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How and Why Transtheoretic Transdiagnostic Psychotherapy Works

By: , Posted on: January 13, 2016

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Two blogs ago I explain why cognitive behavior therapy works. In my previous blog I introduced a broader form of treatment called Transtheoretic Transdiagnostic Psychotherapy (TTP). This approach is transtheoretic because Bio«Psychology Network explanatory system presented in Section 1 of my book Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is fully compatible with the Big Five clinical orientations (behavioral, cognitive, cognitive-behavioral, psychodynamic & pharmacologic). This approach is transdiagnostic because it explains why Barlow et al.’s. (2011) Unified Protocol for treating emotional disorders and other empirically supported treatments work. I explain more below. Here I explain how and why TTP works.

The ability to explain why treatments work is crucial to their acceptance by professionals and the public. Freud created what I called the Big Bang of psychotherapy on page 340 of my book:

I refer to Freud’s (1905) (http://www.clarku.edu/research/archives/archives/FreudandJung.cfm) 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. News of this historic event spread rapidly across America to the west coast and back again to the east coast, and then across the Atlantic ocean to Europe and then to Asia. Freud’s psychoanalytic theory and therapy were then known worldwide. All clinical psychologists who were trained over the next half century were largely trained in psychodynamic theory and therapy. Some doctoral programs continue to specialize in this form of clinical training. Other doctoral clinical programs include elements of psychodynamic theory and therapy as background. Programs that exclude psychodynamic theory and therapy likely do so in a reactionary way. These programs have also been influenced by Freudian thinking and therapy, but in an adversarial and rebellious way.

Freudian theory continues to inform contemporary psychotherapy even though the data on symptom substitution that I present in my book falsifies key psychodynamic considerations of how symptoms form and how they should be treated. The main point here is that no amount of negative evidence ever displaces a bad theory. Only a better theory can do that. This is because evidence can always be criticized in one way or another whereas theories provide explanations that are based on beliefs. Beliefs always trump evidence. Religious and political convictions provide clear illustrations of this. The Bio«Psychology Network (BPN) Explanatory System discussed next explains why transtheoretic transdiagnostic psychotherapy works.

Bio«Psychology Network (BPN) Explanatory System

The Bio«Psychology Network Explanatory System presented in Section 1 of my book is based on four core and now nine corollary network principles. The ninth principle was formulated after my book was published and is available on my faculty website.

The brain is a network of neural networks. Consequently some form of network theory is required to understand how it works; how cognition and affect interact to produce behavior. Wilson (1998) coined the term consilience to refer to the fact that all natural sciences must be consistent with one another. This means that psychology must be consilient with neuroscience if it is to actually become a natural science. McClelland and Rumelhart (1986) and Rumelhart and McClelland (1986) provided a way to integrate psychology and neuroscience. They demonstrated that psychology can be done using parallel distributed processing connectionist neural network (PDP-CNN) models that implement the following neuroscience facts:

  1. Some form of multilayered neural architecture is involved.
  2. Each processing node, simulated neuron, is connected to many others.
  3. Each of these connections, simulated synapses, is characterized by a connection weight. Positive values simulate degrees of excitation. Negative values simulate degrees of inhibition.
  4. Each simulated neuron in other than the sensory input layer receives multiple inputs that simulate dendrites.
  5. The sum of these inputs triggers an output from the receiving node, according to a transfer function, if inputs exceed a threshold.

Experience-dependent plasticity (EDP) mechanisms enable real neural networks to form memories and thereby learn by changing the excitatory or inhibitory properties of synapses that connect neurons to each other. Parallel distributed processing connectionist neural network models use mathematical equations to simulate how EDP mechanisms form memories and learn. These models have successfully simulated a broad spectrum of psychological phenomena because everything psychological depends upon learning and memory.

Tryon (2014) extracted four core and eight corollary network principles after reviewing many PDP-CNN models. The four core network principles form an explanatory nucleus in that this nucleus is part of every processing cycle. The first core principle concerns the fact that activation cascades unconsciously across neural networks. The second core principle is that experience-dependent plasticity mechanisms modify synaptic connections in ways that enable these networks to form memories and learn. The third core principle is that the network cascade referred to in Principle 1 necessarily transforms stimuli. Such transformations are the hallmark of cognition. People respond to their representations of reality. The fourth core principle concerns a distinction between activation and reactivation in neural networks. Activations refer to the consequences of perceived stimuli. Reactivations refer to the reconstituted network states that are memory-based.

These core network principles give rise to nine additional corollary network principles. As in the mathematical sense, corollaries are true because what they are corollary to is true. All of these corollary principles have received extensive support from empirical psychological research. My book discusses eight of these principles. I discovered a ninth principle after my book was published. It is described in a document that is available on my Fordham faculty web page. I continuously numbered these network principles. Hence, the first corollary network principle is Network Principle 5.

The first corollary network principle (#5) concerns priming. EDP mechanisms biologically reinforce previously taken processing pathways. Even repeated sub-liminal stimulus presentations can predictably modify how super-liminal stimuli will be processed. The second corollary network principle (#6) concerns part-whole pattern completion. Neural networks excel at filling-in information gaps as illustrated by the well replicated tendency of people to recognize a fried given only a fleeting glimpse of them and to see what they think occurred as is the case with eye witness testimony. The third corollary network principle (#7) concerns the tendency of neural networks to seek consonance and avoid dissonance. Extensive social psychological research has consistently validated this principle. The fourth corollary network principle (#8) concerns dissonance induction and reduction. This principle derives from how neural networks are trained and retrained. All empirically supported treatments induce dissonance and control how it is reduced. The fifth corollary network principle (#9) concerns memory superposition. Unlike computers that store memories in separate locations, neural networks store multiple memories in the same location. This fact explain the well-established memory phenomenon that people confuse the source of memories and when they occurred. The sixth corollary network principle (#10) concerns prototype formation. Networks naturally extract prototypes because they extract and emphasize averages while diminishing or discarding deviations. The seventh corollary network principle (#11) concerns graceful degradation. The distributed network and parallel processing features make these networks resilient in the face of damage. The eighth corollary network principle (#12) distinguishes top-down from bottom-up processing. Top-down processing explains how expectations modify perception and how placebo and nocebo effects work. The ninth corollary network principle (#13) concerns resonance. The mirror neuron systems of two people, two primates, or one person and one primate mutually activate, resonate, when one observes the other.

These core and corollary network principles provide mechanism information that is fully consistent with all of the Big Five clinical orientations: cognitive, behavioral, cognitive-behavioral, psychodynamic, and pharmacologic. This means that psychotherapy based on these network principles is transtheoretic. Hence, this approach to psychotherapy can be applied to all of the disorders that the Big Five clinical orientations have addressed which makes the proposed approach transdiagnostic.

Read 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.

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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 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.

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