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Computational Neuropsychology Simulation: Personality

By: , Posted on: December 8, 2014

Cognitive Neuroscience and PsychotherapyThe topic of personality is of great general interest. In this blog post I highlight two connectionist neural network simulations of personality that I believe are among the most important articles published concerning personality in the last century! My main reason for making this extraordinary statement is that these simulations have theoretically integrated two opposing research methods for the psychological study of personality in a way that it consistent with neuroscience.

The ideographic method of studying personality investigates one person at a time. Freud initiated the ideographic method of studying personality through his psychoanalysis of individual patients. Freud created what I call the Big Bang of Psychotherapy on page 370 of my book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory.

I refer to Freud’s (1905) lectures at Clark University where he presented a complete clinical package consisting of: (a) a theory of psychopathology; (b) a clinical method of treating all psychological disorders; and (c) supporting evidence in the form of case studies (p. 370, bold font in the original).

Freud’s disciples, such as Carl Jung and Alfred Adler, among others, extended this ideographic study of personality in various ways. Their writings are mainly what people think about when they hear the word “personality”. College courses offered by psychology departments concerning personality continue to present and discuss the teachings of these personologists. Clinical psychologists treat individuals and are therefore mainly interested in these theories.

The nomothetic method of studying personality involves administering “objective” personality tests to groups of people. I placed the term “objective” in quotes because it is a bit of a misnomer because only the method of scoring is objective. The questions themselves call for subjective information about thoughts, feelings, and behaviors. Answers to these questions are then correlated across people and factor analyzed to extract a few latent constructs called factors that account for as much of the observed variation among these correlations as possible. The following five factors have been consistently extracted: Extraversion, Neuroticism, Openness to Experience, Agreeableness, and Conscientiousness. Nomothetic methods are preferred by academic science-oriented psychologists because a) personality tests have known psychometric properties of reliability and validity, b) groups of people are involved which presumably makes the results more generalizable than studying any one person or even several people, and c) statistical methods are used for analysis.

The major problem here is that the results of nomothetic studies do not pertain to any single person and therefore are of little if any use to clinicians who treat individuals. Nomothetic researchers dismiss the results of ideographic investigators on the basis that they are subjective, unreliable, biased, and in general unscientific. Almost all personologists from both camps have developed their theories independent of neuroscience. So we have ended up with two competing camps of psychologists arguing with one another while both work in isolation from neuroscience to their detriment. This is a deplorable state of affairs and one that will not likely result in cumulative science. The connectionist neural network simulations by Read and Miller (2002) and Read et al. (2010) combine the ideographic and nomothetic methods in a way that that is consistent with neuroscience! This is truly a remarkable and revolutionary achievement.

The simulation by Read et al. (2010) provides the virtual personalities simulated by Read and Miller (2002) with the ability to learn from experience and therefore develop. Both simulations are based on well-known neuroscience evidence. I refer to the Behavioral Activation System (BAS) that governs sensitivity to reward (Gray, 1987, 1991; Gray & McNaughton, 2000; Pickering & Gray, 1999) and the Behavioral Inhibition System (BIS) that governs sensitivity to punishment (Depue, 1996; Depue & Collins, 1999). Read and his colleagues added a third network that governs the level of disinhibition/constraint (IS) in the two goal-based systems. The BAS and BIS are considered to be two goal-driven systems that reflect personality dispositions. Read and Miller (2002) effectively simulated neuroticism by increasing the gain associated with the BIS network. They effectively simulated extroversion by increasing the gain associated with the BAS network. They effectively simulated conscientiousness by augmenting the gain to the IS network. They also effectively simulated two types of low inhibition individuals. Read and Miller (2002) discovered that temperaments could be simulated by varying the parameters of these three network systems.

The two personality simulations reported above provide common ground for all personality investigators and clinical psychologists. Such simulations are attractive to clinical psychologists because they enable them to simulate what their client’s personality might do in various situations. These simulations enable us to understand personality in terms of motivations that are generated by neural networks. These simulations are of interest to nomothetic investigators because groups can be simulated by randomly or systematically varying the network parameters.

