Dataset Information

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression.

ABSTRACT:

Background

Theoretical models of neural mechanisms underlying Cognitive Behavior Therapy (CBT) for major depressive disorder (MDD) propose that psychotherapy changes neural functioning of prefrontal cortical structures associated with cognitive-control processes (DeRubeis, Siegle, & Hollon, ); however, MDD is persistent and characterized by long-lasting vulnerabilities to recurrence after intervention, suggesting that underlying neural mechanisms of MDD remain despite treatment. It follows that identification of treatment-resistant aberrant neural processes in MDD may inform clinical and research efforts targeting sustained remission. Thus, we sought to identify brain regions showing aberrant neural functioning in MDD that either (1) fail to exhibit substantive change (nonresponse) or (2) exhibit functional changes (response) following CBT.

Methods

To identify treatment-resistant neural processes (as well as neural processes exhibiting change after treatment), we collected functional magnetic resonance imaging (fMRI) data of MDD patients (n = 58) before and after CBT as well as never-depressed controls (n = 35) before and after a similar amount of time. We evaluated fMRI data using conjunction analyses, which utilized several contrast-based criteria to characterize brain regions showing both differences between patients and controls at baseline and nonresponse or response to CBT.

Results

Findings revealed nonresponse in a cerebellar region and response in prefrontal and parietal regions.

Conclusions

Results are consistent with prior theoretical models of CBT's direct effect on cortical regulatory processes but expand on them with identification of additional regions (and associated neural systems) of response and nonresponse to CBT.

SUBMITTER: Strege MV

PROVIDER: S-EPMC10651800 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Publications

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression.

Strege Marlene V MV Richey John A JA Siegle Greg J GJ

Psychological medicine 20230516 1

<h4>Background</h4>Theoretical models of neural mechanisms underlying Cognitive Behavior Therapy (CBT) for major depressive disorder (MDD) propose that psychotherapy changes neural functioning of prefrontal cortical structures associated with cognitive-control processes (DeRubeis, Siegle, & Hollon, ); however, MDD is persistent and characterized by long-lasting vulnerabilities to recurrence after intervention, suggesting that underlying neural mechanisms of MDD remain despite treatment. It follo ...[more]

PMID: 37191029

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Project description:ObjectiveWe tested nomothetic and idiographic convergence and change in 3 symptom measures during acute-phase cognitive therapy (CT) for depression and compared outcomes among patients showing different change patterns.MethodOutpatients (N = 362; 69% women; 85% White; age M = 43 years) with recurrent major depressive disorder according to criteria in the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000) completed the Hamilton Rating Scale for Depression (Hamilton, 1960), Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961), and Inventory for Depressive Symptomatology-Self-Report (Rush, Gullion, Basco, Jarrett, & Trivedi, 1996) on 14 occasions as well as pre/post-CT measures of social-interpersonal functioning and negative cognitive content.ResultsThe 3 symptom measures marked the same severity and change constructs, and we offer improved formulas for intermeasure score conversions via their common factor. Pre/post-CT symptom reductions were large (ds = 1.71-1.92), and nomothetic symptom curves were log-linear (larger improvements earlier and smaller improvements later in CT). Nonetheless, only 30% of individual patients showed clear log-linear changes, whereas other patients showed linear (e.g., steady decreases; 20%), 1-step (e.g., a quick drop; 16%), and unclassified (34%) patterns. Log-linear, linear, and 1-step patients were generally similar to one another and superior to unclassified patients post-CT in symptom levels, response and stable remission rates, social-interpersonal functioning, and cognitive content (median d = 0.69).ConclusionsReaching a low-symptom "destination" at the end of CT via any coherent "path" is more important in the short term than which path patients take. We discuss implications for theories of change, clinical monitoring of individuals' progress in CT, and the need to investigate long-term outcomes of patients with differing patterns of symptom change.

Project description:ImportanceMajor depressive disorder is prevalent and impairing. Parsing neurocomputational substrates of reinforcement learning in individuals with depression may facilitate a mechanistic understanding of the disorder and suggest new cognitive therapeutic targets.ObjectiveTo determine associations among computational model-derived reinforcement learning parameters, depression symptoms, and symptom changes after treatment.Design, setting, and participantsIn this mixed cross-sectional-cohort study, individuals performed reward and loss variants of a probabilistic learning task during functional magnetic resonance imaging at baseline and follow-up. A volunteer sample with and without a depression diagnosis was recruited from the community. Participants were assessed from July 2011 to February 2017, and data were analyzed from May 2017 to May 2021.Main outcomes and measuresComputational model-based analyses of participants' choices assessed a priori hypotheses about associations between components of reward-based and loss-based learning with depression symptoms. Changes in both learning parameters and symptoms were then assessed in a subset of participants who received cognitive behavioral therapy (CBT).ResultsOf 101 included adults, 69 (68.3%) were female, and the mean (SD) age was 34.4 (11.2) years. A total of 69 participants with a depression diagnosis and 32 participants without a depression diagnosis were included at baseline; 48 participants (28 with depression who received CBT and 20 without depression) were included at follow-up (mean [SD] of 115.1 [15.6] days). Computational model-based analyses of behavioral choices and neural data identified associations of learning with symptoms during reward learning and loss learning, respectively. During reward learning only, anhedonia (and not negative affect or arousal) was associated with model-derived learning parameters (learning rate: posterior mean regression β = -0.14; 95% credible interval [CrI], -0.12 to -0.03; outcome sensitivity: posterior mean regression β = 0.18; 95% CrI, 0.02 to 0.37) and neural learning signals (moderation of association between striatal prediction error and expected value signals: t97 = -2.10; P = .04). During loss learning only, negative affect (and not anhedonia or arousal) was associated with learning parameters (outcome shift: posterior mean regression β = -0.11; 95% CrI, -0.20 to -0.01) and disrupted neural encoding of learning signals (association with subgenual anterior cingulate prediction error signals: r = -0.28; P = .005). Symptom improvement following CBT was associated with normalization of learning parameters that were disrupted at baseline (reward learning rate: posterior mean regression β = 0.15; 90% CrI, 0.001 to 0.41; loss outcome shift: posterior mean regression β = 0.42; 90% CrI, 0.09 to 0.77).Conclusions and relevanceIn this study, the mapping of reinforcement learning components to symptoms of major depression revealed mechanistic features associated with these symptoms and points to possible learning-based therapeutic processes and targets.

Dataset Information

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression.

Background

Methods

Results

Conclusions

Publications

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression.

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