1,042 research outputs found

    Information processing in mood disorders

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

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    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

    Assessing the Construct Validity of Aberrant Salience

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    We sought to validate the psychometric properties of a recently developed paradigm that aims to measure salience attribution processes proposed to contribute to positive psychotic symptoms, the Salience Attribution Test (SAT). The “aberrant salience” measure from the SAT showed good face validity in previous results, with elevated scores both in high-schizotypy individuals, and in patients with schizophrenia suffering from delusions. Exploring the construct validity of salience attribution variables derived from the SAT is important, since other factors, including latent inhibition/learned irrelevance (LIrr), attention, probabilistic reward learning, sensitivity to probability, general cognitive ability and working memory could influence these measures. Fifty healthy participants completed schizotypy scales, the SAT, a LIrr task, and a number of other cognitive tasks tapping into potentially confounding processes. Behavioural measures of interest from each task were entered into a principal components analysis, which yielded a five-factor structure accounting for ∼75% of the variance in behaviour. Implicit aberrant salience was found to load onto its own factor, which was associated with elevated “Introvertive Anhedonia” schizotypy, replicating our previous finding. LIrr loaded onto a separate factor, which also included implicit adaptive salience, but was not associated with schizotypy. Explicit adaptive and aberrant salience, along with a measure of probabilistic learning, loaded onto a further factor, though this also did not correlate with schizotypy. These results suggest that the measures of LIrr and implicit adaptive salience might be based on similar underlying processes, which are dissociable both from implicit aberrant salience and explicit measures of salience

    fMRI in Translation: The Challenges Facing Real-World Applications

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    Functional neuroimaging has increased our understanding of human brain function tremendously and has become a standard tool in clinical and cognitive neuroscience research. We briefly review its methodological foundations and describe remaining challenges for translational research. The application of neuroimaging results to individual subjects, for example in predicting treatment response or determining the veracity of a statement, is limited by these challenges, in particular by the anatomical and statistical procedures commonly employed. We thus argue for sincere caution in the translation of functional neuroimaging to real-world applications

    Antidepressant medications in dementia: evidence and potential mechanisms of treatment-resistance

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    Depression in dementia is common, disabling and causes significant distress to patients and carers. Despite widespread use of antidepressants for depression in dementia, there is no evidence of therapeutic efficacy, and their use is potentially harmful in this patient group. Depression in dementia has poor outcomes and effective treatments are urgently needed. Understanding why antidepressants are ineffective in depression in dementia could provide insight into their mechanism of action and aid identification of new therapeutic targets. In this review we discuss why depression in dementia may be a distinct entity, current theories of how antidepressants work and how these mechanisms of action may be affected by disease processes in dementia. We also consider why clinicians continue to prescribe antidepressants in dementia, and novel approaches to understand and identify effective treatments for patients living with depression and dementia

    Measuring cognitive effort without difficulty

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    An important finding in the cognitive effort literature has been that sensitivity to the costs of effort varies between individuals, suggesting that some people find effort more aversive than others. It has been suggested this may explain individual differences in other aspects of cognition; in particular that greater effort sensitivity may underlie some of the symptoms of conditions such as depression and schizophrenia. In this paper, we highlight a major problem with existing measures of cognitive effort that hampers this line of research, specifically the confounding of effort and difficulty. This means that behaviour thought to reveal effort costs could equally be explained by cognitive capacity, which influences the frequency of success and thereby the chance of obtaining reward. To address this shortcoming, we introduce a new test, the Number Switching Task (NST), specially designed such that difficulty will be unaffected by the effort manipulation and can easily be standardised across participants. In a large, online sample, we show that these criteria are met successfully and reproduce classic effort discounting results with the NST. We also demonstrate the use of Bayesian modelling with this task, producing behavioural parameters which can be associated with other measures, and report a preliminary association with the Need for Cognition scale

    Personally-valued voices engage reward-motivated behaviour and brain responses

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    Humans often attach notions of value to hearing the voices of specific loved ones, yet there is sparse scientific evidence supporting these claims. We present three experiments-two behavioural and one neuroimaging (functional magnetic resonance imaging: fMRI) - that tested whether personally-valued voices engage reward-motivated behaviour and associated brain responses. Using novel voice incentive delay (VID) tasks, we show that listeners respond faster in anticipation of hearing the speaking voice of their music idol than when anticipating an unfamiliar voice or a pure tone (Experiment 1). A second behavioural experiment indicated that familiarity alone was insufficient to engage stronger reward-motivated behaviour in comparison with an unfamiliar identity (Experiment 2). These behavioural patterns were further reflected in an fMRI experiment, where the idol voice condition most strongly engaged brain regions associated with reward processing while responses to other familiar and unfamiliar voice conditions were often equivalent (Experiment 3). Taken together, these studies provide evidence that voices can be effective rewards, in particular when they are associated with intense parasocial interest. Future research should determine whether these findings generalise to personally known individuals

    Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance

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    Although avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-related avoidance in the form of an approach-avoidance reinforcement learning task, by adapting a paradigm from the non-human animal literature to study the same cognitive processes in human participants. We used computational modelling to probe the putative cognitive mechanisms underlying approach-avoidance behaviour in this task and investigated how they relate to subjective task-induced anxiety. In a large online study (n = 372), participants who experienced greater task-induced anxiety avoided choices associated with punishment, even when this resulted in lower overall reward. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards. We replicated these findings in an independent sample (n = 627) and we also found fair-to-excellent reliability of measures of task performance in a sub-sample retested 1 week later (n = 57). Our findings demonstrate the potential of approach-avoidance reinforcement learning tasks as translational and computational models of anxiety-related avoidance. Future studies should assess the predictive validity of this approach in clinical samples and experimental manipulations of anxiety

    Correction: Measuring cognitive effort without difficulty

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    In vivo multi-parameter mapping of the habenula using MRI

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    The habenula is a small, epithalamic brain structure situated between the mediodorsal thalamus and the third ventricle. It plays an important role in the reward circuitry of the brain and is implicated in psychiatric conditions, such as depression. The importance of the habenula for human cognition and mental health make it a key structure of interest for neuroimaging studies. However, few studies have characterised the physical properties of the human habenula using magnetic resonance imaging because its challenging visualisation in vivo, primarily due to its subcortical location and small size. To date, microstructural characterization of the habenula has focused on quantitative susceptibility mapping. In this work, we complement this previous characterisation with measures of longitudinal and effective transverse relaxation rates, proton density and magnetisation transfer saturation using a high-resolution quantitative multi-parametric mapping protocol at 3T, in a cohort of 26 healthy participants. The habenula had consistent boundaries across the various parameter maps and was most clearly visualised on the longitudinal relaxation rate maps. We have provided a quantitative multi-parametric characterisation that may be useful for future sequence optimisation to enhance visualisation of the habenula, and additionally provides reference values for future studies investigating pathological differences in habenula microstructure
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