Garry D. Honey

Substantia nigra/ventral tegmental reward prediction error disruption in psychosis

While dopamine systems have been implicated in the pathophysiology of schizophrenia and psychosis for many years, how dopamine dysfunction generates psychotic symptoms remains unknown. Recent theoretical interest has been directed at relating the known role of midbrain dopamine neurons in reinforcement learning, motivational salience and prediction error to explain the abnormal mental experience of psychosis. However, this theoretical model has yet to be explored empirically. To examine a link between psychotic experience, reward learning and dysfunction of the dopaminergic midbrain and associated target regions, we asked a group of first episode psychosis patients suffering from active positive symptoms and a group of healthy control participants to perform an instrumental reward conditioning experiment. We characterized neural responses using functional magnetic resonance imaging. We observed that patients with psychosis exhibit abnormal physiological responses associated with reward prediction error in the dopaminergic midbrain, striatum and limbic system, and we demonstrated subtle abnormalities in the ability of psychosis patients to discriminate between motivationally salient and neutral stimuli. This study provides the first evidence linking abnormal mesolimbic activity, reward learning and psychosis.

How Good Is Good Enough in Path Analysis of fMRI Data

This paper is concerned with the problem of evaluating goodness-of-fit of a path analytic model to an interregional correlation matrix derived from functional magnetic resonance imaging (fMRI) data. We argue that model evaluation based on testing the null hypothesis that the correlation matrix predicted by the model equals the population correlation matrix is problematic because P values are conditional on asymptotic distributional results (which may not be valid for fMRI data acquired in less than 10 min), as well as arbitrary specification of residual variances and effective degrees of freedom in each regional fMRI time series. We introduce an alternative approach based on an algorithm for automatic identification of the best fitting model that can be found to account for the data. The algorithm starts from the null model, in which all path coefficients are zero, and iteratively unconstrains the coefficient which has the largest Lagrangian multiplier at each step until a model is identified which has maximum goodness by a parsimonious fit index. Repeating this process after bootstrapping the data generates a confidence interval for goodness-of-fit of the best model. If the goodness of the theoretically preferred model is within this confidence interval we can empirically say that the theoretical model could be the best model. This relativistic and data-based strategy for model evaluation is illustrated by analysis of functional MR images acquired from 20 normal volunteers during periodic performance (for 5 min) of a task demanding semantic decision and subvocal rehearsal. A model including unidirectional connections from frontal to parietal cortex, designed to represent sequential engagement of rehearsal and monitoring components of the articulatory loop, is found to be irrefutable by hypothesis-testing and within confidence limits for the best model that could be fitted to the data.

Applications of fMRI in translational medicine and clinical practice

Functional MRI (fMRI) has had a major impact in cognitive neuroscience. fMRI now has a small but growing role in clinical neuroimaging, with initial applications to neurosurgical planning. Current clinical research has emphasized novel concepts for clinicians, such as the role of plasticity in recovery and the maintenance of brain functions in a broad range of diseases. There is a wider potential for clinical fMRI in applications ranging from presymptomatic diagnosis, through drug development and individualization of therapies, to understanding functional brain disorders. Realization of this potential will require changes in the way clinical neuroimaging services are planned and delivered.

Effects of Verbal Working Memory Load on Corticocortical Connectivity Modeled by Path Analysis of Functional Magnetic Resonance Imaging Data