Causal mechanism information is available for the first time because these simulations contain sufficient relevant details to explain how different behaviors arise in various situations because of different personalities. This is what personologists have long aspired to do. In my next blog I discuss decision making as constraint satisfaction.

About the Author

Warren TryonWarren W. Tryon received his undergraduate degree from Ohio Northern University in 1966. He was enrolled in the APA approved Doctoral Program in Clinical Psychology at Kent State University from 1966 – 1970. Upon graduation from Kent State, Dr. Tryon joined the Psychology Department faculty at Fordham University in 1970 as an Assistant Professor. He was promoted to Associate Professor in 1977 and to Full Professor in 1983. Licensed as a psychologist in New York State in 1973, he joined the National Register of Health Service Providers in Psychology in 1976, became a Diplomate in Clinical Psychology from the American Board of Professional Psychology (ABPP) in 1984, was promoted to Fellow of Division 12 (Clinical) of the American Psychological Association in 1994 and a fellow of the American Association of Applied and Preventive Psychology in 1996. Also in 1996 he became a Founder of the Assembly of Behavior Analysis and Therapy. In 2003 he joined The Academy of Clinical Psychology. He was Director of Clinical Psychology Training from 1997 to 2003, and presently is in the third and final year of phased retirement. He will become Emeritus Professor of Psychology in May 2015 after 45 years of service to Fordham University. Dr. Tryon has published 179 titles, including 3 books, 22 chapters, and 140 articles in peer reviewed journals covering statistics, neuropsychology, and clinical psychology. He has reviewed manuscripts for 45 journals and book publishers and has authored 145 papers/posters that were presented at major scientific meetings. Dr. Tryon has mentored 87 doctoral dissertations to completion. This is a record number of completed dissertations at the Fordham University Graduate School of Arts and Sciences and likely elsewhere.

His academic lineage is as follows. His mentor was V. Edwin Bixenstein who studied with O. Hobart Mowrer at the University of Illinois who studied with Knight Dunlap at Johns Hopkins University who studied with Hugo Munsterberg at Harvard University who studied with Wilhelm Wundt at the University of Leipzig.

Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is Dr. Tryon’s capstone publication. It is the product of more than a quarter of a century of scholarship. Additional material added after this book was printed is available at www.fordham.edu/psychology/tryon. This includes chapter supplements, a color version of Figure 5.6, and a thirteenth “Final Evaluation” chapter. He is on LinkedIn and Facebook. His email address is wtryon@fordham.edu.

This blog and all others by Dr. Warren Tryon can be found on his Fordham faculty webpage located at www.fordham.edu/psychology/tryon.

Read more from Warren Tryon:

 

References

Carlson, N. R., Miller, H., Heth, C. D., Donahoe, J. W., & Martin, G. N. (2010). Psychology: The science of behavior (7th ed.) (p. 440); Boston: Allyn & Bacon.

Depue, R. A. (1996). A neurobiological framework for the structure of personality and emotion: Implications for personality disorders. In J. Clarkin & M. Lenzenweger (Eds.), Major theories of personality disorders (pp. 347-390). New York: Guilford.

Depue, R. A., & Collins, P. F. (1999). Neurobiology of the structure of personality: Dopamine, facilitation of incentive motivation and extraversion. Behavioral and Brain Sciences, 22, 491–569.

Gray, J. A. (1987). The psychology offear and stress. (2nd ed). New York: Cambridge University Press.

Gray, J. A. (1991). The neuropsychology of temperament. In J. Strelau & A. Angleitner (Eds.), Explorations in temperament: International perspectives on theory and measurement. Perspectives on individual differences (pp. 105–128). New York, NY: Plenum Press.

Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). New York, NY: Oxford University Press.

Pickering, A. D., & Gray, J. A. (1999). The neuroscience of personality. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (2nd ed., pp. 277–299). New York, NY: Guilford Press.

Read, S. J., & Miller, L. C. (2002). Virtual personalities: A neural network model of personality. Personality and Social Psychology Review, 6, 357–369.

Read, S. J., Monroe, B. M., Brownstein, A. L., Yang, Y., Chopra, G., & Miller, L. C. (2010).A neural network model of the structure and dynamics of human personality. Psychological Review, 117, 61–92.

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