induccion de resonancia y reduccion

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Dissonance induction and reduction: A possible principle and connectionist

mechanism for why therapies are effective

Warren W. Tryon , Justin R. Misurell

Department of Psychology, Fordham University, CPR08-00022R1, United States

a r t i c l e i n f o a b s t r a c t

Article history:

Received 27 February 2008

Received in revised form 23 June 2008

Accepted 27 June 2008

Several empirically supported treatments for depression are currently available with little

understanding of either principles or mechanisms that are responsible for their effectiveness.

This article reviews existing principles and nds that they contain little mechanism

information. A connectionist mechanism used to explain why systematic desensitization and

response prevention are effective in treating anxiety disorders is reviewed and generalized to

understand why empirically supported treatments of depression work. This mechanism

suggests adissonance induction followed by reductionprinciple that can guide clinical practice.

Application is extended to learned helplessness and rumination because they are associated

with depression. Implications for clinical practice are provided. Limitations are identied and

discussed.

2008 Elsevier Ltd. All rights reserved.

Keywords:

Empirically supported principles

Mechanisms of change

Dissonance

Connectionism

Depression

Network

Contents

1. Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1298

2. Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1299

3. A connectionist mechanism for anxiety treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1302

4. Validation issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1302

5. Dissonance reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1303

6. Dissonance induction and reduction explains EST's for depression . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1303

7. Biases, learned helplessness and rumination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1305

7.1. Learned helplessness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1305

7.2. Rumination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1305

8. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1306

9. Implications for clinical practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1307

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1307

Considerable research has yielded a variety of empirically supported treatments (ESTs; http://www.therapyadvisor.com/) but

little information on how they work. Kazdin (2007)noted that mechanism information concerning why these interventions are

efcacious is either very limited or absent. This omission has allowed for the possibility of creating a new EST by adding an inert

component to a proven EST, thus enabling the new EST to pass all EST requirements. Rosen and Davidson (2003)referred to such

Clinical Psychology Review 28 (2008) 1297 1309

Corresponding author. Department of Psychology, Fordham University, Bronx, NY 10458-9993, United States. Tel.: +1 914 941 0632; fax: +1 914 941 0137.

E-mail address:[email protected](W.W. Tryon).

0272-7358/$ see front matter 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.cpr.2008.06.003

Contents lists available at ScienceDirect

Clinical Psychology Review
http://www.therapyadvisor.com/mailto:[email protected]://dx.doi.org/10.1016/j.cpr.2008.06.003http://www.sciencedirect.com/science/journal/02727358http://www.sciencedirect.com/science/journal/02727358http://dx.doi.org/10.1016/j.cpr.2008.06.003mailto:[email protected]://www.therapyadvisor.com/


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interventions as Purple Hat therapies because wearing a purple hat lined with magnets during desensitization or exposure

therapy could become a new EST. Wearing the hat makes the therapy new and using desensitization or exposure techniques

enables the new therapy to pass the required empirical tests. This is problematic for several reasons. First, it needlessly increases

the number of choices students in clinical training must learn and from which clients are forced to choose. Second, it increases the

science-practice gap by increasing the number of empirically supported treatments that practicing clinicians are expected to learn

and use. Third, the proponents of such new therapies can attribute efcacy substantially or mainly to the inert component given

the absence of any requirement to evaluate the necessity and/or sufciency of each putatively therapeutic element. While this

practice may help promote the commercial interests of particular practitioners, it is likely to retard psychological science,

dissemination of empirically supported treatments, and development of more effective clinical treatments. Rosen and Davidson

(2003) recommend establishing empirically supported principles (ESPs) as a way to curb the proliferation of Purple Hat

therapies. However, knowledge of such principles leaves open the further question of the mechanism(s) by which these principles

work. This article identies a dissonance induction/reduction principle as a possible explanatory basis for why empirically supported

treatments of anxiety and depression work and presents a basic connectionist model as a possible mechanism.

1. Principles

Castonguay and Beutler (2006)suggested guidelines for identifying empirically supported principles of psychotherapy. They

dened therapeutic principles as, the conditions under which a concept (participant, relationship quality, or intervention) will be

effective.(p. 6). Empirically supported principles were divided into three main categories: participant factors(characteristics of

both therapist and patient), relationship factors (attributes of the therapeutic relationship that are effective), and intervention

factors (the strategies and techniques employed during therapy). Within the same volume, Follette and Greenberg (2006)

identied the following six empirically supported intervention principles for treating dysphoric disorders, derived from a thorough

review of EST's for depression: challenging cognitions and behaviors by introducing new experiences; increasing the patient's

opportunities for receiving positive reinforcement; improving the patient's interpersonal functioning; improving the patient's

marital, familial, and larger social environment to maintain symptom remission and prevent relapse; increasing the patient's self

awareness, acceptance and regulation of their emotions; providing a highly structured and problem focused treatment regimen.

These three categories and six principles were identied by reviewing the literature. Validity of these categories has not been

questioned on methodological grounds; i.e., the procedures used to identify them. Nor has the empirical validity of these three

categories and six principles been questioned. We used the same inductive, literature-based methods to formulate the dissonance

induction/reduction principle that explains why empirically supported treatments for anxiety and depression work. Hence, we

take this principle to be validated and empirically supported to the same degree that Castonguay and Beutler's (2006)three

categories andFollette and Greenberg's (2006)six principles are.

We began by searching the literature for articles related to the topic of empirically supported principles using the following

search terms: empirically supported principles, empirically supported strategies, and empirically supported techniques.

