Akila Kadambi, Gennady Erlikhman, Micah Johnson, Martin M Monti, Marco Iacoboni, Hongjing Lu
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引用次数: 0
Abstract
Humans can recognize their whole-body movements even when displayed as dynamic dot patterns. The sparse depiction of whole-body movements, coupled with a lack of visual experience watching ourselves in the world, has long implicated non-visual mechanisms to self-action recognition. We aimed to identify the neural systems for this ability. Using general linear modeling and multivariate analyses on human brain imaging data from male and female participants, we first found that cortical areas linked to motor processes, including frontoparietal and primary somatomotor cortices, exhibit greater engagement and functional connectivity when recognizing self-generated versus other-generated actions. Next, we show that these regions encode self-identity based on motor familiarity, even after regressing out idiosyncratic visual cues using multiple regression representational similarity analysis. Last, we found the reverse pattern for unfamiliar individuals: encoding localized to occipito-temporal visual regions. These findings suggest that self-awareness from actions emerges from the interplay of motor and visual processes.Significance Statement: We report for the first time that self-recognition from visual observation of our whole-body actions implicates brain regions associated with motor processes. On functional neuroimaging data, we found greater activity and unique representational patterns in brain areas and networks linked to motor processes when viewing our own actions relative to viewing the actions of others. These findings introduce an important role of motor mechanisms in distinguishing the self from others.
期刊介绍:
JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles