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Aberrant salience network (bilateral insula and anterior cingulate cortex) connectivity during information processing in schizophrenia

Schizophrenia Research, 2-3, 123, pages 105 - 115

Abstract

A salience network, comprising bilateral insula and anterior cingulate cortex (ACC), is thought to play a role in recruiting relevant brain regions for the processing of sensory information. Here, we present a functional network connectivity (FNC) analysis of spatial networks identified during somatosensation, performed to test the hypothesis that salience network connectivity is disturbed during information processing in schizophrenia. 19 medicated individuals with schizophrenia and 19 matched healthy controls participated in a functional magnetic resonance imaging study. 100 Hz vibrotactile stimuli were presented to the right index fingertip while whole-head blood oxygenation level-dependent contrast gradient-echo echo-planar images were acquired. Six spatial components of interest were identified using group independent component analysis: (1) bilateral insula, superior temporal and precentral gyrus (INS); (2) dorsal ACC; (3) left dorsolateral frontal and parietal cortex (left central executive network (LCEN)); (4) right dorsolateral frontal and parietal cortex (RCEN); (5) ventromedial frontal cortex (FDMN); and (6) precuneus, posterior cingulate and angular gyrus (PDMN). Maximal-lagged correlation was examined between all pairwise combinations of components. Significantly reduced FNC was observed in schizophrenia compared to controls between: INS and ACC; INS and FDMN; and LCEN and PDMN. There was no evidence of increased FNC in schizophrenia. Reduced salience network connectivity during information processing in schizophrenia suggests disturbance to the system which effects changes between contextually-relevant functional brain states. This aberrance may provide a mechanistic explanation of several clinical features of the disorder.

Keywords: Schizophrenia, Functional network connectivity, Salience network.

1. Introduction

Fundamental to our current understanding of human brain function is the existence of large-scale distributed networks consisting of modular units between and within which information flows. Assessment of resting-state connectivity in functional magnetic resonance imaging (fMRI) data has revealed that activity in sensory, motor and language networks remains temporally correlated even in the absence of a stimulus (Beckmann et al, 2005 and Cordes et al, 2000), suggesting that the brain is organised into intrinsic networks whose activity waxes and wanes according to contemporaneous demands ( Fox et al., 2005 ). For example, the central executive network (CEN) is a robust attentional network comprising dorsolateral prefrontal and parietal regions activated in a task-positive manner by various attentional, working memory and response selection tasks (Corbetta et al, 2002, Hester et al, 2007, and Meda et al, 2008), while activity in the default mode network (DMN; Raichle et al., 2001 ), comprising the medial prefrontal, posterior cingulate, precuneus and lateral parietal cortex, is negatively correlated with CEN activity and elevated by self-referential tasks ( Gusnard et al., 2001 ).

A coherent network comprising dorsal anterior cingulate cortex (ACC) and bilateral insula has recently been identified in blood oxygenation level dependent (BOLD) data (Seeley et al, 2007 and Sridharan et al, 2008). While task-positive activity is observed in this network, the Salience Network (SN), during attentional, working memory and response-selection paradigms (Menon et al, 2001 and Ridderinkhof et al, 2004), SN also responds to pain, uncertainty and other homeostatic challenges (Grinband et al, 2006 and Peyron et al, 2000). Together these findings imply that SN activity is not task-specific but rather salience-driven, be that salience cognitive, emotional or homeostatic ( Seeley et al., 2007 ). SN activity has been further characterised using functional network connectivity (FNC) measures, which assess dynamic relationships between spatial components derived using independent component analysis (ICA), a data-driven method of blind source separation (Calhoun et al, 2009 and Jafri et al, 2008). Sridharan et al. (2008) investigated the temporal relationship of SN activity relative to CEN and DMN activity in diverse datasets. They reported that onset latency was consistently and significantly lower in both ACC and fronto-insular (FI) regions of the SN when compared to regions of the CEN and DMN. Furthermore, they observed that right FI activity Granger-caused ACC activity and had a powerful causal influence on the other regions studied. These results were proposed to provide evidence that the SN acts to switch between CEN and DMN activity in a context-dependent manner. In addition, recent multi-task evidence suggests the SN is unique in consistently exhibiting activity related to core processes necessary for the selection, initiation and maintenance of a task-relevant mode of brain function ( Dosenbach et al., 2006 ).

