analysis of a randomized control trial of cognitive training with concurrent real or sham brain stimulation (39 older adults with mild cognitive impairment; mean age, 71). Moderation analyses, with change in episodic memory or executive function as the outcome, PAE or baseline resting-state connectivity as the moderator and baseline neurodegeneration as the predictor are the methods used in the study. The result of the study is that PAE stability and baseline default mode network (DMN) connectivity disrupted the effect of neurodegeneration on plasticity in executive function but not episodic memory. The study concludes that PAE stability and degree of DMN integrity both explained cognitive training outcome variability, by reducing the adverse effect of neurodegeneration on cognitive plasticity. We highlight the need to account for PAE, brain aging factors and their interactions with plasticity in cognitive training.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10939393/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139521843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eleanor Moses, Nicole Nelson, Jessica Taubert, Alan J Pegna
Oxytocin (OT) alters social cognition partly through effects on the processing and appraisal of faces. It is debated whether the hormone also impacts the processing of other, non-social, visual stimuli. To this end, we conducted a randomized, counter-balanced, double-blind, placebo (PL)-controlled within-subjects' electro-encephalography (EEG) study with cismale participants (to control for gender dimorphic hormonal effects; n = 37). Participants received intranasal OT (24IU) and completed a one-back task viewing emotional (fearful/ happy) and neutral faces, and threat (snakes/spiders) and non-threat (mushrooms/flowers) non-social stimuli. OT differentially impacted event-related potentials (ERP)s to faces and non-social stimuli. For faces regardless of emotion, OT evoked greater occipital N1 and anterior P1 amplitudes at ∼155 ms than after PL, and lead to sustained differences over anterior, bilateral parietal and occipital sites from 205 ms onwards. For all non-social stimuli, OT evoked greater right parietal N1 amplitudes, and later only impacted threat stimuli over right parietal and occipital sites. None of these OT-induced modulations was related to individual anxiety levels. This pattern of results indicates that OT differentially modulates the processing of faces and non-social stimuli, and that the hormone's effect on visual processing and cognition does not occur as a function of non-clinical levels of anxiety.
{"title":"Oxytocin differentially modulates the early neural responses to faces and non-social stimuli.","authors":"Eleanor Moses, Nicole Nelson, Jessica Taubert, Alan J Pegna","doi":"10.1093/scan/nsae010","DOIUrl":"10.1093/scan/nsae010","url":null,"abstract":"<p><p>Oxytocin (OT) alters social cognition partly through effects on the processing and appraisal of faces. It is debated whether the hormone also impacts the processing of other, non-social, visual stimuli. To this end, we conducted a randomized, counter-balanced, double-blind, placebo (PL)-controlled within-subjects' electro-encephalography (EEG) study with cismale participants (to control for gender dimorphic hormonal effects; n = 37). Participants received intranasal OT (24IU) and completed a one-back task viewing emotional (fearful/ happy) and neutral faces, and threat (snakes/spiders) and non-threat (mushrooms/flowers) non-social stimuli. OT differentially impacted event-related potentials (ERP)s to faces and non-social stimuli. For faces regardless of emotion, OT evoked greater occipital N1 and anterior P1 amplitudes at ∼155 ms than after PL, and lead to sustained differences over anterior, bilateral parietal and occipital sites from 205 ms onwards. For all non-social stimuli, OT evoked greater right parietal N1 amplitudes, and later only impacted threat stimuli over right parietal and occipital sites. None of these OT-induced modulations was related to individual anxiety levels. This pattern of results indicates that OT differentially modulates the processing of faces and non-social stimuli, and that the hormone's effect on visual processing and cognition does not occur as a function of non-clinical levels of anxiety.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10876073/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139901107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The tendency of all humans to experience loneliness at some point in their lives implies that it serves an adaptive function. Building on biological theories of herding in animals, according to which collective movement emerges from local interactions that are based on principles of attraction, repulsion and alignment, we propose an approach that synthesizes these principles with theories of loneliness in humans. We present here the 'herding model of loneliness' that extends these principles into the psychological domain. We hold that these principles serve as basic building blocks of human interactions and propose that distorted attraction and repulsion tendencies may lead to inability to align properly with others, which may be a core component in loneliness emergence and perpetuation. We describe a neural model of herding in humans and suggest that loneliness may be associated with altered interactions between the gap/error detection, reward signaling, threat and observation-execution systems. The proposed model offers a framework to predict the behavior of lonely individuals and thus may inform intervention designs for reducing loneliness intensity.
