Vincent Man

The expanding cognitive-behavioural therapy treatment umbrella for the anxiety disorders: disorder-specific and transdiagnostic approaches.

Cognitive-behavioural therapy (CBT) is an empirically supported treatment for anxiety disorders. CBT treatments are based on disorder-specific protocols that have been developed to target individual anxiety disorders, despite that anxiety disorders frequently co-occur and are comorbid with depression. Given the high rates of diagnostic comorbidity, substantial overlap in dimensional symptom ratings, and extensive evidence that the mood and anxiety disorders share a common set of psychological and biological vulnerabilities, transdiagnostic CBT protocols have recently been developed to treat the commonalities among the mood and anxiety disorders. We conducted a selective review of empirical developments in the transdiagnostic CBT treatment of anxiety and depression (2008–2013). Preliminary evidence suggests that theoretically based transdiagnostic CBT approaches lead to large treatment effects on the primary anxiety disorder, considerable reduction of diagnostic comorbidity, and some preliminary effects regarding the impact on the putative, shared psychological mechanisms. However, the empirical literature remains tentative owing to relatively small samples, limited direct comparisons with disorder-specific CBT protocols, and the relative absence of the study of disorder-specific compared with shared mechanisms of action in treatment. We conclude with a treatment conceptualization of the new transdiagnostic interventions as complementary, rather than contradictory, to disorder-specific CBT.

Hierarchical Brain Systems Support Multiple Representations of Valence and Mixed Affect

We review the psychological literature on the organization of valence, discussing theoretical perspectives that favor a single dimension of valence, multiple valence dimensions, and positivity and negativity as dynamic and flexible properties of mental experience that are contingent upon context. Turning to the neuroscience literature that spans three levels of analysis, we discuss how positivity and negativity can be represented in the brain. We show that the evidence points toward both separable and overlapping brain systems that support affective processes depending on the level of resolution studied. We move from large-scale brain networks that underlie generalized processing, to functionally specific subcircuits, finally to intraregional neuronal distributions, where the organization and interaction across levels allow for multiple types of valence and mixed evaluations.

Task-linked diurnal brain network reorganization in older adults: A graph theoretical approach

Testing older adults in the morning generally improves behavioral performance relative to afternoon testing. Morning testing is also associated with brain activity similar to that of young adults. Here, we used graph theory to explore how time of day (TOD) affects the organization of brain networks in older adults across rest and task states. We used nodes from the automated anatomical labeling atlas to construct participant-specific correlation matrices of fMRI data obtained during 1-back tasks with interference and rest. We computed pairwise group differences for key graph metrics, including small-worldness and modularity. We found that older adults tested in the morning and young adults did not differ on any graph metric. Both of these groups differed from older adults tested in the afternoon during the tasks—but not rest. Specifically, the latter group had lower modularity and small-worldness (indices of more efficient network organization). Across all groups, higher modularity and small-worldness strongly correlated with reduced distractibility on an implicit priming task. Increasingly, TOD is seen as important for interpreting and reproducing neuroimaging results. Our study emphasizes how TOD affects brain network organization and executive control in older adults.

Disrupted cortico-limbic connectivity during reward processing in remitted bipolar I disorder

Bipolar disorder (BD) is associated with elevated reward sensitivity and persistent positive affect, yet the neural mechanisms underlying these patterns are not well understood. In the present study, we examined putative disruptions in communication within a well‐known cortico‐limbic reward circuit during reward processing as a potential contributing mechanism to these symptoms.

Differential spatiotemporal representations along the hippocampal long axis in humans

Increased place field size and signal autocorrelation along the dorsoventral hippocampal axis in rodents are considered a fundamental aspect of hippocampal organization, yet such evidence is lacking in humans. Using fMRI, we report corresponding evidence of increasing neural similarity from posterior to anterior hippocampus (dorsoventral homologues) in humans. These findings help account for observed shifting in representational granularity, from global context (anterior) to local details (posterior), along the hippocampal axis.

Contextual Influences on Value-based Choice

Biases in choice behavior are shaped by both immediately encountered cues as well as the background context in which these cues are embedded. Here we examine the mechanisms that underlie the integration of contextual and cue information, and the manner in which these sources of information shape behavior. We demonstrate contextual influence on choice dissociated from cue information using a value-based multi-alternative choice task while recording neural activity using electroencephalography. Consistent with work on negativity biases, we show that contextual attributes related to loss, reflected along central-parietal sites in the gamma (30-59 Hz) frequency range, are prioritized and drive behavior to prevent loss. We employ a multi-alternative sequential sampling computational model to show that contextual and cue information are integrated through the decision process to shape choice responses, and link this integrative process to a neural signature in the gamma frequency band.

Decomposing the neural pathways mediating value-based choice

Understanding the neural implementation of value-based choice has been an important focus of neuroscience for several decades. Although a consensus has emerged regarding the brain regions involved, disagreement persists regarding precise regional functions and how value information flows between value-based choice regions. In the current study, we isolate neural activity related to decision-making using a gambling task where expected gains and losses are dissociated from the received outcomes of choices. We apply multilevel modelling and mediation analysis to formally test whether brain regions identified as part of the value-based choice network mediate between perceptions of expected value and choices to take or pass a gamble. A critical function in decision-making is accruing and representing value information to drive choice. Several regions have been assigned this role, including ventromedial prefrontal (vmPFC) and posterior parietal cortex (PPC), and the ventral striatum (VStr). The implied chain of events is one where regions that support the process of gathering relevant information mediate the relationship between choice and representations of value in other brain regions. Here, we formally test whether distinct brain regions express interregional mediation consistent with this chain of processes. We observe that activity in vmPFC does not predict choice, but rather is highly associated with outcome evaluation. By contrast, both PPC and VStr (bilaterally) mediate between expected value and choice. Interregional mediation analyses reveal that VStr fully mediates between PPC and choice. Together these results suggest that VStr, and not vmPFC nor PPC, functions as an important driver of late stage choice. Significance Statement Making choices that maximize gain and minimize loss is critical for success. Our paradigm and analytic approach allowed isolation of choice-related neural signals from outcome-related signals. The vmPFC is involved at outcome rather than at choice. Isolating choice-related neural activity, we formally demonstrate that VStr and PPC mediate between expected value and choice. Our approach adds significant innovation by using generalized multilevel modelling to predict behavior with concurrent neural activity and formally testing the fully mediated pathway from stimulus through neural activity to behavior. Applying interregional multilevel mediation analysis, we demonstrate that ventral striatum comprises a final, critical step in processing value-based choice, mediating the relationship between value representation and choice.