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ABSTRACT: The dopamine system has been linked to anhedonia in depression and both the positive and negative symptoms of schizophrenia, but it remains unclear how dopamine dysfunction could mechanistically relate to observed symptoms. There is considerable evidence that phasic dopamine signals encode prediction error (differences between expected and actual outcomes), with reinforcement learning theories being based on prediction error-mediated learning of associations. It has been hypothesized that abnormal encoding of neural prediction error signals could underlie anhedonia in depression and negative symptoms in schizophrenia by disrupting learning and blunting the salience of rewarding events, and contribute to psychotic symptoms by promoting aberrant perceptions and the formation of delusions. To test this, we used model based functional magnetic resonance imaging and an instrumental reward-learning task to investigate the neural correlates of prediction errors and expected-reward values in patients with depression (n=15), patients with schizophrenia (n=14) and healthy controls (n=17). Both patient groups exhibited abnormalities in neural prediction errors, but the spatial pattern of abnormality differed, with the degree of abnormality correlating with syndrome severity. Specifically, reduced prediction errors in the striatum and midbrain were found in depression, with the extent of signal reduction in the bilateral caudate, nucleus accumbens and midbrain correlating with increased anhedonia severity. In schizophrenia, reduced prediction error signals were observed in the caudate, thalamus, insula and amygdala-hippocampal complex, with a trend for reduced prediction errors in the midbrain, and the degree of blunting in the encoding of prediction errors in the insula, amygdala-hippocampal complex and midbrain correlating with increased severity of psychotic symptoms. Schizophrenia was also associated with disruption in the encoding of expected-reward values in the bilateral amygdala-hippocampal complex and parahippocampal gyrus, with the degree of disruption correlating with psychotic symptom severity. Neural signal abnormalities did not correlate with negative symptom severity in schizophrenia. These findings support the suggestion that a disruption in the encoding of prediction error signals contributes to anhedonia symptoms in depression. In schizophrenia, the findings support the postulate of an abnormality in error-dependent updating of inferences and beliefs driving psychotic symptoms. Phasic dopamine abnormalities in depression and schizophrenia are suggested by our observation of prediction error abnormalities in dopamine-rich brain areas, given the evidence for dopamine encoding prediction errors. The findings are consistent with proposals that psychiatric syndromes reflect different disorders of neural valuation and incentive salience formation, which helps bridge the gap between biological and phenomenological levels of understanding.
Brain 06/2011; 134(Pt 6):1751-64. · 9.46 Impact Factor
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ABSTRACT: Vessel size imaging is an emerging magnetic resonance imaging (MRI) technique which has been demonstrated to provide clinically relevant information about microvascular morphology. While previous studies of vessel size in humans relied on MRI contrast agents or hypercapnia-induced changes in blood oxygenation, the technique described here uses transient hyperoxia to alter the venous blood oxygenation. The experimental paradigm consisted of two 3-minute intervals of breathing 100% O(2) interleaved with three 2-minute intervals of breathing room air. Parametric maps of the mean venous vessel radius were calculated from changes in the blood oxygenation level dependent (BOLD) contrast which were measured using a combined spin-echo (SE) and gradient echo (GE) echo-planar imaging (EPI) sequence. The corresponding mean values in grey and white matter were r=6.5±0.3 μm and r=6.2±0.3 μm (n=6). While the hypercapnia technique requires a specialised gas mixture containing a low concentration of CO(2) (typically 5-6%), the hyperoxia technique presented here uses the inhalation of medical oxygen (100% O(2)) which is routinely available in a clinical environment. Furthermore, 100% O(2) is generally better tolerated than low doses of CO(2) which makes this technique particularly suitable for applications in critically ill patients.
NeuroImage 01/2011; 55(3):1063-7. · 5.89 Impact Factor
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ABSTRACT: To test the prediction of survival using magnetic resonance imaging (MRI)-derived global and regional brain volumes in subjects aged 78 to 79 without dementia.
Observational follow-up study.
University teaching hospital.
Participants born in 1921, recruited in 1997/98 to a longitudinal study, who underwent brain MRI in 1999/2000.
Vital status on May 12, 2006, global and regional brain volumes.
