Page 124 - MEGIN Book Of Abstracts - 2023

power and both SI and depression were associated. of distinguishing BD from UD based on clinical objec-
Two regions of the salience network (anterior insula, tive biomarkers as early as possible. Here, we aimed to
anterior cingulate) were then probed using dynamic integrate brain neuroimaging data and an advanced
causal modeling to test for ketamine effects. machine learning technique to predict different types
of mood disorder patients at the individual level.
RESULTS Clinically, patients showed significantly re-
duced SI and depression after ketamine administration. METHODS Eyes closed resting-state magnetoencepha-
In addition, distinct regions in the anterior insula were lography (MEG) data were collected from 23 BD, 30 UD,
found to be associated with SI compared with depres- and 31 healthy controls (HC). Individual power spectra
sion. In modeling of insula-anterior cingulate connec- were estimated by Fourier transform, and statistic spec-
tivity, ketamine lowered the membrane capacitance for tral differences were assessed via a cluster permutation
superficial pyramidal cells. Finally, connectivity be- test. A support vector machine classifier was further
tween the insula and anterior cingulate was associated applied to predict different mood disorder types based
with improvements in depression symptoms. on discriminative oscillatory power.

CONCLUSIONS These findings suggest that the ante- RESULTS Both BD and UD showed decreased frontal-
rior insula plays a key role in SI, perhaps via its role in central gamma/beta ratios comparing to HC, in which
salience detection. In addition, transient changes in gamma power (30-75 Hz) was decreased in BD while
superficial pyramidal cell membrane capacitance and beta power (14-30 Hz) was increased in UD vs HC. The
subsequent increases in cortical excitability might be a support vector machine model obtained significant
mechanism through which ketamine improves SI. high classification accuracies distinguishing three
groups based on mean gamma and beta power (BD:
Keywords: Depression, Gamma, Insula, Ketamine, Magne- 79.9%, UD: 81.1%, HC: 76.3%, P < .01).
toencephalography, Suicidal ideation
CONCLUSIONS In combination with resting-state MEG
Biological psychiatry. Cognitive neuroscience and data and machine learning technique, it is possible
neuroimaging (2020), Vol. 5, No. 3 (31928949) (9 citations) to make an individual and objective prediction for
mode disorder types, which in turn has implications for
diagnosis precision and treatment decision of mood
Magnetoencephalography resting-state spectral disorder patients.
fingerprints distinguish bipolar depression and
unipolar depression (2020) Keywords: MEG, bipolar depression, resting state, support
vector machine, unipolar depression
Jiang, Haiteng; Dai, Zhongpeng; Lu, Qing; Yao, Zhijian
Bipolar disorders (2020), Vol. 22, No. 6 (31729112) (9
Department of Psychiatry, the Affiliated Brain Hospital of citations)
Nanjing Medical University, Nanjing, China; Child Develop-
ment and Learning Science, Key Laboratory of Ministry
of Education, Nanjing, China; Medical College of Nanjing Association between increased theta cordance and
University, Nanjing, China early response to ECT in late-life depression (2020)

OBJECTIVES In clinical practice, bipolar depres- Ward, Michael J; Karim, Helmet T; Jessen, Zachary F;
sion (BD) and unipolar depression (UD) appear to Ghuman, Avniel Singh; Richardson, R Mark; Reynolds,
have similar symptoms, causing BD being frequently Charles F; Karp, Jordan F
misdiagnosed as UD, leading to improper treatment
decision and outcome. Therefore, it is in urgent need Department of Neurological Surgery, University of Pitts-

 ontents  Index 103
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