These search terms were entered into both PsychInfo and PubMed databases. An online search of PsychInfo for empirically

supported principles yielded 20 articles regarding a diverse range of clinical phenomena including hypnosis ( Lynn & Cardena,

2007; Lynn & Kirsch, 2006; Lynn, Matthews & Fraioli, 2006), emotion-focused therapy (Greenberg, 2004, 2005a,b, 2006; Elliott &

Greenberg, 2007), adolescent stuttering and language uency (Bernstein, 2005; Sturtevant, Boyd & Brozo, 2006), group processes

(Burlingame, Fuhriman & Johnson, 2001; Burlingame & Taylor, 1992; Nitza, 2005 ), couples therapy (Christensen, Doss & Atkins,

2005), and post-traumatic stress disorder (Housley & Beutler, 2007; Tryon, 2005). An article byWagner (2005)presented a case

study where empirically supported principles of behavior therapy were applied to a woman suffering from a variety of post-

traumatic and anxiety symptoms as well as exhibiting problems symptomatic of borderline personality disorder. Only 4 of the 20

articles directly addressed the prescient need for identifying and listing empirically supported principles of change (APA

Presidential Task Force on Evidence-Based Practice, 2006; Rosen & Davison, 2003; Tashiro & Mortensen, 2006; Tryon, 2005). These

theoretical articles each advocated for the further development and identication of empirically supported principles in the

interest of advancing knowledge within the eld and effectiveness in the clinic. Tashiro and Mortensen (2006) argued for

utilization of several well established social psychological constructs in the search for empirically supported principles. A similarnumber of hits were yielded through the PsychInfo search of empirically supported strategies (25 articles) and empirically

supported techniques(6 articles).

An online search of the National Library of Medicine (Pub Med) for empirically supported principlesyielded 21 articles. Of

these articles, ve pertained to medical rather than psychological empirically supported principles of change. Six articles were

cross-listed with the above ndings fromPsychInfo. The remaining 11 articles again addressed empirically supported principles for

diverse psychological phenomena including drug and alcohol addiction (Carroll & Rounsaville, 2007; Libby & Riggs, 2005; Liddle

et al., 2002), adolescent therapy and prevention research (Mufson & Sills, 2006; Shirk, Talmi & Olds, 2000; Weissberg, Kumpfer &

Seligman, 2003), couples therapy (Freedman, Low, Markman & Stanley, 2002), post-traumatic stress disorder (Wagner, 2003;

Wagner, Rizvi & Harned, 2007), strategies for integrating various evidence based practices and tailoring them to meet the specic

needs of individuals (Beutler, Moleiro & Talebi, (2002). While a similar number of hits were yielded through the PubMed search for

empirically supported strategies (56 articles), there were considerably more hits for empirically supported techniques +

psychotherapy(140), reecting the broad scope that the latter search terms address.

We classi

ed the articles into several groups. One group of articles identi

ed common factors associated with effectivetreatments. Common factors do not provide mechanism information because they do not identify a sequence of causal events that

1298 W.W. Tryon, J.R. Misurell / Clinical Psychology Review 28 (2008) 12971309


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explains how and/or why they are effective. A related group of studies consist of components analyses. They demonstrate which

aspects of treatment are necessary and or sufcient to produce change but do not explain what it is about those components, that

creates therapeutic change let alone specify a causal sequence that creates these changes. A third group of articles identies what

can be called black box and arrow diagrams that are offered as an explanatory mechanism. The boxes are labeled with terms, such

as self-schema, but nothing is said regarding how schemas work to produce the effects attributed to them. Arrows from one box to

another imply causality but details regarding the mechanism by which these changes occur are absent.

Functional explanations were prominent during the 1950's and 1960's when behavior therapy began to demonstrate

therapeutic efcacy. Two forms of functional analytic explanations were provided. Classical conditioning (S-R) explanations

associated antecedent stimuli with subsequent responses. Operant conditioning (R-S) explanations were based on response

variation and selection (reinforcement). The absence of psychological mediation between stimulus and response or between

response and stimulus was criticized and drew the label black box for such functional explanations. The cognitive revolution

lled these black boxes with cognitive processes, including, but not limited, to attention and schemas but the mindbody problem

precluded mechanism information capable of explaining how stimuli gave rise to these cognitive processes and how these

cognitive processes caused the therapeutic outcomes associated with empirically supported therapies. Squire, Knowlton, and

Musen (1993)argued that Ultimately, one wants to understand cognition not just as an abstraction, or in terms that are simply

plausible or internally consistent. Rather, onewants to know as specically and concretely as possible how the job is actually done.

(p. 454). The literature reviewed above indicates that satisfactory explanatory principles have not yet emerged. Further mechanism

information is needed.

2. Mechanisms

Kazdin (2007)dened mechanism as, the basis for the effect, i.e., the processes or events that are responsible for the change;

the reasons why change occurred or how change came about.(p. 3). Mechanism information entails a causal sequence of events

leading to change. Unfortunately, it appears that while the eld of clinical psychology can condently assert that empirically

supported therapies create change, there is little published information about how these changes occur (cf. Kazdin, 2007). Our

interest here is to identify a sequence of causal events that explains how and why empirically supported treatments work.

We searched the literature for such mechanisms using the following search terms one at a time so as to identify as many

relevant articles as possible: mechanisms of change+depression,and mechanisms of change+depression+psychotherapy.An

online search of Psych Info for mechanisms of change+depressionyielded 38 articles, of which 18 were relevant to the current

discussion in that they purportedly dealt with hypothesized mechanisms of change in therapies for depression. The mechanisms of

change suggested in these articles include: cognitive mediation in general (Hollon & Shelton, 1991; Jarrett, 1984; Robins & Hayes,

1993), cognitive mediation and information processing changes (Ingram & Hollon, 1986), cognitive mediation through

restructuring, learning problem solving skills and providing feedback between changes in cognitions and behaviors (Fennell,

1983), cognitive mediation through self monitoring, logical analysis, and hypothesis testing (Jarrett & Nelson, 1987), cognitive

mediation through explanatory style change (Seligman, Castellon, & Cacciola,1988), mindfulness training (Lynch & Bronner, 2006;

Segal, Teasdale, & Williams, 2004), behavioral activation (Martell, Addis, & Dimidjian, 2004), and treatment alliance (Chilly, 2005).

