Selective serotonin reuptake inhibitors (SSRIs) are first-line pharmacological treatments for depression and anxiety. However, little is known about how pharmacological action is related to cognitive and affective processes. Here, we examine whether specific reinforcement learning processes mediate the treatment effects of SSRIs.

The PANDA trial was a multicentre, double-blind, randomized clinical trial in UK primary care comparing the SSRI sertraline with placebo for depression and anxiety. Participants (N = 655) performed an affective Go/NoGo task three times during the trial and computational models were used to infer reinforcement learning processes.

There was poor task performance: only 54% of the task runs were informative, with more informative task runs in the placebo than in the active group. There was no evidence for the preregistered hypothesis that Pavlovian inhibition was affected by sertraline. Exploratory analyses revealed that in the sertraline group, early increases in Pavlovian inhibition were associated with improvements in depression after 12 weeks. Furthermore, sertraline increased how fast participants learned from losses and faster learning from losses was associated with more severe generalized anxiety symptoms.

The study findings indicate a relationship between aversive reinforcement learning mechanisms and aspects of depression, anxiety, and SSRI treatment, but these relationships did not align with the initial hypotheses. Poor task performance limits the interpretability and likely generalizability of the findings, and highlights the critical importance of developing acceptable and reliable tasks for use in clinical studies.

This article presents research supported by NIHR Program Grants for Applied Research (RP-PG-0610-10048), the NIHR BRC, and UCL, with additional support from IMPRS COMP2PSYCH (JM, QH) and a Wellcome Trust grant (QH).

As part of the Research Domain Criteria (RDoC) initiative, the NIMH seeks to improve experimental measures of cognitive and positive valence systems for use in intervention research. However, many RDoC tasks have not been psychometrically evaluated as a battery of measures. Our aim was to examine the factor structure of 7 such tasks chosen for their relevance to schizophrenia and other forms of serious mental illness. These include the n-back, Sternberg, and self-ordered pointing tasks (measures of the RDoC cognitive systems working memory construct); flanker and continuous performance tasks (measures of the RDoC cognitive systems cognitive control construct); and probabilistic learning and effort expenditure for reward tasks (measures of reward learning and reward valuation constructs).

The sample comprised 286 cognitively healthy participants who completed novel versions of all 7 tasks via an online recruitment platform, Prolific, in the summer of 2022. The mean age of participants was 38.6 years (SD = 14.5, range 18-74), 52% identified as female, and stratified recruitment ensured an ethnoracially diverse sample. Excluding time for instructions and practice, each task lasted approximately 6 minutes. Task order was randomized. We estimated optimal scores from each task including signal detection d-prime measures for the n-back, Sternberg, and continuous performance task, mean accuracy for the flanker task, win-stay to win-shift ratio for the probabilistic learning task, and trials completed for the effort expenditure for reward task. We used parallel analysis and a scree plot to determine the number of latent factors measured by the 7 task scores. Exploratory factor analysis with oblimin (oblique) rotation was used to examine the factor loading matrix.

The scree plot and parallel analyses of the 7 task scores suggested three primary factors. The flanker and continuous performance task both strongly loaded onto the first factor, suggesting that these measures are strong indicators of cognitive control. The n-back, Sternberg, and self-ordered pointing tasks strongly loaded onto the second factor, suggesting that these measures are strong indicators of working memory. The probabilistic learning task solely loaded onto the third factor, suggesting that it is an independent indicator of reinforcement learning. Finally, the effort expenditure for reward task modestly loaded onto the second but not the first and third factors, suggesting that effort is most strongly related to working memory.

Our aim was to examine the factor structure of 7 RDoC tasks. Results support the RDoC suggestion of independent cognitive control, working memory, and reinforcement learning. However, effort is a factorially complex construct that is not uniquely or even most strongly related to positive valance. Thus, there is reason to believe that the use of at least 6 of these tasks are appropriate measures of constructs such as working memory, reinforcement learning and cognitive control.

Cognitive deficits in patients diagnosed with schizophrenia are a core feature of the disorder. There are currently no treatments for these cognitive deficits. Our aim was to examine and compare patterns of increased versus decreased activity in the central executive network (CEN), salience network (SN), and default mode network (DMN) between healthy controls (HCs) and patients diagnosed with schizophrenia (SZs) as well as to explore the influence of task load on these networks between HCs and SZs.

