Time-resolved connectome of the five-factor model of personality

Abstract The human brain is characterized by highly dynamic patterns of functional connectivity. However, it is unknown whether this time-variant ‘connectome’ is related to the individual differences in the behavioural and cognitive traits described in the five-factor model of personality. To answer this question, inter-network time-variant connectivity was computed in n = 818 healthy people via a dynamical conditional correlation model. Next, network dynamicity was quantified throughout an ad-hoc measure (T-index) and the generalizability of the multi-variate associations between personality traits and network dynamicity was assessed using a train/test split approach. Conscientiousness, reflecting enhanced cognitive and emotional control, was the sole trait linked to stationary connectivity across several circuits such as the default mode and prefronto-parietal network. The stationarity in the ‘communication’ across large-scale networks offers a mechanistic description of the capacity of conscientious people to ‘protect’ non-immediate goals against interference over-time. This study informs future research aiming at developing more realistic models of the brain dynamics mediating personality differences.

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Functional Connectome of the Five-Factor Model of Personality

Personality Neuroscience ◽

10.1017/pen.2017.2 ◽

2018 ◽

Vol 1 ◽

Cited By ~ 16

Author(s):

Nicola Toschi ◽

Roberta Riccelli ◽

Iole Indovina ◽

Antonio Terracciano ◽

Luca Passamonti

Keyword(s):

Functional Connectivity ◽

Large Scale ◽

Factor Model ◽

Brain Connectivity ◽

Five Factor Model ◽

Mechanistic Explanation ◽

Data Sets ◽

Personality Differences ◽

Human Connectome Project ◽

Maximal Information Coefficient

Abstract A key objective of the emerging field of personality neuroscience is to link the great variety of the enduring dispositions of human behaviour with reliable markers of brain function. This can be achieved by analysing big data-sets with methods that model whole-brain connectivity patterns. To meet these expectations, we exploited a large repository of personality and neuroimaging measures made publicly available via the Human Connectome Project. Using connectomic analyses based on graph theory, we computed global and local indices of functional connectivity (e.g., nodal strength, efficiency, clustering, betweenness centrality) and related these metrics to the five-factor model (FFM) personality traits (i.e., neuroticism, extraversion, openness, agreeableness, and conscientiousness). The maximal information coefficient was used to assess for linear and nonlinear statistical dependencies across the graph “nodes”, which were defined as distinct large-scale brain circuits identified via independent component analysis. Multivariate regression models and “train/test” approaches were used to examine the associations between FFM traits and connectomic indices as well as to assess the generalizability of the main findings, while accounting for age and sex variability. Conscientiousness was the sole FFM trait linked to measures of higher functional connectivity in the fronto-parietal and default mode networks. This offers a mechanistic explanation of the behavioural observation that conscientious people are reliable and efficient in goal-setting or planning. Our study provides new inputs to understanding the neurological basis of personality and contributes to the development of more realistic models of the brain dynamics that mediate personality differences.

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Individual Differences and Mindfulness

10.31234/osf.io/z2cx6 ◽

2019 ◽

Cited By ~ 2

Author(s):

Johannes Alfons Karl ◽

Ronald Fischer

Keyword(s):

Individual Differences ◽

Factor Model ◽

Five Factor Model ◽

Future Research ◽

Reinforcement Sensitivity Theory ◽

Dispositional Mindfulness ◽

Sensitivity Theory ◽

Reinforcement Sensitivity ◽

The Individual ◽

External Stimuli

What makes some people more mindful than others? Previous research has indicated that dispositional mindfulness is related to both the five factor model (FFM) and the reinforcement sensitivity theory (RST). However, previous research has examined those associations in isolation. We examined the unique effects of RST and the FFM on mindfulness in a sample 399 participants. Overall, we found the individual facets of mindfulness were differentially correlated with RST and FFM dimensions. Specifically, RST (BIS) and FFM (Neuroticism) dimensions that draw attention to external stimuli negatively correlated with mindfulness except for Observing. In contrast, FFM dimensions Openness and Conscientiousness correlated positively with mindfulness, suggesting a pattern where individuals routinely allocate attention to internal stimuli (being mindful) in order to explore (Openness) or to regulate these experiences (Conscientiousness). Our findings provide new insights into the underlying individual difference structure of being mindfulness and implies that mindfulness may not be a unitary construct. We suggest that future research should investigate mindfulness correlates at the facet level instead of the higher level of overall mindfulness.

