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Clinical Implications of Dissonance Induction and Reduction

By: , Posted on: February 25, 2015

Warren CarnivalPrinciple 8, as presented in my book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory, concerns dissonance induction and reduction. I represented this principle in Blog 28 (click here for a full link to my blog archive). This principle is probably the most important principle for clinical practice because it explains how and why all effective psychological therapies work regardless of the theoretical orientation from which they were derived. Yes, this means that the efficacy and effectiveness of behavioral, cognitive, cognitive behavioral and psychodynamic therapies can all be explained by Principle 8.

Principle 8 is an extension of Principle 7 that I discussed in my previous blog. There we saw that people prefer consonance. Artificial neural networks “naturally” seek consonance by virtue of how they are trained. This parallel between real and artificial neural networks is sufficiently complete that how and why psychological treatments work can be explained by how artificial neural networks are trained and especially how they are retrained. Let me explain.

Neural networks begin their existence as multilayered systems where the nodes, simulated neurons, of one layer are connected to the nodes in the adjacent layer by simulated synapses that initially carry small random connection weights. Positive weights represent excitation; negative weights represent inhibition. Simulated sensory inputs to one layer cascade across one or more so-called “middle layers” to an output layer. There the difference between computed and desired values is called the Hamming distance. Subsequent training entails modifying all connection weights so as to reduce the Hamming distance. This is directly analogous to modifying regression weights in order to reduce the sum of squared differences between predicted and observed data points.

Once a network has learned to behave in some desired way, we may wish to retrain it. This can be done by the same methods that were used in the original training. Or, a more direct method can be used; one that is more like exposure and response prevention (ERP) behavior therapy. The trainer can clamp the output nodes to what the new task requires. This immediately places the network into a state of dissonance since the computed values pertain to the old task; not to the new one. The network reduces this dissonance by adjusting the connection weights until they become consistent with these output values. The network will likely take multiple processing cycles to settle into the new configuration where the computed values now conform to what the new task requires.

Psychotherapy works in much the same way as Tryon (2005) and Tryon and Misurell (2008) have explained. Let’s consider treatment of anxiety disorders of either the phobic or obsessive compulsive (OC) variety. Prior to treatment, the client’s neural network produces avoidant cognitions, feelings, and behaviors in the case of phobias and rituals in the case of OC disorder. Exposure and response prevention effectively clamps the output nodes to a new state. For example, the phobic client is presented with stimuli that elicit fear but the therapist requires continued exposure during the therapy session rather than avoidance. The OC client is asked to touch a “contaminated” object but the therapist prevents washing during the therapy session. These methods activate experience-dependent plasticity mechanisms that cause the client’s neural networks to change in ways that are more consistent with their behavior during therapy. These gradual changes effect thoughts and feelings. Multiple treatments are needed to make measurable progress. But the brain changes that I refer to actually show up on brain scans as evidence by the work of Jeffrey Schwartz that is succinctly summarized by Volk (2013).

Barlow has spent over 25+ years developing empirically supported treatments. He has distilled the common elements of various treatments into a unified protocol. Allen et al. (2008) and Barlow et al. (2011) describe this protocol. Remarkably, this protocol appears to have been designed around Principle 8 even though it wasn’t. Put otherwise, the 25+ years of clinical evidence developed by Barlow and his associates constitute empirical support for and clinical relevance of Principle 8.

The effectiveness of more traditional therapies can also be explained by Principle 8. Therapists induce dissonance when they ask their clients to think in new ways or to change their life style in specific ways. Therapists support their clients emotionally using their therapeutic relationship and working alliance while the client endures this therapeutic dissonance. Clients improve if such “exposure” continues. Hence, Principle 8 applies to all effective psychotherapies regardless of their theoretical origins.

Cognitive Neuroscience and Psychotherapy coverRead more from Warren Tryon on SciTech Connect:

Warren’s book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is available for purchase on the Elsevier Store. Use discount code “STC215” at checkout and save up to 30% on your very own copy.

About the Author

Warren ComputerWarren 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 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

This blog and all others by Dr. Warren Tryon can be found on his Fordham faculty webpage.

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