Multivariate sharp-wave ripples in schizophrenia during awake state.

AIMS: Schizophrenia (SZ) is a brain disorder characterized by psychotic symptoms and cognitive dysfunction. Recently, irregularities in sharp-wave ripples (SPW-Rs) have been reported in SZ. As SPW-Rs play a critical role in memory, their irregularities can cause psychotic symptoms and cognitive dysfunction in patients with SZ. In this study, we investigated the SPW-Rs in human SZ. METHODS: We measured whole-brain activity using magnetoencephalography (MEG) in patients with SZ (n = 20) and sex- and age-matched healthy participants (n = 20) during open-eye rest. We identified SPW-Rs and analyzed their occurrence and time-frequency traits. Furthermore, we developed a novel multivariate analysis method, termed "ripple-gedMEG" to extract the global features of SPW-Rs. We also examined the association between SPW-Rs and brain state transitions. The outcomes of these analyses were modeled to predict the positive and negative syndrome scale (PANSS) scores of SZ. RESULTS: We found that SPW-Rs in the SZ (1) occurred more frequently, (2) the delay of the coupling phase (3) appeared in different brain areas, (4) consisted of a less organized spatiotemporal pattern, and (5) were less involved in brain state transitions. Finally, some of the neural features associated with the SPW-Rs were found to be PANSS-positive, a pathological indicator of SZ. These results suggest that widespread but disorganized SPW-Rs underlies the symptoms of SZ. CONCLUSION: We identified irregularities in SPW-Rs in SZ and confirmed that their alternations were strongly associated with SZ neuropathology. These results suggest a new direction for human SZ research.

The Characteristics of Power Spectral Density in Bipolar Disorder at the Resting State.

Bipolar disorder (BD) is a common psychiatric disorder, but its pathophysiology is not fully elucidated. The current study focused on its electrophysiological characteristics, especially power spectral density (PSD). Resting state with eyes opened magnetoencephalography data were collected from 21 patients with BD and 22 healthy controls. The whole brain's PSD was calculated from source reconstructed waveforms at each frequency band (delta: 1-3 Hz, theta: 4-7 Hz, alpha: 8-12 Hz, low beta: 13-19 Hz, high beta: 20-29 Hz, and gamma: 30-80 Hz). We compared PSD values on the marked vertices at each frequency band between healthy and patient groups using a Mann-Whitney rank test to examine the relationship between significantly different PSD and clinical measures. The PSD in patients with BD was significantly decreased in lower frequency bands, mainly in the default mode network (DMN) areas (bilateral medial prefrontal cortex, bilateral precuneus, left inferior parietal lobe, and right temporal cortex in the alpha band) and salience network areas (SAL; left anterior insula [AI] at the delta band, anterior cingulate cortex at the theta band, and right AI at the alpha band). No significant differences in PSD were observed at low beta and high beta. PSD was not correlated with age or other clinical scales. Altered PSDs of the DMN and SAL were observed in the delta, theta, and alpha bands. These alterations contribute to the vulnerability of BD through the disturbance of self-referential mental activity and switching between the default mode and frontoparietal networks.

Frequency-Specific Resting Connectome in Bipolar Disorder: An MEG Study.

BACKGROUND: Bipolar disorder (BD) is a serious psychiatric disorder that is associated with a high suicide rate, and for which no clinical biomarker has yet been identified. To address this issue, we investigated the use of magnetoencephalography (MEG) as a new prospective tool. MEG has been used to evaluate frequency-specific connectivity between brain regions; however, no previous study has investigated the frequency-specific resting-state connectome in patients with BD. This resting-state MEG study explored the oscillatory representations of clinical symptoms of BD via graph analysis. METHODS: In this prospective case-control study, 17 patients with BD and 22 healthy controls (HCs) underwent resting-state MEG and evaluations for depressive and manic symptoms. After estimating the source current distribution, orthogonalized envelope correlations between multiple brain regions were evaluated for each frequency band. We separated regions-of-interest into seven left and right network modules, including the frontoparietal network (FPN), limbic network (LM), salience network (SAL), and default mode network (DMN), to compare the intra- and inter-community edges between the two groups. RESULTS: In the BD group, we found significantly increased inter-community edges of the right LM-right DMN at the gamma band, and decreased inter-community edges of the right SAL-right FPN at the delta band and the left SAL-right SAL at the theta band. Intra-community edges in the left LM at the high beta band were significantly higher in the BD group than in the HC group. The number of connections in the left LM at the high beta band showed positive correlations with the subjective and objective depressive symptoms in the BD group. CONCLUSION: We introduced graph theory into resting-state MEG studies to investigate the functional connectivity in patients with BD. To the best of our knowledge, this is a novel approach that may be beneficial in the diagnosis of BD. This study describes the spontaneous oscillatory brain networks that compensate for the time-domain issues associated with functional magnetic resonance imaging. These findings suggest that the connectivity of the LM at the beta band may be a good objective biological biomarker of the depressive symptoms associated with BD.