We investigated the hypothesis that there are load-related changes in the integrated function of frontoparietal working memory networks. Functional magnetic resonance imaging time-series data from 10 healthy volunteers performing a graded n-back verbal working memory task were modeled using path analysis. Seven generically activated regions were included in the model: left/right middle frontal gyri (L/R MFG), left/right inferior frontal gyri (L/R IFG), left/right posterior parietal cortex (L/R PPC), and supplementary motor area (SMA). The model provided a good fit to the 1-back (chi(2) = 7.04, df = 8, P = 0.53) and 2-back conditions (chi(2) = 9.35, df = 8, P = 0.31) but not for the 3-back condition (chi(2) = 20.60, df = 8, P = 0.008). Model parameter estimates were compared overall among conditions: there was a significant difference overall between 1-back and 2-back conditions (chi(2)(diff) = 74.77, df = 20, P < 0.001) and also between 2-back and 3-back conditions (chi(2)(diff) = 96.28, df = 20, P < 0.001). Path coefficients between LIFG and LPPC were significantly different from zero in both 1-back and 2-back conditions; in the 2-back condition, additional paths from LIFG to LPPC via SMA and to RMFG from LMFG and LPPC were also nonzero. This study demonstrated a significant change in functional integration of a neurocognitive network for working memory as a correlate of increased load. Enhanced inferior frontoparietal and prefrontoprefrontal connectivity was observed as a correlate of increasing memory load, which may reflect greater demand for maintenance and executive processes, respectively.

From prediction error to psychosis: ketamine as a pharmacological model of delusions

Recent cognitive neuropsychiatric models of psychosis emphasize the role of attentional disturbances and inappropriate incentive learning in the development of deLusions. These models highlight a pre-psychotic period in which the patient experiences perceptual and attentional disruptions. Irrelevant details and numerous associations between stimuli, thoughts and percepts are imbued with inappropriate significance and the attempt to rationalize and account for these bizarre experiences results in the formation of delusions. The present paper discusses delusion formation in terms of basic associative learning processes. Such processes are driven by prediction error signaLs. Prediction error refers to mismatches between an organisms expectation in a given environment and what actually happens and it is signalled by both dopaminergic and glutamatergic mechanisms. Disruption of these neurobiological systems may underie delusion formation. We review similarities between acute psychosis and the psychotic state induced by the NMDA receptor antagonist drug ketamine, which impacts upon both dopaminergic and glutamatergic function. We conclude by suggesting that ketamine may provide an appropriate model to investigate the formative stages of symptom evolution in schizophrenia, and thereby provide a window into the earliest and otherwise inaccessible aspects of the disease process.

Prediction Error during Retrospective Revaluation of Causal Associations in Humans: fMRI Evidence in Favor of an Associative Model of Learning

Associative learning theory assumes that prediction error is a driving force in learning. A competing view, probabilistic contrast (PC) theory, is that learning and prediction error are unrelated. We tested a learning phenomenon that has proved troublesome for associative theory--retrospective revaluation--to evaluate these two models. We previously showed that activation in right lateral prefrontal cortex (PFC) provides a reliable signature for the presence of prediction error. Thus, if the associative view is correct, retrospective revaluation should be accompanied by right lateral PFC activation. PC theory would be supported by the absence of this activation. Right PFC and ventral striatal activation occurred during retrospective revaluation, supporting the associative account. Activations appeared to reflect the degree of revaluation, predicting later brain responses to revalued cues. Our results support a modified associative account of retrospective revaluation and demonstrate the potential of functional neuroimaging as a tool for evaluating competing learning models.

De-coupling of cognitive performance and cerebral functional response during working memory in schizophrenia.

Working memory dysfunction is considered to be fundamental to the cognitive and clinical features evident in schizophrenia. Functional neuroimaging studies have begun to elucidate the neurobiological basis of such deficits, however, interpretation of these studies may be confounded by performance impairment, when the cognitive load exceeds the limited response capacity of patients with schizophrenia. In this study, patients were pre-selected on the basis of intact performance on a relatively low-load verbal working memory task, in order to mitigate against performance confounds. Subjects included 20 right-handed male subjects with chronic schizophrenia, and 20 right-handed, age-matched, male healthy controls, without personal or familial psychiatric history. All subjects underwent fMRI scanning whilst performing a verbal n-back task. There were no significant between-group differences in target identification; the patient group showed a significantly increased mean response latency. Both groups demonstrated robust fronto-parietal activation. In the control subjects, the power of functional response was positively correlated with reaction time in bilateral posterior parietal cortex, however, this coupling of behavioural performance and cerebral response was not evident in the patients. This deficit, apparent within the performance capacity of the patients, may represent a fundamental abnormality in schizophrenia, and may compromise performance at higher cognitive loads.