The remaining seven articles (Craighead, Craighead, & Ilardi, 1998; Karasu, 1990a,b; Moras, 2006; Reinecke, 2002; Safran & Inck,

1995; Williams, 1997) provided general reviews for the treatment of depression.

An online search of the National Library of Medicine (Pub Med) for mechanisms of change + depression + psychotherapy

yielded eight relevant articles out of 65 citations. These articles included Kazdin's (2007)discussion of criteria for establishing

mediators and mechanisms of change in therapy, cognitive mediation as a mechanism of change in Cognitive Behavior Therapy

(CBT) for depression (Brewin, 1989; Hollon, Stewart, & Strunk, 2006; Garrett, Ingram, Rand, & Sawalani, 2007; Muran, Gorman,

Safran, Twining, Samstag, & Winston, 1995;Robins & Hayes, 1993) interpersonal processes as mechanism (Blatt, Quinlan, Zuroff,

Pilkonis, 1996; Kelly, Cyranowski, & Frank, 2007), and neurological processes (De Raedtm, 2006).

Currently, the literature consists of proposed mechanisms of change that do not have compelling explanatory power. For

instance, cognitive mediation, the most frequently cited mechanism in the literature on Cognitive Therapy (CT) for depression, is a

broad construct and one that may include an array of processes such as cognitive restructuring, challenging dysfunctionalthoughts, learning problem solving skills, self monitoring of automatic thoughts, hypothesis testing, logical analysis, and changing

attribution styles but does not address the issue of how these changes can and do take place. No explanation of how these

processes occur is offered.

There are other aws in the cognitive mediation as mechanism for change hypothesis. Cognitive mediation strategies are

often presented in box and arrow models, which describe the ow of functionality but fail to provide mechanism information for

how this functionality occurs. Identifying factors such as cognitive mediation (Dimidjian et al., 2006; Jacobson et al., 1996)

behavioral activation, or therapeutic alliance (Andrusyna, Luborsky, Pham, & Tang, 2007) does not provide any mechanism by

which the stipulated psychological and/or behavioral changes take place.

One can also discuss mechanisms from a levels of analysis perspective. Behavioral explanations are considered to be complete

by their advocates despite being limited to observable behaviors and their functional relationships including setting conditions.

The cognitive revolution currently endorsed by the great majority of psychologists, soundly rejected, and continues to reject, this

claim. Cognitive psychologists extended the S-R model to an S-O-R model. Psychological explanations frequently ll the Owith

box and arrow diagrams that describe the

ow of functionality among psychological constructs and processes such as attention,perception, cognition, expectations, etc. These explanations are thought to provide psychological mechanism information but have

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not answered the mechanism questions raised by Kazdin (2007). This level of analysis is therefore incomplete. The issue of

parsimony is secondary to the matter of completeness. Simple explanations that fail to give a full account of a phenomenon may be

parsimonious but are decient. We now turn to cognitive neuroscience for additional mechanism details. Whereas neuroscience is

completely reductionistic and cognitive science disregards biology, cognitive neuroscience seeks to understand how mind arises

from the brain (cf.,Ilardi, 2000a,b).

Parallel Distributed Processing (PDP) Connectionist Neural Network (CNN) models constitute an important part of cognitive

neuroscience. They extend the S-O-R model in at least the following six ways that further our understanding of how empirically

supported treatments work. First, connectionist models extend the serial S-O-R model to a parallel network model. Fig.1 illustrates

one very simple example. Multiple S-nodes replace the single Sand are arranged as a layer. Multiple O-nodes replace the single

O and are arranged as a layer. Multiple R-nodes replace the single R and are also arranged as a layer. Many S-nodes are typically

required to encode all of the stimuli or relevant stimulus microfeatures. The number of O-nodes required depends upon how many

cognitive and affective factorsare required to effectively process the information contained in the stimulus array. The number of

R-nodes is determined by the level of response specicity required. Like the S-O-R model, all S-nodes are connected to all O-nodes,

and all O-nodes are connected to all R-nodes in the simplest connectionist feed-forward network models (cf., Fig. 1). Hence,

processing moves from S to O to R just like it does in the S-O-R model. Notice that the nodes in each layer are not connected

horizontally which is the case in more complex models that implement lateral inhibition. Other complex connectionist archi-

tectures have feedback loops.

The second way in which connectionist models extend the S-O-R model is by providing details regarding how activation

proceeds from layer to layer. Such information is conspicuously absent for S-R and S-O-R models. Consider the network diagramed

in Fig. 1 which can either be described as consisting of three layers of processing nodes (neurons) and/or as two layers of

connection weights (synapses). The top layer of nodes represents stimulus features. Each node can represent a separate stimulus or

stimulus microfeature.Fig. 2illustrates how a 55 articial retina might be used to perceive the letter A. The on-off (1 or 0)

pattern concatenated across rows of the articial retina create the S-node vector that represents the network's perceptionof the

letter A. Alternatively, the S-nodes can be thought of as the output of one or more other attention/perception networks that are

implied but not explicitly represented.

When an S-node is activated, i.e., when its digital status goes from 0 to 1, this activation automatically spreads out across each

line leading from the node in question to all other nodes to which it is connected in the same way that activation of a real neuron

automatically spreads down its axon when it res. Activation fromall S-nodes simultaneously and automatically spreads across the

Fig. 1.A simple connectionist network model consisting of three layers of processing nodes or neurons (lled circles) and two layers of connection weights or

synapses (lines).

Fig. 2.An example of how a 5 5 articial retina might be used to activate 25 S-nodes when perceiving the letter

A

. Digital 1 means that the stimulus node is on.Digital 0 means that the stimulus node is off. The digital values for each row are concatenated to comprise S-node input or partial input.



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network during each processing cycle. Many such processing cycles are included in every computer simulation. Computationally,

spreading activation is implemented by multiplying the status of the node/neuron (1=on, 0=off) by the connection weight,

ranging from 1 (fully inhibitory) through zero to +1 (fully excitatory), associated with each connecting link. Activation, either

excitatory or inhibitory, spreads in direct proportion to the connection weight if the node is on. A connection weight of zero

nullies node activation.

