Personality Neuroscience最新文献

{"title":"Computational Phenotyping: Using Models to Understand Individual Differences in Personality, Development, and Mental Illness.","authors":"Edward H Patzelt,&nbsp;Catherine A Hartley,&nbsp;Samuel J Gershman","doi":"10.1017/pen.2018.14","DOIUrl":"https://doi.org/10.1017/pen.2018.14","url":null,"abstract":"<p><p>This paper reviews progress in the application of computational models to personality, developmental, and clinical neuroscience. We first describe the concept of a computational phenotype, a collection of parameters derived from computational models fit to behavioral and neural data. This approach represents individuals as points in a continuous parameter space, complementing traditional trait and symptom measures. One key advantage of this representation is that it is mechanistic: The parameters have interpretations in terms of cognitive processes, which can be translated into quantitative predictions about future behavior and brain activity. We illustrate with several examples how this approach has led to new scientific insights into individual differences, developmental trajectories, and psychopathology. We then survey some of the challenges that lay ahead.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e18"},"PeriodicalIF":0.0,"publicationDate":"2018-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.14","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960829","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}

{"title":"Norms and the Flexibility of Moral Action.","authors":"Oriel FeldmanHall,&nbsp;Jae-Young Son,&nbsp;Joseph Heffner","doi":"10.1017/pen.2018.13","DOIUrl":"https://doi.org/10.1017/pen.2018.13","url":null,"abstract":"<p><p>A complex web of social and moral norms governs many everyday human behaviors, acting as the glue for social harmony. The existence of moral norms helps elucidate the psychological motivations underlying a wide variety of seemingly puzzling behavior, including why humans help or trust total strangers. In this review, we examine four widespread moral norms: Fairness, altruism, trust, and cooperation, and consider how a single social instrument-reciprocity-underpins compliance to these norms. Using a game theoretic framework, we examine how both context and emotions moderate moral standards, and by extension, moral behavior. We additionally discuss how a mechanism of reciprocity facilitates the adherence to, and enforcement of, these moral norms through a core network of brain regions involved in processing reward. In contrast, violating this set of moral norms elicits neural activation in regions involved in resolving decision conflict and exerting cognitive control. Finally, we review how a reinforcement mechanism likely governs learning about morally normative behavior. Together, this review aims to explain how moral norms are deployed in ways that facilitate flexible moral choices.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e15"},"PeriodicalIF":0.0,"publicationDate":"2018-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.13","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960828","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}

{"title":"Affective Neuroscience Theory and Personality: An Update.","authors":"Christian Montag, Kenneth L Davis","doi":"10.1017/pen.2018.10","DOIUrl":"10.1017/pen.2018.10","url":null,"abstract":"<p><p>The present work gives a short overview of central aspects of Jaak Panksepp's <i>Affective Neuroscience Theory</i> (AN theory) and its relevance for modern personality neuroscience. In contrast to the widely used Big Five approach to studying and understanding human personality, AN theory provides researchers with a distinct roadmap to the biological basis of personality, including molecular and neuroanatomical candidates, to understand individual differences in human behavior. Such molecular and neuroanatomical brain candidates have been derived by means of electrical brain stimulation and pharmacological challenges, while investigating primary emotional systems anchored in the subcortical mammalian brain. Research results derived from the study of emotions in mammals are also of relevance for humans because ancient layers of our minds-those layers where primary emotions originate-have been homologously conserved across species. From an evolutionary perspective, this makes sense because primal emotions represent \"built-in tools for survival\" for all mammals. In this context, Montag and Panksepp recently illustrated a potential ancient neurobiological effect by carving out robust associations between individual differences in primary emotions (assessed via self-report) and the Big Five in a cross-cultural study with data from the United States, Germany, and China. These associations together with some ideas derived from MacLean's Triune Brain concept highlighted (a) that primary emotions likely represent the phylogenetically oldest parts of human personality and (b) that primary emotions influence human personality in a bottom-up fashion given their localization in ancient subcortical brain regions. A comment on the work by Montag and Panksepp asked for insights on putative links between primary emotions and facets of the Big Five. Therefore, we provide some first insights into such associations from recent Germany data. In addition, the present work provides a new short version of the Affective Neuroscience Personality Scales to assess individual differences in primary emotions.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e12"},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960825","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}