{"title":"Away from the herd: loneliness as a dysfunction of social alignment.","authors":"Simone G Shamay-Tsoory, Alisa Kanterman","doi":"10.1093/scan/nsae005","DOIUrl":"10.1093/scan/nsae005","url":null,"abstract":"<p><p>The tendency of all humans to experience loneliness at some point in their lives implies that it serves an adaptive function. Building on biological theories of herding in animals, according to which collective movement emerges from local interactions that are based on principles of attraction, repulsion and alignment, we propose an approach that synthesizes these principles with theories of loneliness in humans. We present here the 'herding model of loneliness' that extends these principles into the psychological domain. We hold that these principles serve as basic building blocks of human interactions and propose that distorted attraction and repulsion tendencies may lead to inability to align properly with others, which may be a core component in loneliness emergence and perpetuation. We describe a neural model of herding in humans and suggest that loneliness may be associated with altered interactions between the gap/error detection, reward signaling, threat and observation-execution systems. The proposed model offers a framework to predict the behavior of lonely individuals and thus may inform intervention designs for reducing loneliness intensity.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10873844/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139577227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michele Deodato, Martin Seeber, Kevin Mammeri, Christoph M Michel, Patrik Vuilleumier
Neuroticism is a personality trait with great clinical relevance, defined as a tendency to experience negative affect, sustained self-generated negative thoughts and impaired emotion regulation. Here, we investigated spontaneous brain dynamics in the aftermath of negative emotional events and their links with neuroticism in order to shed light on the prolonged activity of large-scale brain networks associated with the control of affect. We recorded electroencephalography (EEG) from 36 participants who were asked to rest after watching neutral or fearful video clips. Four topographic maps (i.e. microstates classes A, B, C and D) explained the majority of the variance in spontaneous EEG. Participants showed greater presence of microstate D and lesser presence of microstate C following exposure to fearful stimuli, pointing to changes in attention- and introspection-related networks previously associated with these microstates. These emotional effects were more pronounced for participants with low neuroticism. Moreover, neuroticism scores were positively correlated with microstate C and negatively correlated with microstate D, regardless of previous emotional stimulation. Our results reveal distinctive effects of emotional context on resting-state EEG, consistent with a prolonged impact of negative affect on the brain, and suggest a possible link with neuroticism.
