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Testing Brain Structure Predictions from Personality Neuroscience

Journal of Neuroscience and Neuropharmacology

Opinion - (2022) Volume 8, Issue 3

Testing Brain Structure Predictions from Personality Neuroscience

Farkas A*
 
*Correspondence: Farkas A, Department of Neuropharmacology, Belgium, Email:

Author info »

Abstract

The goal of personality neuroscience is to identify links between brain measurements and psychological characteristics. Small sample size and the exclusion of out-of-sample prediction are only two of the reasons that have severely constrained findings yet. We took advantage of the recent availability of a sizable database and the development of precise standards for best practices in neuroimaging analyses of individual differences. The Human Connectome Project database contained 884 young, healthy adults' resting-state functional magnetic resonance imaging (fMRI) data. We used individual functional connectivity matrices to attempt to predict personality qualities from the "Big Five," as measured by the Neuroticism/Extraversion/Openness Five-Factor Inventory exam. We measured how well the neuroimaging data might predict each of the five personality characteristics using a crossvalidated framework and test-retest replication after regressing for possible confounds (such as age, gender, handedness, and fluid intelligence).

Introduction

Three distinct (published) denoising methods for fMRI data, two methods for intersubject alignment and brain parcellation, and three distinct linear models for prediction were all put to the test. We used average connectivity from both imaging sessions (1 hour of data) for final prediction analyses because measurement noise is known to moderate statistical associations. This analytic pipeline produced the highest predictability overall. Openness to experience was the only aspect of personality that consistently predicted behavior across all outcomes (test/retest; three denoising procedures; two alignment schemes; and three models). To come up with theories on the connections between each of the Big Five personality traits and the volume of various brain areas, we developed a novel theory of the biological underpinnings of these qualities. Results from structural magnetic resonance imaging of 116 healthy people, adjusted for age, sex, and whole-brain volume, validated our theories for four out of the five traits: extraversion, neuroticism, agreeableness, and conscientiousness. The medial orbitofrontal cortex, a part of the brain that processes information about rewards and extraversion was correlated. Brain areas linked to danger, punishment, and negative affect are found in greater quantity in those who are neurotic. The volume of brain areas that process information about the intents and moods of others is correlated with agreeableness. A part of the brain involved in planning and voluntary control of behavior, the lateral prefrontal cortex, showed a correlation between conscientiousness and volume. The relationship between brain structure, especially the relative volumes of various brain areas, and brain function will be tested as ideas regarding which brain regions are likely to be physically related to each of the Big Five elements are put to the test.

According to the theory that larger populations of neurons can produce larger outputs and can therefore be more influential than smaller populations of neurons, a specific brain structure's greater-than-average volume may indicate greater-than-average power to carry out specific functions associated with that structure. A structure's volume may be less than average if it is more efficient or if it has been streamlined to carry out a certain purpose or collection of functions. There is strong support for the idea that bigger is more effective. Training on certain activities has been proven to increase the volume of brain regions that are crucial for specific tasks. Conscientiousness, one of the so-called "big five" personality traits that describe self-control and goal-directed conduct, has emerged as a reliable predictor for this objective in the long history of determining characteristics to predict academic achievement. The neuroanatomical bases of trait conscientiousness and the underlying brain mechanism connecting trait conscientiousness and academic achievement are still mostly unknown. Here, we used a voxel-based morphometry technique based on structural magnetic resonance imaging to estimate the cortical Grey Matter Volume (GMV) in 148 high school students from the same grade to investigate these problems. A wholebrain regression analysis revealed that trait conscientiousness was favourably correlated with the GMV in the bilateral Superior Parietal Lobes (SPL) and negatively correlated with the GMV in the right Middle Frontal Gyrus (MFG). The effects of the SPL and MFG volume on academic performance were further mitigated, according to a mediation study, by trait conscientiousness. What's significant is that our findings held even after controlling for overall IQ, family socioeconomic position, and the "big five" personality qualities other than conscientiousness. Overall, our research points to the frontoparietal network's GMV as a neurostructural indicator of adolescents' conscientiousness and reveals a potential brain-personality-success pathway for predicting academic performance, wherein grey matter structures influence academic performance through trait conscientiousness.

Five Factor Model

Linking the wide range of persistent human behavior traits with accurate indicators of brain activity is a major goal of the developing area of personality neuroscience. Big data sets may be analyzed using techniques that simulate whole-brain connection patterns to achieve this. To fulfill these expectations, we used a sizable collection of personality and neuroimaging measurements that the Human Connectome Project made available to the general public. We generated global and local indices of functional connection (e.g., nodal strength, efficiency, clustering, and betweenness centrality) using connectomic studies based on graph theory and connected these metrics to the Five-Factor Model (FFM) personality characteristics (i.e., neuroticism, extraversion, openness, agreeableness, and conscientiousness). The graph's "nodes," which were identified by independent component analysis as discrete, large-scale brain circuits, were evaluated for linear and nonlinear statistical relationships using the maximum information coefficient. While controlling for age and sex differences, multivariate regression models and "train/test" strategies were employed to investigate the relationships between FFM features and connectomic markers as well as to evaluate the generalizability of the key findings. Only the FFM characteristic of conscientiousness was associated with measurements of increased functional connectivity in the frontoparietal and default mode networks. This provides a mechanical explanation for the behavioural finding that dependable and effective goal-setting and planning are traits of conscientious persons. The study of personality neuroscience strives to comprehend the neurological bases of variation in cognitive and emotional processes as well as the neuronal roots of individual variations in behaviour. Although other personality models have also been developed to explain a wide range of behaviours, including clinical disorders, occupational/educational performance, and economic decisions, extensive research in personality has shown that the complexity of human behaviour can be described by an aggregate taxonomy known as the Five-Factor Model (FFM).