{"title":"Human metacognition across domains: insights from individual differences and neuroimaging.","authors":"Marion Rouault,&nbsp;Andrew McWilliams,&nbsp;Micah G Allen,&nbsp;Stephen M Fleming","doi":"10.1017/pen.2018.16","DOIUrl":"https://doi.org/10.1017/pen.2018.16","url":null,"abstract":"<p><p>Metacognition is the capacity to evaluate and control one's own cognitive processes. Metacognition operates over a range of cognitive domains, such as perception and memory, but the neurocognitive architecture supporting this ability remains controversial. Is metacognition enabled by a common, domain-general resource that is recruited to evaluate performance on a variety of tasks? Or is metacognition reliant on domain-specific modules? This article reviews recent literature on the domain-generality of human metacognition, drawing on evidence from individual differences and neuroimaging. A meta-analysis of behavioral studies found that perceptual metacognitive ability was correlated across different sensory modalities, but found no correlation between metacognition of perception and memory. However, evidence for domain-generality from behavioral data may suffer from a lack of power to identify correlations across model parameters indexing metacognitive efficiency. Neuroimaging data provide a complementary perspective on the domain-generality of metacognition, revealing co-existence of neural signatures that are common and distinct across tasks. We suggest that such an architecture may be appropriate for \"tagging\" generic feelings of confidence with domain-specific information, in turn forming the basis for priors about self-ability and modulation of higher-order behavioral control.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":"1 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.16","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9112851","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}

{"title":"The Virtual Personalities Neural Network Model: Neurobiological Underpinnings.","authors":"Stephen J Read,&nbsp;Ashley D Brown,&nbsp;Peter Wang,&nbsp;Lynn C Miller","doi":"10.1017/pen.2018.6","DOIUrl":"https://doi.org/10.1017/pen.2018.6","url":null,"abstract":"<p><p>The Virtual Personalities Model is a motive-based neural network model that provides both a psychological model and a computational implementation that explicates the dynamics and often large within-person variability in behavior that arises over time. At the same time the same model can produce -- across many virtual personalities - between subject variability in behavior that when factor analyzed yields familiar personality structure (e.g., the Big-5). First, we describe our personality model and its implementation as a neural network model. Second, we focus on detailing the neurobiological underpinnings of this model. Third, we examine the learning mechanisms, and their biological substrates, as ways that the model gets \"wired up\", discussing Pavlovian and instrumental conditioning, Pavlovian to instrumental transfer (PIT), and habits. Finally, we describe the dynamics of how initial differences in propensities (e.g., dopamine functioning), wiring differences due to experience, and other factors could operate together to develop and change personality over time, and how this might be empirically examined. Thus, our goal is to contribute to the rising chorus of voices seeking a more precise neurobiologically-based science of the complex dynamics underlying personality.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36665753","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}

{"title":"A Tribute to Jaak Panksepp (1943-2017).","authors":"Kenneth L Davis, Christian Montag","doi":"10.1017/pen.2018.5","DOIUrl":"10.1017/pen.2018.5","url":null,"abstract":"<p><p>This article gives a short overview on the life and achievements of Jaak Panksepp. Jaak Panksepp dedicated his life to the study of mammalian emotions. By means of electrical stimulation of the brain and psychopharmacological challenges he carved out seven primary emotional systems being highly conserved across different species of mammals including homo sapiens. The primary emotional systems are called SEEKING, CARE, LUST, PLAY (positive emotions), and FEAR, RAGE, SADNESS (negative emotions). While his early career was characterized by the direct study of these primary emotions in mammals, in his late career he invested more and more time in applying his knowledge to different fields of psychology including personality neuroscience and psychiatry.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e9"},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219686/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960447","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}

{"title":"A computational network control theory analysis of depression symptoms.","authors":"Yoed N Kenett,&nbsp;Roger E Beaty,&nbsp;John D Medaglia","doi":"10.1017/pen.2018.15","DOIUrl":"https://doi.org/10.1017/pen.2018.15","url":null,"abstract":"<p><p>Rumination and impaired inhibition are considered core characteristics of depression. However, the neurocognitive mechanisms that contribute to these atypical cognitive processes remain unclear. To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in subclinical depression. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that subclinical depression is negatively related to higher integration abilities in the right anterior insula, replicating and extending previous studies implicating atypical switching between the default mode and executive control networks in depression. We also find that subclinical depression is related to the ability to \"drive\" the brain system into easy to reach neural states in several brain regions, including the bilateral lingual gyrus and lateral occipital gyrus. These findings highlight brain regions less known in their role in depression, and clarify their roles in driving the brain into different neural states related to depression symptoms.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.15","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36917011","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}