Each node in the second and third layers simulates dendritic summation by adding up the weighted inputs into it; i.e., adding

the products of on-off status times the connection weight associated with each and every link leading into that node. A sigmoidal

(S-shaped) activation function, also known as a transfer function, determines if the sum of the inputs is sufcient to activate the

receiving node. If so, then activation (inhibitory or excitatory) continues across all links exiting from that node. If not, then

activation down that branch of the network terminates unless fed by another pathway. This process ends with some response

nodes turned on, activated, and others turned off. The numerical vector that characterizes the status of the R-nodes can be

converted into a visual display by reversing the process illustrated in Fig. 2. That is, beginning with a string of 25 digits, one can

start in the upper left hand corner of the display and proceed row by row turning a pixel black given a 1 or white given a 0. A vocal

response can be generated by submitting the R-node vector to a voice synthesizer.

The ability to compute a result that can be compared to data from experiments with people constitutes the third extension of

the S-O-R model provided by PDP-CNN models. This occur when the same number of R-nodes are used as participants have

response alternatives so that simulated behavior can be compared with actual behavior and the model empirically supported or

falsied. PDP-CNN modeling is an active and growing part of psychology as exemplied by contemporary research at the Center for

Molecular and Behavioral Neuroscience Newark (http://www.gluck.edu/html/research_overview.html ), the University of

Pittsburgh and Carnegie Mellon (www.cnbc.cmu.edu), the Neuroscience Institute at the University of California, Berkeley (http://

neuroscience.berkeley.edu/ ), the Center for Mind and Brain at the University of California, Davis (http://mindbrain.ucdavis.edu/),

the Center for Cognitive Neuroscience at Dartmouth College (http://ccn.dartmouth.edu/), the Center for Cognitive Neuroscience at

Duke University (http://www.mind.duke.edu/ ), and the Center or Cognitive Neuroscience at the University of Pennsylvania (http://

ccn.upenn.edu/), among other research centers.

The fourth way that PDP-CNN models extend the S-O-R model deserves special emphasis. PDP-CNN models are especially

informative because they simulate experience-dependent plasticity. They provide a way to systematically explore how functional

properties of networks change as a consequence of processing information.Skinner (1989)correctly anticipated the functional

properties of brain plasticity when he maintained that experience changes the organism. In a behavioral analysis, contingencies of

reinforcement change the way we respond to stimuli. It is a changed person, not a memory, that has been stored. (p. 14). More

specically Skinner wrote When, for example, a hungry rat presses a lever and receives food and the rate of pressing immediately

increases, cognitive psychologists want to say that the rat has learned a rule. It now knows and can remember that pressing the

lever produces food.But pressing the lever produces foodis a description of the contingencies we have built into the apparatus.

We have no reason to suppose that the rat formulates and stores such a description. The contingencies change the rat, which then

survives as a changed rat (p. 14). Extensive neuroscience studies have conrmed this view and have clearly shown that brain

plasticity in general and synaptic change in particular are the basic mechanisms that mediate learning and memory (e.g., Bear,

Connors, & Paradiso, 2007; Krasne, 2002; Martin, Bartsch, Bailey, & Kandel, 2000; Moscovitch, Chein, Talmi, & Cohn, 2007 ).

Connectionist models are informative because they simulate experience-dependent synaptic plasticity by modifying connection

weights as a result of network processing. The network survives as a changed network that subsequently processes stimuli

differently than before. These models have effectively simulated learning, memory, and a wide variety of psychological phenomena

dependent upon these processes (e.g., Arbib, 2002; Bechtel & Abrahamsen, 1991; Commons, Grossberg, & Staddon, 1991;

Martindale, 1991; McLeod, Plunkett, & Rolls,1998; O'Reilly, & Munakata, 2000; Rumelhart & McClelland, 1986a,b; Parks, Levine, &

Long,1998; Rolls & Treves,1998). Skinner was correct in maintaining that experience changes people. Experience-dependent brain

plasticity is the mechanism by which such changes occur and they alter the way people think, feel, and behave. PDP-CNN models

simulate these changes in articial neural networks. Experience-dependent plasticity is central to understanding how learning-

based therapies work. They work because they change the networks1 that implement cognition, affect, and behavior.

The fth way that PDP-DNN models extend the S-O-R model is that they enable one to study how experience-dependent

changes cumulate over time to modify thoughts, feelings, and behavior in ways that can be compared with empirical data obtainedfrom psychological experiments in order to empirically support or falsify these models. This complex and highly dynamic process

requires computer simulation because the details necessary to compute simulated results with sufcient accuracy to enable a

compelling comparison with empirical data greatly exceeds the precision provided by words alone. For example, back propagation

is one common method for changing connection weights after each network processing cycle. This method begins by computing

the discrepancy between the actual and desired activation pattern across the R-nodes. In the clinical example presented below, it is

the difference, dissonance, between the therapist arranged response and the response that the network would have otherwise

created. This difference is used to systematically modify connection weights between the middle (O-nodes) and bottom (R-nodes)

and then used to modify connection weights between the top (S-nodes) and middle (O-nodes). Hence, connection weight changes

are made backwards, up through the network, one level at a time resulting in the name back propagation. While it is widely

recognized that back propagation does not correspond to an actual biological process, it is also widely accepted as a valid

1 The brain may be conceptualized as a network of interconnected networks that form functional modules.

http://www.gluck.edu/html/research_overview.htmlhttp://www.cnbc.cmu.edu/http://neuroscience.berkeley.edu/http://neuroscience.berkeley.edu/http://mindbrain.ucdavis.edu/http://ccn.dartmouth.edu/http://www.mind.duke.edu/http://ccn.upenn.edu/http://ccn.upenn.edu/http://ccn.upenn.edu/http://ccn.upenn.edu/http://www.mind.duke.edu/http://ccn.dartmouth.edu/http://mindbrain.ucdavis.edu/http://neuroscience.berkeley.edu/http://neuroscience.berkeley.edu/http://www.cnbc.cmu.edu/http://www.gluck.edu/html/research_overview.html


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mathematical method for simulating the experience-dependent synaptic changes that are known to occur in real neural networks.