According to the FFM, neuroticism, extraversion, openness, agreeableness, and conscientiousness are all-encompassing terms used to describe the persistent behavioural tendencies of people. Personality psychology encourages the creation of thorough taxonomies of personality traits to promote a systematic approach to comprehending individual variations in behavior, emotion, motivation, and cognition. These descriptive taxonomies, however, have not often been connected to actual data from brain studies. Individual variations are relevant to basic science, education, and health, and are thus a growing area of study in cognitive, affective, and social neuroscience. However, these initiatives have not always been thorough or methodical. Neurobiological theories of personality are being tested and improved upon through a new field of study called personality neuroscience. The big five personality qualities of extraversion, neuroticism, agreeableness, conscientiousness and openness/Intellect were tested using Magnetic Resonance Imaging (MRI) in the study described in this article.

Personality neuroscience is a field of study that is quickly growing. It includes not just structural and functional neuroimaging but also studies in molecular genetics, psychophysiology, and psychopharmacology. Broad theoretical frameworks are required to organize facts and produce predictions for results in this subject to accrue systematically. To create such a framework, the big five model provides a viable taxonomy of qualities. A theory of the biological underpinnings of the big five factors is a crucial step toward the integration of individual differences research in psychology and neuroscience. The big five factors are significant predictors of outcomes in mental and physical health, well-being, education, work, and relationships. The findings of this study provide evidence in support of such a notion, showing that personality neuroscience may be used to increase knowledge of human psychology. We estimate their prevalence in the 587 study participants who were diagnosed with dementia at the outset, compared to similar symptoms in 2050 participants who were not diagnosed with dementia.

We describe their co-occurrence pair-wise and use factor analysis to analyse the pattern of co-occurrence, as well as investigate demographic and clinical correlates for each symptom we describe.

We also present the BPSD profile in the 244 participants with dementia at baseline who were available for reassessment 2 years later, as well as the 348 participants who developed dementia between the baseline and follow-up interviews.

Dementia patients are frequently admitted to an acute hospital. In the United Kingdom, approximately 6% of people with dementia are inpatients in general hospitals at any given time, compared to approximately 0.6% of over-65s without dementia. Dementia patients are admitted to the hospital two to three times more frequently than people of the same age who do not have dementia. In the United States, hospital admissions for people over the age of 85 with dementia increased from 700,000 in 2000 to 1.2 million in 2008.

Concerns have grown in the United Kingdom about the care given to frail older people who are admitted to acute hospitals.

BPSD (Behavioural and Psychological Symptoms of Dementia) refers to a group of symptoms that include agitation, aggression, delusions, hallucinations, depression, and apathy. These symptoms are common, multifactorial in nature, and are most likely the result of complex interactions between the severity of dementia, the environment, and other illnesses. They are upsetting for both dementia patients and those who care for them.

Family caregivers have provided detailed reports on how BPSD can worsen during hospitalisation and how acute hospital staff struggle to manage these symptoms adequately; however, data on the prevalence of behavioural and psychiatric symptoms in this setting are lacking. This is critical if we are to develop and evaluate BPSD management strategies in the acute hospital setting, particularly effective non-pharmacological interventions, and to better justify the need for liaison psychiatry services in this setting. The primary goal of this study was to look at the prevalence of BPSD in older people who were admitted to the hospital unexpectedly for medical reasons. Our specific goals were to (a) describe the prevalence and subtypes of BPSD in this population and (b) investigate patient characteristics associated with BPSD.

Author Info

Farkas A*
 
Editorial office, Journal of Neuroscience and Neuropharmacology, Brussels, Belgium
 

Citation: Farkas A, Testing Brain Structure Predictions From Personality Neuroscience. J Neurosci Neuropharmacol. 2022, 8.3, 001-002.

Received: 02-Jun-2022, Manuscript No. NCOA-22-67521; Editor assigned: 04-Jun-2022, Pre QC No. NCOA-22-67521 (PQ); Reviewed: 16-Jun-2022, QC No. NCOA-22-67521 (Q); Revised: 21-Jun-2022, Manuscript No. NCOA-22-67521 (R); Published: 27-Jul-2022, DOI: 10.4172/2469-9780.2022.8.3.172

Copyright: ©2022 Farkas A. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.