Gordon D. Waiter

Expected value and prediction error abnormalities in depression and schizophrenia

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.

Abnormal temporal difference reward-learning signals in major depression

Anhedonia is a core symptom of major depressive disorder (MDD), long thought to be associated with reduced dopaminergic function. However, most antidepressants do not act directly on the dopamine system and all antidepressants have a delayed full therapeutic effect. Recently, it has been proposed that antidepressants fail to alter dopamine function in antidepressant unresponsive MDD. There is compelling evidence that dopamine neurons code a specific phasic (short duration) reward-learning signal, described by temporal difference (TD) theory. There is no current evidence for other neurons coding a TD reward-learning signal, although such evidence may be found in time. The neuronal substrates of the TD signal were not explored in this study. Phasic signals are believed to have quite different properties to tonic (long duration) signals. No studies have investigated phasic reward-learning signals in MDD. Therefore, adults with MDD receiving long-term antidepressant medication, and comparison controls both unmedicated and acutely medicated with the antidepressant citalopram, were scanned using fMRI during a reward-learning task. Three hypotheses were tested: first, patients with MDD have blunted TD reward-learning signals; second, controls given an antidepressant acutely have blunted TD reward-learning signals; third, the extent of alteration in TD signals in major depression correlates with illness severity ratings. The results supported the hypotheses. Patients with MDD had significantly reduced reward-learning signals in many non-brainstem regions: ventral striatum (VS), rostral and dorsal anterior cingulate, retrosplenial cortex (RC), midbrain and hippocampus. However, the TD signal was increased in the brainstem of patients. As predicted, acute antidepressant administration to controls was associated with a blunted TD signal, and the brainstem TD signal was not increased by acute citalopram administration. In a number of regions, the magnitude of the abnormal signals in MDD correlated with illness severity ratings. The findings highlight the importance of phasic reward-learning signals, and are consistent with the hypothesis that antidepressants fail to normalize reward-learning function in antidepressant-unresponsive MDD. Whilst there is evidence that some antidepressants acutely suppress dopamine function, the long-term action of virtually all antidepressants is enhanced dopamine agonist responsiveness. This distinction might help to elucidate the delayed action of antidepressants. Finally, analogous to recent work in schizophrenia, the finding of abnormal phasic reward-learning signals in MDD implies that an integrated understanding of symptoms and treatment mechanisms is possible, spanning physiology, phenomenology and pharmacology.

Structural white matter deficits in high-functioning individuals with autistic spectrum disorder: a voxel-based investigation.

A number of imaging and neuropathological studies have reported structural abnormalities in white matter areas such as the corpus callosum in autism spectrum disorder (ASD). Differences in both global brain volume and the size of specific neural structures have been reported. In order to expand these previously reported findings and to describe more precisely the nature of such structural changes, we performed a voxel-based morphometric whole brain analysis, using a group-specific template, in male adolescents with ASD. Fifteen individuals with normal intelligence and ASD, and a group of 16 controls, matched for age, sex, and IQ, were investigated. High-resolution T1-weighted 3D data sets were acquired and analysed. Local white matter volume deficits were found in the corpus callosum, particularly in the anterior splenium and isthmus, and right hemisphere. White matter volume deficits were also found in the left middle temporal, right middle frontal, and left superior frontal gyri. No significant areas of increased white matter volume were found. Our findings support the hypothesis that reduced white matter volume in the corpus callosum and right hemisphere may play a role in the pathophysiology of ASD.

An fMRI study of Joint Attention Experience

Although much is now known about eye movement detection, little is known about the higher cognitive processes involved in joint attention. We developed video stimuli which when watched, engender an experience of joint attention in the observer. This allowed us to compare an experience of joint attention to nonjoint attention within an fMRI scanning environment. Joint attention was associated with activity in the ventromedial frontal cortex, the left superior frontal gyrus (BA10), cingulate cortex, and caudate nuclei. The ventromedial frontal cortex has been consistently shown to be activated during mental state attribution tasks. BA10 may serve a cognitive integration function, which in this case seems to utilize a perception-action matching process. The activation we identified in BA10 overlaps with a location of increased grey matter density that we recently found to be associated with autistic spectrum disorder. This study therefore constitutes evidence that the neural substrate of joint attention also serves a mentalizing function. The developmental failure of this substrate in the left anterior frontal lobe may be important in the etiology of autistic spectrum disorder.

Do mirror neuron areas mediate mu rhythm suppression during imitation and action observation

Mu rhythm is an EEG measure of resting motor neurons, which is normally suppressed by input because of action observation or movement execution. This characteristic has caused mu suppression to be used as proxy marker for mirror neuron activation. However, there is little direct evidence that fluctuations in mu rhythm suppression reflect concurrent fluctuations in mirror neuron activity. A manual imitation paradigm was used to look at correlations between mu rhythm and BOLD response, by recording sequential EEG and fMRI measures to allow within-subject correlation analyses. Participants were instructed to imitate or observe actions involving the movement of a handle with their right hand. Mu power modulation, defined as mu power changes between conditions, correlated negatively with BOLD response in right inferior parietal lobe, premotor cortex and inferior frontal gyrus; putative mirror neuron areas. Clusters were also identified in bilateral cerebellum, left medial frontal gyrus, right temporal lobe and thalamus. This suggests that mu suppression involves a range of structures that modulate motor preparation activities and are sensitive to visual input, including but not restricted to the human analogue of the mirror neuron system.

