Search

Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mechanisms underlying AH in schizophrenia may offer insight into the pathophysiology associated with AH more broadly across multiple neuropsychiatric disease conditions. In this paper, we address the problem of classifying schizophrenia patients with and without a history of AH, and healthy control (HC) subjects. To this end, we performed feature extraction from resting state functional magnetic resonance imaging (rsfMRI) data and applied machine learning classifiers, testing two kinds of neuroimaging features: (a) functional connectivity (FC) measures computed by lattice auto-associative memories (LAAM), and (b) local activity (LA) measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF). We show that it is possible to perform classification within each pair of subject groups with high accuracy. Discrimination between patients with and without lifetime AH was highest, while discrimination between schizophrenia patients and HC participants was worst, suggesting that classification according to the symptom dimension of AH may be more valid than discrimination on the basis of traditional diagnostic categories. FC measures seeded in right Heschl's gyrus (RHG) consistently showed stronger discriminative power than those seeded in left Heschl's gyrus (LHG), a finding that appears to support AH models focusing on right hemisphere abnormalities. The cortical brain localizations derived from the features with strong classification performance are consistent with proposed AH models, and include left inferior frontal gyrus (IFG), parahippocampal gyri, the cingulate cortex, as well as several temporal and prefrontal cortical brain regions. Overall, the observed findings suggest that computational intelligence approaches can provide robust tools for uncovering subtleties in complex neuroimaging data, and have the potential to advance the search for more neuroscience-based criteria for classifying mental illness in psychiatry research.

Background: Mood disturbances in methamphetamine (MA) abusers likely influence drug use, but the neurobiological bases for these problems are poorly understood., Objective: To assess regional brain function and its possible relationships with negative affect in newly abstinent MA abusers., Design: Two groups were compared by measures of mood and cerebral glucose metabolism ([18F]fluorodeoxyglucose positron emission tomography) during performance of a vigilance task., Setting: Participants were recruited from the general community to a research center., Participants: Seventeen abstaining (4-7 days) MA abusers (6 women) were compared with 18 control subjects (8 women)., Main Outcome Measures: Self-reports of depressive symptoms and anxiety were measured, as were global and relative glucose metabolism in the orbitofrontal, cingulate, lateral prefrontal, and insular cortices and the amygdala, striatum, and cerebellum., Results: Abusers of MA provided higher self-ratings of depression and anxiety than control subjects and differed significantly in relative regional glucose metabolism: lower in the anterior cingulate and insula and higher in the lateral orbitofrontal area, middle and posterior cingulate, amygdala, ventral striatum, and cerebellum. In MA abusers, self-reports of depressive symptoms covaried positively with relative glucose metabolism in limbic regions (eg, perigenual anterior cingulate gyrus and amygdala) and ratings of state and trait anxiety covaried negatively with relative activity in the anterior cingulate cortex and left insula. Trait anxiety also covaried negatively with relative activity in the orbitofrontal cortex and positively with amygdala activity., Conclusions: Abusers of MA have abnormalities in brain regions implicated in mood disorders. Relationships between relative glucose metabolism in limbic and paralimbic regions and self-reports of depression and anxiety in MA abusers suggest that these regions are involved in affective dysregulation and may be an important target of intervention for MA dependence.