Author Correction: Intersensory attention deficits in schizophrenia relate to ongoing sensorimotor beta oscillations
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Intersensory attention deficits in schizophrenia relate to ongoing sensorimotor beta oscillations
This study tested whether intersensory attention deficits in people with schizophrenia (SZ) relate to aberrant ongoing oscillations in sensory cortices. Electroencephalography (EEG) was recorded while individuals with schizophrenia (N = 27) and healthy controls (HC; N = 27) performed a visual-tactile target detection task. Ongoing alpha (8–12 Hz) and lower beta (13–20 Hz) band oscillations in visual and sensorimotor cortices were examined. Behavioral data suggested an intersensory attention deficit in patients. EEG data revealed stronger alpha-band oscillations for tactile vs. visual attention conditions in the visual cortex of both study groups. In the sensorimotor cortex contralateral to the tactile stimulation site, patients showed an additional intersensory attention effect in ongoing beta-band oscillations, which was negatively related to cognitive and positive symptoms of the PANSS. Our findings extend previous results from unisensory attention research and suggest that deficits in intersensory attention and alterations in sensorimotor beta oscillations are related to schizophrenia symptomatology.
Shared genetic architecture and causal relationship between frailty and schizophrenia
The complex relationship between frailty and schizophrenia has yet to be fully understood. This study aims to clarify their relationship by investigating their genetic links. We hypothesize a shared genetic architecture and a bidirectional causal relationship between the two conditions. Utilizing summary genetic data from European genome-wide association studies, we analyzed genetic associations through global and local correlations, shared genomic loci, tissue enrichments, and functional genes. Bidirectional Mendelian Randomization (MR) was employed to infer causality. Our findings show a positive genetic correlation between frailty and schizophrenia (LDSC: rg = 0.117, p = 6.686 × 10−7; HDL: rg = 0.101, p = 5.63 × 10−13) and local correlations in three genomic regions (chr9: 94167203-96671698, p = 2.21 × 10−6; chr11: 112459488-114257728, p = 1.01 × 10−5; and chr18: 77149991-78017158, p = 9.57 × 10−6). We identified 111 genomic loci associated with both conditions and demonstrated that genetic variants for frailty and schizophrenia share tissue enrichments and functional genes in brain. MR analysis suggests that frailty increases the likelihood of schizophrenia (OR: 1.763, 95% CI: 1.259–2.468, p = 0.001) and vice versa (β: 0.012, 95% CI: 0.006–0.018, p < 0.001). Our research supports the presence of a shared genetic basis and bidirectional causality between frailty and schizophrenia. These findings necessitate further investigation in diverse populations to confirm and expand on this genetic understanding.
Along-tract white matter abnormalities and their clinical associations in recent-onset and chronic schizophrenia
Structural impairments in white matter tracts are well-documented in schizophrenia, though their clinical implications remain limited. Most previous studies using diffusion-weighted magnetic resonance imaging (dMRI) and tractography relied on averaged diffusion indices, potentially obscuring localized changes in white matter tracts. Tractometry enables the investigation of localized changes at specific points along white matter tracts. We used dMRI and centerline tractometry to examine along-tract white matter abnormalities in 55 patients with recent-onset schizophrenia, 69 with chronic schizophrenia, and 77 healthy controls. Fractional anisotropy (FA) and peak length were measured at individual points along tract trajectories. Group differences in diffusion indices and their associations with clinical variables, including the Positive and Negative Syndrome Scale (PANSS), were analyzed using linear mixed models and Spearman’s rho. In recent-onset schizophrenia, reduced FA was observed in the genu and splenium of the corpus callosum, along with deviations in peak length across multiple white matter tracts. The peak length of association tracts showed a negative correlation with antipsychotic dose. In chronic schizophrenia, widespread reductions in FA and deviations in peak length were identified across various white matter tracts. Decreased FA in commissural tracts was negatively associated with the PANSS negative score, antipsychotic dose, and illness duration. This study identified along-tract white matter abnormalities in recent-onset and chronic schizophrenia and revealed their associations with clinical symptoms. Localized measurements along tract trajectories enhance the detection of clinically relevant abnormalities compared to traditional methods relying on averaged diffusion indices.
Weaker top-down cognitive control and stronger bottom-up signaling transmission as a pathogenesis of schizophrenia
The clinical symptoms of schizophrenia are highly heterogeneous, with the most striking symptoms being cognitive deficits and perceptual disturbances. Cognitive deficits are typically linked to abnormalities in top-down mechanisms, whereas perceptual disturbances stem from dysfunctions in bottom-up processing. However, it remains unclear whether schizophrenia is primarily driven by top-down control mechanisms, bottom-up perceptual processes, or their interaction. We hypothesized that abnormal top-down and bottom-up interactions constitute the neural mechanisms of schizophrenia. Considering that autoencoders can identify hidden data features and support vector machines are capable of automatically locating the classification hyperplane, we developed an improved stacked autoencoder-support vector machine (ISAE-SVM) model for diagnosing schizophrenia based on resting-state functional magnetic resonance imaging data. A permutation test was used to identify the 213 most discriminative functional connections from the model’s output features. Functional connections linking regions of higher cognitive functions and lower perceptual tasks were extracted to further examine their relevance to clinical symptoms. Finally, spectral dynamic causal modeling (sDCM) was used to analyze the dynamic causal interaction between brain regions corresponding to these functional connections. Our results showed that the ISAE-SVM model achieved an average classification accuracy of 82%. Notably, five resting-state functional connections spanning both cognitive and sensory brain areas were significantly correlated with Positive and Negative Syndrome Scale scores. Furthermore, sDCM analysis revealed weakened top-down regulation and enhanced bottom-up signaling in schizophrenia. These findings support our hypothesis that impaired top-down regulation and enhanced bottom-up signaling contribute to the neural mechanisms of schizophrenia.
Bridging the gap between aberrant time processing and cognitive dysfunction in schizophrenia: a potential core feature?
Historical context The study of temporal perception and its disruptions in schizophrenia has long been studied in experimental psychology. As early as the late 19th…
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