In more ancient times, yoga philosophy, ‘Bramacharya’ refers to one of the Yamas or moral codes. Traditionally bramacharya meant conservation of sacred creative energies including sexual energy. If we consider the energy that we expend to be revered, are we really directing our actions the way that we wish to and in the most productive and fulfilling manner. Working long hours, end-to-end meetings and home-life challenges can drain this driving force of our creative energy leading to burn-out, apathy and total overwhelm. Therefore, ensuring that our life-style allows space for our own unique creativity to flourish will enhance emotional well-being and fulfilment. We all have creative abilities, but often they have been numbed and dumbed by society placing greater emphasis on left-hemisphere tasks, goals, endpoints and cognition (ways of thinking).
When we let go of linear thinking... pushing, striving, grasping, gripping and we think more like the trees, like the seasons, like the stars. In order to take a step higher ascending in divine flow, we can release another layer. As the leaves flutter to the earth, cut away another entrenched samskara, knot or thought pattern, leave behind ways of being that are unhelpful, unhealthy, unhappy. Think like a tree and gather in all your sprawling energetic entanglements, gather in your hurrying, gather in your rushing, gather in your worrying. Harness your creative life force, brahmacharya through the winter seasons. Allow your energy to build and sparkle again to ride atop the next wave that will appear, without fear. Think like a tree because... spring-time will come again this year.
The National Institutes of Mental Health has proposed that mental disorders concern maladaptive forms of normal personality traits, for example openness has been correlated with higher incidences of psychoticism. This critical report evaluates the biological basis of personality traits, focussing on openness in relationship to psychoticism. Individual differences in openness may be attributed in part to fluctuating neuro-circuitry within the DN (default network) and FPCN (fronto-parietal control network ), examined using fMRI. Other influencing factors to the openness-psychotiscm spectrum may include intelligence and exposure to nature during childhood. Future studies utilising a seed-based fMRI to measure neuronal global efficiency and examining the role of different neurotransmitters displayed will assist deeper understanding.
Introduction and Background
It is a well-known adage that a relaxed mind is a creative mind. Since the development of personality trait theory in the 1940s (Cattell, 1945), the trait of openness has been reasoned to demonstrate a greater susceptibility to heightened imaginative states alongside artistic and aesthetic creative abilities (Costa and McCrae, 1992). Differing personality types such as these are evident as we observe and spend time in the company of others. Individuals can be inclined toward being shy or more exuberant; anxious or calm; combative or mild. A personality trait is defined as a psychological structure that forms consistent behavioural patterns, particularly evident in social situations and emotional expression (Maltby et al., 2017). Whereas a behavioural state is a transient characteristic that can fluctuate (Tellegen, 1988).
The most widely recognised theory known as ‘The Big 5’ adopts the Five-Factor Model (FFM) measuring five unrelated categories of personality (Costa and McCrae, 1992, 2005). The FFM was deduced from language, including important elements of personality like emotion and social interactions (John & Srivastava, 1999). The FFM consist of Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness and are measured using the Neuroticism-Extraversion-Openness Five Factor Inventory self-reported questionnaire. The FFM has been used to predict for example: creativity (Puryear et al., 2017), leadership skills (Nei et al., 2018) depression (Allen et al., 2018) and antisocial behaviours (Vize et al., 2018). This critical report evaluates measures used to investigate the biological basis of personality traits, focussing on openness and its relationship with psychoticism.
Trait development may stem from behavioural adaptations to environmental pressures. Traits are proposed to reflect nuanced sensitivity to rewarding and punishing stimuli (Ketterson E & Nolan V, 1999). Both dis-inhibition and constraint in response to such stimuli are highly correlated with measures of psychoticism through under-controlling and over-controlling behaviours (Burt, 2008). As such, personality development may determine the appearance of psychological disturbances through life (Shiner R & Caspi A, 2002). Trait differences can be attributed to neuro-circuitry, for example disruptions within the fronto-parietal control network (FPCN) is witnessed in schizophrenic patients who can experience psychoticism (Spreng et al., 2019). More recently, the National Institutes of Mental Health proposed mental disorders involve extreme, maladaptive forms of normal personality traits (Kotov et al., 2017; Love & Holder, 2014; Widiger, 2005). Thus, personality traits are important indicators as we strive to improve the mental health and well-being of humankind.