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La influencia de la personalidad en el uso de Instagram/ The influence of personality on Instagram use

Aloma: Revista de Psicologia, Ciències de l'Educació i de l'Esport ◽

10.51698/aloma.2018.36.2.23-31 ◽

2018 ◽

Vol 36 (2) ◽

pp. 23-31

Author(s):

Carla Casado Riera ◽

Xavier Carbonell

Keyword(s):

Social Network ◽

Online Social Networks ◽

Ad Hoc ◽

Factor Model ◽

Five Factor Model ◽

Online Social Network ◽

Redes Sociales ◽

Personality Differences ◽

Positive Correlations ◽

Los Grupos

Instagram es una red social en creciente auge, por lo que es necesario comprender cómo las personas se presentan en este contexto y cómo influye la personalidad en su uso. Los objetivos del presente estudio fueron estudiar la influencia de la personalidad en el uso de Instagram, según el modelo de los cinco grandes y analizar las diferencias de personalidad entre los usuarios que utilizan Instagram y los no usuarios. El NEO Five-Factory Inventory (NEO-FFI) se utilizó para estudiar la personalidad y para el análisis de la actividad en Instagram un cuestionario ad hoc. Los 401 participantes se reclutaron a través de las redes sociales en línea: 262 usuarios de Instagram y 139 no usuarios. Se hallaron relaciones positivas entre la extraversión con el número de seguidores y el de usuarios seguidos. Respecto a la edad de los participantes, se encontraron diferencias significativas en los grupos de rangos de edad de 18-25 años y de 26-35 años. En concreto, las personas de estos rangos de edad más extravertidas siguen a más usuarios y tienen más seguidores en su cuenta de Instagram. Por otro lado, se halló una relación positiva entre la apertura y el número de publicaciones y seguidores en Instagram. La responsabilidad correlacionó con un mayor número de publicaciones únicamente en el grupo de edad de 26 a 35 años. En neuroticismo y amabilidad no se hallaron correlaciones significativas. Por último, se observó que las personas que utilizan Instagram presentan una mayor extraversión que las que no disponen de una cuenta en esta red social. Estos resultados resaltan la influencia de la personalidad en el uso de Instagram. Instagram is a constantly growing online social network, and as such it is necessary to know how people present themselves in this context and how personality influences their use of the network. The objectives of the present study were to use the Five Factor Model to study the influence of personality on the Instagram use and to analyse the personality differences between Instagram users and non-users. In order to assess personality, the Neo Five Factory Inventory (NEO-FFI) was administered, and to analyse Instagram activity an ad hoc questionnaire was used. The 401 participants were recruited through online social networks: 262 of them were Instagram users and 139 non-users. Positive correlations were found between extraversion and users’ the number of followers and the number of other users they follow. Regarding the age of the participants, significant differences were found in the groups of age ranges of 18-25 years old and 26-35 years old. Specifically, people in these more extraverted age ranges follow more users and have more followers on their Instagram accounts. Meanwhile, a positive correlation was found between openness to experiences, and number of posts and number of followers on Instagram. Conscientiousness correlated with a greater number of posts, but only in one age group: users 26-35 years old. No significant correlations were found with neuroticism and agreeableness. Finally, it was observed that people who use Instagram have higher levels of extraversion than those who do not have an account on this social network. These results highlight the influence of personality on Instagram.

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An fMRI investigation of the relations between Extraversion, internalizing psychopathology, and neural activation following reward receipt in the Human Connectome Project sample

Personality Neuroscience ◽

10.1017/pen.2020.11 ◽

2020 ◽

Vol 3 ◽

Author(s):

Courtland S. Hyatt ◽

Emily S. Hallowell ◽

Max M. Owens ◽

Brandon M. Weiss ◽

Lawrence H. Sweet ◽

...

