Hot metacognition: poorer metacognitive efficiency following acute but not traumatic stress.

Aberrations to metacognition-the ability to reflect on and evaluate self-performance-are a feature of poor mental health. Theoretical models of post-traumatic stress disorder propose that following severe stress or trauma, maladaptive metacognitive evaluations and appraisals of the event drive the development of symptoms. Empirical research is required in order to reveal whether disruptions to metacognition cause or contribute to symptom development in line with theoretical accounts, or are simply a consequence of ongoing psychopathology. In two experiments, using hierarchical Bayesian modelling of metacognition measured in a memory recognition task, we assessed whether distortions to metacognition occur at a state-level after an acute stress induction, and/or at a trait-level in a sample of individuals experiencing intrusive memories following traumatic stress. Results from experiment 1, an in-person laboratory-based experiment, demonstrated that heightened psychological responses to the stress induction were associated with poorer metacognitive efficiency, despite there being no overall change in metacognitive efficiency from pre- to post-stress (N = 27). Conversely, in experiment 2, an online experiment using the same metamemory task, we did not find evidence of metacognitive alterations in a transdiagnostic sample of patients with intrusive memory symptomatology following traumatic stress (N = 36, compared to 44 matched controls). Our results indicate a relationship between state-level psychological responses to stress and metacognitive alterations. The lack of evidence for pre- to post-stress differences in metamemory illustrates the importance for future studies to reveal the direction of this relationship, and consequently the duration of stress-associated metacognitive impairments and their impact on mental health.

A core component of psychological therapy causes adaptive changes in computational learning mechanisms.

BACKGROUND: Cognitive distancing is an emotion regulation strategy commonly used in psychological treatment of various mental health disorders, but its therapeutic mechanisms are unknown. METHODS: 935 participants completed an online reinforcement learning task involving choices between pairs of symbols with differing reward contingencies. Half (49.1%) of the sample was randomised to a cognitive self-distancing intervention and were trained to regulate or 'take a step back' from their emotional response to feedback throughout. Established computational (Q-learning) models were then fit to individuals' choices to derive reinforcement learning parameters capturing clarity of choice values (inverse temperature) and their sensitivity to positive and negative feedback (learning rates). RESULTS: Cognitive distancing improved task performance, including when participants were later tested on novel combinations of symbols without feedback. Group differences in computational model-derived parameters revealed that cognitive distancing resulted in clearer representations of option values (estimated 0.17 higher inverse temperatures). Simultaneously, distancing caused increased sensitivity to negative feedback (estimated 19% higher loss learning rates). Exploratory analyses suggested this resulted from an evolving shift in strategy by distanced participants: initially, choices were more determined by expected value differences between symbols, but as the task progressed, they became more sensitive to negative feedback, with evidence for a difference strongest by the end of training. CONCLUSIONS: Adaptive effects on the computations that underlie learning from reward and loss may explain the therapeutic benefits of cognitive distancing. Over time and with practice, cognitive distancing may improve symptoms of mental health disorders by promoting more effective engagement with negative information.

A transdiagnostic meta-analysis of acute augmentations to psychological therapy.

At least half of all patients with mental health disorders do not respond adequately to psychological therapy. Acutely enhancing particular biological or psychological processes during psychological therapy may improve treatment outcomes. However, previous studies are confined to specific augmentation approaches, typically assessed within single diagnostic categories. Our objective was to assess to what degree acute augmentations of psychological therapy reduce psychiatric symptoms and estimate effect sizes of augmentation types (for example, brain stimulation or psychedelics). We searched Medline, PsycINFO and Embase for controlled studies published between database inception and 25 May 2022. We conducted a preregistered random-effects meta-analysis (PROSPERO CRD42021236403). We identified 108 studies (N = 5,889). Acute augmentation significantly reduced the severity of mental health problems (Hedges' g = -0.27, 95% CI: [-0.36, -0.18]; P < 0.0001), particularly for the transdiagnostic dimensions 'Fear' and 'Distress'. This result survived a trim-and-fill analysis to account for publication bias. Subgroup analyses revealed that pharmacological, psychological and somatic augmentations were effective, but to varying degrees. Acute augmentation approaches are a promising route to improve outcomes from psychological therapy.