{"title":"Some Metatheoretical Principles for Personality Neuroscience.","authors":"Neil McNaughton, Luke D Smillie","doi":"10.1017/pen.2018.9","DOIUrl":"10.1017/pen.2018.9","url":null,"abstract":"<p><p>Theories in personality neuroscience must aim to be consistent with several levels of explanation. If we view personality traits as constructs located only at the psychological level, we must still make their explanations compatible with observations and theories at lower levels, particularly with what we know at the neural level. If we view personality traits as constructs located only at the neural level, we will still need to predict their emergent effects at the psychological level. Personality theory at present treats traits as psychological-level constructs, with even the recent neurally oriented Cybernetic Big Five Theory specified in terms of a \"conceptual nervous system\" and not requiring complete or immediate translation into neural mechanisms. Here, we argue for the existence of phylogenetically old, neural-level traits that are substantially conserved across many vertebrate species. We first ask what known mechanisms control trait-like properties of neural systems: Focusing on hormones, the GABA_A receptor, and amine neurotransmitter systems. We derive from what we know about these sources of neuronal modulation some metatheoretical principles to guide the future development of those aspects of personality theory, starting with neural-level trait constructs and drawing implications for higher-level trait psychology observations. Current descriptive approaches such as the Big Five are an essential precursor to personality neuroscience, but may not map one-to-one to the mechanisms and constructs of a neuroscience-based approach to traits.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e11"},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960448","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}

{"title":"Network Neuroscience and Personality.","authors":"Sebastian Markett,&nbsp;Christian Montag,&nbsp;Martin Reuter","doi":"10.1017/pen.2018.12","DOIUrl":"https://doi.org/10.1017/pen.2018.12","url":null,"abstract":"<p><p>Personality and individual differences originate from the brain. Despite major advances in the affective and cognitive neurosciences, however, it is still not well understood how personality and single personality traits are represented within the brain. Most research on brain-personality correlates has focused either on morphological aspects of the brain such as increases or decreases in local gray matter volume, or has investigated how personality traits can account for individual differences in activation differences in various tasks. Here, we propose that personality neuroscience can be advanced by adding a network perspective on brain structure and function, an endeavor that we label personality network neuroscience. With the rise of resting-state functional magnetic resonance imaging (MRI), the establishment of connectomics as a theoretical framework for structural and functional connectivity modeling, and recent advancements in the application of mathematical graph theory to brain connectivity data, several new tools and techniques are readily available to be applied in personality neuroscience. The present contribution introduces these concepts, reviews recent progress in their application to the study of individual differences, and explores their potential to advance our understanding of the neural implementation of personality. Trait theorists have long argued that personality traits are biophysical entities that are not mere abstractions of and metaphors for human behavior. Traits are thought to actually exist in the brain, presumably in the form of conceptual nervous systems. A conceptual nervous system refers to the attempt to describe parts of the central nervous system in functional terms with relevance to psychology and behavior. We contend that personality network neuroscience can characterize these conceptual nervous systems on a functional and anatomical level and has the potential do link dispositional neural correlates to actual behavior.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e14"},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.12","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960827","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}

{"title":"On Curiosity: A Fundamental Aspect of Personality, a Practice of Network Growth.","authors":"Perry Zurn,&nbsp;Danielle S Bassett","doi":"10.1017/pen.2018.3","DOIUrl":"https://doi.org/10.1017/pen.2018.3","url":null,"abstract":"<p><p>Human personality is reflected in patterns-or <i>networks</i>-of behavior, either in thought or action. Curiosity is an oft-treasured component of one's personality, commonly associated with information-seeking proclivities with distinct neurophysiological correlates. The markers of curiosity can differ substantially across people, suggesting the possibility that personality also determines the architectural style of one's curiosity. Yet progress in defining those styles, and marking their neurophysiological basis, has been hampered by fairly fundamental difficulties in defining curiosity itself. Here, we offer and exercise a definition of the practice of curiosity as knowledge network building, one particular pattern of thought behavior. To unpack this definition and motivate its utility, we begin with a short primer on network science and describe how the mathematical object of a network can be used to map items and relations that are characteristic of bodies of knowledge. Next, we turn to a discussion of how networks grow, how their growth can be modeled, and how the practice of curiosity can be formalized as a process of network growth. We pay particular attention to how individuals may differ in how they build their knowledge networks, and discuss how the sort, manner, and action of building can be modulated by experience. We discuss how this definition of the practice of curiosity motivates new experiments and theory development at the interdisciplinary intersection of network science, personality neuroscience, education, and curiosity studies. We close with a note on the potential of network science to inform studies of other domains of personality, and the patterns of thought- or action-behavior characteristic thereof.</p>","PeriodicalId":36424,"journal":{"name":"Personality Neuroscience","volume":" ","pages":"e13"},"PeriodicalIF":0.0,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/pen.2018.3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37960826","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}