Keyword(s):

Personality Traits ◽

Personality Trait ◽

Factor Model ◽

Five Factor Model ◽

Effect Sizes ◽

Levels Of Analysis ◽

Future Research ◽

Neural Activation ◽

Internalizing Psychopathology ◽

Human Connectome Project

Abstract Quantitative models of psychopathology (i.e., HiTOP) propose that personality and psychopathology are intertwined, such that the various processes that characterize personality traits may be useful in describing and predicting manifestations of psychopathology. In the current study, we used data from the Human Connectome Project (N = 1050) to investigate neural activation following receipt of a reward during an fMRI task as one shared mechanism that may be related to the personality trait Extraversion (specifically its sub-component Agentic Extraversion) and internalizing psychopathology. We also conducted exploratory analyses on the links between neural activation following reward receipt and the other Five-Factor Model personality traits, as well as separate analyses by gender. No significant relations (p < .005) were observed between any personality trait or index of psychopathology and neural activation following reward receipt, and most effect sizes were null to very small in nature (i.e., r < |.05|). We conclude by discussing the appropriate interpretation of these null findings, and provide suggestions for future research that spans psychological and neurobiological levels of analysis.

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Development and Assessment of a New Framework for Agricultural Nonpoint Source Pollution Control

Water ◽

10.3390/w13223156 ◽

2021 ◽

Vol 13 (22) ◽

pp. 3156

Author(s):

Lili Zhou ◽

Runzhe Geng

Keyword(s):

Spatial Distribution ◽

Large Scale ◽

Factor Model ◽

Five Factor Model ◽

Pollution Source ◽

Nonpoint Source ◽

Vegetation Coverage ◽

Buffer Strip ◽

Rural Living ◽

Agricultural Nonpoint Source

The transport of agricultural nonpoint source (NPS) pollutants in water pathways is affected by various factors such as precipitation, terrain, soil erosion, surface and subsurface flows, soil texture, land management, and vegetation coverage. In this study, based on the transmission mechanism of NPS pollutants, we constructed a five-factor model for predicting the path-through rate of NPS pollutants. The five indices of the hydrological processes, namely the precipitation index (α), terrain index (β), runoff index (TI), subsurface runoff index (LI), and buffer strip retention index (RI), are integrated with the pollution source data, including the rural living, livestock and farmland data, obtained from the national pollution source census. The proposed model was applied to the headwater of the Miyun Reservoir watershed for identifying the areas with high path-through rates of agricultural NPS pollutants. The results demonstrated the following. (1) The simulation accuracy of the model is acceptable in mesoscale watersheds. The total nitrogen (TN) and total phosphorus (TP) agriculture loads were determined as 705.11 t and 3.16 t in 2014, with the relative errors of the simulations being 19.62% and 24.45%, respectively. (2) From the spatial distribution of the agricultural NPS, the TN and TP resource loads were mainly distributed among the upstream of Dage and downstream of Taishitun, as well as the towns of Bakshiying and Gaoling. The major source of TN was found to be farmland, accounting for 47.6%, followed by livestock, accounting for 37.4%. However, the path-through rates of TP were different from those of TN; rural living was the main TP source (65%). (3) The path-through rates of agricultural NPS were the highest for the towns of Wudaoying, Dage, Tuchengzi, Anchungoumen, and Huodoushan, where the path-through rate of TN ranged from 0.17 to 0.26. As for TP, it was highest in Wudaoying, Kulongshan, Dage, and Tuchengzi, with values ranging from 0.012 to 0.019. (4) A comprehensive analysis of the distribution of the NPS pollution load and the path-through rate revealed the towns of Dage, Wudaoying, and Tuchengzi as the critical source areas of agricultural NPS pollutants. Therefore, these towns should be seriously considered for effective watershed management. In addition, compared with field monitoring, the export coefficient model, and the physical-based model, the proposed five-factor model, which is based on the path-through rate and the mechanism of agricultural NPS pollutant transfer, cannot only obtain the spatial distribution characteristics of the path-through rate on a field scale but also be applicable to large-scale watersheds for estimating the path-through rates of NPS pollutants.

