Computational modeling of electric fields for prefrontal tDCS across patients with schizophrenia and mood disorders

Uenishi, Shinya; Tamaki, Atsushi; Yamada, Shinichi; Yasuda, Kasumi; Ikeda, Natsuko; Mizutani-Tiebel, Yuki; Keeser, Daniel; Padberg, Frank; Tsuji, Tomikimi; Kimoto, Sohei und Takahashi, Shun (2022): Computational modeling of electric fields for prefrontal tDCS across patients with schizophrenia and mood disorders. In: Psychiatry Research-Neuroimaging, Bd. 326, 111547

Abstract

This cross-diagnostic study aims to computationally model electric field (efield) for prefrontal transcranial direct current stimulation in mood disorders and schizophrenia. Enrolled were patients with major depressive disorder (n = 23), bipolar disorder (n = 24), schizophrenia (n = 23), and healthy controls (n = 23). The efield was simulated using SimNIBS software (ver.2.1.1). Electrodes were placed at the left and right prefrontal areas and the current intensity was set to 2 mA intensity. Schizophrenia and major depressive disorder groups showed significantly lower 99.5th percentile efield strength than healthy controls. In voxel-wise analysis, patients with schizophrenia showed a significant reduction of simulated efield strength in the bilateral frontal lobe, cerebellum and brain stem compared with healthy controls. Among the patients with schizophrenia, reduction of simulated efield strength was not significantly correlated with psychiatric symptoms or global functioning. The patients with bipolar disorder showed no significant difference in simulated efield strength compared with healthy controls, and there was no significant difference between the clinical groups. Our results suggest attenuated electrophysiological response to transcranial direct current stimulation to the prefrontal cortex in patients with schizophrenia, and to some extent in patients with major depressive disorder.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 0925-4927
• Sprache: Englisch