Clinical features of schizophrenia including perseverative behaviour and disordered thought can be explained by disturbance to the system responsible for switching between context-relevant brain modes. Furthermore, recent reformulations of the dopamine hypothesis of psychosis emphasise that abnormal salience and novelty attribution follow D2-receptor dysregulation in midbrain structures, with normal context- and stimulus-driven systems of salience and novelty attribution being usurped by endogenously-driven mechanisms. Delusions result from top-down attempts to integrate these abnormal experiences into a cognitive framework (Kapur, 2004 and Kapur et al, 2005). It is conceivable that dysfunction of these midbrain salience attribution mechanisms could produce disturbed SN activity.

Jafri et al. (2008) presented constrained-lagged correlation to assess FNC in schizophrenia. Investigating maximal-lagged correlations between pair-wise combinations of ICA-derived components in a constrained time window, they found that individuals with schizophrenia had broadly abnormal FNC between numerous networks as compared to healthy individuals during resting-state conditions. While individuals with schizophrenia exhibited reduced FNC compared to healthy individuals between bilateral temporal and parietal components, they showed widespread increases in FNC between, for example, the frontal and posterior DMN components, and frontal DMN and visual system components. This pattern of predominantly increased connectivity in schizophrenia supports theories of neural dysmodularity in the disorder ( David, 1994 ).

Using constrained-lagged correlation to assess FNC in a somatosensory information-processing dataset, we address the hypotheses that:

  • 1. In healthy individuals, significant correlation will be observed between ACC and insula regions suggesting the existence of a functionally coherent SN.
  • 2. In healthy individuals, SN activity will precede activity in other functional networks in accord with the notion that SN acts to dynamically recruit networks in a context-relevant fashion ( Sridharan et al., 2008 ).
  • 3. In individuals with schizophrenia, the above predictions will be less well confirmed: nodes of the SN will be less correlated with each other and less predictive of activity within other functional networks.

2. Methods

2.1. Participants

19 right-handed healthy individuals (27 ± 7 years, (mean ± standard deviation)) and 19 right-handed individuals satisfying DSM-IV ( American Psychiatric Association, 1994 ) criteria for schizophrenia (30 ± 7 years) were recruited. Handedness was assessed using the Annett questionnaire (1970) . Groups were mean matched for age, sex, current intellectual function and parental occupation. This information is outlined in Table 1 (A).

Table 1 Participant details.

(A) Demographic data including socioeconomic group as defined by national statistics socio-economic classification (NS-SEC; Rose and Pevalin, 2001 ); handedness as defined by Annett (1970) ; current intellectual functioning (QUICK test, Ammons and Ammons, 1962 ); sex; and ethnicity ( http://www.statistics.gov.uk ). Mean and standard deviation in brackets.
Variable Healthy right-handed group (n = 19) Schizophrenia group (n = 19)
  Mean Mean
Socioeconomic group 2.2 (1.5) 2.9 (1.5)
Handedness 10.7 (3.7) 10.3 (1.7)
IQ 106.2 (9.5) 100.3 (10.4)
Sex 17 male, 2 female 17 male, 2 female
Ethnicity a 15 W, 3 M, 1 A 13 W, 3 M, 1 A, 2 B
 
(B) Medications prescribed to the schizophrenia group (n = 19) at time of study.
Medication Number of participants receiving medication Dosage range
Risperidone: oral 4 2–4 mg oral daily
Consta (IM) 1 37.5 mg every two weeks
Aripiprazole 6 10–25 mg oral daily
Olanzapine 4 10–12.5 mg oral daily
Clozapine 2 400 mg oral daily
Quetiapine 1 150 mg oral daily
Flupenthixol 1 40 mg depot every four weeks
 
(C) Clustered signs and symptoms of psychotic illness (SSPI) scores for participants in schizophrenia group. Mean and standard deviation in brackets.
Symptom cluster Mean
Psychomotor poverty 2.8 (2.4)
Reality distortion 3.4 (2.2)
Disorganisation 0.3 (0.6)

a W, White; M, mixed; 2 Asian/British Asian; B, Black/Black British.