Statistical power for cluster analysis.

BACKGROUND: Cluster algorithms are gaining in popularity in biomedical research due to their compelling ability to identify discrete subgroups in data, and their increasing accessibility in mainstream software. While guidelines exist for algorithm selection and outcome evaluation, there are no firmly established ways of computing a priori statistical power for cluster analysis. Here, we estimated power and classification accuracy for common analysis pipelines through simulation. We systematically varied subgroup size, number, separation (effect size), and covariance structure. We then subjected generated datasets to dimensionality reduction approaches (none, multi-dimensional scaling, or uniform manifold approximation and projection) and cluster algorithms (k-means, agglomerative hierarchical clustering with Ward or average linkage and Euclidean or cosine distance, HDBSCAN). Finally, we directly compared the statistical power of discrete (k-means), "fuzzy" (c-means), and finite mixture modelling approaches (which include latent class analysis and latent profile analysis). RESULTS: We found that clustering outcomes were driven by large effect sizes or the accumulation of many smaller effects across features, and were mostly unaffected by differences in covariance structure. Sufficient statistical power was achieved with relatively small samples (N = 20 per subgroup), provided cluster separation is large (Δ = 4). Finally, we demonstrated that fuzzy clustering can provide a more parsimonious and powerful alternative for identifying separable multivariate normal distributions, particularly those with slightly lower centroid separation (Δ = 3). CONCLUSIONS: Traditional intuitions about statistical power only partially apply to cluster analysis: increasing the number of participants above a sufficient sample size did not improve power, but effect size was crucial. Notably, for the popular dimensionality reduction and clustering algorithms tested here, power was only satisfactory for relatively large effect sizes (clear separation between subgroups). Fuzzy clustering provided higher power in multivariate normal distributions. Overall, we recommend that researchers (1) only apply cluster analysis when large subgroup separation is expected, (2) aim for sample sizes of N = 20 to N = 30 per expected subgroup, (3) use multi-dimensional scaling to improve cluster separation, and (4) use fuzzy clustering or mixture modelling approaches that are more powerful and more parsimonious with partially overlapping multivariate normal distributions.

Interoceptive pathways to understand and treat mental health conditions.

An increasing recognition that brain and body are dynamically coupled has enriched our scientific understanding of mental health conditions. Peripheral signals interact centrally to influence how we think and feel, generating our sense of the internal condition of the body, a process known as interoception. Disruptions to this interoceptive system may contribute to clinical conditions, including anxiety, depression, and psychosis. After reviewing the nature of interoceptive disturbances in mental health conditions, this review focuses on interoceptive pathways of existing and putative mental health treatments. Emerging clinical interventions may target novel peripheral treatment mechanisms. Future treatment development requires forward- and back-translation to uncover and target specific interoceptive processes in mental health to elucidate their efficacy relative to interventions targeting other factors.

Disrupted Dorsal Mid-Insula Activation During Interoception Across Psychiatric Disorders.

OBJECTIVE: Maintenance of bodily homeostasis relies on interoceptive mechanisms in the brain to predict and regulate bodily state. While altered neural activation during interoception in specific psychiatric disorders has been reported in many studies, it is unclear whether a common neural locus underpins transdiagnostic interoceptive differences. METHODS: The authors conducted a meta-analysis of neuroimaging studies comparing patients with psychiatric disorders with healthy control subjects to identify brain regions exhibiting convergent disrupted activation during interoception. Bibliographic, neuroimaging, and preprint databases through May 2020 were searched. A total of 306 foci from 33 studies were extracted, which included 610 control subjects and 626 patients with schizophrenia, bipolar or unipolar depression, posttraumatic stress disorder, anxiety, eating disorders, or substance use disorders. Data were pooled using a random-effects model implemented by the activation likelihood estimation algorithm. The preregistered primary outcome was the neuroanatomical location of the convergence of peak voxel coordinates. RESULTS: Convergent disrupted activation specific to the left dorsal mid-insula was found (Z=4.47, peak coordinates: -36, -2, 14; volume: 928 mm3). Studies directly contributing to the cluster included patients with bipolar disorder, anxiety, major depression, anorexia, and schizophrenia, assessed with task probes including pain, hunger, and interoceptive attention. A series of conjunction analyses against extant meta-analytic data sets revealed that this mid-insula cluster was anatomically distinct from brain regions involved in affective processing and from regions altered by psychological or pharmacological interventions for affective disorders. CONCLUSIONS: These results reveal transdiagnostic, domain-general differences in interoceptive processing in the left dorsal mid-insula. Disrupted mid-insular activation may represent a neural marker of psychopathology and a putative target for novel interventions.

