Developing Dimensional, Pandiagnostic Inhibitory Control Constructs With Self-Report and Neuropsychological Data

The Relations Between an Inventory-Based Measure of Executive Function and Impulsivity Factors in Alcohol- and Cannabis-Relevant Outcomes

OBJECTIVE

While the lack of relation between performance- and inventory-based executive function (EF) measures is well documented, there remains ambiguity between self-report EFs and closely related constructs (e.g., impulsivity) assessed via the same method. The degree of convergence between purported EF measures with similar yet distinct constructs contain important theoretical implications for available EF assessment strategies and their construct validity. A newer measure of EF, the Behavior Regulation Inventory of Executive Functions-Adult (BRIEF-A), allows for more direct comparisons to self-reported measures of impulsivity, such as the commonly used Urgency, Planning, Perseverance, Sensation Seeking-Positive Urgency (UPPS-P) assessment.

METHOD

The present study used factor analysis and hierarchical regression to explore the associations between the BRIEF-A and UPPS-P, using alcohol and cannabis consumption across various outcomes (i.e., quantity-frequency and consequences) as an external criterion. Participants were 339 undergraduate students (Mage = 19.35; Female = 63%) from a large southwestern university.

RESULTS

The BRIEF-A and UPPS-P demonstrated strong correlations at both higher- and lower order facets. While the BRIEF-A was a significant correlate to many substance use outcomes, these relations were generally weaker than those seen with the UPPS-P. Hierarchical regression suggested limited contributions of the BRIEF-A over and above the UPPS-P.

CONCLUSIONS

Overall, this study suggested substantial overlap between impulsigenic factors and EFs when measured by self-report, and limited utility of EF measures to account for unique variance with substance use outcomes in this sample.

Relations of gray matter volume to dimensional measures of cognition and affect in mood disorders

Understanding the relationship between brain measurements and behavioral performance is an important step in developing approaches for early identification of any psychiatric difficulties and interventions to modify these challenges. Conventional methods to identify associations between regional brain volume and behavioral measures are not optimized, either in scale, scope, or specificity. To find meaningful associations between brain and behavior with greater sensitivity and precision, we applied data-driven factor analytic models to identify and extract individual differences in latent cognitive functions embedded across several computerized cognitive tasks. Furthermore, we simultaneously utilized a keyword-based neuroimaging meta-analytic tool (i.e., NeuroSynth), restricted atlas-parcel matching, and factor-analytic models to narrow down the scope of search and to further aggregate gray matter volume (GMV) data into empirical clusters. We recruited an early adult community cross-sectional sample (Total n = 177, age 18-30) that consisted of individuals with no history of any mood disorder (healthy controls, n = 44), those with remitted major depressive disorder (rMDD, n = 104), and those with a diagnosis of bipolar disorder currently in euthymic state (eBP, n = 29). Study participants underwent structural magnetic resonance imaging (MRI) scans and separately completed behavioral testing using computerized measures. Factor-analyzing five computerized tasks used to assess aspects of cognitive and affective processing resulted in seven latent dimensions: (a) Emotional Memory, (b) Interference Resolution, (c) Reward Sensitivity, (d) Complex Inhibitory Control, (e) Facial Emotion Sensitivity, (f) Sustained attention, and (g)Simple Impulsivity/Response Style. These seven dimensions were then labeled with specific keywords which were used to create neuroanatomical maps using NeuroSynth. These masks were further subdivided into GMV clusters. Using regression, we identified GMV clusters that were predictive of individual differences across each of the aforementioned seven cognitive dimensions. We demonstrate that a dimensional approach consistent with core principles of RDoC can be utilized to identify structural variability predictive of critical dimensions of human behavior.

Cognitive factor structure and measurement invariance between healthy controls and patients with major depressive disorder

Cognitive impairments are crucial in functional outcomes of major depressive disorder (MDD). The effectiveness of currently available treatment methods for cognitive deficits is suboptimal. A cognitive test battery is often applied to evaluate cognition with multiple interrelated and difficult-to-interpret outcomes. Generating cognitive factor scores after the confirmation of a common cognitive structure and measurement invariance between healthy controls (HCs) and patients may aid in understanding cognition further. This methodology has been applied for several neuropsychiatric disorders, but not for MDD. Therefore, we conducted a series of exploratory factor analyses (EFA), confirmatory factor analyses (CFA), and multiple groups CFA (MGCFA) for a cognitive test battery in HCs and patients with MDD. The initial EFA of 106 HCs yielded a three-factor model-comprising attention, memory, and executive function. The CFA confirmed the initial model in other 94 HCs with revisions, which reasonably fit the cognitive data of 54 patients with MDD. MGCFA supported the measurement invariance of the determined model between HCs and patients with MDD. The associations of cognitive factor scores with age or education and the effect sizes of group differences in cognitive factor scores externally validated the determined model. In conclusion, this is the first study to demonstrate the measurement invariance of a cognitive model between HCs and patients with MDD using MGCFA. The measurement invariance substantiated valid group comparisons of factor scores and their relationships with other markers. The current results may be applicable for the development of improved treatment strategies for cognitive impairments in MDD.

