Discriminating autism spectrum disorders from schizophrenia by investigation of mental state attribution on an on-line mentalizing task: A review and meta-analysis
Review articleOpen access

AbstractIn recent years, theories of how humans form a “theory of mind” of others (“mentalizing”) have increasingly been called upon to explain impairments in social interaction in mental disorders, such as autism spectrum disorders (ASD) and schizophrenia. However, it remains unclear whether tasks that assess impairments in mentalizing can also contribute to determining differential deficits across disorders, which may be important for early identification and treatment. Paradigms that challenge mentalizing abilities in an on-line, real-life fashion have been considered helpful in detecting disease-specific deficits. In this review, we are therefore summarizing results of studies that assess the attribution of mental states using an animated triangles task. Behavioral as well as brain imaging studies in ASD and schizophrenia have been taken into account. While for neuroimaging methods, data are sparse and investigation methods inconsistent, we performed a meta-analysis of behavioral data to directly investigate performance deficits across disorders. Here, more impaired abilities in the appropriate description of interactions were found in ASD patients than in patients with schizophrenia. Moreover, an analysis of first-episode (FES) versus longer lasting (LLS) schizophrenia showed that usage of mental state terms was reduced in the LLS group. In our review and meta-analysis, we identified performance differences between ASD and schizophrenia that seem helpful in targeting differential deficits, taking into account different stages of schizophrenia. However, to tackle the deficits in more detail, studies are needed that directly compare patients with ASD and schizophrenia using behavioral or neuroimaging methods with more standardized task versions.

Request full text

References (0)

Cited By (0)

No reference data.
No citation data.
Join Copernicus Academic and get access to over 12 million papers authored by 7+ million academics.
Join for free!