Spontaneous activity in default-mode network predicts ascription of self-relatedness to stimuli

Pengmin Qin, Simone Grimm, Niall-William Duncan, Yan Fan, Zirui Huang, Timothy Joseph Lane, Xuchu Weng, M. Bajbouj, Georg Northoff

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Abstract

Spontaneous activity levels prior to stimulus presentation can determine how that stimulus will be perceived. It has also been proposed that such spontaneous activity, particularly in the default-mode network (DMN), is involved in self-related processing. We therefore hypothesised that pre-stimulus activity levels in the DMN predict whether a stimulus is judged as self-related or not. Participants were presented in the MRI scanner with a white noise stimulus that they were instructed contained their name or another. They then had to respond with which name they thought they heard. Regions where there was an activity level difference between self and other response trials 2 s prior to the stimulus being presented were identified. Pre-stimulus activity levels were higher in the right temporoparietal junction, the right temporal pole and the left superior temporal gyrus in trials where the participant responded that they heard their own name than trials where they responded that they heard another. Pre-stimulus spontaneous activity levels in particular brain regions, largely overlapping with the DMN, predict the subsequent judgement of stimuli as self-related. This extends our current knowledge of self-related processing and its apparent relationship with intrinsic brain activity in what can be termed a rest-self overlap. © The Author (2016). Published by Oxford University Press.
LanguageEnglish
Pages693-702
Number of pages10
JournalSocial Cognitive and Affective Neuroscience
Volume11
Issue number4
DOIs
StatePublished - 2016

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Spontaneous activity in default-mode network predicts ascription of self-relatedness to stimuli. / Qin, Pengmin; Grimm, Simone; Duncan, Niall-William; Fan, Yan; Huang, Zirui; Lane, Timothy Joseph; Weng, Xuchu; Bajbouj, M.; Northoff, Georg.

In: Social Cognitive and Affective Neuroscience, Vol. 11, No. 4, 2016, p. 693-702.

Research output: Contribution to journalArticle

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