Analyses focused on a secondary dataset comprising Blood Oxygen-Level Dependent (BOLD) data collected from 25 HCs and 27 SZs who completed a working memory (WM) task (N-back) with 5 load conditions while undergoing functional magnetic resonance imaging (fMRI). Region of interest (ROI) data were analyzed using linear mixed-effects models.

Group activation differences were found in the posterior salience network (pSN), default mode network (DMN), dorsal default mode network (dDMN), and ventral default mode network (vDMN) showing greater activity for SZs. Specifically, pSN, DMN, dDMN, and vDMN all showed increased activity in SZs compared to HCs. The curve of brain activity was consistent between HCs and SZs with the exception of the vDMN, where HCs show greater activation at modest mental workload (quadratic curve) and SZs showed greater brain activation at lower mental workload (linear). In the CEN, there were no group differences, and the response curve was the same for both groups.

These group differences demonstrate network difference between HCs and SZs and could show value in treatments targeting cognitive deficits in SZs from a large-scale brain network connectivity perspective. Future studies are needed to confirm these results with larger sample size in order to examine potential subtleties of interactions between these networks.

Agricultural workers are immersed in environments associated with increased risk for adverse psychiatric and neurological outcomes. Agricultural work-related risks to brain health include exposure to pesticides, heavy metals, and organic dust. Despite this, there is a gap in our understanding of the underlying brain systems impacted by these risks. This study explores clinical and cognitive domains, and functional brain activity in agricultural workers. We hypothesized that a history of agricultural work-related risks would be associated with poorer clinical and cognitive outcomes as well as changes in functional brain activity within cortico-striatal regions.

The sample comprised 17 agricultural workers and a comparison group of 45 non-agricultural workers recruited in the Northern Colorado area. All participants identified as White and non-Hispanic. The mean age of participants was 51.7 years (SD = 21.4, range 18-77), 60% identified as female, and 37% identified as male. Participants completed the National Institute of Health Toolbox (NIH Toolbox) and Montreal Cognitive Assessment (MoCA) on their first visit. During the second visit, they completed NIH Patient-Reported Outcomes Measurement Information System (PROMIS) measures and underwent functional magnetic resonance imaging (fMRI; N = 15 agriculture and N = 35 non-agriculture) while completing a working memory task (Sternberg). Blood oxygen-level dependent (BOLD) response was compared between participants. Given the small sample size, the whole brain voxel-wise group comparison threshold was set at alpha = .05, but not otherwise corrected for multiple comparisons. Cohen’s d effect sizes were estimated for all voxels.

Analyses of cognitive scores showed significant deficits in episodic memory for the agricultural work group. Additionally, the agricultural work group scored higher on measures of self-reported anger, cognitive concerns, and social participation. Analyses of fMRI data showed increased BOLD activity around the orbitofrontal cortex (medium to large effects) and bilaterally in the entorhinal cortex (large effects) for the agricultural work group. The agricultural work group also showed decreased BOLD activity in the cerebellum and basal ganglia (medium to large effects).

To our knowledge, this study provides the first-ever evidence showing differences in brain activity associated with a history of working in agriculture. These findings of poorer memory, concerns about cognitive functioning, and increased anger suggest clinical relevance. Social participation associated with agricultural work should be explored as a potential protective factor for cognition and brain health. Brain imaging data analyses showed increased activation in areas associated with motor functioning, cognitive control, and emotion. These findings are limited by small sample size, lack of diversity in our sample, and coarsely defined risk. Despite these limitations, the results are consistent with an overall concern that risks associated with agricultural work can lead to cognitive and psychiatric harm via changes in brain health. Replications and future studies with larger sample sizes, more diverse participants, and more accurately defined risks (e.g., pesticide exposure) are needed.

Deficits in cognitive ability are common among patients with schizophrenia. The MATRICS Consensus Cognitive Battery (MCCB) was designed to assess cognitive ability in studies of patients diagnosed with schizophrenia and has demonstrated high test-retest reliability with minimal practice effects, even in multi-site trials. However, given the motivational challenges associated with schizophrenia, it is unknown whether performance on MCCB tasks affects performance at later stages of testing. The goal of this study was to determine whether there are differences between people with and without schizophrenia in how their performance on individual MCCB tasks influences their performance throughout the battery.