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Software Defined Networking Flow Table Management of OpenFlow Switches Performance and Security Challenges: A Survey

Future Internet ◽

10.3390/fi12090147 ◽

2020 ◽

Vol 12 (9) ◽

pp. 147 ◽

Cited By ~ 1

Author(s):

Babangida Isyaku ◽

Mohd Soperi Mohd Zahid ◽

Maznah Bte Kamat ◽

Kamalrulnizam Abu Bakar ◽

Fuad A. Ghaleb

Keyword(s):

Large Scale ◽

Network Performance ◽

Software Defined Networking ◽

Cloud Services ◽

Future Research ◽

Control Plane ◽

Processing Load ◽

Flow Table ◽

Data Plane ◽

Large Scale Networks

Software defined networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane. The data plane is composed of forwarding elements called switches and the control plane is composed of controllers. SDN is gaining popularity from industry and academics due to its advantages such as centralized, flexible, and programmable network management. The increasing number of traffics due to the proliferation of the Internet of Thing (IoT) devices may result in two problems: (1) increased processing load of the controller, and (2) insufficient space in the switches’ flow table to accommodate the flow entries. These problems may cause undesired network behavior and unstable network performance, especially in large-scale networks. Many solutions have been proposed to improve the management of the flow table, reducing controller processing load, and mitigating security threats and vulnerabilities on the controllers and switches. This paper provides comprehensive surveys of existing schemes to ensure SDN meets the quality of service (QoS) demands of various applications and cloud services. Finally, potential future research directions are identified and discussed such as management of flow table using machine learning.

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Do voices carry valid information about a speaker's personality?

10.31234/osf.io/9a68c ◽

2019 ◽

Author(s):

Julia Stern ◽

Christoph Schild ◽

Benedict C Jones ◽

Lisa Marie DeBruine ◽

Amanda Hahn ◽

...

Keyword(s):

Individual Differences ◽

Personality Traits ◽

Factor Model ◽

Five Factor Model ◽

Secondary Data ◽

Future Research ◽

Voice Pitch ◽

Formant Frequencies ◽

Negative Relationships ◽

Valid Information

Research on links between peoples’ personality traits and their voices has primarily focused on other peoples’ personality judgments about a target person based on a target person’s vocal characteristics, particularly voice pitch. However, it remains unclear whether individual differences in voices are linked to actual individual differences in personality traits, and thus whether vocal characteristics are indeed valid cues to personality. Here, we investigate how the personality traits of the Five Factor Model of Personality, sociosexuality, and dominance are related to measured fundamental frequency (voice pitch) and formant frequencies (formant position). For this purpose, we conducted a secondary data analysis of a large sample (2,217 participants) from eleven different, independent datasets with a Bayesian approach. Results suggest substantial negative relationships between voice pitch and self-reported sociosexuality, dominance and extraversion in men and women. Thus, personality might at least partly be expressed in people’s voice pitch. Evidence for an association between formant frequencies and self-reported personality traits is not compelling but remains uncertain. We discuss potential underlying biological mechanisms of our effects and suggest a number of implications for future research.

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Exploring the Structure of Narcissism: Towards an Integrated Solution

10.31219/osf.io/wpcjq ◽

2019 ◽

Cited By ~ 1

Author(s):

Michael L Crowe ◽

Donald Lynam ◽

William Keith Campbell ◽

Josh Miller

Keyword(s):

Factor Structure ◽

Externalizing Behavior ◽

Precise Measurement ◽

Factor Model ◽

Five Factor Model ◽

Future Research ◽

Parsimonious Model ◽

Amazon's Mechanical Turk ◽

Criterion Variables ◽

Three Factor

Objective: Despite decades of work on narcissism there remain many active areas of exploration and debate including a clear and consensual description of its underlying components. Understanding narcissism’s factor structure is necessary for precise measurement and investigation of specific psychological and behavioral processes. The aim of the current study was to explore the structure of narcissism by examining it at varying hierarchical levels. Method: Participants recruited from Amazon’s Mechanical Turk (N = 591) completed 303 narcissism items encompassing 46 narcissism scales and subscales. Criterion variables measuring the Five Factor Model, self-esteem, aggression, and externalizing behavior were also collected. Results: A series of factor analyses reveal the factor structure of narcissism at a range of specificities. No more than five meaningful factors (i.e., Grandiosity, Neuroticism, Antagonism, Distrustful Self-reliance, Attention-seeking) were identified and the most parsimonious model appears to be a three-factor structure. Narcissism scales that effectively capture each of the identified factors are identified. Factors diverged in their associations with criterion variables. Conclusions: A three-factor model (i.e., Agentic Extraversion, Narcissistic Neuroticism, Self-centered Antagonism) seems to be the most parsimonious conceptualization. Larger factor solutions are discussed, but future research will be necessary to determine the value of these increasingly narrow factors.

