| 1. |
- Hamilton, Paul J., et al.
(författare)
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Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder
- 2016
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Ingår i: Psychiatry Research. - : Elsevier. - 0925-4927 .- 1872-7506. ; 249, s. 91-96
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Tidskriftsartikel (refereegranskat)abstract
- Neural models of major depressive disorder (MDD) posit that over-response of components of the brains salience network (SN) to negative stimuli plays a crucial role in the pathophysiology of MDD. In the present proof-of-concept study, we tested this formulation directly by examining the affective consequences of training depressed persons to down-regulate response of SN nodes to negative material. Ten participants in the real neurofeedback group saw, and attempted to learn to down-regulate, activity from an empirically identified node of the SN. Ten other participants engaged in an equivalent procedure with the exception that they saw SN-node neurofeedback indices from participants in the real neurofeedback group. Before and after scanning, all participants completed tasks assessing emotional responses to negative scenes and to negative and positive self-descriptive adjectives. Compared to participants in the sham-neurofeedback group, from pre- to post-training, participants in the realneurofeedback group showed a greater decrease in SN-node response to negative stimuli, a greater decrease in self-reported emotional response to negative scenes, and a greater decrease in self-reported emotional response to negative self-descriptive adjectives. Our findings provide support for a neural formulation in which the SN plays a primary role in contributing to negative cognitive biases in MDD. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
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| 2. |
- Hamilton, Paul, et al.
(författare)
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Striatal dopamine deficits predict reductions in striatal functional connectivity in major depression: a concurrent C-11-raclopride positron emission tomography and functional magnetic resonance imaging investigation
- 2018
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Ingår i: Translational Psychiatry. - : NATURE PUBLISHING GROUP. - 2158-3188. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Major depressive disorder (MDD) is characterized by the altered integration of reward histories and reduced responding of the striatum. We have posited that this reduced striatal activation in MDD is due to tonically decreased stimulation of striatal dopamine synapses which results in decremented propagation of information along the corticostriatal-pallido-thalamic (CSPT) spiral. In the present investigation, we tested predictions of this formulation by conducting concurrent functional magnetic resonance imaging (fMRI) and C-11-raclopride positron emission tomography (PET) in depressed and control (CTL) participants. We scanned 16 depressed and 14 CTL participants with simultaneous fMRI and C-11-raclopride PET. We estimated raclopride binding potential (BPND), voxel-wise, and compared MDD and CTL samples with respect to BPND in the striatum. Using striatal regions that showed significant between-group BPND differences as seeds, we conducted whole-brain functional connectivity analysis using the fMRI data and identified brain regions in each group in which connectivity with striatal seed regions scaled linearly with BPND from these regions. We observed increased BPND in the ventral striatum, bilaterally, and in the right dorsal striatum in the depressed participants. Further, we found that as BPND increased in both the left ventral striatum and right dorsal striatum in MDD, connectivity with the cortical targets of these regions (default-mode network and salience network, respectively) decreased. Deficits in stimulation of striatal dopamine receptors in MDD could account in part for the failure of transfer of information up the CSPT circuit in the pathophysiology of this disorder.
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| 3. |
- Karayannis, Nicholas Vasilis., et al.
(författare)
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Pain acceptance and psychological inflexibility predict pain interference outcomes for persons with chronic pain receiving pain psychology
- 2023
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Ingår i: Scandinavian Journal of Pain. - : Walter de Gruyter. - 1877-8860 .- 1877-8879. ; 23:3, s. 464-475
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Awareness (being present), acceptance, and engagement (committed action) are three dimensions of psychological flexibility. Understanding these in the context of chronic pain may identify treatment targets to help refine individual treatment. Our objective was to test the predictive capacity of three dimensions within the psychological flexibility model on the longitudinal trajectory of pain interference.Methods: Patients receiving pain psychology treatment at a pain management center participated in this pragmatic clinical longitudinal study (n=86 with at least three assessments; Mean age=51 years; Gender=60 females, 26 males). Measures included the Five Facet Mindfulness Questionnaire (FFMQ-SF); Chronic Pain Acceptance Questionnaire (CPAQ-8); Psychological Inflexibility in Pain Scale (PIPS-12); and Committed Action Questionnaire (CAQ-8). The dependent variable was the Patient Reported Outcomes Information System (PROMIS) Pain Interference (PI). We used latent growth modelling to analyze scores assessed within 180 days of patient care.Results: Psychological inflexibility (PIPS-12) and pain acceptance (CPAQ-8) measured at baseline predicted PI outcomes (n=86). PIPS-12 showed a direct relationship with pain interference (PI), where higher PIPS-12 scores predicted significantly higher PI mean scores on average across the study period (ρ=0.422, r2=0.382) but also predicted significantly greater decreases in PI across time (ρ=−0.489, r2=0.123). Higher CPAQ-8 scores predicted significantly lower PI mean scores on average across the study period (ρ=−0.478, r2=0.453) but also significantly smaller decreases in PI across time (ρ=0.495, r2=0.076). Awareness (FFMQ-SF) and engagement (CAQ-8) were not predictive of PI outcomes.Conclusions: Patients who entered pain psychology treatment with lower pain acceptance and higher psychological inflexibility showed the largest reductions in pain interference across time. These results contribute towards a novel prognostic understanding of the predictive roles of an enhancing dimension and limiting dimension of psychological flexibility.
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| 4. |
- McWhinney, Sean R, et al.
(författare)
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Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.
- 2024
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Ingår i: Human brain mapping. - 1097-0193. ; 45:8
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Tidskriftsartikel (refereegranskat)abstract
- Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
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| 5. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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