The mathematics of back propagation gradually enables the network to settle into an increasingly consonant state analogous to

how homeostasis enables biological systems to settle down once perturbed.

It is important to emphasize that the systematic changes in the connection weights that link how one node inuences the next

necessarily changes the way that the network processes subsequent stimuli and consequently changes how the network model

thinks, feels,and behaves.PDP-CNNs simulate to a rough rst degree of approximation the experience-dependent plasticity

that characterizes real brains. PDP-CNN models are more tractable and open to study than real brains are and enable an exper-

imental analysis of their functional properties and operating characteristics.

The sixth extension of the S-O-R model provided by PDP-CNN models pertains to vocabulary. Psychologists have developed a

vocabulary to describe their concepts, principles, and ndings whereas biologists have developed a different vocabulary to

describe their concepts, principles, and ndings. Very little overlap exists between these vocabularies and little progress has been

made translating one vocabulary into the other. Generalizing the S-O-R model into a network model brings with it a network

vocabulary as illustrated by terms used above to describe how these models work. Doing psychology with network models enables

psychologists and neuroscientists to use a similar vocabulary and thereby communicate better and possibly collaborate more

fruitfully with each other.

The six extensions of the S-O-R model provided by PDP-CNN models substantially increase the mechanism information

available to psychologists. Clinicians can effectively conceptualize activation cascading across network layers thereby changing the

network due to experience-dependent plasticity with the result that the network processes subsequent stimuli differently than

before and leave the mathematical details to investigators to implement with a research context. We now use our connectionist

approach to better understand why empirically supported treatments work for anxiety disorders before extending this perspective

to explain why empirically supported treatments for depression work.

3. A connectionist mechanism for anxiety treatment

The network of a phobic person before treatment can be understood to function as follows. The top stimulus row pertains to

anxiety-related stimuli. Their activation is processed down through the connections diagramed by the solid lines to the nodes in

the second layer as described in the previous section, which, like the O in the S-O-R model is where anxiety-related cognitions and

emotions are located/processed. More than two such nodes are clearly required but are not illustrated for simplicity. In principle

entire multilevel networks could be placed here but are not illustrated to keep matters simple. Activation of the nodes in this

middle layer cascades across the second layer of connection weights, synapses, as described above and will activate one or more R-

nodes in the bottom response layer that represents pretreatment avoidance behaviors.

The activation cascade across network layers characteristic of the pretreatment state leads to a network output that is

characteristic of pretreatment behaviors which primarily entail avoidance in the case of phobias. Response prevention articially

changes the behavioral response represented by the R-nodes to the desired behavior of non-avoidance or approach. In network

terms, one is said to clamp the output response nodes to a new activation pattern; one that corresponds to the desired

therapeutic response such as remaining in the presence of the phobic stimuli instead of escaping from them. Presentation of

phobic stimuli causes the network to process in the usual pretreatment way up to the point where it attempts to recreate the

pretreatment response pattern on the R-node layer. The pattern of activation to which the therapist has set the R-nodes conicts

with, is dissonant with, the activation pattern that the network would have otherwise created. Given that networks naturally tend

to maximize consonance, such discrepancy drives synaptic change in the direction of making the network connections more

consistent with the R-node activation pattern that is the clamped output; i.e., therapeutic response. The resulting experience-

dependent network changes alter how the network processes subsequent stimuli which include how people think and feel about

those stimuli and how they react to them. Dissonance induction/reduction describes sequential network states that mediate

experience-dependent plasticity. All actual and simulated evidence consistent with this sequence empirically support the

dissonance induction/reduction principle.

4. Validation issues

The section more fully addresses the question How valid is the dissonance induction/reduction principle? Mathematics is a

deductive system that enables one to prove the truth/validity of a conclusion. Science is an inductive system that empirically

supports hypotheses based on consistency between expectation and observation. No amountof evidence canprove the validity of a

hypothesis because subsequent data can falsify it at any future time. This is why we speak of empirically supported treatments

rather than empirically proven treatments. Falsication is more compelling in that it entails immediate contradiction which

seriously undercuts a hypothesis. Prospective studies that hypothesize/predict and then observe are preferred and at present no

such studies are available to test the dissonance induction/reduction principle offered here because the principle has just been

formulated here. However, retrospective studies are also capable of supporting or falsifying hypotheses and valid hypotheses must

be as consistent with previously published evidence as with evidence yet to be collected.Castonguay and Beutler (2006)inferred

three categories of empirically supported principles on this basis. Follette and Greenberg (2006) identied six empirically

supported intervention principles on this basis. In the next section we use their methods to infer the dissonance induction/

reduction principle from a large methodologically sound empirical social psychological literature. Consequently, the dissonanceinduction/reduction principle is similarly valid.



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5. Dissonance reduction

Cognitive dissonance is a deeply rooted well supported explanatory social psychological principle Inspired by Lewin's eld-

theoretical approach (Lewin, 1936),Heider (1958)applied the principle of consonance to interpersonal relationships between two

persons and an attitude object which could be another person, a topic of conversation, or an event in the form of POX diagrams

where P = person, O = other person, and X = attitude object. The lines connecting the three vertices of the resulting triangle take on

positive or negative valences. Triads with 0 or 2 negative valences are consonant as negative times negative is positive. Triads with

1 or 3 negative valences are dissonant and motivate change towards consonance. Festinger (1957)acknowledged Heider's work

(p. 7) but emphasized the motivational nature of cognitive dissonance. Bem (1967)provided a radical behavioral reinterpretation

of dissonance theory and the empirical research literature generated by Festinger and his colleagues. This reformulation of

theoretic reformulation is problematic in at least three critical ways. First, it is premised on the position that self-observation is a

behavior without cognitive representation. Referring to the psychological process of introspection regarding one's self-concept as a

behavior of self-observation is an essential part of what the cognitive revolution rejected about behaviorism. Behavior, as

empirically studied by behaviorists is always restricted to what can be publically observed. Behavioral theory however labels

psychological processes as coverants; i.e., operants of the mind (cf. Homme, 1965) and discusses them like observable

behaviors. The cognitive revolution recognized that psychological states are not identical to observable behaviors and authorized

cognitive theories and explanations of behavior and behavior change; i.e., behavior therapy became cognitive behavior therapy.