Avoiding monetary loss: A human habenula functional MRI ultra-high field study.

A number of convergent human neuroimaging and animal studies suggest that habenula neurons fire in anticipation of non-rewarding outcomes, and suppress their firing in anticipation of rewarding outcomes. This normative function of the habenula appears disrupted in depression, and may be critical to the anti-depressant effects of ketamine. However, studying habenula functionality in humans using standard 3 T MRI is inherently limited by its small size. We employed ultra-high field (7 T) fMRI to investigate habenular activity in eighteen healthy volunteers during a Monetary Incentive Delay Task, focussing on loss avoidance, monetary loss and neutral events. We assessed neural activation in the field of view (FOV) in addition to ROI-based habenula-specific activity and generalized task-dependent functional connectivity. Whole FOV results indicated substantial neural differences between monetary loss and neutral outcomes, as well as between loss avoidance and neutral outcomes. Habenula-specific analyses showed bilateral deactivation during loss avoidance, compared to other outcomes. This first investigation into the habenula's role during loss avoidance revealed that the left habenula further differentiated between loss avoidance and monetary loss. Functional connectivity between the right habenula and the ipsilateral hippocampus and subcallosal cingulate (regions implicated in memory and depression pathophysiology) was enhanced when anticipating potential losses compared to anticipating neutral outcomes. Our findings suggest that the human habenula responds most strongly to outcomes of loss avoidance when compared to neutral and monetary losses, suggesting a role for the habenula in both reward and aversive processing. This has critical relevance to understanding the pathophysiology of habenula function in mood and other neuropsychiatric disorders, as well as the mechanism of action of habenula-targeting antidepressants such as ketamine.

Predicting Response to Brain Stimulation in Depression: a Roadmap for Biomarker Discovery.

PURPOSE OF REVIEW: Clinical response to brain stimulation treatments for depression is highly variable. A major challenge for the field is predicting an individual patient's likelihood of response. This review synthesises recent developments in neural predictors of response to targeted brain stimulation in depression. It then proposes a framework to evaluate the clinical potential of putative 'biomarkers'. RECENT FINDINGS: Largely, developments in identifying putative predictors emerge from two approaches: data-driven, including machine learning algorithms applied to resting state or structural neuroimaging data, and theory-driven, including task-based neuroimaging. Theory-driven approaches can also yield mechanistic insight into the cognitive processes altered by the intervention. SUMMARY: A pragmatic framework for discovery and testing of biomarkers of brain stimulation response in depression is proposed, involving (1) identification of a cognitive-neural phenotype; (2) confirming its validity as putative biomarker, including out-of-sample replicability and within-subject reliability; (3) establishing the association between this phenotype and treatment response and/or its modifiability with particular brain stimulation interventions via an early-phase randomised controlled trial RCT; and (4) multi-site RCTs of one or more treatment types measuring the generalisability of the biomarker and confirming the superiority of biomarker-selected patients over randomly allocated groups.

Neural effects of antidepressant medication and psychological treatments: a quantitative synthesis across three meta-analyses.

BACKGROUND: Influential theories predict that antidepressant medication and psychological therapies evoke distinct neural changes. AIMS: To test the convergence and divergence of antidepressant- and psychotherapy-evoked neural changes, and their overlap with the brain's affect network. METHOD: We employed a quantitative synthesis of three meta-analyses (n = 4206). First, we assessed the common and distinct neural changes evoked by antidepressant medication and psychotherapy, by contrasting two comparable meta-analyses reporting the neural effects of these treatments. Both meta-analyses included patients with affective disorders, including major depressive disorder, generalised anxiety disorder and panic disorder. The majority were assessed using negative-valence tasks during neuroimaging. Next, we assessed whether the neural changes evoked by antidepressants and psychotherapy overlapped with the brain's affect network, using data from a third meta-analysis of affect-based neural activation. RESULTS: Neural changes from psychotherapy and antidepressant medication did not significantly converge on any region. Antidepressants evoked neural changes in the amygdala, whereas psychotherapy evoked anatomically distinct changes in the medial prefrontal cortex. Both psychotherapy- and antidepressant-related changes separately converged on regions of the affect network. CONCLUSIONS: This supports the notion of treatment-specific brain effects of antidepressants and psychotherapy. Both treatments induce changes in the affect network, but our results suggest that their effects on affect processing occur via distinct proximal neurocognitive mechanisms of action.

