Leveraging cognitive neuroscience for making and breaking real-world habits.

Habits are the behavioral output of two brain systems. A stimulus-response (S-R) system that encourages us to efficiently repeat well-practiced actions in familiar settings, and a goal-directed system concerned with flexibility, prospection, and planning. Getting the balance between these systems right is crucial: an imbalance may leave people vulnerable to action slips, impulsive behaviors, and even compulsive behaviors.

Reliable, rapid, and remote measurement of metacognitive bias.

Metacognitive biases have been repeatedly associated with transdiagnostic psychiatric dimensions of 'anxious-depression' and 'compulsivity and intrusive thought', cross-sectionally. To progress our understanding of the underlying neurocognitive mechanisms, new methods are required to measure metacognition remotely, within individuals over time. We developed a gamified smartphone task designed to measure visuo-perceptual metacognitive (confidence) bias and investigated its psychometric properties across two studies (N = 3410 unpaid citizen scientists, N = 52 paid participants).

Confidence biases in problem gambling.

Background And Aims: Subjective confidence plays an important role in guiding behaviour, especially when objective feedback is unavailable. Systematic misjudgements in confidence can foster maladaptive behaviours and have been linked to various psychiatric disorders. In this study, we adopted a transdiagnostic approach to examine confidence biases in problem gamblers across three levels: local decision confidence, global task performance confidence, and overall self-esteem.

Elevated emotion network connectivity is associated with fluctuations in depression.

Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time, rather than necessarily more severe depression.

An observational treatment study of metacognition in anxious-depression.

Prior studies have found metacognitive biases are linked to a transdiagnostic dimension of anxious-depression, manifesting as reduced confidence in performance. However, previous work has been cross-sectional and so it is unclear if under-confidence is a trait-like marker of anxious-depression vulnerability, or if it resolves when anxious-depression improves. Data were collected as part of a large-scale transdiagnostic, four-week observational study of individuals initiating internet-based cognitive behavioural therapy (iCBT) or antidepressant medication.

The Effectiveness of Low-Intensity Psychological Interventions for Comorbid Depression and Anxiety in Patients with Long-Term Conditions: A Real-World Naturalistic Observational Study in IAPT Integrated Care.

Background: Low-intensity psychological interventions may be a cost-effective, accessible solution for treating depression and anxiety in patients with long-term conditions, but evidence from real-world service settings is lacking. This study examined the effectiveness of low-intensity psychological interventions provided in the Improving Access to Psychological Therapies programme in England for patients with and without long-term conditions.

Methods: A retrospective analysis was conducted on patients (total N = 21,051, long-term conditions n = 4024) enrolled in three low-intensity psychological interventions, i.

Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable replication study of two independent ageing cohorts.

Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship.

Heterogeneous factors influence social cognition across diverse settings in brain health and age-related diseases.

Aging may diminish social cognition, which is crucial for interaction with others, and significant changes in this capacity can indicate pathological processes like dementia. However, the extent to which non-specific factors explain variability in social cognition performance, especially among older adults and in global settings, remains unknown. A computational approach assessed combined heterogeneous contributors to social cognition in a diverse sample of 1063 older adults from 9 countries.

Estimating the prognostic value of cross-sectional network connectivity for treatment response in depression.

Background: Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small-sample studies comparing single responder non-responder networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance.

Methods: = 40 518 patients receiving treatment for depression in routine care in England from 2015-2020 were analysed.

Resting-State Functional Connectivity Differences Following Experimental Manipulation of the Orbitofrontal Cortex in Two Directions via Theta-Burst Stimulation.

Compulsive behaviors (CBs) have been linked to orbitofrontal cortex (OFC) function in animal and human studies. However, brain regions function not in isolation but as components of widely distributed brain networks-such as those indexed via resting-state functional connectivity (RSFC). Sixty-nine individuals with CB disorders were randomized to receive a single session of neuromodulation targeting the left OFC-intermittent theta-burst stimulation (iTBS) or continuous TBS (cTBS)-followed immediately by computer-based behavioral "habit override" training.

Identifying Transdiagnostic Mechanisms in Mental Health Using Computational Factor Modeling.