Patients were recruited during a stable phase of schizophrenia. Stability was defined as a change of less than 10 points in their Global Assessment of Function (GAF; DSM-IV; American Psychiatric Association, 1994 ) score, assessed six weeks prior and immediately prior to study participation, and no change in type or dose of medication in the six weeks prior to participation. Diagnosis was made using DSM-IV criteria based on all available information, including case-file review, clinical interview and consensus meeting between research psychiatrists. All patients, apart from one receiving flupenthixol decanoate injection, were prescribed atypical antipsychotic medication at the time of study, with all medications prescribed for at least six weeks prior to study. Medication details are given in Table 1 (B). Chlorpromazine equivalent doses were computed for oral antipsychotic medication using data presented by Woods (2003) . In the case of flupenthixol decanoate, 10 mg via injection per week was taken to equate to 10 mg oral per day, while for long-acting risperidone Consta injection, 25 mg Consta injection every 14 days was taken to equate to 4 mg oral risperidone per day, in accordance with the recommendation of the British National Formulary ( Joint Formulary Committee, 2008 ). The presence and degree of psychotic signs and symptoms were assessed using Signs and Symptoms of Psychotic Illness (SSPI) classification ( Liddle et al., 2002 ) within one week of scanning. Scores are shown in Table 1 (C). Healthy recruits had no history of severe mental illness in a first-degree relative, no personal history of neurological treatment and no currently prescribed medication. Procedures complied with local ethics committee approval. Participants gave informed written consent before taking part.

2.2. Experimental procedure

A piezoelectric stimulator (T220-H4-503 Standard Brass Shim Bending Element, Piezo Systems, Inc., U.S.A.) was securely attached to the fleshy portion of the right index fingertip. Somatosensory vibratory stimuli were delivered as a sinusoid waveform produced by ICL-8038CCPD (Harris Semiconductor Corp., U.S.A.) precision waveform generators. The four-minute task comprised 14 cycles of a 1 s ON-period and 16 s OFF-period. Event frequency and task length were determined according to our previous study of somatosensory processing showing robust BOLD activation in areas of interest to this study ( Francis et al., 2000 ). During the ON-period the stimulator delivered a 100 Hz stimulus of amplitude 100 μm. Participants were instructed that this was a passive task requiring no motor response during stimulation and to stay relaxed but to attend the stimuli. Throughout the paradigm a central fixation cross was presented to the subject using optical-fibre goggles (Avotech, U.S.A.). A somatosensory task was chosen based on previous studies using this procedure at 3 Tesla in healthy individuals ( Francis et al., 2000 ) and schizophrenia ( White et al., 2009 ). Furthermore, although auditory symptoms are more prominent in clinical descriptions of schizophrenia, somatosensory abnormalities such as tactile hallucination remain nonetheless common. Relevantly, the somatosensory system has proven fruitful for investigating the recruitment of distributed attentional networks in schizophrenia ( Huang et al., 2010 ).

Scanning was performed on a 3 Tesla Philips Achieva MRI scanner (Philips, Netherlands). Blood oxygenation level-dependent (BOLD) contrast gradient-echo echo-planar images were acquired using an eight-channel SENSE head coil with SENSE factor 2 in anterior–posterior direction, TR/TE 1436/35 ms, flip angle 80°, 80 × 80 matrix, with an in-plane resolution of 3 mm × 3 mm and 4 mm slice thickness. The TR was selected to ensure data collection was jittered over cycles. A single dynamic image comprised 24 contiguous axial slices acquired in descending order. 167 dynamics were acquired during the fMRI paradigm.

2.3. Data analysis

fMRI data preprocessing was performed using SPM2 (Statistical Parametric Mapping, Wellcome Department of Imaging Neuroscience, University of London, UK). Data were corrected for slice-timing differences and spatially realigned. Movement parameters were assessed for each participant, and participants excluded if movement exceeded 3 mm. Data were subsequently spatially normalised to the SPM2 template. Spatial smoothing using a 5 mm full width at half maximum Gaussian kernel was performed and a high-pass temporal filter applied to minimise effects of low-frequency physiological and scanner-derived confounds.