The Computational, Pharmacological, and Physiological Determinants of Sensory Learning under Uncertainty.

The ability to represent and respond to uncertainty is fundamental to human cognition and decision-making. Noradrenaline (NA) is hypothesized to play a key role in coordinating the sensory, learning, and physiological states necessary to adapt to a changing world, but direct evidence for this is lacking in humans. Here, we tested the effects of attenuating noradrenergic neurotransmission on learning under uncertainty. We probed the effects of the ß-adrenergic receptor antagonist propranolol (40 mg) using a between-subjects, double-blind, placebo-controlled design. Participants performed a probabilistic associative learning task, and we employed a hierarchical learning model to formally quantify prediction errors about cue-outcome contingencies and changes in these associations over time (volatility). Both unexpectedness and noise slowed down reaction times, but propranolol augmented the interaction between these main effects such that behavior was influenced more by prior expectations when uncertainty was high. Computationally, this was driven by a reduction in learning rates, with people slower to update their beliefs in the face of new information. Attenuating the global effects of NA also eliminated the phasic effects of prediction error and volatility on pupil size, consistent with slower belief updating. Finally, estimates of environmental volatility were predicted by baseline cardiac measures in all participants. Our results demonstrate that NA underpins behavioral and computational responses to uncertainty. These findings have important implications for understanding the impact of uncertainty on human biology and cognition.

A Causal Role for Gastric Rhythm in Human Disgust Avoidance.

Rotten food, maggots, bodily waste-all elicit disgust in humans. Disgust promotes survival by encouraging avoidance of disease vectors1 but is also implicated in prejudice toward minority groups; avoidance of environmentally beneficial foods, such as insect protein; and maladaptive avoidance behavior in neuropsychiatric conditions.2-5 Unlike fear, pathological disgust is not improved substantially by exposure therapy clinically,6 nor in experimental work does behavioral avoidance of disgusting images habituate following prolonged exposure.7,8 Under normal physiological conditions, perception of disgusting stimuli disrupts myoelectrical rhythms in the stomach,9-13 inducing gastric dysrhythmias that correlate with neural signatures of disgust.11 However, the causal role of gastric rhythm in disgust avoidance is unknown. We manipulated gastric rhythm using domperidone, a peripheral dopamine D2/D3 antagonist and common anti-emetic, at a dose (10 mg) that acts to convert gastric dysrhythmias to normal rhythms.9 In a preregistered, randomized, double-blind, placebo-controlled crossover design in 25 healthy volunteers (aged 18-25), we measured the effects of domperidone on core disgust avoidance, using eye tracking to measure implicit (oculomotor) avoidance of disgusting images (feces) before and after an "exposure" intervention (monetary reinforcement for looking at disgusting images).7,8 We find that domperidone significantly reduces oculomotor disgust avoidance following incentivized exposure. This suggests that domperidone may weaken the "immunity" of disgust to habituation, putatively by reducing gastric dysrhythmias during incentivized engagement with disgusting stimuli. This indicates a causal role for disgust-related visceral changes in disgust avoidance, supporting the hypothesis that physiological homeostasis contributes to emotional experience.

The neurochemical substrates of habitual and goal-directed control.