Most psychiatric disorders do not occur in isolation, and most psychiatric symptom dimensions are not uniquely expressed within a single diagnostic category. Current treatments fail to work for around 25% to 40% of individuals, perhaps due at least in part to an overreliance on diagnostic categories in treatment development and allocation. In this review, we describe ongoing efforts in the field to surmount these challenges and precisely characterize psychiatric symptom dimensions using large-scale studies of unselected samples via remote, online, and "citizen science" efforts that take a dimensional, mechanistic approach.

The Precision in Psychiatry (PIP) study: Testing an internet-based methodology for accelerating research in treatment prediction and personalisation.

Background: Evidence-based treatments for depression exist but not all patients benefit from them. Efforts to develop predictive models that can assist clinicians in allocating treatments are ongoing, but there are major issues with acquiring the volume and breadth of data needed to train these models. We examined the feasibility, tolerability, patient characteristics, and data quality of a novel protocol for internet-based treatment research in psychiatry that may help advance this field.

Developments in scalable strategies for detecting early markers of cognitive decline.

Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment.

Machine learning of language use on Twitter reveals weak and non-specific predictions.

Depressed individuals use language differently than healthy controls and it has been proposed that social media posts can be used to identify depression. Much of the evidence behind this claim relies on indirect measures of mental health and few studies have tested if these language features are specific to depression versus other aspects of mental health. We analysed the Tweets of 1006 participants who completed questionnaires assessing symptoms of depression and 8 other mental health conditions.

A double-blind study assessing the impact of orbitofrontal theta burst stimulation on goal-directed behavior.

Patients with disorders of compulsivity show impairments in goal-directed behavior, which have been linked to orbitofrontal cortex (OFC) dysfunction. We recently showed that continuous theta burst stimulation (cTBS), which reduces OFC activity, had a beneficial effect on compulsive behaviors both immediately and at 1 week follow-up compared with inhibitory TBS (iTBS). In this same sample, we investigated whether two behavioral measures of goal-directed control (devaluation success on a habit override task; model-based planning on the two-step task) were also affected by acute modulation of OFC activity.

Using language in social media posts to study the network dynamics of depression longitudinally.

Network theory of mental illness posits that causal interactions between symptoms give rise to mental health disorders. Increasing evidence suggests that depression network connectivity may be a risk factor for transitioning and sustaining a depressive state. Here we analysed social media (Twitter) data from 946 participants who retrospectively self-reported the dates of any depressive episodes in the past 12 months and current depressive symptom severity.

New principles and new paths needed for online research in mental health: Commentary on Burnette et al. (2021).

Online methods have become a powerful research tool, allowing us to conduct well-powered studies, to explore and replicate effects, and to recruit often rare and diverse samples. However, concerns about the validity and reliability of the data collected from some platforms have reached crescendo. In this issue, Burnette et al.

Psychedelic Therapy's Transdiagnostic Effects: A Research Domain Criteria (RDoC) Perspective.

Accumulating clinical evidence shows that psychedelic therapy, by synergistically combining psychopharmacology and psychological support, offers a promising transdiagnostic treatment strategy for a range of disorders with restricted and/or maladaptive habitual patterns of emotion, cognition and behavior, notably, depression (MDD), treatment resistant depression (TRD) and addiction disorders, but perhaps also anxiety disorders, obsessive-compulsive disorder (OCD), Post-Traumatic Stress Disorder (PTSD) and eating disorders. Despite the emergent transdiagnostic evidence, the specific clinical dimensions that psychedelics are efficacious for, and associated underlying neurobiological pathways, remain to be well-characterized. To this end, this review focuses on pre-clinical and clinical evidence of the acute and sustained therapeutic potential of psychedelic therapy in the context of a transdiagnostic dimensional systems framework.

Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases.

Social feedback can selectively enhance learning in diverse domains. Relevant neurocognitive mechanisms have been studied mainly in healthy persons, yielding correlational findings. Neurodegenerative lesion models, coupled with multimodal brain measures, can complement standard approaches by revealing direct multidimensional correlates of the phenomenon.