Functional neuroanatomy of action selection in schizophrenia

Schizophrenia remains an enigmatic disorder with unclear neuropathology. Recent advances in neuroimaging and genetic research suggest alterations in glutamate-dopamine interactions adversely affecting synaptic plasticity both intracortically and subcortically. Relating these changes to the manifestation of symptoms presents a great challenge, requiring a constrained framework to capture the most salient elements. Here, a biologically-grounded computational model of basal ganglia-mediated action selection was used to explore two pathological processes that hypothetically underpin schizophrenia. These were a drop in the efficiency of cortical transmission, reducing both the signal-to-noise ratio (SNR) and overall activity levels; and an excessive compensatory upregulation of subcortical dopamine release. It was proposed that reduced cortical efficiency was the primary process, which led to a secondary disinhibition of subcortical dopamine release within the striatum. This compensation was believed to partly recover lost function, but could then induce disorganised-type symptoms - summarised as selection ”Instability” - if it became too pronounced. This overcompensation was argued to be countered by antipsychotic medication. The model’s validity was tested during an fMRI (functional magnetic resonance imaging) study of 16 healthy volunteers, using a novel perceptual decision-making task, and was found to provide a good account for pallidal activation. Its account for striatum was developed and improved with a small number of principled model modifications: the inclusion of fast spiking interneurons within striatum, and their inhibition by the basal ganglia’s key regulatory nucleus, external globus pallidus. A key final addition was the explicit modelling of dopaminergic midbrain, which is dynamically regulated by both cortex and the basal ganglia. This enabled hypotheses concerning the effects of cortical inefficiency, compensatory dopamine release and medication to be directly tested. The new model was verified with a second set of 12 healthy controls. Its pathological predictions were compared to data from 12 patients with schizophrenia. Model simulations suggested that Instability went hand-in-hand with cortical inefficiency and secondary dopamine upregulation. Patients with high Instability scores showed a loss of SNR within decision-related cortex (consistent with cortical inefficiency); an exaggerated response to task demands within substantia nigra (consistent with dopaminergic upregulation); and had an improved fit to simulated data derived from increasingly cortically-inefficient models. Simulations representing the healthy state provided a good account for patients’ motor putamen, but only cortically-inefficient simulations representing the ill state provided a fit for ventral-anterior striatum. This fit improved as the simulated model became more medicated (increased D2 receptor blockade). The relative improvement of this account correlated with patients’ medication dosage. In summary, by distilling the hypothetical neuropathology of schizophrenia into two simplified umbrella processes, and using a computational model to consider their effects within action selection, this work has successfully related patients’ fMRI activation to particular symptomatology and antipsychotic medication. This approach has the potential to improve patient care by enabling a neurobiological appreciation of their current illness state, and tailoring their medication level appropriately

Impairment in acquisition of conditioned fear in schizophrenia

Individuals with schizophrenia show impairments in associative learning. One well-studied, quantifiable form of associative learning is Pavlovian fear conditioning. However, to date, studies of fear conditioning in schizophrenia have been inconclusive, possibly because they lacked sufficient power. To address this issue, we pooled data from four independent fear conditioning studies that included a total of 77 individuals with schizophrenia and 74 control subjects. Skin conductance responses (SCRs) to stimuli that were paired (the CS + ) or not paired (CS−) with an aversive, unconditioned stimulus were measured, and the success of acquisition of differential conditioning (the magnitude of CS + vs. CS− SCRs) and responses to CS + and CS− separately were assessed. We found that acquisition of differential conditioned fear responses was significantly lower in individuals with schizophrenia than in healthy controls (Cohen’s d = 0.53). This effect was primarily related to a significantly higher response to the CS− stimulus in the schizophrenia compared to the control group. Moreover, the magnitude of this response to the CS− in the schizophrenia group was correlated with the severity of delusional ideation (p = 0.006). Other symptoms or antipsychotic dose were not associated with fear conditioning measures. In conclusion, individuals with schizophrenia who endorse delusional beliefs may be over-responsive to neutral stimuli during fear conditioning. This finding is consistent with prior models of abnormal associative learning in psychosis

Keeping up with the kids: the value of co-production in the study of irritability in youth depression and its underlying neural circuitry

Irritability is a core symptom of adolescent depression, characterized by an increased proneness to anger or frustration. Irritability in youth is associated with future mental health problems and impaired social functioning, suggesting that it may be an early indicator of emotion regulation difficulties. Adolescence is a period during which behavior is significantly impacted by one's environment. However, existing research on the neural basis of irritability typically use experimental paradigms that overlook the social context in which irritability occurs. Here, we bring together current findings on irritability in adolescent depression and the associated neurobiology and highlight directions for future research. Specifically, we emphasize the importance of co-produced research with young people as a means to improve the construct and ecological validity of research within the field. Ensuring that our research design and methodology accurately reflect to lives of young people today lays a strong foundation upon which to better understand adolescent depression and identify tractable targets for intervention

Disrupted limbic-prefrontal effective connectivity in response to fearful faces in lifetime depression

