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Abstract #1699

Impaired interactions of large-scale networks predict relapse behavior in heroin-dependent individuals

Qiang Li 1, Jiajie Chen1, Jierong Liu1, Wei Li1, and Wei Wang1

1Tangdu Hospital, Fourth Military Medical University, Xi'an, People's Republic of China

Coupling of large-scale brain networks may underlie cognitive dysfunction in psychiatric disorders including addiction. However, whether the deficit of interactions among large-scale brain networks is associated with relapse behavior of heroin addiction remains unknown. This is the first neuroimaging study to assess coupling of large-scale networks that predict relapse in heroin addiction. In this study, we utilized a resting-state functional connectivity method of functional magnetic resonance imaging and found that abnormally higher functional connectivity between the SN and DMN, and lower functional connectivity between the left ECN and DMN were associated with the relapse behavior in treated heroin-dependent patients.

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