Mapping prodromal psychosis: A critical review of neuroimaging studies

Institute of Psychiatry, Department of Psychosis Studies, London, UK.
European Psychiatry (Impact Factor: 3.44). 09/2011; 27(3):181-91. DOI: 10.1016/j.eurpsy.2011.06.006
Source: PubMed


The onset of schizophrenia is usually preceded by a prodromal phase characterized by functional decline and subtle prodromal symptoms, which include attenuated psychotic phenomena, cognitive deterioration and a decline in socio-occupational function. Preventive interventions during this phase are of great interest because of the impressive clinical benefits. However, available psychopathological criteria employed to define a high risk state for psychosis have low validity and specificity. Consequently there is an urgent need of reliable neurocognitive markers linked to the pathophysiological mechanisms that underlie schizophrenia. Neuroimaging techniques have rapidly developed into a powerful tool in psychiatry as they provide an unprecedented opportunity for the investigation of brain structure and function. This review shows that neuroimaging studies of the prodromal phases of psychosis have the potentials to identify core structural and functional markers of an impending risk to psychosis and to clarify the dynamic changes underlying transition to psychosis and to address significant correlations between brain structure or function and prodromal psychopathology. Additionally, neurochemical methods can address the key role played by neurotransmitters such as dopamine and glutamate during the psychosis onset. To conclude, multimodal neuroimaging may ultimately clarify the neurobiology of the prodromal phases by the integration of functional, structural and neurochemical findings.

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    • "Working memory deficits are considered to be a central manifestation of the pathophysiology of schizophrenia (Forbes et al., 2009) and behavioural deficits in working memory processing (Pflueger et al., 2007) are already evident before the onset of the disorder in individuals with an at-risk mental state (ARMS) (Fusar-Poli et al., 2012d). Alterations in functional brain activity (Smieskova et al., 2012a) during working memory processing have been reported in ARMS subjects. "
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    ABSTRACT: The psychosis high-risk state is accompanied by alterations in functional brain activity during working memory processing. We used binary automatic pattern-classification to discriminate between the at-risk mental state (ARMS), first episode psychosis (FEP) and healthy controls (HCs) based on n-back WM-induced brain activity. Linear support vector machines and leave-one-out-cross-validation were applied to fMRI data of matched ARMS, FEP and HC (19 subjects/group). The HC and ARMS were correctly classified, with an accuracy of 76.2% (sensitivity 89.5%, specificity 63.2%, p = 0.01) using a verbal working memory network mask. Only 50% and 47.4% of individuals were classified correctly for HC vs. FEP (p = 0.46) or ARMS vs. FEP (p = 0.62), respectively. Without mask, accuracy was 65.8% for HC vs. ARMS (p = 0.03) and 65.8% for HC vs. FEP (p = 0.0047), and 57.9% for ARMS vs. FEP (p = 0.18). Regions in the medial frontal, paracingulate, cingulate, inferior frontal and superior frontal gyri, inferior and superior parietal lobules, and precuneus were particularly important for group separation. These results suggest that FEP and HC or FEP and ARMS cannot be accurately separated in small samples under these conditions. However, ARMS can be identified with very high sensitivity in comparison to HC. This might aid classification and help to predict transition in the ARMS.
    Clinical neuroimaging 10/2015; DOI:10.1016/j.nicl.2015.09.015 · 2.53 Impact Factor
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    • "However, conversion rates vary across studies applying these criteria (Simon et al., 2011; Fusar-Poli et al., 2012a). Therefore, additional parameters have been investigated, including neuroimaging (Fusar-Poli et al., 2012b), neuropsychological (Becker et al., 2010; Fusar-Poli et al., 2012c; Pukrop and Ruhrmann, 2012), and neurophysiological measures (Shin et al., 2011). Particularly, event related potentials have been identified as potential biological predictors of psychosis, e.g. "
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    ABSTRACT: Background Prediction studies in subjects at Clinical High Risk (CHR) for psychosis are hampered by a high proportion of uncertain outcomes. We therefore investigated whether quantitative EEG (QEEG) parameters can contribute to an improved identification of CHR subjects with a later conversion to psychosis. Methods This investigation was a project within the European Prediction of Psychosis Study (EPOS), a prospective multicenter, naturalistic field study with an 18-month follow-up period. QEEG spectral power and alpha peak frequencies (APF) were determined in 113 CHR subjects. The primary outcome measure was conversion to psychosis. Results Cox regression yielded a model including frontal theta (HR = 1.82; [95% CI 1.00–3.32]) and delta (HR = 2.60; [95% CI 1.30–5.20]) power, and occipital–parietal APF (HR = .52; [95% CI .35–.80]) as predictors of conversion to psychosis. The resulting equation enabled the development of a prognostic index with three risk classes (hazard rate 0.057 to 0.81). Conclusions Power in theta and delta ranges and APF contribute to the short-term prediction of psychosis and enable a further stratification of risk in CHR samples. Combined with (other) clinical ratings, EEG parameters may therefore be a useful tool for individualized risk estimation and, consequently, targeted prevention.
    Schizophrenia Research 03/2014; 153(1-3). DOI:10.1016/j.schres.2014.01.019 · 3.92 Impact Factor
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    • "This incorporates information obtained from other modalities as regressors for whole-brain analyses and also allows voxel-wise multimodal correlation. BPM has been used widely for integrative analysis of different neuroimaging modalities (19–21). On the basis of our previous findings (17), we expected a direct relationship between perfusion and GM within the areas with the most marked hypoperfusion during the acute effects of heroin. "
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    ABSTRACT: Structure and function in the human healthy brain are closely related. In patients with chronic heroin exposure, brain imaging studies have identified long-lasting changes in gray matter (GM) volume. More recently, we showed that acute application of heroin in dependent pa-tients results in hypoperfusion of fronto-temporal areas compared with the placebo condition. However, the relationship between structural and cerebral blood flow (CBF) changes in heroin addiction has not yet been investigated. Moreover, it is not known whether there is any interaction between the chronic structural changes and the short and long term effects on per-fusion caused by heroin. Using a double-blind, within-subject design, heroin or placebo (saline) was administrated to 15 heroin-dependent patients from a stable heroin-assisted treat-ment program, in order to observe acute short-term effects. Arterial spin labeling (ASL) was used to calculate perfusion quantification maps in both treatment conditions, while Voxel Based Morphometry (VBM) was conducted to calculate regional GM density. VBM and ASL data were used to calculate homologous correlation fields by Biological Parametric Mapping (BPM). We correlated each perfusion condition (heroin and placebo) separately with a VBM sample that was identical for the two treatment conditions. It was assumed that heroin-associated perfusion is manifested in short term effects, while placebo-associated perfusion is more related to long term effects. Correlation analyses revealed a significant positive correlation in frontal and temporal areas between GM and both perfusion conditions (heroin and placebo). The heroin-associated perfusion was also negatively correlated with GM in the left thalamus and right cuneus. These findings indicate that, in heroin-dependent patients, low GM volume is positively associated with low perfusion within fronto-temporal regions.
    Frontiers in Psychiatry 10/2013; 4:135. DOI:10.3389/fpsyt.2013.00135
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May 21, 2014