Our daily decisions are governed by the arbitration between goal-directed and habitual strategies. However, the neurochemical basis of this arbitration is unclear. We assessed the contribution of dopaminergic, serotonergic, and opioidergic systems to this balance across reward and loss domains. Thirty-nine participants (17 healthy controls, 15 patients with pathological gambling, and 7 with binge eating disorder) underwent positron emission tomography (PET) imaging with [18F]FDOPA, [11C]MADAM and [11C]carfentanil to assess presynaptic dopamine, and serotonin transporter and mu-opioid receptor binding potential. Separately, participants completed a modified two-step task, which quantifies the degree to which decision-making is influenced by goal-directed or habitual strategies. All participants completed a version with reward outcomes; healthy controls additionally completed a version with loss outcomes. In the context of rewarding outcomes, we found that greater serotonin transporter binding potential in prefrontal regions was associated with habitual control, while greater serotonin transporter binding potential in the putamen was marginally associated with goal-directed control; however, the findings were no longer significant when controlling for the opposing valence (loss). In blocks with loss outcomes, we found that the opioidergic system, specifically greater [11C]carfentanil binding potential, was positively associated with goal-directed control and negatively associated with habit-directed control. Our findings illuminate the complex neurochemical basis of goal-directed and habitual behavior, implicating differential roles for prefrontal and subcortical serotonin in decision-making across healthy and pathological populations.

Neural predictors of treatment response to brain stimulation and psychological therapy in depression: a double-blind randomized controlled trial.

Standard depression treatments, including antidepressant medication and cognitive behavioural therapy (CBT), are ineffective for many patients. Prefrontal transcranial direct current stimulation (tDCS) has been proposed as an alternative treatment, but has shown inconsistent efficacy for depression, and its mechanisms are poorly understood. We recruited unmedicated patients with major depressive disorder (N = 71 approached; N = 39 randomised) for a mechanistic, double-blind, randomized controlled trial consisting of eight weekly sessions of prefrontal tDCS administered to the left prefrontal cortex prior to CBT. We probed (1) whether tDCS improved the efficacy of CBT relative to sham stimulation; and (2) whether neural measures predicted clinical response. We found a modest and non-significant effect of tDCS on clinical outcome over and above CBT (active: 50%; sham: 31.6%; odds ratio: 2.16, 95% CI = 0.59-7.99), but a strong relationship, predicted a priori, between baseline activation during a working memory task in the stimulated prefrontal region and symptom improvement. Repeating our analyses of symptom outcome splitting the sample according to this biomarker revealed that tDCS was significantly superior to sham in individuals with high left prefrontal cortex activation at baseline; we also show 86% accuracy in predicting clinical response using this measure. Exploratory analyses revealed several other regions where activation at baseline was associated with subsequent response to CBT, irrespective of tDCS. This mechanistic trial revealed variable, but predictable, clinical effects of prefrontal tDCS combined with CBT for depression. We have discovered a potential explanation for this variability: individual differences in baseline activation of the region stimulated. Such a biomarker could potentially be used to pre-select patients for trials and, eventually, in the clinic.

The effect of frontoparietal paired associative stimulation on decision-making and working memory.

Previous single-site neurostimulation experiments have unsuccessfully attempted to shift decision-making away from habitual control, a fast, inflexible cognitive strategy, towards goal-directed control, a flexible, though computationally expensive strategy. We employed a dual-target neurostimulation approach in 30 healthy participants, using cortico-cortical paired associative stimulation (ccPAS) to target two key nodes: lateral prefrontal cortex (LPFC) and intraparietal sulcus (IPS), to test whether decision-making can be artificially shifted from habitual toward goal-directed control. Participants received three active stimulations, delivered at least six days apart (each involving 100 paired pulses over the IPS and LPFC, varying the interstimulus interval): two interventional, time-relevant ccPAS (10 msec interval) and one control, non-time-relevant ccPAS (100 msec interval). Following stimulation, participants completed a sequential learning task, measuring goal-directed/habitual control, and a working memory task. IPS→LPFC ccPAS (stimulating IPS, then LPFC with a 10 msec interval) shifted decision-making from habitual toward goal-directed control, compared to control ccPAS. There was no effect of LPFC→IPS ccPAS, nor an effect of any PAS condition on working memory. Previous studies have shown ccPAS effects outside the motor domain targeting prefrontal regions on response inhibition, attentional bias, and alpha asymmetry. The present study measures the behavioural effects of parietal-prefrontal PAS, focusing on a highly complex decision-making task and working memory. If confirmed in larger studies, this would be the first instance of neurostimulation successfully shifting decision-making from habitual to goal-directed control, putatively via inducing long-term potentiation between the IPS and LPFC. However, we found no effect in the other direction (LPFC→IPS ccPAS), and no effect on working memory overall. PAS is a relatively new neuromodulatory technique in the cognitive arsenal, and this study could help guide future approaches in healthy and disordered decision-making.