C-reactive protein and affective inhibition in bipolar disorder

BACKGROUND

Individuals with bipolar disorder (BD) experience cognitive and affective processing deficits that often persist beyond the remission of acute mood symptoms. One possible biological mechanism for these deficits involves the potential effects of chronic low-grade peripheral inflammation on brain function. Peripheral inflammation has been associated with reduced executive functioning and memory performance, as well as altered reward processing in BD, but whether it is also implicated in cognitive-affective processing remains unknown.

METHOD

Peripheral inflammation was measured by serum C-reactive protein (CRP) in 119 adults with BD I or II, age 18-65. All participants completed the Affective Go/No-Go Task, a measure of cognitive-emotional processing. Correlations of CRP with discrimination of and response times to Negative, Positive, and Neutral words were performed before and after adjustment for severity of residual depressive symptoms and other demographic and clinical characteristics associated with inflammation.

RESULTS

Increased CRP was significantly associated with reduced negative target discriminability, which was also significantly reduced compared to positive and neutral target conditions. Additionally, greater CRP was associated with faster response times for both negative hits and commissions, as well as positive commissions.

CONCLUSIONS

This study adds to existing research demonstrating associations between inflammation and cognition or reward sensitivity and motivation separately in BD, by raising the possibility that inflammation is also implicated in the integration of cognitive-affective processing. Assessment of these associations over time is warranted to determine involvement of inflammation and cognitive-emotional processing in course of illness and identify critical periods for possible modulation of inflammation.

Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control

BACKGROUND

Resting-state graph-based network edges can be powerful tools for identification of mood disorders. We address whether these edges can be integrated with Research Domain Criteria (RDoC) constructs for accurate identification of mood disorder-related markers, while minimizing active symptoms of disease.

METHODS

We compared 132 individuals with currently remitted or euthymic mood disorder with 65 healthy comparison participants, ages 18-30 years. Subsets of smaller brain parcels, combined into three prominent networks and one network of parcels overlapping across these networks, were used to compare edge differences between groups. Consistent with the RDoC framework, we evaluated individual differences with performance measure regressors of inhibitory control and reward responsivity. Within an omnibus regression model, we predicted edges related to diagnostic group membership, performance within both RDoC domains, and relevant interactions.

RESULTS

There were several edges of mood disorder group, predominantly of greater connectivity across networks, different than those related to individual differences in inhibitory control and reward responsivity. Edges related to diagnosis and inhibitory control did not align well with prior literature, whereas edges in relation to reward responsivity constructs showed greater alignment with prior literature. Those edges in interaction between RDoC constructs and diagnosis showed a divergence for inhibitory control (negative interactions in default mode) relative to reward (positive interactions with salience and emotion network).

CONCLUSIONS

In conclusion, there is evidence that prior simple network models of mood disorders are currently of insufficient biological or diagnostic clarity or that parcel-based edges may be insufficiently sensitive for these purposes.

Mechanisms of rumination change in adolescent depression (RuMeChange): study protocol for a randomised controlled trial of rumination-focused cognitive behavioural therapy to reduce ruminative habit and risk of depressive relapse in high-ruminating adolescents

BACKGROUND

Adolescent-onset depression often results in a chronic and recurrent course, and is associated with worse outcomes relative to adult-onset depression. Targeting habitual depressive rumination, a specific known risk factor for relapse, may improve clinical outcomes for adolescents who have experienced a depressive episode. Randomized controlled trials (RCTs) thus far have demonstrated that rumination-focused cognitive behavioral therapy (RFCBT) reduces depressive symptoms and relapse rates in patients with residual depression and adolescents and young adults with elevated rumination. This was also observed in a pilot RCT of adolescents at risk for depressive relapse. Rumination can be measured at the self-report, behavioral, and neural levels- using patterns of connectivity between the Default Mode Network (DMN) and Cognitive Control Network (CCN). Disrupted connectivity is a putative important mechanism for understanding reduced rumination via RFCBT. A feasibility trial in adolescents found that reductions in connectivity between DMN and CCN regions following RFCBT were correlated with change in rumination and depressive symptoms.

METHOD

This is a phase III two-arm, two-stage, RCT of depression prevention. The trial tests whether RFCBT reduces identified risk factors for depressive relapse (rumination, patterns of neural connectivity, and depressive symptoms) in adolescents with partially or fully remitted depression and elevated rumination. In the first stage, RFCBT is compared to treatment as usual within the community. In the second stage, the comparator condition is relaxation therapy. Primary outcomes will be (a) reductions in depressive rumination, assessed using the Rumination Response Scale, and (b) reductions in resting state functional magnetic resonance imaging connectivity of DMN (posterior cingulate cortex) to CCN (inferior frontal gyrus), at 16 weeks post-randomization. Secondary outcomes include change in symptoms of depression following treatment, recurrence of depression over 12 months post-intervention period, and whether engagement with therapy homework (as a dose measure) is related to changes in the primary outcomes.

