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Guiral JA. Neuropsychological dimensions related to alterations of verbal self-monitoring neural networks in schizophrenic language: systematic review. Front Psychiatry 2024; 15:1356726. [PMID: 38501094 PMCID: PMC10944891 DOI: 10.3389/fpsyt.2024.1356726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 01/23/2024] [Indexed: 03/20/2024] Open
Abstract
Although schizophrenia has traditionally been interpreted as a disorder of thought, contemporary perspectives suggest that it may be more appropriate to conceptualize it as a disorder of language connectivity. The linguistic anomalies present in schizophrenia possess distinctive characteristics that, despite certain connections, are not comparable to aphasic disorders. It is proposed that these anomalies are the result of dysfunctions in verbal self-monitoring mechanisms, which may influence other neuropsychological dimensions. This study set out to examine the neuropsychological dimensions associated with alterations in the neural networks of verbal self-monitoring in schizophrenic language, based on the scientific evidence published to date. Exhaustive searches were conducted in PubMed, Web of Science, and Scopus to identify magnetic resonance studies that evaluated verbal self-monitoring mechanisms in schizophrenia. Of a total of 133 articles identified, 22 were selected for qualitative analysis. The general findings indicated alterations in frontotemporoparietal networks and in systems such as the insula, amygdala, anterior cingulate cortex, putamen, and hippocampus. Despite the heterogeneity of the data, it is concluded that language plays a fundamental role in schizophrenia and that its alterations are linked with other neuropsychological dimensions, particularly emotional and perceptual ones.
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Affiliation(s)
- Julián Andrés Guiral
- Humanities, EAFIT University, Medellín, Colombia
- Instituto de Neuropsicología y Lenguaje, EAFIT University, Medellín, Colombia
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Xu L, Hong X, Tang Y, Cui H, Wei Y, Qian Z, Su W, Tang X, Hu Y, Zhang D, Zheng W, Wang Y, Hu H, Zhu J, Zhang T, Wang J. Direct and indirect effects of error monitoring on social functioning in a cohort with high-risk and first-episode psychosis. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110904. [PMID: 38036033 DOI: 10.1016/j.pnpbp.2023.110904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/09/2023] [Accepted: 11/24/2023] [Indexed: 12/02/2023]
Abstract
Error monitoring plays a key role in people's adjustment to social life. This study aimed to examine the direct (DE) and indirect effects (IDE) of error monitoring, as indicated by error-related negativity (ERN), on social functioning in a clinical cohort from high-risk (APS) to first-episode psychosis (FEP). This study recruited 100 outpatients and 49 healthy controls (HC). ERN was recorded during a modified flanker task; social functioning was evaluated using the social scale of global functioning. The path analysis was executed using the "lavaan" package. When controlling for age and education, the clinical cohort had a smaller ERN than the HC group (F1, 145 = 19.58, p < 0.001, partial η2 = 0.12, 95%CI: 0.04-0.22). ERN demonstrated no substantial direct impact on current social functioning; however, it manifested indirect influences on social functioning via the disorganization factor of the Positive and Negative Syndrome Scale, both with (standardized IDE: -0.139, p = 0.009) and without (standardized IDE: -0.087, p = 0.018) accounting for the diagnosis, defined as a dummy variable (FEP = 1 and APS = 0) and included as a covariate. These findings suggest that error monitoring, as indicated by ERN, may serve as a potential prognostic indicator of social functioning in patients with psychosis.
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Affiliation(s)
- LiHua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - XiangFei Hong
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - YingYing Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - HuiRu Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - YanYan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - ZhenYing Qian
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - WenJun Su
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - XiaoChen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - YeGang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - Dan Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - WenSi Zheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - YingChan Wang
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - Hao Hu
- Department of Early Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - JunJuan Zhu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - TianHong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China; Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - JiJun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai 201203, PR China; Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, PR China.
