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1. Value-directed remembering in first-episode schizophrenia.

   https://doi.org/10.1037/neu0000840  

   Patterson, Tara K. ; Nuechterlein, Keith H. ; Subotnik, Kenneth L. ; Castel, Alan D. ; Knowlton, Barbara J. ( June 2022 , Neuropsychology)
2. Heart Rate Variability in Schizophrenia and Autism

   https://doi.org/10.3389/fpsyt.2021.760396  

   Haigh, Sarah M. ; Walford, Tabatha P. ; Brosseau, Pat ( November 2021 , Frontiers in Psychiatry)

   Suppressed heart rate variability (HRV) has been found in a number of psychiatric conditions, including schizophrenia and autism. HRV is a potential biomarker of altered autonomic functioning that can predict future physiological and cognitive health. Understanding the HRV profiles that are unique to each condition will assist in generating predictive models of health. In the current study, we directly compared 12 adults with schizophrenia, 25 adults with autism, and 27 neurotypical controls on their HRV profiles. HRV was measured using an electrocardiogram (ECG) channel as part of a larger electroencephalography (EEG) study. All participants also completed the UCLA Loneliness Questionnaire as a measure of social stress. We found that the adults with schizophrenia exhibited reduced variability in R-R peaks and lower low frequency power in the ECG trace compared to controls. The HRV in adults with autism was slightly suppressed compared to controls but not significantly so. Interestingly, the autism group reported feeling lonelier than the schizophrenia group, and HRV did not correlate with feelings of loneliness for any of the three groups. However, suppressed HRV was related to worse performance on neuropsychological tests of cognition in the schizophrenia group. Together, this suggests that autonomic functioning is more abnormal in schizophrenia than in autism and could be reflecting health factors that are unique to schizophrenia. 

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3. Oculomotor inhibition and location priming in schizophrenia.

   https://doi.org/10.1037/abn0000683  

   Bansal, Sonia ; Gaspelin, Nicholas ; Robinson, Benjamin M ; Hahn, Britta ; Luck, Steven J ; Gold, James M ( August 2021 , Journal of Abnormal Psychology)
4. Nonlinear dynamics underlying sensory processing dysfunction in schizophrenia

   https://doi.org/10.1073/pnas.1810572116  

   Lainscsek, Claudia ; Sampson, Aaron L. ; Kim, Robert ; Thomas, Michael L. ; Man, Karen ; Lainscsek, Xenia ; The COGS Investigators ; Swerdlow, Neal R. ; Braff, David L. ; Sejnowski, Terrence J. ; et al ( February 2019 , Proceedings of the National Academy of Sciences)

   Natural systems, including the brain, often seem chaotic, since they are typically driven by complex nonlinear dynamical processes. Disruption in the fluid coordination of multiple brain regions contributes to impairments in information processing and the constellation of symptoms observed in neuropsychiatric disorders. Schizophrenia (SZ), one of the most debilitating mental illnesses, is thought to arise, in part, from such a network dysfunction, leading to impaired auditory information processing as well as cognitive and psychosocial deficits. Current approaches to neurophysiologic biomarker analyses predominantly rely on linear methods and may, therefore, fail to capture the wealth of information contained in whole EEG signals, including nonlinear dynamics. In this study, delay differential analysis (DDA), a nonlinear method based on embedding theory from theoretical physics, was applied to EEG recordings from 877 SZ patients and 753 nonpsychiatric comparison subjects (NCSs) who underwent mismatch negativity (MMN) testing via their participation in the Consortium on the Genetics of Schizophrenia (COGS-2) study. DDA revealed significant nonlinear dynamical architecture related to auditory information processing in both groups. Importantly, significant DDA changes preceded those observed with traditional linear methods. Marked abnormalities in both linear and nonlinear features were detected in SZ patients. These results illustrate the benefits of nonlinear analysis of brain signals and underscore the need for future studies to investigate the relationship between DDA features and pathophysiology of information processing.

    

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5. Computational modeling of excitatory/inhibitory balance impairments in schizophrenia

   https://doi.org/10.1016/j.schres.2020.03.027  

   Qian, Ning ; Lipkin, Richard M. ; Kaszowska, Aleksandra ; Silipo, Gail ; Dias, Elisa C. ; Butler, Pamela D. ; Javitt, Daniel C. ( April 2020 , Schizophrenia Research)

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