Biology subjects

Murray, G. K.

Publications and source records attributed to Murray, G. K..

4 recordsLinked to original sources

bioRxiv2018

Neural correlates of reward anticipation in 2000 children aged 9-10 years: relation to psychotic-like experiences and depressive symptoms

BackgroundSchizophrenia spectrum disorders and depression have been associated with reductions in brain activation during reward anticipation. It is not known whether brain signals associated with reward anticipation relate to psychopathology dimensions of depression or schizophrenia in childhood prior to adolescence.\n\nMethodWe examined whether fMRI brain correlates of reward anticipation related to psychotic-like experiences and symptoms of depression, in 2129 children from the ABCD study aged 9-10 years.Psychotic-like experiences and depression were assessed using the Prodromal Questionnaire Brief Child version and the K-SADS. We fused regional MRI summary statistics for reward anticipation activation in the ABCD study data release 1.0 (contrast of expected large reward versus neutral expectation). Relations between brain activation and psychopathology were assessed using linear regressions in R for 82 brain regions, corrected for multiple comparisons for the number of regions using false discovery rate.\n\nResultsFrom several regressions, there was an isolated unilateral association between right parsorbitalis activation and psychotic-like experiences, but no other significant associations between brain activation and psychopathology.\n\nConclusionsIn 9-10 year old children, reward anticipation is not strongly related to psychotic-like experiences or depression. As previous evidence links depression and schizophrenia to reduced reward anticipation in adults and older adolescents, it appears likely that such associations develop over the adolescent period: this can be tested in follow-up studies of the ABCD cohort.

neuroscience↗

bioRxiv2018

Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning

The predictive coding framework construes the brain as performing a specific form of hierarchical Bayesian inference. In this framework the precision of cortical unsigned prediction error (surprise) signals is proposed to play a key role in learning and decision-making, and to be controlled by dopamine. To test this hypothesis, we re-analysed an existing data-set from healthy individuals who received a dopamine agonist, antagonist or placebo and who performed an associative learning task under different levels of outcome precision. Computational reinforcement-learning modelling of behaviour provided support for precision-weighting of unsigned prediction errors. Functional MRI revealed coding of unsigned prediction errors relative to their precision in bilateral superior frontal gyri and dorsal anterior cingulate. Cortical precision-weighting was (i) perturbed by the dopamine antagonist sulpiride, and (ii) associated with task performance. These findings have important implications for understanding the role of dopamine in reinforcement learning and predictive coding in health and illness.

neuroscience↗

bioRxiv2017

Dopaminergic drug treatment remediates exaggerated cingulate prediction error responses in obsessive-compulsive disorder

RationalePatients with obsessive-compulsive disorder (OCD) have been found to show exaggerated error responses and prediction error learning signals in a variety of EEG and fMRI tasks, with data converging on the anterior cingulate cortex as a key locus of dysfunction. Considerable evidence has linked prediction error processing to dopaminergic function.\n\nObjectiveIn this study we investigate potential dopaminergic dysfunction during reward processing in the context of OCD.\n\nMethodsWe studied OCD patients (n=18) and controls (n=18) whilst they learned probabilistic associations between abstract stimuli and monetary rewards in the fMRI scanner involving administration (on separate visits) of: a dopamine receptor agonist, pramipexole 0.5mg; a dopamine receptor antagonist, amisulpride 400mg, and placebo. We fitted a Q-learning computational model to fMRI prediction error responses; group differences were examined in anterior cingulate and nucleus accumbens regions of interest.\n\nResultsThere were no significant group, drug or interaction effects in number of correct choices; computational modeling suggested a marginally significant difference in learning rates between groups (p=0.089, partial 2=0.1). In the imaging results, there was a significant interaction of group by drug (p=0.013, partial 2=0.13). OCD patients showed abnormally strong cingulate signaling of prediction errors during omission of an expected reward, with unexpected reduction by both pramipexole and amisulpride (p=0.014, partial 2=0.26, 1-{beta} error probability=0.94). Exaggerated cingulate prediction error signaling to omitted reward in placebo was related to trait subjective difficulty in self-regulating behavior in OCD.\n\nConclusionsOur data support cingulate dysfunction during reward processing in OCD, and bidirectional remediation by dopaminergic modulation, suggesting that exaggerated cingulate error signals in OCD may be of dopaminergic origin. The results help to illuminate the mechanisms through which dopamine receptor antagonists achieve therapeutic benefit in OCD. Further research is needed to disentangle the different functions of dopamine receptor agonists and antagonists during bidirectional modulation of cingulate activation.

neuroscience↗

bioRxiv2017

Abnormal reward prediction error signalling in antipsychotic naive individuals with first episode psychosis or clinical risk for psychosis

Ongoing research suggests preliminary, though not entirely consistent, evidence of neural abnormalities in signalling prediction errors in schizophrenia. Supporting theories suggest mechanistic links between the disruption of these processes and the generation of psychotic symptoms. However, it is not known at what stage in psychosis these impairments in prediction error signalling develop. One major confound in prior studies is the use of medicated patients with strongly varying disease durations. Our study aims to investigate the involvement of the meso-cortico-striatal circuitry during reward prediction error signalling in the earliest stages of psychosis. We studied patients with first episode psychosis (FEP) and help-seeking individuals at risk for psychosis due to subthreshold prodromal psychotic symptoms. Patients with either FEP (n = 14), or at-risk for developing psychosis (n= 30), and healthy volunteers (n = 39) performed a reinforcement learning task during fMRI scanning. ANOVA revealed significant (p<0.05 family-wise error corrected) prediction error signalling differences between groups in the dopaminergic midbrain and right middle frontal gyrus (dorsolateral prefrontal cortex, DLPFC). Patients with FEP showed disrupted reward prediction error signalling compared to controls in both regions. At-risk patients showed intermediate activation in the midbrain that significantly differed from controls and from FEP patients, but DLPFC activation that did not differ from controls. Our study confirms that patients with FEP have abnormal meso-cortical signalling of reward prediction errors, whilst reward prediction error dysfunction in the at-risk patients appears to show a more nuanced pattern of activation with a degree of midbrain impairment but preserved cortical function.

neuroscience↗