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Xu L, Zhu T, Tang Y, Tang X, Qian Z, Wei Y, Cui H, Hu Y, Zhang D, Wang Y, Zhu J, Li H, Liu X, Zhang T, Hong X, Wang J. Impaired insight and error-monitoring deficits among outpatients with attenuated psychosis syndrome and first-episode psychosis. J Psychiatr Res 2024; 170:33-41. [PMID: 38101208 DOI: 10.1016/j.jpsychires.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 11/23/2023] [Accepted: 12/06/2023] [Indexed: 12/17/2023]
Abstract
We aimed to determine the relationship between electrophysiological signatures of error monitoring and clinical insight among outpatients with attenuated psychosis syndrome (APS) and first-episode psychosis (FEP). Error-related negativity (ERN), error positivity (Pe), and correct response negativity (CRN) were recorded during a modified flanker task for patients with FEP (n = 32), APS individuals (n = 58), and healthy controls (HC, n = 49). Clinical insight was measured using the Schedule of Assessment of Insight (SAI) and included awareness of illness (SAI-illness), relabeling of specific symptoms (SAI-symptoms), and treatment compliance (SAI-treatment). Compared with HC, patients with FEP showed smaller ERN (p < 0.001) and Pe (p = 0.011) amplitudes and individuals with APS showed smaller ERN amplitude (p = 0.009). No significant difference in CRN amplitude was observed among the groups. A smaller negative amplitude of ERN correlated with a lower score on SAI-symptoms (b = -0.032, 95% CI: 0.062 to -0.002, p = 0.035) and a decreased total score of SAI (b = -0.096, 95% CI: 0.182 to -0.010, p = 0.029). This links were adjusted for age, education, and diagnosis (a dummy variable with FEP = 1 and APS = 0), and was independent of positive symptoms. SAI-illness was predominantly influenced by diagnosis, whereas SAI-treatment was additionally affected by disorganized communications. Neither Pe nor CRN amplitude exhibited an association with clinical insight. Unconscious error detection, as indicated by ERN, may aid individuals at the preliminary stage of psychosis in recognizing the unusual symptoms.
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Affiliation(s)
- LiHua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - TianYuan Zhu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - YingYing Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - XiaoChen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - ZhenYing Qian
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - YanYan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - HuiRu Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - YeGang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Dan Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - YingChan Wang
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - JunJuan Zhu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Hui Li
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - XiaoHua Liu
- Department of Early Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - TianHong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China; Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China.
| | - XiangFei Hong
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China.
| | - JiJun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, 201203, PR China; Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, 200030, PR China.
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Kirschner H, Klein TA. Beyond a blunted ERN - Biobehavioral correlates of performance monitoring in schizophrenia. Neurosci Biobehav Rev 2021; 133:104504. [PMID: 34922988 DOI: 10.1016/j.neubiorev.2021.12.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 12/02/2021] [Accepted: 12/15/2021] [Indexed: 12/12/2022]
Abstract
Cognitive deficits are well documented in schizophrenia. Here, we reviewed alterations in performance monitoring as potential marker of cognitive deficits in schizophrenia. We found that performance monitoring alterations in schizophrenia are specific to early (indexed by blunted error-related negativity (ERN)) and late (reflected in blunted error positivity (Pe)) internal error processing, while external performance feedback processing in simple response feedback tasks is relatively preserved. We propose, that these performance monitoring deficits may best be interpret as one aspect of disrupted theta band (4-8 Hz) oscillations over medial frontal recordings sites. Midfrontal theta dynamics are an increasingly established direct neural index of the recruitment of cognitive control and are impaired in several clinical populations. While theta-related ERPs (the ERN) may be an easy to assess marker of cognitive deficits in schizophrenia, further work investigating the trial-by-trial dynamics of theta in both the time and time-frequency domain is needed to parse cognitive deficits in schizophrenia into finer levels of detail and evaluate theta modulation as a therapeutic tool.