Reliability of Fronto-Amygdala Coupling during Emotional Face Processing.

One of the most exciting translational prospects for brain imaging research is the potential use of functional magnetic resonance imaging (fMRI) 'biomarkers' to predict an individual's risk of developing a neuropsychiatric disorder or the likelihood of responding to a particular intervention. This proposal depends critically on reliable measurements at the level of the individual. Several previous studies have reported relatively poor reliability of amygdala activation during emotional face processing, a key putative fMRI 'biomarker'. However, the reliability of amygdala connectivity measures is much less well understood. Here, we assessed the reliability of task-modulated coupling between three seed regions (left and right amygdala and the subgenual anterior cingulate cortex) and the dorsomedial frontal/cingulate cortex (DMFC), measured using a psychophysiological interaction analysis in 29 healthy individuals scanned approximately two weeks apart. We performed two runs on each day of three different emotional face-processing tasks: emotion identification, emotion matching, and gender classification. We tested both between-day reliability and within-day (between-run) reliability. We found good-to-excellent within-subject reliability of amygdala-DMFC coupling, both between days (in two tasks), and within day (in one task). This suggests that disorder-relevant regional coupling may be sufficiently reliable to be used as a predictor of treatment response or clinical risk in future clinical studies.

The myeloarchitecture of impulsivity: premature responding in youth is associated with decreased myelination of ventral putamen.

Impulsivity has been suggested as a neurocognitive endophenotype conferring risk across a number of neuropsychiatric conditions, including substance and behavioural addictions, eating disorders, and attention deficit/hyperactivity disorder. We used a paradigm with interspecies translation validity (the four-choice serial reaction time task, 4CSRTT) to assess 'waiting' impulsivity in a youth sample (N = 99, aged 16-26 years). We collected magnetization prepared two rapid acquisition gradient echo (MP2RAGE) scans, which enabled us to measure R1, the longitudinal relaxation rate, a parameter closely related to tissue myelin content, as well as quantify grey matter volume. We also assessed inhibitory control (commission errors) on a Go/NoGo task and measured decisional impulsivity (delay discounting) using the Monetary Choice Questionnaire (MCQ). We found R1 of the bilateral ventral putamen was negatively correlated with premature responding, the index of waiting impulsivity on the 4CSRTT. Heightened impulsivity in youth was significantly and specifically associated with lower levels of myelination in the ventral putamen. Impulsivity was not associated with grey matter volume. The association with myelination was specific to waiting impulsivity: R1 was not associated with decisional impulsivity on the MCQ or inhibitory control on the Go/NoGo task. We report that heightened waiting impulsivity, measured as premature responding on the 4CSRTT, is specifically associated with lower levels of ventral putaminal myelination, measured using R1. This may represent a neural signature of vulnerability to diseases associated with excessive impulsivity and demonstrates the added explanatory power of quantifying the mesoscopic organization of the human brain, over and above macroscopic volumetric measurements.

Cortical Paired Associative Stimulation Influences Response Inhibition: Cortico-cortical and Cortico-subcortical Networks.

BACKGROUND: The ability to stop a suboptimal response is integral to decision making and is commonly impaired across psychiatric disorders. Cortical paired associative stimulation (cPAS) is a form of transcranial magnetic stimulation in which paired pulses can induce plasticity at cortical synapses. Here we used cPAS protocols to target cortico-cortical and cortico-subcortical networks by using different intervals between the paired pulses in an attempt to modify response inhibition. METHODS: A total of 25 healthy volunteers underwent four cPAS sessions in random order 1 week apart: right inferior frontal cortex (IFC) stimulation preceding right presupplementary motor area (pre-SMA) stimulation by 10 or 4 ms and pre-SMA stimulation preceding IFC stimulation by 10 or 4 ms. Subjects were tested on the stop signal task along with the delay discounting task as control at baseline (randomized across sessions and cPAS protocol) and after each cPAS session. RESULTS: The stop signal reaction time showed a main effect of cPAS condition when controlling for age (F3,57 = 4.05, p = .01). Younger subjects had greater impairments in response inhibition when the pre-SMA pulse preceded the IFC pulse by 10 ms. In older individuals, response inhibition improved when the IFC pulse preceded the pre-SMA pulse by 4 ms. There were no effects on delay discounting. CONCLUSIONS: cPAS modified response inhibition through age-dependent long-term potentiation and depression-like plasticity mechanisms via putative cortico-cortical and cortico-subcortical networks. We show for the first time the capacity for cPAS to modify a cognitive process highly relevant to psychiatric disorders.