DISCUSSION

RFCBT will be evaluated as a putative preventive therapy to reduce the risk of depressive relapse in adolescents, and influence the identified self-report, behavioral, and neural mechanisms of change. Understanding mechanisms that underlie change in rumination is necessary to improve and further disseminate preventive interventions.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03859297 , registered 01 March 2019.

A Lifespan Model of Interference Resolution and Inhibitory Control: Risk for Depression and Changes with Illness Progression

The cognitive processes involved in inhibitory control accuracy (IC) and interference resolution speed (IR) or broadly - inhibition - are discussed in this review, and both are described within the context of a lifespan model of mood disorders. Inhibitory control (IC) is a binary outcome (success or no for response selection and inhibition of unwanted responses) for any given event that is influenced to an extent by IR. IR refers to the process of inhibition, which can be manipulated by task design in earlier and later stages through use of distractors and timing, and manipulation of individual differences in response proclivity. We describe the development of these two processes across the lifespan, noting factors that influence this development (e.g., environment, adversity and stress) as well as inherent difficulties in assessing IC/IR prior to adulthood (e.g., cross-informant reports). We use mood disorders as an illustrative example of how this multidimensional construct can be informative to state, trait, vulnerability and neuroprogression of disease. We present aggregated data across numerous studies and methodologies to examine the lifelong development and degradation of this subconstruct of executive function, particularly in mood disorders. We highlight the challenges in identifying and measuring IC/IR in late life, including specificity to complex, comorbid disease processes. Finally, we discuss some potential avenues for treatment and accommodation of these difficulties across the lifespan, including newer treatments using cognitive remediation training and neuromodulation.

Multidimensional imaging techniques for prediction of treatment response in major depressive disorder

A large number of studies have attempted to use neuroimaging tools to aid in treatment prediction models for major depressive disorder (MDD). Most such studies have reported on only one dimension of function and prediction at a time. In this study, we used three different tasks across domains of function (emotion processing, reward anticipation, and cognitive control, plus resting state connectivity completed prior to start of medication to predict treatment response in 13-36 adults with MDD. For each experiment, adults with MDD were prescribed only label duloxetine (all experiments), whereas another subset were prescribed escitalopram. We used a KeyNet (both Task derived masks and Key intrinsic Network derived masks) approach to targeting brain systems in a specific match to tasks. The most robust predictors were (Dichter et al., 2010) positive response to anger and (Gong et al., 2011) negative response to fear within relevant anger and fear TaskNets and Salience and Emotion KeyNet (Langenecker et al., 2018) cognitive control (correct rejections) within Inhibition TaskNet (negative) and Cognitive Control KeyNet (positive). Resting state analyses were most robust for Cognitive control Network (positive) and Salience and Emotion Network (negative). Results differed by whether an -fwhm or -acf (more conservative) adjustment for multiple comparisons was used. Together, these results implicate the importance of future studies with larger sample sizes, multidimensional predictive models, and the importance of using empirically derived masks for search areas.

Cognitive Control as a 5-HT1A-Based Domain That Is Disrupted in Major Depressive Disorder

Heterogeneity within Major Depressive Disorder (MDD) has hampered identification of biological markers (e.g., intermediate phenotypes, IPs) that might increase risk for the disorder or reflect closer links to the genes underlying the disease process. The newer characterizations of dimensions of MDD within Research Domain Criteria (RDoC) domains may align well with the goal of defining IPs. We compare a sample of 25 individuals with MDD compared to 29 age and education matched controls in multimodal assessment. The multimodal RDoC assessment included the primary IP biomarker, positron emission tomography (PET) with a selective radiotracer for 5-HT1A [(11C)WAY-100635], as well as event-related functional MRI with a Go/No-go task targeting the Cognitive Control network, neuropsychological assessment of affective perception, negative memory bias and Cognitive Control domains. There was also an exploratory genetic analysis with the serotonin transporter (5-HTTLPR) and monamine oxidase A (MAO-A) genes. In regression analyses, lower 5-HT1A binding potential (BP) in the MDD group was related to diminished engagement of the Cognitive Control network, slowed resolution of interfering cognitive stimuli, one element of Cognitive Control. In contrast, higher/normative levels of 5-HT1A BP in MDD (only) was related to a substantial memory bias toward negative information, but intact resolution of interfering cognitive stimuli and greater engagement of Cognitive Control circuitry. The serotonin transporter risk allele was associated with lower 1a BP and the corresponding imaging and cognitive IPs in MDD. Lowered 5HT 1a BP was present in half of the MDD group relative to the control group. Lowered 5HT 1a BP may represent a subtype including decreased engagement of Cognitive Control network and impaired resolution of interfering cognitive stimuli. Future investigations might link lowered 1a BP to neurobiological pathways and markers, as well as probing subtype-specific treatment targets.