The sample comprised 92 total participants including 49 cognitively healthy comparison participants and 43 outpatients diagnosed with schizophrenia. The mean age of participants was 44.2 years (SD = 12.0, range 21–69) and 61% identified as male. The Trail Making Test, Brief Assessment of Cognition in Schizophrenia, Hopkins Verbal Learning Test – Revised, Letter-Number Span, and Category Fluency from the MCCB were administered in the same order at 2 different sites and studies from 2016–2022. The autocorrelation between t-scores for task scores within each participant was computed and then compared between control and outpatient participants to determine if there are differences between groups. Group mean t-scores for each task were also compared between groups.

We found no significant difference in autocorrelations across MCCB tasks between healthy comparison participants and outpatients. However, mean performance in all tasks was lower for the outpatient group than for the healthy comparison group. None of the tasks used stood out as having significantly lower mean scores than other tasks for either group.

Our findings suggest that performance on individual MCCB tasks do not affect performance throughout the battery differently between the healthy comparison group and outpatients. This suggests that participants with schizophrenia are not particularly reactive to past performance on MCCB tasks. Additionally, this finding further supports use of the MCCB in this population. Further research is needed to determine whether subgroups of patients and/or different batteries of measures show different patterns of reactivity.

This paper investigates whether age of onset of depression, duration of the last episode, number of episodes, and residual symptoms of depression and anxiety are associated with depression relapse in primary care patients who have been on long–term maintenance antidepressant treatment and no longer meet ICD10 criteria for depression.

An observational cohort using data from ANTLER (N = 478), a double-blind placebo-controlled trial. The primary outcome was time to relapse using the retrospective CIS-R. Participants were followed for 12 months.

Primary outcome was available for 468 participants. Time to relapse in those with more than five previous episodes of depression was shorter, hazard ratio (HR) 1.84 (95% confidence interval [CI] 1.23–2.75) compared to people with two episodes; HR 1.57 (95% CI 1.01–2.43) after adjustment. The residual symptoms of depression at baseline were also associated with increased relapse: HR 1.05 (95% CI 1.01–1.09) and HR 1.06 (95% CI 1.01–1.12) in the adjusted model. There was evidence of reduced rate of relapse in older age of onset group: HR 0.86 (95% CI 0.78–0.95); HR attenuated after adjustment HR 0.91 (95% CI 0.81–1.02). There was no evidence of an association between duration of the current episode and residual anxiety symptoms with relapse.

The number of previous episodes and residual symptoms of depression were associated with increased likelihood of relapse. These factors could inform joint decision making when patients are considering tapering off maintenance antidepressant treatment or considering other treatments to prevent relapse.

1. (1) To be able to apply Ehlers and Clark’s (2000) cognitive model to PTSD arising from bereavement trauma.

2. (2) To recognise how the core treatment components differ for PTSD associated with traumatic bereavement than for PTSD linked to trauma where there is no loss of life.

3. (3) To discover how to conduct imagery transformation for the memory updating procedure in CT-PTSD for loss trauma.

Antidepressants have been proposed to act via their influence on emotional processing. We investigated the effect of discontinuing maintenance antidepressant treatment on positive and negative self-referential recall and the association between self-referential recall and risk of relapse.

The ANTLER trial was a large (N = 478) pragmatic double-blind trial investigating the clinical effectiveness of long-term antidepressant treatment for preventing relapse in primary care patients. Participants were randomised to continue their maintenance antidepressants or discontinue via a taper to placebo. We analysed memory for positive and negative personality descriptors, assessed at baseline, 12- and 52-week follow-up.

The recall task was completed by 437 participants. There was no evidence of an effect of discontinuation on self-referential recall at 12 [positive recall ratio 1.00, 95% CI (0.90–1.11), p = 0.93; negative recall ratio 1.00 (0.87–1.14), p = 0.87] or 52 weeks [positive recall ratio 1.03 (0.91–1.17), p = 0.62; negative recall ratio 1.00 (0.86–1.15), p = 0.96; ratios larger than one indicate higher recall in the discontinuation group], and no evidence of an association between recall at baseline or 12 weeks and later relapse [baseline, positive hazard ratio (HR) 1.02 (0.93–1.12), p = 0.74; negative HR 1.01 (0.90–1.13), p = 0.87; 12 weeks, positive HR 0.99 (0.89–1.09), p = 0.81; negative HR 0.98 (0.84–1.14), p = 0.78; ratios larger than one indicate a higher frequency of relapse in those with higher recall].

We found no evidence that discontinuing long-term antidepressants altered self-referential recall or that self-referential recall was associated with risk of relapse. These findings suggest that self-referential recall is not a neuropsychological marker of antidepressant action.