More than the sum of its parts: Merging network psychometrics and network neuroscience with application in autism

Joe Bathelt, Hilde M. Geurts, Denny Borsboom

Research output: Contribution to journalArticlepeer-review


Network approaches that investigate the interaction between symptoms or behaviours have opened new ways of understanding psychological phenomena in health and disorder. In parallel, network approaches that characterise the interaction between brain regions have become the dominant approach in neuroimaging research. Combining these parallel approaches would enable new insights into the interaction between behaviours and their brain-level correlates. In this paper, we introduce a methodology for combining network psychometrics and network neuroscience. This approach utilises the information from the psychometric network to obtain neural correlates for each node in the psychometric network (network-based regression). We illustrate the approach by highlighting the interaction between autistic traits and their resting-state functional associations. To this end, we utilise data from 172 male autistic participants (10–21 years) from the autism brain data exchange (ABIDE, ABIDE-II). Our results indicate that the network-based regression approach can uncover both unique and shared neural correlates of behavioural measures. In addition, the methodology enables us to isolate mechanisms at the brain-level that are unique to particular behavioural variables. For instance, our example analysis indicates that the overlap between communication and social difficulties is not reflected in the overlap between their functional correlates.
Original languageEnglish
Pages (from-to)1-33
Number of pages33
JournalNetwork Neuroscience
Publication statusPublished - 20 Dec 2021

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