Schneiderian first rank symptoms in schizophrenia: A developmental neuroscience evaluation

Tikka, Sai Krishna; Nizamie, S. Haque; Das, Archana Kumari; Agarwal, Nidhi; Goyal, Nishant

doi:10.1016/j.ijdevneu.2016.02.001

Cited by 6 publications

(5 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Changes to the rest/task difference on neuronal measures could thus manifest as a failure to demarcate self and other, or self disorder. For instance, the typical human ability to engage in self-referential processing more reliably than comparable non-self-referential processing may depend on a typical rest-task difference in the brain, which is then impaired in schizophrenia (25,29,30). The basic model of self thus incorporates the view that sense of self is a metacognitive faculty that is compromised in schizophrenia (54, 55) while also situating this faculty in relationship to the resting state activity of the brain.…”

Section: Discussionmentioning

confidence: 99%

“…Source monitoring accounted for the most articles, which were predominantly from Ford and colleagues, who used a simple task with (1) a talk condition, and (2) a listen condition in which the recording of the talk condition is played back to the participant (36-40, 42, 43, 45, 46). In addition to these paradigms, some studies presented resting-state data and/or data on the difference between the resting state and task-related activity (16,27,29,47,48).…”

Section: Paradigms or Tasks Probing The Self And Behavioral Datamentioning

confidence: 99%

“…Figure 7 summarizes results that were obtained either prestimulus or during a resting state (16,29,36,37,47), including measures from both individual frequency bands and other dynamic measures. In addition, Kindler et al ( 48) compared periods with auditory verbal hallucinations to periods when these were not present in a resting-state study of EEG microstates and found that a specific class of microstates situated in the FIGURE 5 | Changes in individual frequency bands.…”

Section: Measures Of Brain Dynamicsmentioning

confidence: 99%

See 2 more Smart Citations

Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies

Hamilton

Northoff

2021

Front. Psychiatry

View full text Add to dashboard Cite

Background: Interest in disordered sense of self in schizophrenia has recently re-emerged in the literature. It has been proposed that there is a basic self disturbance, underlying the diagnostic symptoms of schizophrenia, in which the person's sense of being a bounded individual continuous through time loses stability. This disturbance has been documented phenomenologically and at the level of cognitive tasks. However, the neural correlates of basic self disorder in schizophrenia are poorly understood.Methods: A search of PubMed was used to identify studies on self and schizophrenia that reported EEG or MEG data.Results: Thirty-three studies were identified, 32 using EEG and one using MEG. Their operationalizations of the self were divided into six paradigms: self-monitoring for errors, proprioception, self-other integration, self-referential processing, aberrant salience, and source monitoring. Participants with schizophrenia were less accurate on self-referential processing tasks and had slower response times across most studies. Event-related potential amplitudes differed across many early and late components, with reduced N100 suppression in source monitoring paradigms being the most replicated finding. Several studies found differences in one or more frequency band, but no coherent overall finding emerged in this area. Various other measures of brain dynamics also showed differences in single studies. Only some of the study designs were adequate to establish a causal relationship between the self and EEG or MEG measures.Conclusion: The broad range of changes suggests a global self disturbance at the neuronal level, possibly carried over from the resting state. Further studies that successfully isolate self-related effects are warranted to better understand the temporal-dynamic and spatial-topographic basis of self disorder and its relationship to basic self disturbance on the phenomenological level.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Paradigms or Tasks Probing The Self And Behavioral Datamentioning

confidence: 99%

Section: Measures Of Brain Dynamicsmentioning

confidence: 99%

See 1 more Smart Citation

Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies

Hamilton

Northoff

2021

Front. Psychiatry

View full text Add to dashboard Cite

show abstract

“…[ 8 ] Electroencephalographic (EEG) activity, particularly resting-state activity, has been proposed as potential biomarkers for diagnosing SCZ. [ 9 10 11 12 ] Besides the advantage of being cost-effective and of unparalleled temporal resolution inherent to EEG, studying resting-state activity enhances the ease and reproducibility of the procedure. In fact, some studies have shown resting-state EEG to differentiate positive and negative symptom (NS) subgroups of SCZ.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence-based classification of schizophrenia: A high density electroencephalographic and support vector machine study

