Schizophrenia patients often manifest semantic processing deficits. It has been proposed that these deficits stem from disorganized semantic representations in the brain. However, no study has yet examined the neural correlates of semantic disorganization by directly evaluating semantic representations in the brain. We used voxelwise modeling on functional magnetic resonance imaging signals to evaluate the semantic representations associated with several thousand words in individual patient brains. We then compared the structural properties of semantic representations to those in healthy controls. The variability of semantic representations was smaller both within individual patients and across patients compared to controls. Surrogate data analysis suggests that the observed reduction in representational variability is associated with disorganization of categorical information. To our knowledge, these findings provide the first evidence for sematic disorganization in schizophrenia at the level of brain representations.

Objectives Schizophrenia is a mental illness that presents with thought disorders including delusions and disorganized speech. Thought disorders have been regarded as a consequence of the loosening of associations between semantic concepts since the term “schizophrenia” was first coined by Bleuler. However, a mechanistic account of this cardinal disturbance in terms of functional dysconnection has been lacking. To evaluate how aberrant semantic connections are expressed through brain activity, we characterized large-scale network structures of concept representations using functional magnetic resonance imaging (fMRI). Study Design We quantified various concept representations in patients’ brains from fMRI activity evoked by movie scenes using encoding modeling. We then constructed semantic brain networks by evaluating the similarity of these semantic representations and conducted graph theory-based network analyses. Study Results Neurotypical networks had small-world properties similar to those of natural languages, suggesting small-worldness as a universal property in semantic knowledge networks. Conversely, small-worldness was significantly reduced in networks of schizophrenia patients and was correlated with psychological measures of delusions. Patients’ semantic networks were partitioned into more distinct categories and had more random within-category structures than those of controls. Conclusions The differences in conceptual representations manifest altered semantic clustering and associative intrusions that underlie thought disorders. This is the first study to provide pathophysiological evidence for the loosening of associations as reflected in randomization of semantic networks in schizophrenia. Our method provides a promising approach for understanding the neural basis of altered or creative inner experiences of individuals with mental illness or exceptional abilities, respectively.