Clinical utility of magnetic resonance imaging in first-episode psychosis.

There is no consensus as to whether magnetic resonance imaging (MRI) should be used as part of the initial clinical evaluation of patients with first-episode psychosis (FEP).(a) To assess the logistical feasibility of routine MRI; (b) to define the clinical significance of radiological abnormalities in patients with FEP.Radiological reports from MRI scans of two FEP samples were reviewed; one comprised 108 patients and 98 healthy controls recruited to a research study and the other comprised 241 patients scanned at initial clinical presentation plus 66 healthy controls.

Network-Level Dysconnectivity in Drug-Naïve First-Episode Psychosis: Dissociating Transdiagnostic and Diagnosis-Specific Alterations.

The neuroimaging literature provides compelling evidence for functional dysconnectivity in people with psychosis. However, it is likely that at least some of the observed alterations represent secondary effects of illness chronicity and/or antipsychotic medication. In addition, the extent to which these alterations are specific to psychosis or represent a transdiagnostic feature of psychiatric illness remains unclear.

Does neuroanatomy account for superior temporal dysfunction in early psychosis? A multimodal MRI investigation.

Background: Neuroimaging studies of ultra-high risk (UHR) and first-episode psychosis (FEP) have revealed widespread alterations in brain structure and function. Recent evidence suggests there is an intrinsic relationship between these 2 types of alterations; however, there is very little research linking these 2 modalities in the early stages of psychosis.

Methods: To test the hypothesis that functional alteration in UHR and FEP articipants would be associated with corresponding structural alteration, we examined brain function and structure in these participants as well as in a group of healthy controls using multimodal MRI.

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine.

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions.

Using structural neuroimaging to make quantitative predictions of symptom progression in individuals at ultra-high risk for psychosis.

Neuroimaging holds the promise that it may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups, which do not permit accurate inferences at the level of the individual. We examined the potential of structural Magnetic Resonance Imaging (MRI) data for making accurate quantitative predictions about symptom progression in individuals at ultra-high risk for developing psychosis.

Auditory verbal hallucinations and brain dysconnectivity in the perisylvian language network: a multimodal investigation.

Neuroimaging studies of schizophrenia have indicated that the development of auditory verbal hallucinations (AVHs) is associated with altered structural and functional connectivity within the perisylvian language network. However, these studies focussed mainly on either structural or functional alterations in patients with chronic schizophrenia. Therefore, they were unable to examine the relationship between the 2 types of measures and could not establish whether the observed alterations would be expressed in the early stage of the illness.

The effects of psychotherapy on brain function: a systematic and critical review.

Over the past two decades, the development of neuroimaging techniques has allowed the non-invasive investigation of neuroplastic changes associated with psychotherapeutic treatment. The aim of the present article is to present a systematic and critical review of longitudinal studies addressing the impact of psychotherapy on the brain published to date. After summarizing the results reported in the literature for each psychiatric disorder separately (i.

Elucidating neuroanatomical alterations in the at risk mental state and first episode psychosis: a combined voxel-based morphometry and voxel-based cortical thickness study.

Previous studies have reported alterations in grey matter volume and cortical thickness in individuals at high risk of developing psychosis and patients in the early stages of the disorder. Because these studies have typically focused on either grey matter volume or cortical thickness separately, the relationship between these two types of alterations is currently unclear. In the present investigation we used both voxel-based cortical thickness (VBCT) and voxel-based morphometry (VBM) to examine neuroanatomical differences in 21 individuals with an At Risk Mental State (ARMS) for psychosis, 26 patients with a First Episode of Psychosis (FEP) and 24 healthy controls.

Quantitative prediction of individual psychopathology in trauma survivors using resting-state FMRI.

Neuroimaging techniques hold the promise that they may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups. This study employed a multivariate approach to examine the potential of resting-state functional magnetic resonance imaging (MRI) data for making accurate predictions about psychopathology in survivors of the 2008 Sichuan earthquake at an individual level.

Pattern classification of brain activation during emotional processing in subclinical depression: psychosis proneness as potential confounding factor.

We used Support Vector Machine (SVM) to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II). Two groups were subsequently formed: (i) subclinical (mild) mood disturbance (n = 17) and (ii) no mood disturbance (n = 17).

Attentional modulation of source attribution in first-episode psychosis: a functional magnetic resonance imaging study.

Background: In patients with schizophrenia, the misattribution of self-generated events to an external source is associated with the presence of psychotic symptoms. The aim of this study was to investigate how this misattribution is influenced by dysfunction of attentional processing, which is also impaired in schizophrenia.

Methods: Participants underwent functional Magnetic Resonance Imaging (fMRI) while listening to prerecorded speech.

Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review.

Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical and functional differences between healthy individuals and patients suffering a wide range of neurological and psychiatric disorders. Significant only at group level however these findings have had limited clinical translation, and recent attention has turned toward alternative forms of analysis, including Support-Vector-Machine (SVM). A type of machine learning, SVM allows categorisation of an individual's previously unseen data into a predefined group using a classification algorithm, developed on a training data set.

Multivariate pattern classification reveals differential brain activation during emotional processing in individuals with psychosis proneness.

Among the general population, individuals with subthreshold psychotic-like experiences, or psychosis proneness (PP), can be psychometrically identified and are thought to have a 10-fold increased risk of psychosis. They also show impairments in measures of emotional functioning parallel to schizophrenia. Whilst previous studies have revealed altered brain activation in patients with schizophrenia during emotional processing, it is unclear whether these alterations are also expressed in individuals with high PP.

Dysconnectivity in schizophrenia: where are we now?

The disconnection hypothesis suggests that the core symptoms of schizophrenia (SZ) are related to aberrant, or 'dys-', connectivity between distinct brain regions. A proliferation of functional and structural neuroimaging studies have been conducted to investigate this hypothesis, across the full course of the disorder; from people at Ultra-High-Risk of developing psychosis to patients with chronic SZ. However the results of these studies have not always been consistent, and to date, there have been no attempts to summarise the results of both methodologies in conjunction.

Genetic variation in neuregulin1 is associated with differences in prefrontal engagement in children.

The majority of psychopathology is rooted early in life and first emerges during childhood and adolescence. However, little is known about how risk genes affect brain function to increase biological vulnerability to psychopathology in childhood, because most imaging genetic studies published so far have been conducted on adult participants. We examined the impact of neuregulin1 (NRG1), a probable susceptibility gene for schizophrenia and bipolar disorder, on brain function in a sample of 102 ten- to twelve-year-old children.