Blain et al., (2019)
Psychosis has previously been linked to higher levels of openness (Crego et al., 2018). However, research has provided contradictory opinions on whether openness and psychoticism align. Watson et al, (2019) found no relationship. Correlation may depend on how psychoticism is assessed, using NEO FFI other measures such as the Big Five Inventory (BFI) (Soto & John, 2017). Whereas Crego et al, (2018) proposed that more ‘open’ individuals tend to display openness to fantasy, peculiar perceptions, and eccentric behaviours. Congruent with psychosis as a loss of contact with reality, which can include perceiving events and innocuous stimuli with salience (Arciniegas, 2015). Symptoms of psychoticism can also include hallucinations, anhedonia (the inability to feel pleasure in typically pleasurable situations), social isolation and confusion. Psychoticism symptoms are present within the general population (10-15%) with persistent characteristics in the absence of disease (McGrath et al., 2015). Studying these traits within the general population, allows for increased sample sizes and less co-morbidity and medication confounds.
Blain et al, (2019) investigated the personality-psychopathology continuum focussing upon the ‘Openness-Psychoticism’ dimension by examining the default network (DN) and fronto-parietal control network (FPCN) within the brain utilising ‘Resting State’ functional Magnetic Resonance Imaging (fMRI). fMRI examines mechanistic neural networks. Resting state is thought to represent a ‘readiness’ activation enabling us to react to stimuli (Deris et al., 2016). Observing functional connectivity via fMRI demonstrates patterns of neuronal temporal synchrony and can be useful in determining the risk of psychosis (Spreng et al., 2019). The DN, also known to be involved in simulation of experience rather than task-based cognitive processes has central hubs within the medial prefrontal cortex, posterior cingulate cortex, with additional nodes in hippocampus, parietal, and temporal cortices (Buckner R & DiNicola L., 2019). The FPCN is primarily composed of the dorsolateral prefrontal cortex and posterior parietal cortex. In counterbalance to the DN, the FPCN is involved with cognitive control and problem solving (Sharp S & Leach R, 2014).
The study of the biological basis of personality traits and psychiatric diagnoses has benefited from utilising resting state data gathered from over 1000 subjects within The Human Connectome Project (Van Essen et al., 2012). This publicly available data provides a large sample size of fMRI data collected at baseline in task-based studies when participants are not explicitly engaging in cognitive processes. Intelligence, known to be negatively correlated with individuals experiencing higher levels of psychosis was also measured. Intelligence relates to intellectual confidence and active engagement with abstract/semantic info (Arciniegas, 2015). Participants were recruited excluding those with severe mental or psychiatric disorders, however including those with mild psychopathology. Self-reported measures of personality were collected using the NEO-FFI and the Achenbach self-report scale (ASR) to measure psychotic-like experiences. Four resting state fMRI scans were conducted to examine DN and FPCN activity.
Psychoticism was found to have a strong and significant positive correlation with openness. Psychoticism and openness were found to be positively correlated to DN coherence and negatively with FPCN coherence. Intelligence increases with FPCN coherence suggesting higher IQ may play a modulatory effect encouraging optimal functioning within the psychosis – openness spectrum. Cognitive control processes are thought to provide higher reasoning preventing psychopathology associated with openness. Further, cognitive stimulation treatments are included as a critical part of broader psychiatric rehabilitative programs for schizophrenic patients experiencing psychoticism (McGrath J et al., 2008). Psychoticism, is known to involve experiential simulation, which in turn involves DN activity (Buckner R & DiNicola L., 2019). Researchers report that increased DN activity is present in schizophrenics and those most at risk from psychosis Increased DN activation is also reported in individuals with higher mind wandering and creativity (Buckner R & DiNicola L., 2019) and positively correlates with openness. The research findings are congruent with schizophrenia research and suggest a similar biological basis of psychotic-like episodes within normal range traits. It is possible that mind wandering experienced with openness may directly compete with the demands of working memory. Further, psychopathology is typically caused by extremity in normal personality mechanisms that interfere with goal directed functioning.