Background: Multiple brain imaging studies of negative emotional bias in major depressive disorder (MDD) have used images of fearful facial expressions and focused on the amygdala and the prefrontal cortex. The results have, however, been inconsistent, potentially due to small sample sizes (typically N < 50 ). It remains unclear if any alterations are a characteristic of current depression or of past experience of depression, and whether there are MDD-related changes in effective connectivity between the two brain regions.Methods: Activations and effective connectivity between the amygdala and dorsolateral prefrontal cortex (DLPFC) in response to fearful face stimuli were studied in a large population-based sample from Generation Scotland. Participants either had no history of MDD ( N = 664 in activation analyses, N = 474 in connectivity analyses) or had a diagnosis of MDD during their lifetime (LMDD, N = 290 in activation analyses, N = 214 in connectivity analyses). The within-scanner task involved implicit facial emotion processing of neutral and fearful faces.Results: Compared to controls, LMDD was associated with increased activations in left amygdala ( PFWE = 0.031 , k E = 4 ) and left DLPFC ( PFWE = 0.002 , k E = 33 ), increased mean bilateral amygdala activation ( β = 0.0715, P = 0.0314 ), and increased inhibition from left amygdala to left DLPFC, all in response to fearful faces contrasted to baseline. Results did not appear to be attributable to depressive illness severity or antidepressant medication status at scan time.Limitations: Most studied participants had past rather than current depression, average severity of ongoing depression symptoms was low, and a substantial proportion of participants were receiving medication. The study was not longitudinal and the participants were only assessed a single time.Conclusions: LMDD is associated with hyperactivity of the amygdala and DLPFC, and with stronger amygdala to DLPFC inhibitory connectivity, all in response to fearful faces, unrelated to depression severity at scan time. These results help reduce inconsistency in past literature and suggest disruption of ‘bottom-up’ limbic-prefrontal effective connectivity in depression

Prediction of depression in individuals at high familial risk of mood disorders using functional magnetic resonance imaging [Article]

Objective Bipolar disorder is a highly heritable condition. First-degree relatives of affected individuals have a more than a ten-fold increased risk of developing bipolar disorder (BD), and a three-fold risk of developing major depressive disorder (MDD) than the general population. It is unclear however whether differences in brain activation reported in BD and MDD are present before the onset of illness. Methods We studied 98 young unaffected individuals at high familial risk of BD and 58 healthy controls using functional Magnetic Resonance Imaging (fMRI) scans and a task involving executive and language processing. Twenty of the high-risk subjects subsequently developed MDD after the baseline fMRI scan. Results At baseline the high-risk subjects who later developed MDD demonstrated relatively increased activation in the insula cortex, compared to controls and high risk subjects who remained well. In the healthy controls and high-risk group who remained well, this region demonstrated reduced engagement with increasing task difficulty. The high risk subjects who subsequently developed MDD did not demonstrate this normal disengagement. Activation in this region correlated positively with measures of cyclothymia and neuroticism at baseline, but not with measures of depression. Conclusions These results suggest that increased activation of the insula can differentiate individuals at high-risk of bipolar disorder who later develop MDD from healthy controls and those at familial risk who remain well. These findings offer the potential of future risk stratification in individuals at risk of mood disorder for familial reasons

Associations of negative affective biases and depressive symptoms in a community-based sample

Acknowledgements. We thank professor Jonathan Roiser (University College London, UK) and professor emeritus Ian Deary (University of Edinburgh, UK) for their input on task selection and statistical analysis. We also acknowledge all researchers who have contributed to the collection of data for the current study. Most importantly, we would like to thank all participants of Generation Scotland, and particularly those of the STRADL subcohort, for their participation in the research. Financial support. Stratifying Resilience and Depression Longitudinally is supported by the Wellcome Trust through a Strategic Award (Grant No. 104036/Z/14/Z) and through an Investigator Award (Grant No. 220857/Z/ 20/Z). The Chief Scientist Office of the Scottish Government Health Department (Grant No. CZD/16/6), Scottish Funding Council (Grant No. HR03006) and Wellcome Trust (Grant No. 216767/Z/19/Z) provided core support for Generation Scotland.Peer reviewedPublisher PD

Associations of negative affective biases and depressive symptoms in a community-based sample

Background: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. Methods: Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals

Hair glucocorticoids are associated with childhood adversity, depressive symptoms and reduced global and lobar grey matter in Generation Scotland

ACKNOWLEDGEMENTS We would like to thank all of the Generation Scotland participants for their contribution to this study. We also thank the research assistants, clinicians and technicians for their help in collecting the data. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. This study was also supported and funded by the Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’ (STRADL) (Reference 104036/Z/14/Z). We acknowledge the support of the British Heart Foundation (RE/18/5/34216). CG is supported by the Medical Research Council and the University of Edinburgh through the Precision Medicine Doctoral Training Programme. MCB is supported by a Guarantors of Brain Non-Clinical Post-Doctoral Fellowship. JMW is funded by the UK Dementia Research Institute which is funded by the UK Medical Research Council, Alzheimer’s Research UK and Alzheimer’s SocietyPeer reviewedPublisher PD