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Affiliation(s)
- H Kirschner
- Institute of Psychology, Otto-von-Guericke University, D-39106, Magdeburg, Germany.
| | - T A Klein
- Institute of Psychology, Otto-von-Guericke University, D-39106, Magdeburg, Germany; Center for Behavioral Brain Sciences, D-39106, Magdeburg, Germany.
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Frontal neural metabolite changes in schizophrenia and their association with cognitive control: A systematic review. Neurosci Biobehav Rev 2021; 132:224-247. [PMID: 34864431 PMCID: PMC8830497 DOI: 10.1016/j.neubiorev.2021.11.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 11/05/2021] [Accepted: 11/09/2021] [Indexed: 01/01/2023]
Abstract
GABA levels are decreased in medial frontal brain areas of schizophrenia patients. Glutamate levels are lower in medial and lateral frontal areas in chronic patients. Working memory performance is associated with frontal GABA and Glu. Prediction errors are associated Glu and medial frontal GABA. Processing speed correlates with medial frontal GABA levels.
A large proportion of patients with schizophrenia exhibit deficits in cognitive control functions including working memory, processing speed and inhibitory control, which have been associated with frontal brain areas. In this systematic review, we investigated differences between chronic schizophrenia patients, first-episode (FEP) patients and healthy control groups in the neurometabolite levels of GABA, glutamate, glutamine and Glx in frontal brain areas. Additionally, we reviewed correlations between cognitive control functions or negative symptoms and these neurometabolite levels. Several studies reported decreased GABA or glutamate concentrations in frontal lobe areas, particularly in chronic schizophrenia patients, while the results were mixed for FEP patients. Working memory performance and prediction errors have been associated with frontal GABA and glutamate levels, and processing speed with frontomedial GABA levels in chronic patients. The relationship between metabolites and negative symptom severity was somewhat inconsistent. Future studies should take the participants' age, medication status or responsivity, disease stage and precise anatomical location of the voxel into account when comparing neurometabolite levels between schizophrenia patients and healthy controls.
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Butz MV, Achimova A, Bilkey D, Knott A. Event-Predictive Cognition: A Root for Conceptual Human Thought. Top Cogn Sci 2020; 13:10-24. [PMID: 33274596 DOI: 10.1111/tops.12522] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 10/11/2020] [Accepted: 10/11/2020] [Indexed: 12/11/2022]
Abstract
Our minds navigate a continuous stream of sensorimotor experiences, selectively compressing them into events. Event-predictive encodings and processing abilities have evolved because they mirror interactions between agents and objects-and the pursuance or avoidance of critical interactions lies at the heart of survival and reproduction. However, it appears that these abilities have evolved not only to pursue live-enhancing events and to avoid threatening events, but also to distinguish food sources, to produce and to use tools, to cooperate, and to communicate. They may have even set the stage for the formation of larger societies and the development of cultural identities. Research on event-predictive cognition investigates how events and conceptualizations thereof are learned, structured, and processed dynamically. It suggests that event-predictive encodings and processes optimally mediate between sensorimotor processes and language. On the one hand, they enable us to perceive and control physical interactions with our world in a highly adaptive, versatile, goal-directed manner. On the other hand, they allow us to coordinate complex social interactions and, in particular, to comprehend and produce language. Event-predictive learning segments sensorimotor experiences into event-predictive encodings. Once first encodings are formed, the mind learns progressively higher order compositional structures, which allow reflecting on the past, reasoning, and planning on multiple levels of abstraction. We conclude that human conceptual thought may be grounded in the principles of event-predictive cognition constituting its root.
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Affiliation(s)
- Martin V Butz
- Neuro-Cognitive Modeling Group, Department of Computer Science, Department of Psychology, Faculty of Science, University of Tübingen
| | - Asya Achimova
- Neuro-Cognitive Modeling Group, Department of Computer Science, Department of Psychology, Faculty of Science, University of Tübingen
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