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Updated: Aug 7, 2026
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Correlation of symptom clusters of schizophrenia with absolute powers of main frequency bands in quantitative EEG
Andres Gross1, Sirkka-Liisa Joutsiniemi, Ranan Rimon
1Helsinki University Central Hospital, Department of Psychiatry, Välskärinkatu 12 A, 00260 Helsinki, Finland. andres.gross@luukku.com
Background:
Research of QEEG activity power spectra has shown intriguing results in patients with schizophrenia. Different symptom clusters have been correlated to QEEG frequency bands. The findings have been to some extent inconsistent. Replication of the findings of previous research is thus an important task. In the current study we investigated the correlations between the absolute powers of delta, theta, alpha, and beta frequency bands over the fronto-central scalp area (FC) with the PANSS subscales and the Liddle's factors in 16 patients with schizophrenia.The authors hypothesised a priori the correlations reported by Harris et al (1999) of PANSS negative subscale with delta power, Liddle's psychomotor poverty with delta and beta powers, disorganisation with delta power and reality distortion with alpha power on the midline FC.
Methods:
The sample consisted of 16 patients with chronic schizophrenia considered as having insufficient clinical response to conventional antipsychotic treatment and evidencing a relapse. The correlations between quantitative electroencephalography (QEEG) absolute powers of delta (1.5-3.0 Hz), theta (3.0-7.5 Hz), alpha (7.5-12.5 Hz), and beta (12.5-20.0 Hz) frequency bands over the fronto-central scalp area (FC) with PANSS subscales and Liddle's factors (reality distortion, disorganisation, psychomotor poverty) were investigated.
Results:
Significant positive correlations were found between the beta and psychomotor poverty (p < 0.05). Trends towards positive correlations (p < 0.1) were observed between delta and PANSS negative subscale and psychomotor poverty. Alpha did not correlate with reality distortion and delta did not correlate with disorganisation.Post hoc analysis revealed correlations of the same magnitude between beta and psychopathology generally over FC.
Conclusion:
The a priori hypothesis was partly supported by the correlation of the beta and psychomotor poverty. Liddle's factors showed correlations of the same magnitude with PANSS subscales. Supplementary analysis showed beta frequency correlating non-specifically over FC with a wide range of psychiatric symptomatology in patients with schizophrenia having a relapse.