Second, and corollary to therst problem, Bem (1967) referred to interpersonal judgments as behaviors which they are not; they

are private cognitive events, not publically observable behaviors. Third, and also corollary to therst problem, Bem (1967) asserted

that self-perception is a special case of interpersonal perception. Perception is an inferred psychological process; not an observable

behavior. However,Bem's (1967, 1970, 1972)central thesis that people are inuenced by their experience is emphasized here as

experience-dependent plasticity and is a core component of connectionist models. Bandura (1977)moved well beyond Bem's

behavioral model by explicitly recognizing self-related psychological processes as pertinent to psychological and behavioral

change.

A huge empirical literature culminated in an 84 volume work edited byAbelson, Aronson, McGuire, Newcomb, Rosenberg, and

Tannenbaum (1968) that provided much empirical support for dissonance theory. Jordan (1968)noted thatFestinger's (1957)

cognitive dissonance,Osgood, Suci, and Tannenbaum's (1957) congruence, Abelson and Rosenberg's (1958)symbolic psycho-logic,

Newcomb's (1953) strain towards symmetry, and Cartwright and Harary's (1956)structural balance all share a common interest in

the perception and/or cognition of consistency and/or contradiction. Jordan (1968)claried the contribution of Heider's work to

these theories of cognitive consistency. Further empirical support derives from contemporary research in social cognition that has

incorporated principles of cognitive dissonance (e.g.,Aronson, 1999; Hamilton, 2005; Kunda, 1999). Kunda (1990)emphasized the

role that emotions play in dissonance theory. She empirically supported the proposition that emotion warps cognition in her

seminal article on motivated reasoning (Kunda, 1990). She demonstrated that the reasons people give for their behaviors are

frequently inuenced by their emotional state. Stated succinctly, There is considerable evidence that people are more likely to

arrive at conclusions that they want to arrive at, but their ability to do so is constrained by their ability to construct seemingly

reasonable justications for these conclusions(Kunda, 1990, p. 480). In the absence of any reason to prefer one conclusion over

another and when motivated to make an accurate and logical decision, people can carefully weigh and consider facts despite

limitations imposed by various cognitive biases that include ignoring base rate effects and peculiar ideas about probability. When

motivated to prefer one conclusion over another however, people frequently maintain an illusion of objectivity(Kunda, 1990, p.

483) by selectively and creatively combining beliefs and evidence to support the preferred conclusion with the understanding that

people can only be made to believe what reason permits. Kunda (1990) presented evidence that performing counter-attitudinal

behaviors and freely engaging in behavior that may have negative consequences creates dissonance because they are inconsistent

with a positive self-image resulting in attitudinal and/or behavioral change to preserve a positive self-image. There is evidence that

the process of dissonance reduction entails selective memory search of prior beliefs combined with selective emphasis of

supporting evidence and discounting or omitting contradictory facts resulting in a hypothesis-conrmation bias. This body of

research demonstrates that dissonant states are frequently converted to consonant ones that are consistent with emotional states

and desires as much as circumstance allows thereby providing empirical support for connectionist models that emphasizeconsonance and constraint satisfaction. The dissonance induction/reduction principle has been induced from, and therefore is

empirically supported by the empirical literature cited above.

6. Dissonance induction and reduction explains EST's for depression

The purpose of this section is to apply thedissonance induction/reductionprinciple to EST's for depression including behavior

therapy (BT), cognitive therapy (CT), and interpersonal psychotherapy (IPT; Nathan & Gorman, 2002). Though each modality differs

in its underlying assumptions regarding the etiology and maintenance of depression and therapeutic emphases, we shall argue

that cognitive dissonance induction and reduction is a commonly shared principle, not only in terms of symptom maintenance, but

symptom alleviation as well. It should be noted, however, that although the dissonance induction/reduction principle is common

to the following therapeutic modalities, it is not the only principle responsible for the success of those treatments.

The behavioral therapy (BT) approach based on operant conditioning for treating depression proposed by Lewinsohn and

colleagues (Lewinsohn, Youngren, & Grosscup, 1979; Lewinsohn, Hoberman, Teri, & Hauztinger, 1985) can be understood in termsof dissonance induction/reduction. Lewinsohn et al. (1985) suggested that individuals who areprone to depression tend to focus on



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their own inadequacies and failures rather than attending to factors in the environment that may potentially be responsible for

negative outcomes. This view is strengthened because it is consonant with how depressed individuals think, feel and behave.

Individuals who become stuck in this negative feedback loop may exhibit withdrawal and avoidance behaviors, which have the

unfortunate consequence of reducing opportunities to receive positive reinforcement from their environment. Lost opportunities

for receiving positive reinforcement may be particularly acute in the interpersonal arena (Zeiss, Lewinsohn, & Munoz, 1979).

Operant treatment for depression focuses on changing the patient's overt behaviors and creates dissonance with their current

cognitions and emotions. BT affects change by motivating depressed individuals to increase their opportunities for receiving

positive reinforcement and to engage in more pleasurable activities, particularly in the social sphere. Social skills training, anger

management, and conict resolution are also used and puts the person in an active position which is dissonant with their passive,

depressive state (Lewinsohn et al., 1985). This creates dissonance with current cognitions and emotions. Subsequently, thoughts,

feelings, and behaviors change in constructive ways given therapeutic guidance as network dissonance is replaced by consonance.