神经质是一种与临床密切相关的人格特质,它被定义为倾向于体验负面情绪、持续自我产生负面想法以及情绪调节能力受损。在这里,我们研究了负面情绪事件发生后大脑的自发动态及其与神经质的联系,以揭示与情绪控制相关的大规模大脑网络的长期活动。我们记录了36名参与者的脑电图(EEG),要求他们在观看中性或恐惧视频片段后休息。四个地形图(即微状态 A、B、C 和 D 类)解释了自发脑电图的大部分差异。受试者在受到恐惧刺激后,微状态 D 的出现率较高,而微状态 C 的出现率较低,这表明以前与这些微状态相关的注意力和内省相关网络发生了变化。这些情绪效应对神经质程度低的参与者更为明显。此外,神经质得分与微状态 C 呈正相关,而与微状态 D 呈负相关,与之前的情绪刺激无关。我们的研究结果揭示了情绪环境对静息状态脑电图的独特影响,这与负面情绪对大脑的长期影响是一致的,并表明这可能与神经质有关。
{"title":"Combined effects of neuroticism and negative emotional context on spontaneous EEG dynamics.","authors":"Michele Deodato, Martin Seeber, Kevin Mammeri, Christoph M Michel, Patrik Vuilleumier","doi":"10.1093/scan/nsae012","DOIUrl":"10.1093/scan/nsae012","url":null,"abstract":"<p><p>Neuroticism is a personality trait with great clinical relevance, defined as a tendency to experience negative affect, sustained self-generated negative thoughts and impaired emotion regulation. Here, we investigated spontaneous brain dynamics in the aftermath of negative emotional events and their links with neuroticism in order to shed light on the prolonged activity of large-scale brain networks associated with the control of affect. We recorded electroencephalography (EEG) from 36 participants who were asked to rest after watching neutral or fearful video clips. Four topographic maps (i.e. microstates classes A, B, C and D) explained the majority of the variance in spontaneous EEG. Participants showed greater presence of microstate D and lesser presence of microstate C following exposure to fearful stimuli, pointing to changes in attention- and introspection-related networks previously associated with these microstates. These emotional effects were more pronounced for participants with low neuroticism. Moreover, neuroticism scores were positively correlated with microstate C and negatively correlated with microstate D, regardless of previous emotional stimulation. Our results reveal distinctive effects of emotional context on resting-state EEG, consistent with a prolonged impact of negative affect on the brain, and suggest a possible link with neuroticism.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10873851/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139708936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Internet addiction symptomatology (IAS) is characterized by persistent and involuntary patterns of compulsive Internet use, leading to significant impairments in both physical and mental well-being. Here, a connectome-based predictive modeling approach was applied to decode IAS from whole-brain resting-state functional connectivity in healthy population. The findings showed that IAS could be predicted by the functional connectivity between prefrontal cortex with the cerebellum and limbic lobe and connections of the occipital lobe with the limbic lobe and insula lobe. The identified edges associated with IAS exhibit generalizability in predicting IAS within an independent sample. Furthermore, we found that the unique contributing network, which predicted IAS in contrast to the prediction networks of alcohol use disorder symptomatology (the range of symptoms and behaviors associated with alcohol use disorder), prominently comprised connections involving the occipital lobe and other lobes. The current data-driven approach provides the first evidence of the predictive brain features of IAS based on the organization of intrinsic brain networks, thus advancing our understanding of the neurobiological basis of Internet addiction disorder (IAD) susceptibility, and may have implications for the timely intervention of people potentially at risk of IAD.
{"title":"Connectome-based predictive modeling of Internet addiction symptomatology.","authors":"Qiuyang Feng, Zhiting Ren, Dongtao Wei, Cheng Liu, Xueyang Wang, Xianrui Li, Bijie Tie, Shuang Tang, Jiang Qiu","doi":"10.1093/scan/nsae007","DOIUrl":"10.1093/scan/nsae007","url":null,"abstract":"<p><p>Internet addiction symptomatology (IAS) is characterized by persistent and involuntary patterns of compulsive Internet use, leading to significant impairments in both physical and mental well-being. Here, a connectome-based predictive modeling approach was applied to decode IAS from whole-brain resting-state functional connectivity in healthy population. The findings showed that IAS could be predicted by the functional connectivity between prefrontal cortex with the cerebellum and limbic lobe and connections of the occipital lobe with the limbic lobe and insula lobe. The identified edges associated with IAS exhibit generalizability in predicting IAS within an independent sample. Furthermore, we found that the unique contributing network, which predicted IAS in contrast to the prediction networks of alcohol use disorder symptomatology (the range of symptoms and behaviors associated with alcohol use disorder), prominently comprised connections involving the occipital lobe and other lobes. The current data-driven approach provides the first evidence of the predictive brain features of IAS based on the organization of intrinsic brain networks, thus advancing our understanding of the neurobiological basis of Internet addiction disorder (IAD) susceptibility, and may have implications for the timely intervention of people potentially at risk of IAD.</p>","PeriodicalId":94208,"journal":{"name":"Social cognitive and affective neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10878364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139708937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}