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Guillermo Horga

2 papers in the library · 140 citations · publishing 2016-2020

Papers

Auditory Hallucinations and the Brain’s Resting-State Networks: Findings and Methodological Observations

Schizophrenia Bulletin June 8, 2016 Ben Alderson‐day, Kelly Diederen, Charles Fernyhough et al. 134 citations

Resting-state brain networks may help explain hallucinations across different sensory modalities and populations. This report from the International Consortium on Hallucination Research reviews evidence linking resting-state alterations to auditory hallucinations, finding connectivity differences in left-hemisphere auditory and language regions, plus atypical interactions of the default mode network with networks for cognitive control and salience. Similar patterns appear in visual hallucinations, suggesting both domain-general and modality-specific network changes. However, high methodological heterogeneity across studies limits direct comparisons. The authors offer recommendations for future research on resting-state connectivity and hallucinations.

Distinct Hierarchical Alterations of Intrinsic Neural Timescales Account for Different Manifestations of Psychosis

bioRxiv Preprint Server February 7, 2020 Kenneth Wengler, Andrew T. Goldberg, George Chahine et al. 6 citations preprint

Hallucinations and delusions in schizophrenia may arise from distinct alterations in how the brain integrates information over time across different levels of sensory processing hierarchies. Using resting-state fMRI to measure intrinsic neural timescale (INT), which reflects the time window of neural integration, researchers found that hallucinations were linked to altered INT in lower auditory and somatosensory regions, while delusions were associated with changes in higher hierarchical areas. Computer simulations suggested that local imbalances between excitation and inhibition at different hierarchical levels could underlie these patterns. The findings support hierarchical perceptual-inference models of psychosis and demonstrate INT as a useful tool for studying brain hierarchies.