Cognitive therapy (CT) is the most well researched and empirically supported psycho-social treatment for depression (Butler &

Beck, 1995; Dobson,1989). CTgrew out ofthe work ofBeck, Rush, Emory, Shaw, and Emery (1979), which indicated that depression

develops and is maintained by dysfunctional beliefs, cognitive errors, and negatively biased interpretations of events. Both the

cognitive and behavioral components of CT are designed to restructure the patient's depressive cognitive schemas or patterns that

are believed to be directly causing the depressive symptoms. Treatment approaches in CT involve a dual approach whereby

behavior techniques are employed in order to increase the frequency of positive activities while concurrently the therapist engages

the depressed individual in the cognitive restructuring of dysfunctional thoughts. Both the cognitive and behavioral components in

Beck's system serve as dissonance induction procedures, which affect change upon the depressive state. However mechanism

information regarding how these changes take place has not been provided. We suggest that actions of the cognitive therapist

create dissonance between the patient's newly acquired cognitions and their current behavioral patterns. For instance, correcting

cognitive errors creates a dissonant state for the patient when long held, but irrational beliefs are challenged and contradictory

evidence is provided that serves to undermine those dysfunctional cognitions.

Other examples of dissonance induction procedures in CT include Socratic Questioning and collaborative empiricism. The

Socratic Method is used to guide the patient towards cognitions that are consonant with a non-depressed state by questioning the

basic assumptions that underlie the individual's dysfunctional cognitions and depressive schemas. Depressive individuals are thus

led to undermine their own negative positions and to seek a point of view that is more consonant with a non-depressed state.

Collaborative empiricism is also a dissonance induction procedure. Through collaborative empiricism, the patient is encouraged

to collect experiential evidence that is dissonant with their previously held negative cognitions and irrational beliefs. By

expeientially disconrming those cognitive distortions, the patient will experience a dissonant state, which as therapy progresses

will cause the patient to adopt a position that is more consonant with not being depressed. The entire process of cognitive

restructuring, considered to be the primary therapeutic mechanism of CT, can be understood as implementing the cognitive

dissonance induction/reduction principle using a variety of cognitive and behavioral techniques.

Interpersonal psychotherapy for depression (IPT) was rst developed by Klerman, Weissman and colleagues (Klerman,

Weissman, Rounseville, & Chevron, 1984; Weissman, Markowitz, & Klerman, 2000). IPT rests on the theory that depression

typically takes place within social contexts (Blanco, Clougherty, Lipsitz, Mufson, & Weissman, 2006). Depressogenic social contexts

may include marital or relational breakups, relocation from one's home, loss of occupation or status, and loss or death of a loved

one. Interpersonal therapists address depressive symptoms by focusing their efforts on the current interpersonal problems that are

leading to symptom manifestation. Like BTand CT, IPT is a structured and present-focused therapeutic modality. Initial sessions are

devoted to gaining an understanding of the interpersonal problems surrounding the patient's depressive symptoms. The patient's

interpersonal problems are formulated in relation to the development of their depressive symptoms according to four categories

including grief, role disputes, role transition, and interpersonal decits. Through IPT, the patient comes to terms with their grief

regarding loss (e.g., of relationships, loved ones, personal abilities, etc.), navigates through difculties associated with changing

social roles (e.g., recognizing the role disputes associated with a divorce), adopts new social roles, and builds social skills to correct

interpersonal decits (e.g., addressing communication patterns that are ineffective). Interpersonal therapists engage in a variety of

techniques designed to help move the patient through the therapeutic process. IPT techniques include clarication, which is

utilized to make the patient aware of the thoughts and feelings they are communicating, encouragement to express affect,exploratory techniques designed to help the patient discover the cognitive and behavioral problems associated with their

depressive symptoms, the analysis of communication failures and inefciencies, behavioral methods such as role playing and

modeling and the use of the therapeutic relationship for identifying maladaptive interpersonal styles. All of the above IPT

components entail the creation and subsequent reduction of cognitive dissonance. Interpersonal therapists help their patients to

acquire new beliefs, experiences and behaviors that are dissonant with symptoms of depression. IPTeffectively creates dissonance

in the social area of functioning for patients with depression. For instance, clarication and encouraging the expression of affect are

effective in getting the patient to consciously recognize and experience painful emotions that may have previously been avoided.

The therapist uses the dissonance created by experiencing these emotions in a supportive context to help the client accept and

move beyond them to a new state that is more consonant with not being depressed. IPT assists the patient in adopting new social

roles, and consequently to develop a new social identity that is dissonant with feelings of loss, grief, sadness and other depressive

emotions but consonant with not being depressed. Utilizing behavioral techniques such as role plays, modeling and interpersonal

skill building, IPT improves self-efcacy. Like in BT, acquiring greater interpersonal competencies also leads to increased oppor-

tunities to receive positive reinforcement and to engage in more pleasurable activities, both of which are more consonant with notbeing depressed.



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10/13

In sum, the rumination literature suggests that patterns of repetitive negative thinking and focus on depressive information

play an important role in the maintenance of depression. Why should this be? What mechanism explains why rumination is so

destructive? After all, computers can repeatedly process information without being altered so why can't people repeatedly process

negative thoughts with impunity? The answer pertains to the well documented neuroscience nding of experience-dependent

brain plasticity. Unlike computers, processing changes the brain. Connectionist models reect experience-dependent brain

plasticity by changing connection weights as a result of processing. Rumination selectively primes and thereby strengthens

processing pathways that support depressive cognition, affect, and behavior such that subsequent activation initiated by related

events will tend to follow those network paths with similar results. This priming effect is directly proportional to the cumulative

ruminative frequency. Stated differently, rumination alters the connections among processing nodes and thereby changes the way

the person thinks, feels, and acts. Thoughts, feelings, and actions that co-occur become associated. The natural part-whole pattern

completion tendency of networks means that activation spreads such that a pessimistic thought activates an associated feeling and

behavior, a depressed feeling activates depressive thoughts and behaviors, and some behaviors activates depressive thoughts and

feelings. This interdependency is strengthened with repeated processing and thereby exacerbates depressive symptoms. Effective

therapies seem to induce cognitive dissonance by priming for positive memories and information that is incompatible with

depressive rumination. This may also be accomplished through intentional forgetting procedures that deactivate the ruminative

cycle (e.g.,Joormann et al., 2005).

