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Article

Resting-State Isolated Effective Connectivity of the Cingulate Cortex as a Neurophysiological Biomarker in Patients with Severe Treatment-Resistant Schizophrenia

1
Department of Neuropsychiatry, Keio University School of Medicine, Tokyo 160-8582, Japan
2
Department of Psychiatry, Komagino Hospital, Tokyo 193-8505, Japan
3
Graduate School of Media and Governance, Keio University, Kanagawa, Tokyo 252-0882, Japan
4
Faculty of Environment and Information Studies, Keio University, Kanagawa, Tokyo 252-0882, Japan
5
Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON M6J 1H4, Canada
*
Authors to whom correspondence should be addressed.
J. Pers. Med. 2020, 10(3), 89; https://doi.org/10.3390/jpm10030089
Received: 21 June 2020 / Revised: 9 August 2020 / Accepted: 12 August 2020 / Published: 14 August 2020
Background: The neural basis of treatment-resistant schizophrenia (TRS) remains unclear. Previous neuroimaging studies suggest that aberrant connectivity between the anterior cingulate cortex (ACC) and default mode network (DMN) may play a key role in the pathophysiology of TRS. Thus, we aimed to examine the connectivity between the ACC and posterior cingulate cortex (PCC), a hub of the DMN, computing isolated effective coherence (iCoh), which represents causal effective connectivity. Methods: Resting-state electroencephalogram with 19 channels was acquired from seventeen patients with TRS and thirty patients with non-TRS (nTRS). The iCoh values between the PCC and ACC were calculated using sLORETA software. We conducted four-way analyses of variance (ANOVAs) for iCoh values with group as a between-subject factor and frequency, directionality, and laterality as within-subject factors and post-hoc independent t-tests. Results: The ANOVA and post-hoc t-tests for the iCoh ratio of directionality from PCC to ACC showed significant findings in delta (t45 = 7.659, p = 0.008) and theta (t45 = 8.066, p = 0.007) bands in the left side (TRS < nTRS). Conclusion: Left delta and theta PCC and ACC iCoh ratio may represent a neurophysiological basis of TRS. Given the preliminary nature of this study, these results warrant further study to confirm the importance of iCoh as a clinical indicator for treatment-resistance. View Full-Text
Keywords: treatment-resistant schizophrenia; causal effective connectivity; isolated effective coherence; resting-state electroencephalography; anterior cingulate cortex; posterior cingulate cortex; default mode network treatment-resistant schizophrenia; causal effective connectivity; isolated effective coherence; resting-state electroencephalography; anterior cingulate cortex; posterior cingulate cortex; default mode network
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MDPI and ACS Style

Wada, M.; Nakajima, S.; Tarumi, R.; Masuda, F.; Miyazaki, T.; Tsugawa, S.; Ogyu, K.; Honda, S.; Matsushita, K.; Kikuchi, Y.; Fujii, S.; Blumberger, D.M.; Daskalakis, Z.J.; Mimura, M.; Noda, Y. Resting-State Isolated Effective Connectivity of the Cingulate Cortex as a Neurophysiological Biomarker in Patients with Severe Treatment-Resistant Schizophrenia. J. Pers. Med. 2020, 10, 89. https://doi.org/10.3390/jpm10030089

AMA Style

Wada M, Nakajima S, Tarumi R, Masuda F, Miyazaki T, Tsugawa S, Ogyu K, Honda S, Matsushita K, Kikuchi Y, Fujii S, Blumberger DM, Daskalakis ZJ, Mimura M, Noda Y. Resting-State Isolated Effective Connectivity of the Cingulate Cortex as a Neurophysiological Biomarker in Patients with Severe Treatment-Resistant Schizophrenia. Journal of Personalized Medicine. 2020; 10(3):89. https://doi.org/10.3390/jpm10030089

Chicago/Turabian Style

Wada, Masataka, Shinichiro Nakajima, Ryosuke Tarumi, Fumi Masuda, Takahiro Miyazaki, Sakiko Tsugawa, Kamiyu Ogyu, Shiori Honda, Karin Matsushita, Yudai Kikuchi, Shinya Fujii, Daniel M. Blumberger, Zafiris J. Daskalakis, Masaru Mimura, and Yoshihiro Noda. 2020. "Resting-State Isolated Effective Connectivity of the Cingulate Cortex as a Neurophysiological Biomarker in Patients with Severe Treatment-Resistant Schizophrenia" Journal of Personalized Medicine 10, no. 3: 89. https://doi.org/10.3390/jpm10030089

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