Group ICA using the Infomax algorithm was performed on preprocessed BOLD data (GIFT toolbox; http://icatb.sourceforge.net ). 20 spatial components were identified, of which six were further evaluated on the basis of congruence between their spatial distribution and networks identified by Sridharan et al. (2008) . These were: (1) bilateral insula, superior temporal and precentral gyrus (INS); (2) dorsal ACC; (3) left dorsolateral frontal and parietal cortex (left central executive network (LCEN)); (4) right dorsolateral frontal and parietal cortex (RCEN); (5) ventromedial frontal cortex (FDMN); and (6) precuneus, posterior cingulate and angular gyrus (PDMN). The first two components are hereafter defined as the SN, the subsequent two as the CEN, and the final two as the DMN. Component timecourses were interpolated to enable detection of sub TR resolution of lags during FNC analysis. FNC was assessed using constrained-lagged correlation between components as presented by Jafri et al. (2008 ; FNC toolbox; http://icatb.sourceforge.net ). Maximal-lagged correlation (−5 to + 5 seconds) was examined between all pair-wise combinations of components, calculated for each participant and averaged within groups. Significant between-group differences in maximal-lagged correlation coefficient and corresponding inter-component lags were also recorded. To control for multiple comparisons, p-values were threshold according to a false discovery rate (FDR; Genovese et al., 2002 ) of 0.05. To assess the relationship between antipsychotic medication and FNC measures, the relationship between prescribed chlorpromazine equivalent dose and Fisher-transformed pairwise correlation coefficients between components was assessed in the schizophrenia group using Pearson's test.

Inter-component temporal dynamics were investigated by calculating peak-locked averages using the peak of the INS component on each trial as the reference time point for that trial. Peak-locked averages for the INS component were calculated by first segmenting the INS component timecourse by event and averaging across events. Then for other components, the average timecourse across trials was computed employing the same alignment of segments as was employed for the INS component, thereby producing an average for each component that was time-locked to the peak of the insula component. Single-subject peak-locked measures were averaged to produce healthy- and schizophrenia-group averages. Between-group differences in peak amplitude of the peak-locked averages were assessed using independent samples t-tests.

3. Results

3.1. Component selection and visualisation

Six components were chosen for FNC analysis. Fig. 1 shows both SN components. Fig. 2 shows left- and right-hemispheric CEN components. Fig. 3 shows frontal and posterior DMN components. The location of selected foci of activation and corresponding z-scores are presented in Table 2 . The 14 excluded components had maximal loadings over cerebrospinal fluid (n = 3); cerebellum (n = 3); white matter (n = 2); visual cortex (n = 2); somatomotor cortex (n = 1); or were dominated by ring-like motion artefacts (n = 3).

gr1

Fig. 1 The Salience Network (SN) identified via group ICA of the somatosensory data overlaid onto a standard T1-weighted brain image. Positive Z-scores are colour-scaled with a threshold of Z = 2.5.

gr2

Fig. 2 The Central Executive Network (CEN) identified via group ICA of the somatosensory data overlaid onto a standard T1-weighted brain image. Positive Z-scores are colour-scaled with a threshold of Z = 2.5.

gr3

Fig. 3 The Default Mode Network (DMN) identified via group ICA of the somatosensory data overlaid onto a standard T1-weighted brain image. Positive Z-scores are colour-scaled with a threshold of Z = 2.5.

Table 2 Foci of activation for the six components of interest. Selected clusters are significant at cluster level corrected with a family-wise error threshold of p < 0.05.

Component Location (Brodmann Area) Z-score Talairach co-ordinates
  x y z
INS Left insula (13) 6.18 −41 −11 9
Right insula (13) 5.49 42 0 0
Left superior temporal gyrus (41) 5.98 −50 −31 15
Right superior temporal gyrus (41) 5.64 53 −29 10
Left precentral gyrus (6) 5.44 −62 3 8
Right precentral gyrus (6) 5.25 55 1 14
ACC Left anterior cingulate gyrus (32) 6.07 3 28 32
Right anterior cingulate gyrus (32) 5.90 −6 22 40
Right medial frontal gyrus (32) 6.24 3 8 47
Left superior frontal gyrus (10) 5.96 −30 51 22
Right superior frontal gyrus (10) 5.14 30 16 15
LCEN Left middle frontal gyrus (8) 5.60 −48 17 41
Left inferior parietal lobe (40) 6.16 −54 −48 45
RCEN Right middle frontal gyrus (8) 5.73 48 20 43
Right inferior parietal lobe (40) 6.23 56 −39 46
Right angular gyrus (39) 5.72 45 −66 36
FDMN Left medial frontal gyrus (10) 7.12 −6 47 11
Right medial frontal gyrus (10) 7.05 6 62 16
PDMN Left precuneus (31) 7.33 −6 −60 25
Right precuneus (7) 6.21 6 −67 50
Left posterior cingulate gyrus (23) 7.50 −3 −34 27
Right posterior cingulate gyrus (31) 7.80 9 −42 35
Left angular gyrus (39) 7.67 −45 −68 31
Right angular gyrus (39) 7.13 48 −71 37

INS, insula; ACC, anterior cingulate cortex; LCEN, left central executive network; RCEN, right central executive network; FDMN, frontal default mode network; PDMN, posterior default mode network.