8. Limitations

We now identify and discuss six limitations to the dissonance induction/reduction principle presented above. First, the dissonance

induction/reduction principle does not fully explain why some therapists succeed more than others who report using the same

techniques. Some therapists may be more effective at inducing dissonance and facilitating its reduction than other therapists. Two

therapists implementing what they believe to be the same therapies may in fact not be duplicating therapeutic procedures. This is

why investigators who study therapeutic outcome videotape sessions and have them rated for compliance with manualized

treatments. Dissonance can be reduced in counterproductive ways. Texts on motivational interviewing (e.g.,Miller & Rollnick, 2002)

caution therapists that the dissonance that they intentionally induce can be reduced through various forms of rationalizations.

Returning to old habits is another unproductive way to reduce dissonance. Some therapists may be better than others at precluding

these unproductive dissonance reducing methods in favor of promoting the desired cognitive, affective, and behavioral changes.

Therapists who manage to duplicate therapeutic procedures may not have the same therapeutic alliance with their clients. The

participant (client and therapist) factors and relationship factors identied byCastonguay and Beutler (2006)remain important and

may bear upon the extent to which the dissonance induction/reduction principle is actually implemented in each case.

Second, the dissonance induction/reduction principle does not explain why some patients fail to improve despite trying

multiple therapies for depression. One possible explanation is that treatment failed either because insufcient dissonance was

induced and/or because induced dissonance was not adequately reduced. Process research specically designed to track

dissonance induction and reduction is required to determine if the principle is defective or if its implementation is ineffective in

non-responsive cases. Lack of response by clients who do not take prescribed medication is not taken as evidence that the

medication is ineffective. Likewise adequate dissonance induction and reduction must occur before improvement can be expected.

Third, the dissonance induction/reductionprinciple does not explain why some people are depression prone and repeatedly get

depressed, while others never get depressed. The dissonance induction/reduction principle does not carry direct etiological

implications. However, it may be that people who never get depressed implement the dissonance induction/reduction principle on

their own or with or without the assistance of family members, friends, and/or others who provide social support. Perhaps

depression-prone individuals make little or no use of this principle. Future research designed to detect natural variations in the

prophylactic and/or therapeutic use of this principle is needed.

Fourth, most therapies that provide even partially effective treatments are due to multiple factors rather than one factor. While

we are claiming that the dissonance induction/reduction principle is an empirically supported principle that explains why

empirically supported treatments work we are not claiming that it is the only therapeutic basis. We acknowledge that the

participant (client and therapist) and relationship factors identi

ed by Castonguay and Beutler (2006) are important. Thedissonance induction/reduction principle falls underCastonguay and Beutler's (2006)intervention factors.

The fth limitation goes to the evidence connecting CBT and brain change. Converging evidence has established that

experience-dependent brain plasticity is the general mechanism responsible for learning and memory (Bear, Connors, & Paradiso,

2007; Krasne, 2002; Martin, Bartsch, Bailey, & Kandel, 2000; Moscovitch, Chein, Talmi, & Cohn, 2007). Supporting data from animal

studies are based on true experiments that entail manipulation. Human imaging studies utilize manipulation in that they

demonstrate brain changes resulting from the administration of CBT for OCD (Frewen, Dozois, & Lanius, 2008; Linden, 2006;

Rosenberg, Benazon, Gilbert, Sullivan, & Moore, 2000; Saxena, & Rauch, 2000), IPT, and CBT for depression (Frewen, Dozois, &

Lanius, 2008; Goldapple et al., 2004; Mayberg, 2003), CBT for OCD and panic, social anxiety and spider phobia (Frewen, Dozois, &

Lanius, 2008; Paquette et al., 2003; Veltman, Tuinebreijer, Willer, Dolan, & Emmelkamp, 2004), and psychotherapy (Roffman,

Marci, Glick, Dougherty, & Rauch, 2005) where therapy constitutes a manipulated independent variable. In so far as these

interventions have procedurally implemented the dissonance induction/reduction principle, these studies have empirically

supported this principle. The dissonance induction/reduction principle in combination with the network model presented above

provides a way to understand how psychological intervention might produce the brain changes associated with therapeuticoutcomes. Future research should endeavor to more directly link the dissonance induction/reduction principle to brain change.



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The sixth limitation is that the dissonance induction/reduction principle does not explain why antidepressant medications,

including placebos, are effective. Medication and expectation effects lay outside the explanatory scope of the dissonance induction/

reduction principle and therefore neither support nor refute this principle.

9. Implications for clinical practice

The main point we want to emphasize is that effective clinicians, regardless of their theoretical orientation, probably

implement the dissonance induction/reduction principle, which we have argued changes the way their clients to think, feel, and

behave because it causes their brain network to process information differently. Three positive expectations result from this view.

First, we expect that clinicians can become more effective by consciously using the dissonance induction/reduction principle in

therapy. Toward this end it is important to note that Motivational Interviewing explicitly prescribes dissonance induction as a way

to help people change their behavior (cf., Draycott & Dabbs, 1998; Miller & Rollnick, 2002; Munch, Tryon, Travaglini, &

Morgenstern, 2006). Second, understanding that dissonance induction/reduction is a common factor responsible for the

effectiveness of ESTs may motivate more clinicians to use more of the procedures where investigators have procedurally

implemented this principle. Third, we anticipate that this trans-theoretical perspective will foster theoretical unication within

psychology and with neuroscience thereby making clinical psychology more consilient (Wilson, 1998).

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