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Inter-Vehicular Communications Using Wireless Ad Hoc Networks

Automotive Informatics and Communicative Systems ◽

10.4018/978-1-60566-338-8.ch007 ◽

2010 ◽

pp. 120-138 ◽

Cited By ~ 3

Author(s):

Raúl Aquino-Santos ◽

Víctor Rangel-Licea ◽

Miguel A. García-Ruiz ◽

Apolinar González-Potes ◽

Omar Álvarez-Cardenas ◽

...

Keyword(s):

Ad Hoc Networks ◽

Large Scale ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Routing Algorithm ◽

Delivery Ratio ◽

Test Bed ◽

Limited Bandwidth ◽

Hoc Networks ◽

Large Scale Networks

This chapter proposes a new routing algorithm that allows communication in vehicular ad hoc networks. In vehicular ad hoc networks, the transmitter node cannot determine the immediate future position of the receiving node beforehand. Furthermore, rapid topological changes and limited bandwidth compound the difficulties nodes experience when attempting to exchange position information. The authors first validate their algorithm in a small-scale network with test bed results. Then, for large-scale networks, they compare their protocol with the models of two prominent reactive routing algorithms: Ad-Hoc On-Demand Distance Vector and Dynamic Source Routing on a multi-lane circular dual motorway, representative of motorway driving. Then the authors compare their algorithm with motorway vehicular mobility, a location-based routing algorithm, on a multi-lane circular motorway. This chapter then provides motorway vehicular mobility results of a microscopic traffic model developed in OPNET, which the authors use to evaluate the performance of each protocol in terms of: Route Discovery Time, End to End Delay, Routing Overhead, Overhead, Routing Load, and Delivery Ratio.

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The development of the Compulsive Sexual Behavior Disorder Scale (CSBD-19): An ICD-11 based screening measure across three languages

Journal of Behavioral Addictions ◽

10.1556/2006.2020.00034 ◽

2020 ◽

Vol 9 (2) ◽

pp. 247-258 ◽

Cited By ~ 2

Author(s):

Beáta Bőthe ◽

Marc N. Potenza ◽

Mark D. Griffiths ◽

Shane W. Kraus ◽

Verena Klein ◽

...

Keyword(s):

Sexual Behavior ◽

High Risk ◽

Measurement Invariance ◽

Large Scale ◽

Factor Model ◽

Five Factor Model ◽

Behavior Disorder ◽

The United States ◽

Compulsive Sexual Behavior ◽

Negative Consequences

AbstractBackgroundCompulsive Sexual Behavior Disorder (CSBD) is included in the eleventh edition of The International Classification of Diseases (ICD-11) as an impulse-control disorder.AimsThe aim of the present work was to develop a scale (Compulsive Sexual Behavior Disorder Scale–CSBD-19) that can reliably and validly assess CSBD based on ICD-11 diagnostic guidelines.MethodFour independent samples of 9,325 individuals completed self-reported measures from three countries (the United States, Hungary, and Germany). The psychometric properties of the CSBD-19 were examined in terms of factor structure, reliability, measurement invariance, and theoretically relevant correlates. A potential threshold was determined to identify individuals with an elevated risk of CSBD.ResultsThe five-factor model of the CSBD-19 (i.e., control, salience, relapse, dissatisfaction, and negative consequences) had an excellent fit to the data and demonstrated appropriate associations with the correlates. Measurement invariance suggested that the CSBD-19 functions similarly across languages. Men had higher means than women. A score of 50 points was found as an optimal threshold to identify individuals at high-risk of CSBD.ConclusionsThe CSBD-19 is a short, valid, and reliable measure of potential CSBD based on ICD-11 diagnostic guidelines. Its use in large-scale, cross-cultural studies may promote the identification and understanding of individuals with a high risk of CSBD.

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