Electroencephalography Spectral Power Density in First-Episode Mania: A Comparative Study with Subsequent Remission Period

Lifetime and point prevalence of psychotic symptoms in adults with bipolar disorders: a systematic review and meta-analysis

Psychotic symptoms, that we defined as delusions or hallucinations, are common in bipolar disorders (BD). This systematic review and meta-analysis aims to synthesise the literature on both lifetime and point prevalence rates of psychotic symptoms across different BD subtypes, including both BD type I (BDI) and BD type II (BDII). We performed a systematic search of Medline, PsycINFO, Embase and Cochrane Library until 5 August 2021. Fifty-four studies (N = 23 461) of adults with BD met the predefined inclusion criteria for evaluating lifetime prevalence, and 24 studies (N = 6480) for evaluating point prevalence. Quality assessment and assessment of publication bias were performed. Prevalence rates were calculated using random effects meta-analysis, here expressed as percentages with a 95% confidence interval (CI). In studies of at least moderate quality, the pooled lifetime prevalence of psychotic symptoms in BDI was 63% (95% CI 57.5-68) and 22% (95% CI 14-33) in BDII. For BDI inpatients, the pooled lifetime prevalence was 71% (95% CI 61-79). There were no studies of community samples or inpatient BDII. The pooled point prevalence of psychotic symptoms in BDI was 54% (95 CI 41-67). The point prevalence was 57% (95% CI 47-66) in manic episodes and 13% (95% CI 7-23.5) in depressive episodes. There were not enough studies in BDII, BDI depression, mixed episodes and outpatient BDI. The pooled prevalence of psychotic symptoms in BDI may be higher than previously reported. More studies are needed for depressive and mixed episodes and community samples.Prospero registration number: CRD 42017052706.

A dimensional approach to affective disorder: The relations between Scl-90 subdimensions and QEEG parameters

OBJECTIVES

QEEG reflects neuronal activity directly rather than using indirect parameters, such as blood deoxygenation and glucose utilization, as in fMRI and PET. The correlation between QEEG spectral power density and Symptom Check List-90-R may help identify biomarkers pertaining to brain function, associated with affective disorder symptoms. This study aims at determining whether there is a relation between QEEG spectral power density and Symptom Check List-90-R symptom scores in affective disorders.

METHODS

This study evaluates 363 patients who were referred for the initial application and diagnosed with affective disorders according to DSM-V, with QEEG and Scl-90-R. Spectral power density was calculated for the 18 electrodes representing brain regions.

RESULTS

Somatization scores were found to be correlated with Pz and O1 theta, O1 and O2 high beta. Whereas FP1 delta activities were correlated with anxiety, F3, F4, and Pz theta were correlated with obsession scores. Interpersonal sensitivity scores were found to be correlated with F4 delta, P3, T5, P4, T6 alpha and T5, and T6 theta activities. While depression scores were correlated with P3 and T4 delta, as well as T4 theta, there was a correlation between anger and F4, as well as T4 alpha and F8 high beta activities. Paranoia scores are correlated with FP1, F7, T6 and F8 theta, T5 and F8 delta, and O2 high beta activities.

CONCLUSIONS

According to our results, anxiety, obsession, interpersonal sensitivity, depression, anger, and paranoia are related to some spectral powers of QEEG. Delta-beta coupling seems to be a neural biomarker for affective dysregulation.

QEEG - spectral power density of brain regions in predicting risk, resistance and resilience for bipolar disorder: A comparison of first degree relatives and unrelated healthy subjects

BACKGROUND

Temperament stems from the brain circuitry. Genetic differences among people are attributable to differences in neurophysiological function. Affective temperament is proposed endophenotype for bipolar affective disorder. QEEG - spectral power density is thought to be an index of general affective and cognitive brain activity. The association of spectral power density with types of affective temperament may enlighten endophenotypes for bipolar affective disorder disposition.

METHOD

TEMPS-A scale and rest QEEG were done on 25 euthymic patients, their healthy first degree relatives (n = 25) and 25 unrelated healthy control subjects. All patients were on lithium maintenance therapy.

RESULTS

F4 and T4 delta wave activity were similar between patients and first degree relatives, while Pz alpha activity was similar in first degree relatives and unrelated healthy subjects (p = 0.025, p = 0.001, p = 0.010). Cyclothymic and hyperthymic temperament scores were similar between patients and first degree relatives but higher than unrelated healthy subjects (p = 0.015, p = 0.010). F7 beta and F7-O2 high beta power were correlated with hyperthymic and irritable temperaments respectively in bipolar subjects (r = 0.439, 0.387; 0.405, 0.364; 0.226, 0.351). T3-F4-T4 delta powers were correlated with cyclothymic temperament in patients and their first degree relatives (r = 0.443, 0.420, 505). Pz alpha power and hyperthymic temperament were inversely correlated in first degree relatives and unrelated healthy subjects (r = -0.256 and -0.311).

CONCLUSION

Medial temporal network may be associated with bipolar affective disorder heritability. On the other hand, left dorsolateral prefrontal beta and high beta activities may be a neural marker for disorder resistance together with right occipital high beta power.

QEEG in affective disorder: about to be a biomarker, endophenotype and predictor of treatment response

QEEG is a relatively easy to apply, cost effective method among many electrophysiologic and functional brain imaging techniques used to assess individuals for diagnosis and determination of the most suitable treatment. Its temporal resolution provides an important advantage. Many specific EEG indicators play a role in the differential diagnosis of neuropsychiatric disorders. QEEG has advantages over EEG in the dimensional approach to symptomatology of psychiatric disorders. The prognostic value of EEG has a long history. Slow wave EEG rhythm has been reported as a predictor and measure of clinical improvement under ECT. The induction level in delta band activity predicts the long term effect of ECT. Current studies focus on the predictive power of EEG on response to pharmacotherapy and somatic treatments other than ECT. This paper discusses either QEEG can be a biomarker and/or an endophenotype in affective disorders, if it has diagnostic and prognostic value and if it can contribute to personalized treatment design, through a review of relevant literature.