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Male, A. G.

Publications and source records attributed to Male, A. G..

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Neuroanatomical Correlates of Negative Symptoms in Schizophrenia

BackgroundSchizophrenia is characterized by widespread structural brain abnormalities, but associations between structural abnormalities and negative symptom severity are not well understood. Negative symptoms have been conceptualized in a hierarchical structure of two second-order dimensions--motivation and pleasure (MAP) and expression (EXP)--and five first-order domains: anhedonia, avolition, and asociality (MAP), and blunted affect and alogia (EXP). A better understanding of the neural circuitry underlying negative symptom dimensions and domains is important given their reported association with poor functional outcome and lack of available treatments. Study DesignThe meta-analysis included 1,591 individuals with schizophrenia across 16 samples with structural imaging and Scale for Assessment of Negative Symptoms data. The study generated correlations of cortical thickness and subcortical volumes with the negative symptom dimensions and domains. Study resultsNegative symptoms showed mainly negative associations with cortical thickness and subcortical volumes. The effect sizes were small but there was a pattern of associations in predominantly frontal lobe cortical thickness and limbic subcortical volumes. The regional correlation patterns of cortical thickness and subcortical volumes with symptom domains support the conceptualized hierarchical structure of negative symptoms: correlations of MAP domains were stronger with the MAP than EXP dimension, and vice versa. Exploratory analyses with receptor densities further supported the hierarchy. ConclusionOur findings reveal small but consistent associations between negative symptom dimensions and predominantly prefrontal region cortical thickness, and limbic region volumes. These findings advance our understanding of the network of anatomical regions that may contribute to the severity of negative symptoms in schizophrenia.

neuroscience↗

Unattended visual stimuli do not produce prediction error responses despite being initially encoded

Prediction error is a basic component of predictive-coding theory of brain processing. According to the theory, each stage of brain processing of sensory information generates a model of the current sensory input; subsequent input is compared against the model and only if there is a mismatch, a prediction error, is further processing performed. Recently, Smout et al. [1] found that a signature of prediction error, the visual (v) mismatch negativity (MMN), for a fundamental property of visual input--its orientation--was absent without attention on the stimuli. This is remarkable because the weight of evidence for MMNs from audition and vision is that they occur without attention. To resolve this discrepancy, we conducted an experiment addressing two alternative explanations for Smout et al.s finding: that it was from a lack of reproducibility or that participants visual systems did not encode the stimuli when attention was on something else. We conducted a similar experiment to Smout et al.s. We showed 21 participants sequences of identically oriented Gabor patches, standards, and, unpredictably, otherwise identical, Gabor patches differing in orientation by {+/-}15{degrees}, {+/-}30{degrees}, and {+/-}60{degrees}, deviants. To test whether participants encoded the orientation of the standards, we varied the numbers of standards preceding a deviant, allowing us to search for a decrease in activity with the number of repetitions of standards--repetition suppression. We diverted participants attention from the oriented stimuli with a central, letter-detection task. We reproduced Smout et al.s finding of no vMMN without attention, strengthening their finding. We also found that our participants showed repetition suppression: they did encode the stimuli pre-attentively. We also found early processing of deviants. We discuss whether this earlier processing of deviants may be why no further processing, in the vMMN time window, occurs.

neuroscience↗