Tikka

Singh

Nizamie

et al. 2020

Indian J Psychiatry

View full text Add to dashboard Cite

Background: Interview-based schizophrenia (SCZ) diagnostic methods are not completely valid. Moreover, SCZ-the disease entity is very heterogeneous. Supervised-Machine-Learning (sML) application of Artificial-Intelligence holds a tremendous promise in solving these issues. Aims: To sML-based discriminating validity of resting-state electroencephalographic (EEG) quantitative features in classifying SCZ from healthy and, positive (PS) and negative symptom (NS) subgroups, using a high-density recording. Settings and Design: Data collected at a tertiary care mental-health institute using a cross-sectional study design and analyzed at a premier Engineering Institute. Materials and Methods: Data of 38-SCZ patients and 20-healthy controls were retrieved. The positive-negative subgroup classification was done using Positive and Negative Syndrome Scale operational-criteria. EEG was recorded using 256-channel high-density equipment. Eight priori regions-of-interest were selected. Six-level wavelet decomposition and Kernel-Support Vector Machine (SVM) method were used for feature extraction and data classification. Statistical Analysis: Mann–Whitney test was used for comparison of machine learning-features. Accuracy, sensitivity, specificity, and area under receiver operating characteristics-curve were measured as discriminatory indices of classifications. Results: Accuracy of classifying SCZ from healthy and PS from NS SCZ, were 78.95% and 89.29%, respectively. While beta and gamma frequency related features most accurately classified SCZ from healthy controls, delta and theta frequency related features most accurately classified positive from negative SCZ. Inferior frontal gyrus features most accurately contributed to both the classificatory instances. Conclusions: SVM-based classification and sub-classification of SCZ using EEG data is optimal and might help in improving the “validity” and reducing the “heterogeneity” in the diagnosis of SCZ. These results might only be generalized to acute and moderately ill male SCZ patients.

show abstract

“…Past studies have noted significantly higher levels of additional psychotic symptoms in individuals with schizophrenia who experience FRS in comparison to those who do not experience FRS (Jablensky, 1992; Tikka, Nizamie, Das, Agarwal, & Goyal, 2016; van Rooijen et al, 2017). However, past research has not addressed whether passivity symptoms (in contrast to FRS auditory hallucinations) are particularly associated with other types of psychotic symptoms, nor whether passivity symptoms might be particularly strongly associated with specific types of psychotic symptoms.…”

mentioning

confidence: 98%

Course and symptom and functional correlates of passivity symptoms in schizophrenia: an 18-year multi-follow-up longitudinal study

Herbener

Harrow

2019

Psychol. Med.

View full text Add to dashboard Cite

Background Change in the experience of oneself may lay the groundwork for the development of additional hallucinations and delusions in individuals with schizophrenia. However, to date, the course and symptom and functioning correlates of passivity symptoms (cf. thought insertion, thought withdrawal) have not been measured consistently over long periods of time. Information on the course and correlates of passivity symptoms is essential for developing models of their contribution to schizophrenic illness. Method Eighty-two individuals diagnosed with schizophrenia or schizoaffective disorder were recruited at an index hospitalization and reassessed at three or more follow-ups over the following 18 years. Results The results indicate that a small group of participants report passivity symptoms at all follow-ups, many reported passivity symptoms at some follow-ups, and the majority of individuals never reported passivity symptoms. The prevalence of passivity symptoms was similar to that for delusions of reference and persecutory delusions. Notably, when individuals did experience passivity symptoms, they also had a greater number of additional psychotic symptoms than individuals without passivity symptoms. Further, the presence of passivity symptoms was associated with work impairment at some assessments. Conclusions Passivity symptoms present episodically, at a similar rate as delusions of reference and persecutory delusions, and when present, they are associated with having a higher number of additional psychotic symptoms, as well as having some impact on work functioning. These results suggest that passivity symptoms may increase vulnerability to additional psychotic symptoms and greater work impairment.

show abstract

Schneiderian first rank symptoms in schizophrenia: A developmental neuroscience evaluation

Cited by 6 publications

References 49 publications

Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies

Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies

Artificial intelligence-based classification of schizophrenia: A high density electroencephalographic and support vector machine study

Course and symptom and functional correlates of passivity symptoms in schizophrenia: an 18-year multi-follow-up longitudinal study

Contact Info

Product

Resources

About