Page 119 - MEGIN Book Of Abstracts - 2023

connectivity network between well-established SA raphy data under a sad expression recognition task. A
group and non-SI group, semi-supervised algorithm hidden Markov model (HMM) was applied to separate
clustered patients with only SI into two groups with the whole neural activity into several brain states, then
different suicide risks. Moreover, Inter-network gamma to characterize the dynamics. To find the disrupted
connectivity between FPN and DMN significantly nega- temporal-spatial characteristics, power estimations
tively correlated with suicide risk and not confounded and fractional occupancy (FO) of each state were
by depression severity. estimated and contrasted between MDDs and HCs.
Three states were found over the period of emotional
CONCLUSION Inter-network gamma connectivity with stimuli processing procedure. The early visual stage
FPN and DMN might be the key neuropathological (0-270 ms) was mainly manifested by state 1, and the
interactions underling the progression from SI to SA. By emotional information processing stage (270-600 ms)
applying semi-supervised clustering to electrophysi- was manifested by state 2, while the state 3 remained
ological data, it is possible to predict individual suicide a steady proportion across the whole period. MDDs ac-
risk. tivated statistically more in limbic system during state
2 (p = 0.0045) and less in frontoparietal control net-
Keywords: Gamma band, Magnetoencephalography work during state 3 (p = 5.38 × 10[-5]) relative to HCs.
(MEG), Major depression, Semi-supervised clustering, Hamilton Depression Rating Scale scores were signifi-
Suicidal ideation, Suicide attempt cantly correlated with the predicted disorder severity
using FO values (p = 0.0062, r = 0.3933). Relative to HCs,
Progress in neuro-psychopharmacology & biological MDDs perceived the sad contents quickly and spent
psychiatry (2022), Vol. 113 (34780814) (4 citations) more time overexpressing the negative emotions.
These phenomena indicated MDD patients might easily
indulge in negative emotion and neglect other things.
Sub-second transient activated patterns to Furthermore, temporal descriptors built by HMM could
sad expressions in major depressive disorders be potential biomarkers for identifying the severity of
discovered via hidden Markov model (2021) depression disorders.

Dai, Zhongpeng; Zhang, Siqi; Wang, Xinyi; Wang, Huan; Keywords: hidden Markov model, magnetoencephalogra-
Zhou, Hongliang; Tian, Shui; Chen, Zhilu; Lu, Qing; Yao, phy, major depressive disorders, negative stimuli
Zhijian
Journal of neuroscience research (2021), Vol. 99, No. 12
Child Development and Learning Science, Key Laboratory of (34585763) (5 citations)
Ministry of Education, Nanjing, China; Nanjing Brain Hospital,
Medical School of Nanjing University, Nanjing, China
Increased theta/alpha synchrony in the habenula-
ABSTRACT The pathological mechanisms of major prefrontal network with negative emotional stimuli
depressive disorders (MDDs) is associated with the in human patients (2021)
overexpression of negative emotions, and the fast
transient-activated patterns underlying overrepresen- Huang, Yongzhi; Sun, Bomin; Debarros, Jean; Zhang,
tation in depression still remain to be revealed to date. Chao; Zhan, Shikun; Li, Dianyou; Zhang, Chencheng;
We hypothesized that the aberrant spatiotemporal Wang, Tao; Huang, Peng; Lai, Yijie; Brown, Peter; Cao,
attributes of the process of sad expressions are related Chunyan; Tan, Huiling
to the neuropathology of MDD and help to detect the
depression severity. We enrolled a total of 96 subjects Nuffield Department of Surgical Sciences, University of
including 47 patients with MDD and 49 healthy con- Oxford, Oxford, United Kingdom; Department of Neurosur-
trols (HCs), and recorded their magnetoencephalog- gery, Affiliated Ruijin Hospital, Shanghai Jiao Tong University

 ontents  Index 98
C