These results are in keeping with the NIMH taxonomy suggesting psychopathology is typically an unbalanced manifestation of normal personality traits. More recent theories posit psychosis and autism as divergent disorders involving opposing FPCN-DN coordination and cognitive processes (Jung R E, 2014). Psychotic symptoms are apparent across disorders such as schizophrenia, mania with psychosis, psychotic depression (McGrath J et al., 2008 ). Therefore, elucidating neural mechanisms underpinning such symptoms may improve assessment and treatment. The researchers argue that the increased sample size improved the statistical power compared to previous studies. However, applying the ASR to measure psychoticism has limitations and generalizations cannot be made for clinical settings. The DSM-5 criteria for psychosis may be more robust for use in future studies. Further, self-reporting on personality, psychotic-like experiences and intelligence could be strengthened by clinical inputs and peer-assessments.
Dubois et al., (2018)
Dubois et al, (2018) also utilized the Human Connectome data set to examine if traits could be evidenced using resting state fMRI data. Two sessions of resting state fMRI were reviewed on different days, NEO-FFI performed on the second day and fluid intelligence measured. Fluid intelligence, age, sex, and handedness confounds were regressed out of the analysis, strengthening methodology. Results from this study contradicted the notion that personality traits were orthogonal. Openness was found to have the greatest predictability from resting state fMRI data followed by extraversion. results from Dubois et al., (2018) provide greater confidence in the methods adopted by Blain et al., (2019).
Dubois et al., (2018) found that resting state functional connectivity explains only 5% max of trait variance therefore this study does not provide a comprehensive understanding of the neurobiology of personality. Dubois et al (2018), used a predictive framework with built in replication and argue that these methods with sample sizes of over 500 participants are essential for reliable research. Complementary personality measures such as face validity and objective assessments are likely to improve limitations from the subjectivity of NEO-FFI questionnaire.
Altogether, the research from Blain et al., (2019) and Dubois et al., (2018) demonstrate that resting state connectivity has the potential to act as a marker for the endophenotype of traits, a clear genetic connection for each. This is especially true for openness. The Big 5 trait display high two-week ‘Test-Retest’ reliability using the FFI-NEO scale manual (Costa & McCrae, 1992, 2005). Openness has been documented with a reliability of Chronbach’s α (internal consistency) greater than 0.8 (CITE). There are likely multiple mechanisms by which trait consistency is controlled including genetics; environment and psychological tendencies (Shiner, R. and Caspi, A. 2003).
Snell et al., (2020)
Traits are thought to have a 50% genetic constituent (Maltby et al., 2017), yet relatively little research has been conducted on gene-environment interactions involved. It is generally inferred (Burt S A, 2008) that negative environments augment genetic risks, for example psychoticism, whilst positive environments supress genetic risks and may allow healthier creative expression, perhaps in part mediated by higher intellectual function. However, the gene / environment interplay to generate behaviour cannot be oversimplified (Turkheimer E, 2020). The epigenome represents a dynamic adaptation to environmental conditions. Regulation of the human genome, as such, is critical for the manifestation of traits which influence personality and behaviour. A growing body of literature show differences in gene expression in due to environmental exposure demonstrating that situations and social worlds exert notable effects on gene expression (Dick, 2011).