Procedural learning in schizophrenia: a functional magnetic resonance imaging investigation

Procedural learning (PL) is a type of rule-based learning in which performance facilitation occurs with practice on task without the need for conscious awareness. Schizophrenic patients have often (though not invariably) been found to show impaired PL. We performed functional magnetic resonance imaging (fMRI) during a blocked, periodic sequence-learning task with groups of: (i) healthy subjects, and (ii) schizophrenic patients on conventional antipsychotics. Healthy subjects showed significant PL, but patients did not. In healthy subjects, PL was associated with increased activation in the striatum, thalamus, cerebellum, precuneus, medial frontal lobe, and cingulate gyrus. The power of activation in the thalamus, striatum, precuneus, cingulate gyrus and BA 6 was related to the magnitude of PL in these subjects. No regions, except the anterior inferior gyrus, were significantly activated in patients. The caudate nucleus, thalamus, precuneus, and sensorimotor regions were activated significantly differently between the two groups. The findings demonstrate the involvement of the striatum, cerebellum, thalamus, cingulate gyrus, precuneus, and sensorimotor regions in PL. Further fMRI studies of PL in normal subjects treated with conventional antipsychotics, drug naïve patients, and patients given atypical antipsychotics would help to clarify the roles of schizophrenic disease processes and antipsychotic medication in impaired PL and associated brain abnormalities in schizophrenia.

Acute ketamine administration alters the brain responses to executive demands in a verbal working memory task: an FMRI study.

We have used functional MRI to determine the effects of ketamine on brain systems activated in association with a working memory task. Healthy volunteers received intravenous infusions of placebo, ketamine at 50 ng/ml plasma concentration, and ketamine at 100 ng/ml. They were scanned while carrying out a verbal working memory task in which we varied the executive requirements (manipulation vs maintenance processes) and the mnemonic load (three vs five presented letters). We previously showed that ketamine produces a specific behavioral impairment in the manipulation task. In the current study, we modified tasks in order to match performance across drug and placebo conditions, and used an event-related fMRI design, allowing us to remove unsuccessful trials from the analysis. Our results suggest a task-specific effect of ketamine on working memory in a brain system comprising frontal cortex, parietal cortex, and putamen. When subjects are required to manipulate presented letters into alphabetical order, as opposed to maintaining them in the order in which they were presented, ketamine is associated with significantly greater activity in this system, even under these performance-matched conditions. No significant effect of ketamine was seen in association with increasing load. This suggests that our findings are not explicable in terms of a nonspecific effect of ketamine when task difficulty is increased. Rather, our findings provide evidence that the predominant effects of low, subdissociative doses of ketamine are upon the control processes engaged by the manipulation task. Furthermore, we have shown that ketamines effects may be elucidated by fMRI even when overt behavioral measures show no evidence of impairment.

Schizophrenia, ketamine and cannabis: evidence of overlapping memory deficits

Drug models of mental illness are considered useful if they provoke its characteristic symptoms. In this respect, ketamine and tetrahydrocannabinol (cannabis) are coming under increasing scrutiny as models for schizophrenia. However, although both undoubtedly produce psychotic symptoms characteristic of the disorder, we argue here that, because schizophrenia is also accompanied by cognitive deficits, a full understanding of the impact of these drugs on cognition will be crucial in taking these models further. Memory deficits are pronounced in schizophrenia and we focus upon patterns of working and episodic memory impairment produced by ketamine and cannabis, identifying overlaps between drug and illness. We suggest that close attention to these deficits can offer insights into core pathophysiology of schizophrenia.