Thirty-seven of 98 (34.9%) participants died during follow-up. After adjustment for cognitive ability at time of MRI examination, childhood intelligence, sex, hypertension, smoking history, obesity, hyperlipidemia, and age at MRI, proportion of intracranial volume occupied by the brain (brain fraction) predicted death before age 85 (P=.04). Participants with brain fraction less than 0.726 had more than twice the relative risk (2.8, 95% confidence interval=1.1-7.3) of death than participants with brain fraction greater 0.726. Lower survival was significantly associated with lower gray matter volumes in bilateral parietal and left frontoparietal areas and with lower white matter volumes in left parietal and right posterior temporal regions. Cox regression analysis showed that parietal white matter volume (P=.003), a subsequent diagnosis of dementia (P<.001), and sex (P=.004) were independent predictors of survival.
In participants aged 78 to 79, a lower global brain fraction predicted survival to approximately age 85. Smaller regional volumetric brain reductions, seen in Alzheimer's disease (AD), also predicted survival independent of dementia. The presence of prodromal AD probably explain the main findings.
Journal of the American Geriatrics Society 04/2010; 58(4):688-95. · 3.74 Impact Factor
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T William J Moorhead,
Viktoria-Eleni Gountouna,
Dominic E Job,
Andrew M McIntosh,
Liana Romaniuk,
G Katherine S Lymer,
Heather C Whalley,
Gordon D Waiter,
David Brennan, Trevor S Ahearn,
Jonathan Cavanagh,
Barrie Condon,
J Douglas Steele,
Joanna M Wardlaw,
Stephen M Lawrie
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ABSTRACT: Structural Magnetic Resonance Imaging (sMRI) of the brain is employed in the assessment of a wide range of neuropsychiatric disorders. In order to improve statistical power in such studies it is desirable to pool scanning resources from multiple centres. The CaliBrain project was designed to provide for an assessment of scanner differences at three centres in Scotland, and to assess the practicality of pooling scans from multiple-centres.
We scanned healthy subjects twice on each of the 3 scanners in the CaliBrain project with T1-weighted sequences. The tissue classifier supplied within the Statistical Parametric Mapping (SPM5) application was used to map the grey and white tissue for each scan. We were thus able to assess within scanner variability and between scanner differences. We have sought to correct for between scanner differences by adjusting the probability mappings of tissue occupancy (tissue priors) used in SPM5 for tissue classification. The adjustment procedure resulted in separate sets of tissue priors being developed for each scanner and we refer to these as scanner specific priors.
Voxel Based Morphometry (VBM) analyses and metric tests indicated that the use of scanner specific priors reduced tissue classification differences between scanners. However, the metric results also demonstrated that the between scanner differences were not reduced to the level of within scanner variability, the ideal for scanner harmonisation.
Our results indicate the development of scanner specific priors for SPM can assist in pooling of scan resources from different research centres. This can facilitate improvements in the statistical power of quantitative brain imaging studies.
BMC Medical Imaging 06/2009; 9:8. · 1.09 Impact Factor
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ABSTRACT: Substantial experimental evidence supports the theory that the dopaminergic system codes a phasic (short duration) signal predicting the delivery of primary reinforcers, such as water when thirsty, during Pavlovian learning. This signal is described by the temporal difference (TD) model. Recently, it has been suggested that the human dopaminergic system also codes more complex cognitive goal states, including those required for human social interaction. Using functional magnetic resonance imaging (fMRI) with 18 healthy subjects, we tested the hypothesis that TD signals would be present during a Pavlovian learning task, and during a social motor response learning task. Using an identical model, TD signals were present in both tasks, although in different brain regions. Specifically, signals were present in the dorsal anterior cingulate, ventral striatum, amygdala, and thalamus with Pavlovian learning, and the dorsal anterior cingulate and bilateral frontal operculum with social motor response learning. The frontal operculum is believed to be the human homologue of the monkey mirror neuron system, and there is evidence which links the region with inference about other peoples' intentions and goals. The results support the contention that the human dopaminergic system predicts both primary reinforcers, and more complex cognitive goal states, such as motor responses required for human social group interaction. Dysfunction of such a mechanism might be associated with abnormal affective responses and incorrect social predictions, as occur in psychiatric disorders.
Human Brain Mapping 07/2008; 30(5):1421-30. · 5.88 Impact Factor
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Annals of General Psychiatry. 01/2008;