Determination of normal regional left ventricular function from cine-MR images using a semi-automated edge detection method

A semi-automated edge detection method for the delineation of the endo- and epicardial borders of the left ventricle from cine MR images has been developed. The feasibility of this was demonstrated by processing end diastolic and end systolic ECG-gated images of four short axis images in 10 healthy subjects. The first derivative method combined with a 2D weighted polynomial fitting procedure was used to determine the endo- and epicardial borders, which then allowed determination of the wall motion, wall thickening, and ejection fraction, of the left ventricle. The results show that the end-systolic radial wall motion varies from (32+/-8)% to (76+/-12)%, and wall thickening from (0.60+/-0.46) cm to (1.26+/-0.50) cm. An average ejection fraction of (69+/-6)% was found which agrees well with literature values. The method described, for the delineation of the borders, reduces considerably the long and tedious operator time inherent in manual measurement and greatly increases the reproducibility of the measurements.

Mine and me: Exploring the neural basis of object ownership

Previous research has shown that encoding information in the context of self-evaluation leads to memory enhancement, supported by activation in ventromedial pFC. Recent evidence suggests that similar self-memory advantages can be obtained under nonevaluative encoding conditions, such as when object ownership is used to evoke self-reference. Using fMRI, the current study explored the neural correlates of object ownership. During scanning, participants sorted everyday objects into self-owned or other-owned categories. Replicating previous research, a significant self-memory advantage for the objects was observed (i.e., self-owned > other-owned). In addition, encoding self-owned items was associated with unique activation in posterior dorsomedial pFC (dMPFC), left insula, and bilateral supramarginal gyri (SMG). Subsequent analysis showed that activation in a subset of these regions (dMPFC and left SMG) correlated with the magnitude of the self-memory advantage. Analysis of the time-to-peak data suggested a temporal model for processing ownership in which initial activation of dMPFC spreads to SMG and insula. These results indicate that a self-memory advantage can be elicited by object ownership and that this effect is underpinned by activity in a neural network that supports attentional, reward, and motor processing.

Salience network-midbrain dysconnectivity and blunted reward signals in schizophrenia

Theories of schizophrenia propose that abnormal functioning of the neural reward system is linked to negative and psychotic symptoms, by disruption of reward processing and promotion of context-independent false associations. Recently, it has been argued that an insula-anterior cingulate cortex (ACC) salience network system enables switching of brain states from the default mode to a task-related activity mode. Abnormal interaction between the insula-ACC system and reward processing regions may help explain abnormal reinforcer processing and symptoms. Here we use functional magnetic resonance imaging to assess the neural correlates of reward processing in schizophrenia. Furthermore, we investigated functional connectivity between the dopaminergic midbrain, a key region for the processing of reinforcers, and other brain regions. In response to rewards, controls activated task related regions (striatum, amygdala/hippocampus and midbrain) and the insula-ACC salience network. Patients similarly activated the insula-ACC salience network system but failed to activate task related regions. Reduced functional connectivity between the midbrain and the insula was found in schizophrenia, with the extent of this abnormality correlating with increased psychotic symptoms. The findings support the notion that reward processing is abnormal in schizophrenia and highlight the potential role of abnormal interactions between the insula-ACC salience network and reward regions.

Prospective multi-centre Voxel Based Morphometry study employing scanner specific segmentations: procedure development using CaliBrain structural MRI data.

BackgroundStructural 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.MethodsWe 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.ResultsVoxel 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.ConclusionOur 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.

Cortical and subcortical mechanisms at the core of imitation

Abstract Imitation is thought to require a perception–action matching process that utilizes the “mirror neuron” system, but other cognitive functions such as error detection may also be required for even simple imitation. We sought to explore the core neural substrate of imitation by examining the imitation of simple finger actions using fMRI. Participants observed one of two actions and were instructed to imitate the action they observed, or to perform the alternative non-matching action. The contrast between imitation and non-matching actions was associated with activation in areas previously associated with imitation and “mirror neuron” functioning, including insula, intraparietal sulcus, dorsal premotor cortex, and superior temporal gyrus. Imitation was also specifically associated with activity in areas of prefrontal cortex, lateral orbitofrontal cortex (OFC), amygdala, red nucleus, thalamus, hippocampus, and substantia nigra. We suggest that lateral OFC responds to action–perception mismatch and other clusters reflect working memory, motor planning, associative learning, and visuo-motor integration of goal-directed action. Although computational models have predicted integration of these functions to enable imitation, their specific brain bases have not previously been identified. Together they offer a potentially powerful means through which matching ones actions to those of others can lead to behavioral modification and development.