Power-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling.

Recently, evidence for endemically low statistical power has cast neuroscience findings into doubt. If low statistical power plagues neuroscience, then this reduces confidence in the reported effects. However, if statistical power is not uniformly low, then such blanket mistrust might not be warranted. Here, we provide a different perspective on this issue, analyzing data from an influential study reporting a median power of 21% across 49 meta-analyses (Button et al., 2013). We demonstrate, using Gaussian mixture modeling, that the sample of 730 studies included in that analysis comprises several subcomponents so the use of a single summary statistic is insufficient to characterize the nature of the distribution. We find that statistical power is extremely low for studies included in meta-analyses that reported a null result and that it varies substantially across subfields of neuroscience, with particularly low power in candidate gene association studies. Therefore, whereas power in neuroscience remains a critical issue, the notion that studies are systematically underpowered is not the full story: low power is far from a universal problem.SIGNIFICANCE STATEMENT Recently, researchers across the biomedical and psychological sciences have become concerned with the reliability of results. One marker for reliability is statistical power: the probability of finding a statistically significant result given that the effect exists. Previous evidence suggests that statistical power is low across the field of neuroscience. Our results present a more comprehensive picture of statistical power in neuroscience: on average, studies are indeed underpowered-some very seriously so-but many studies show acceptable or even exemplary statistical power. We show that this heterogeneity in statistical power is common across most subfields in neuroscience. This new, more nuanced picture of statistical power in neuroscience could affect not only scientific understanding, but potentially policy and funding decisions for neuroscience research.

Vigour in active avoidance.

It would be maladaptive to learn about catastrophes by trial and error alone. Investment in planning and effort are necessary. Devoting too many resources to averting disaster, however, can impair quality of life, as in anxiety and paranoia. Here, we developed a novel task to explore how people adjust effort expenditure (vigor) so as to avoid negative consequences. Our novel paradigm is immersive, enabling us to measure vigor in the context of (simulated) disaster. We found that participants (N = 118) exerted effort to avoid disaster-associated states, adjusting their effort expenditure according to the baseline probability of catastrophe, in agreement with theoretical predictions. Furthermore, negative subjective emotional states were associated both with threat level and with increasing vigor in the face of disaster. We describe for the first time effort expenditure in the context of irreversible losses, with important implications for disorders marked by excessive avoidance.

Prefrontal cortex stimulation does not affect emotional bias, but may slow emotion identification.

Transcranial direct current stimulation (tDCS) has recently garnered attention as a putative depression treatment. However, the cognitive mechanisms by which it exerts an antidepressant effect are unclear: tDCS may directly alter 'hot' emotional processing biases, or alleviate depression through changes in 'cold' (non-emotional) cognitive function. Here, 75 healthy participants performed a facial emotion identification task during 20 minutes of anodal or sham tDCS over the left dorsolateral prefrontal cortex (DLPFC) in a double-blind, within-subject crossover design. A subset of 31 participants additionally completed a task measuring attentional distraction during stimulation. Compared to sham stimulation, anodal tDCS of the left DLPFC resulted in an increase in response latency across all emotional conditions. Bayesian analysis showed definitively that tDCS exerted no emotion-dependent effect on behaviour. Thus, we demonstrate that anodal tDCS produces a general, rather than an emotion-specific, effect. We also report a preliminary finding in the subset of participants who completed the distractibility task: increased distractibility during active stimulation correlated significantly with the degree to which tDCS slowed emotion identification. Our results provide insight into the possible mechanisms by which DLPFC tDCS may treat symptoms of depression, suggesting that it may not alter emotional biases, but instead may affect 'cold' cognitive processes.