3.2. Within-group correlations

Both groups displayed strongest maximal-lagged correlation in the same three inter-component comparisons: ACC-INS (healthy: r = 0.61 ± 0.12 (mean ± standard deviation); schizophrenia: r = 0.43 ± 0.22); INS-LCEN (healthy r = 0.57 ± 0.21; schizophrenia: r = 0.52 ± 0.20); FDMN-PDMN (healthy: r = 0.57 ± 0.17; schizophrenia: r = 0.55 ± 0.23). No significant correlation was observed between Fisher-transformed inter-component correlation coefficients and chlorpromazine equivalent dose of antipsychotic medication in the schizophrenia group.

3.3. Between-group FNC differences

Significantly reduced FNC was observed in schizophrenia compared to healthy individuals between the INS and ACC components (p = 0.039 FDR-corrected), with the INS response preceding the ACC response by approximately 0.5 s. Further significant reductions in FNC in schizophrenia were observed between the LCEN and PDMN (p = 0.013 FDR-corrected), with PDMN lagging LCEN response by approximately 1 s, and between INS and FDMN (p = 0.020 FDR-corrected), with INS activity lagging FDMN activity by approximately 0.1 s.

3.4. Between-group variation in FNC dynamics

Fig. 4 illustrates the temporal dynamics of ACC and FDMN activity relative to peak INS response. These were the components exhibiting a significant group difference in lagged correlation with INS. In both groups ACC activity consistently lags INS activity, with ACC peak occurring in the scan following peak INS response. A weak trend towards reduction in peak INS response amplitude was observed in schizophrenia compared to healthy individuals (p = 0.15, two-tailed). No significant between-group difference in INS-peak-locked ACC amplitude was observed (p = 0.79, two-tailed). FDMN amplitude was negative at the time of the INS peak in both groups. Fig. 5 illustrates that INS-peak-locked right and left CEN maxima lag the INS peak in both groups. CEN peak amplitudes did not significantly differ between the groups.

gr4

Fig. 4 Group mean insula peak-locked plots for the insula (INS), anterior cingulate cortex (ACC) and frontal default mode network (FDMN) components for healthy individuals (left) and individuals with schizophrenia (right). Dynamic numbers are shown relative to insula peak. Vertical black line denotes mean stimulus onset. Error bars denote standard error of the mean.

gr5

Fig. 5 Group mean insula peak-locked plots for the insula (INS), left central executive network (LCEN) and right central executive network (RCEN) components for healthy individuals (left) and individuals with schizophrenia (right). Dynamic numbers are shown relative to insula peak. Vertical black line denotes mean stimulus onset. Error bars denote standard error of the mean.

4. Discussion

The data presented here suggest a robust relationship between ACC and INS BOLD activity in healthy individuals implying the existence of a functional network and confirming this paper's first hypothesis. The ACC-INS comparison produced the strongest maximal-lagged correlation in healthy individuals. Furthermore, the temporal dynamic plots ( Fig. 4 ) and between-group FNC results imply that INS activity precedes ACC activity in healthy individuals suggesting a hierarchical arrangement to this network. It should be stressed that the insula foci are more posterior and lateral to previous findings ( Seeley et al., 2007 ), and that this component extends into superior temporal gyrus and opercular regions. This suggests that these additional areas should be included in the SN. Individuals with schizophrenia exhibit a significantly weaker relationship between INS and ACC activity, and dynamic plots from these individuals illustrate a trend towards attenuated INS peaks compared to healthy individuals. Reduced connectivity within the SN during information processing in schizophrenia suggests a pathophysiological disturbance to the system which effects changes between contextually-relevant functional brain states ( Sridharan et al., 2008 ). This system provides insight into salience response in a broad sense. Kapur (2004) postulated that inappropriate assignment of motivational salience and novelty, caused by an elevated striatal dopamine signal, is responsible for delusional thought in schizophrenia. The data here additionally highlight impairment to the proposed cortical salience response system. It is conceptually plausible that unusual or attenuated switching between functional brain states also underlies the disorganisation and psychomotor poverty dimensions of schizophrenic symptomatology ( Liddle, 1995 ).

