F López-Caballero, B A Coffman, M Curtis, A L Sklar, S Yi, D F Salisbury
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引用次数: 0
Abstract
Predicting symptom progression in first-episode psychosis (FEP) is crucial for tailoring treatment and improving outcomes. Temporal lobe function, indicated by neurophysiological biomarkers like N100, predicts symptom progression and correlates with untreated psychosis. Our recent report showed that source-localized magnetoencephalography (MEG) M100 responses to tones in an oddball paradigm predicted recovery in FEP positive symptoms. This study expands these results with a simpler single-tone paradigm, with both MEG and EEG, and measuring associations across symptom dimensions. We recorded MEG (M100) and EEG (N100) in 29 FEP individuals and assessed symptom severity at baseline and after ∼ 7 months using the Positive and Negative Syndrome Scale (PANSS). Sequential regression analyses predicted symptom change (ΔPANSS) from Duration of untreated Active Psychosis (DAP) and baseline M100, controlling for baseline symptoms. Identical regressions were conducted in a subsample measuring N100 with EEG (n = 24). Smaller baseline M100 predicted worse symptom recovery at follow-up, independent of baseline symptom severity. Longer DAP showed a similar predictive effect, but this relationship was accounted for by M100. Regressions revealed M100 predictions were mostly related to general psychopathology. Identical results were found for N100 measured with EEG. Temporal lobe dysfunction in FEP, especially poor auditory sensory processing, indicates a worse recovery trajectory in general psychopathology. Longer untreated psychosis worsens temporal lobe function, predicting poorer progression. N100 measured with EEG and a single-tone task could be a cost-effective tool for informing clinicians about overall symptom progression, guiding treatment resource allocation and interventions.
期刊介绍:
NeuroImage: Clinical, a journal of diseases, disorders and syndromes involving the Nervous System, provides a vehicle for communicating important advances in the study of abnormal structure-function relationships of the human nervous system based on imaging.
The focus of NeuroImage: Clinical is on defining changes to the brain associated with primary neurologic and psychiatric diseases and disorders of the nervous system as well as behavioral syndromes and developmental conditions. The main criterion for judging papers is the extent of scientific advancement in the understanding of the pathophysiologic mechanisms of diseases and disorders, in identification of functional models that link clinical signs and symptoms with brain function and in the creation of image based tools applicable to a broad range of clinical needs including diagnosis, monitoring and tracking of illness, predicting therapeutic response and development of new treatments. Papers dealing with structure and function in animal models will also be considered if they reveal mechanisms that can be readily translated to human conditions.