Snell et al, 2020 further explored the impact of time spent in natural environments during childhood and adulthood and correlations with openness. 783 participants were recruited across 42 countries bringing a wide cultural perspective. Participants answered a Likert scale questionnaire on how frequently visits to different nature biomes were made through. In this study, the BFI scale was used to measure personality traits. Multivariant regression was conducted across the different nature ‘biomes’ included within the questionnaire and canonical correlation with each of the 5 personality traits was performed.
Time spent within temperate forest was associated with lower anxiety and emotional volatility, measures of neuroticism. Whilst, higher intellectual curiosity and creative imagination were positively correlated with time spent within temperate forest, associated with openness. Intellectual curiosity and creative imagination remained higher independent of adulthood time spent in nature . Whereas time spent in nature needed to continue into adulthood for lower anxiety and emotional volatility to be experienced.
Attention restoration therapy (ART) from time in nature has been known to allow recovery from stress allowing restoration from attentional fatigue (Berto R., 2005). Further studies are required to investigate if over-stimulation of the FCPN contributes to attentional fatigue with potential therapeutic balance reinstated via activation of the DN during time in nature. Research has previously shown lower prefrontal activity during negative-emotion processing in association with time spent in nature, (Tost et al., 2019), strengthening this idea.
The research from Snell et al., (2020), posits that nature can be utilized as a learnt strategy for emotional regulation conditioned through childhood that continues into adulthood. Since psychoticism has been observed in those experiencing higher levels of openness alongside neuroticism, ART and time spent in natural environments could be a proposed method of improving mental well-being. Williams (2018) proposes that time spent in natural environments bring captivation and mind wandering that allow creative solutions. Intriguingly, rapid eye movement processes, known to alleviate mental health disorders such as post-traumatic stress disorder by allowing cognitive reprocessing of traumatic events (Pagal, 2020) may also be involved in such environments elucidated from the effects of high fractal complexity of foliage (Franck, 2019). Limitations of Snell et al’s study (2020) include self-selection via social media advertising therefore participants were more likely to already value nature skewing results in favour of time in nature to ameliorate undesirable behaviours. Memory reliance for subjective questionnaires exploring earlier years also limits the accuracy of data collection. Furthermore, activity confounds performed during time spent in nature were not assessed, which may impact upon gene-environment interaction in the development of personality traits.
The key studies considered in this report offer insight into the mechanistic understanding of neural pathways underlying the trait of openness and environs that are more likely to encourage a balanced manifestation of this trait. On one hand, the FFM has support from self, peer, and spouse validations (Costa & McCrae, 1988), life-span stability (Roberts & DelVecchio, 2000), and cross-cultural integrity (Church, 2001). Researchers also propose the FFM relates to a solid biological basis (Yamagata et al., 2006), and is a reliable predictor in relation to important academic, social-economic and clinical outcomes. The research bank of studies utilising the FFM continues to grow, therefore the framework is a useful too.
However, due to limitations of the NEO-FFI, future personality research could utilize other scales such as the Affective Neuroscience Personality Scale (ANPS) (Davis, 2003) or BFI-2 scale. The underlying biology of personality is not understood fully partially because the FFM did not develop from a theoretical biological background, however the ANPS is an exception, based upon biological concepts originating in rodent neuro-circuitry (Panksepp, 1998), measuring: Anger, Care, Fear, Play, Sadness, Seek and Spirituality. The ANPS is substantially influenced by genetics, including specific neurotransmitter receptor expression for example serotonin and oxytocin.
Further, trait research can benefit from examining global efficiency of neural networks by creating functional maps of activity from seed regions of interest with time series data. This approach provides a seed region and any other region analysis. Future studies could target neural networks stemming from the DN in relation to the openness-psychoticism continuum. Trait theory involves a complex and dynamic interplay of genetics, environment and psychological susceptibilities. Combining methods to include more robust personality scales, seed-based fMRI research and neurotransmitter analysis is required to understand neural pathways and gene-environment interactions involved in the expression of personality traits and disorders in greater detail.