Widespread reduction in maximal-lagged correlation between SN, CEN and DMN components was observed in schizophrenia. Between-group FNC analyses revealed significantly reduced correlation between ACC and INS in schizophrenia compared to healthy individuals. Significant reductions in lagged correlation were also observed for the FDMN-INS and LCEN-PDMN comparisons. These results provide further support for the notion of a generalised disconnection of remote brain processes in schizophrenia ( Friston and Frith, 1995 ). Furthermore, these results, in addition to the dynamic plots, provide empirical support for a schizophrenia-related cognitive dysmetria ( Andreasen et al., 1999 ), whereby the normal timing of coordinated mental processes is impaired.

The paper's second hypothesis, that SN activity would precede activity in other functional networks receives support from the dynamic plots involving INS-peak-locked CEN activity, in which CEN maxima consistently lag INS maxima ( Fig. 5 ). The robustness and lability of schizophrenia-related disruptions to connectivity between SN and other functional networks is currently unclear. While lagged-correlation analysis revealed a significantly reduced correlation between INS and FDMN timecourses in schizophrenia, between-group differences between SN components and CEN components did not reach significance.

Estimates of directional functional connectivity presented in this and previous fMRI work (for example, Sridharan et al., 2008 ) suggest a lag on the timescale of seconds between functional networks. Previous simulated data suggest that structure within functional networks varies on multiple timescales. Transfer entropy, a millisecond scale measure used to capture inter-region directed information flow, reveals functional networks which map well onto structural networks ( Honey et al., 2007 ). Variation in mean magnitude and frequency of transfer entropy measures occurs on the second scale. These fluctuations account for variation in functional connectivity on the second scale and reflect the itinerant nature of neuronal dynamics ( Honey et al., 2007 ). It is conceivable that connectivity between functional networks also varies on multiple timescales and that the lags presented here represent such variation. Conversely, the lag might reflect inter-region variation in vascular supply ( Zou et al., 2009 ). If the lag reflects vascular differences the absolute lag estimate is itself of little relevance to the sequence of neural events but if such a lag exists, the lagged correlation procedure would be expected to enhance the sensitivity with which correlations between neural activity in networks might be detected.

It is necessary to consider the possibility that the between-group differences reported here arise from treatment effects. Studies using positron emission tomography (PET; Lane et al, 2004 and Bartlett et al, 1994) have demonstrated that antipsychotic medication affects regional brain activity in healthy individuals. Nonetheless, many PET and fMRI studies of treatment effects have provided evidence that antipsychotic medications, especially atypical medication, tend to diminish abnormalities of regional brain activation during task performance in schizophrenia (Mendrek et al, 2004 and Bertolino et al, 2004). No significant correlation was observed between FNC measures and chlorpromazine equivalent dosage in the schizophrenia group. Investigation of FNC in medication naïve cases is required.

Overall, the findings presented in this work suggest the existence of a hierarchical salience network involving insula and ACC and further that activity in these structures precedes activity in other task-positive networks in accord with hypothesis (Fig 4 and Fig 5). Significantly weaker relationships were observed in schizophrenia both between SN subnetworks (INS and ACC) and between these subnetworks and other functional networks. These findings imply a plausible mechanism for several clinical features of the disorder and provide further detail to existing models of aberrant salience in schizophrenia.

Role of funding source

Funding for this study was provided by University of Nottingham; the University of Nottingham had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

Contributors

PFL, STF, TPW and VJ designed the study and wrote the protocol. TPW and VJ carried out the data collection and analyses. TPW and PFL undertook the statistical analysis, and TPW wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.

Conflicts of interest

PFL has received honoraria for lecturing in educational events sponsored by the Astra Zeneca, Eli Lilly, Bristol Meyers Squibb and Janssen Pharmaceuticals. None of the other authors have any conflicts of interest.

Acknowledgements

The authors would like to acknowledge the assistance of Ms. Kay Head during data acquisition and Dr. Eileen O'Regan in volunteer recruitment. The authors thank all of the participants for their involvement in this study.

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Footnotes

a Division of Psychiatry, University of Nottingham, A Floor, South Block, Queen's Medical Centre, Nottingham, NG7 2UH, United Kingdom

b Sir Peter Mansfield Magnetic Resonance Centre, University Park, University of Nottingham, Nottingham, NG7 2RD, United Kingdom

lowast Corresponding author. Permanent address: Division of Psychiatry, School of Community Health Sciences, University Park, University of Nottingham, Nottingham, NG7 2UH, United Kingdom.