Neural Signatures of Predictive Strategies Track Individuals Along the Autism-Schizophrenia Continuum.

Researchers studied how people with autism-like traits versus schizophrenia-like traits process information differently. They found that people with autism traits tend to focus more on what they're currently seeing or hearing, while people with schizophrenia traits rely more on their past experiences and expectations. This difference in how the brain processes information might help explain some of the core differences between autism and schizophrenia.

This EEG study investigated how 80 individuals in the general population process predictive information differently based on their autistic and schizotypal traits. Using a probabilistic detection task, researchers found that people's position on an autism-schizophrenia continuum influences their decision-making strategies. Those with higher schizotypal traits relied more heavily on prior knowledge/expectations, while those with higher autistic traits favored current sensory information over prior expectations. The study provides evidence that differences in how the brain weighs prior knowledge versus new sensory input may be fundamental markers distinguishing autism from schizophrenia spectrum conditions, potentially offering insights into risk identification and symptom development.

Findings suggest predictive processing differences could serve as early markers for autism or psychotic spectrum conditions. Understanding these processing differences may inform personalized interventions that account for individual predictive processing styles.

Study conducted in general population rather than clinical autism or schizophrenia samples. Cross-sectional design limits causal inferences. EEG methodology may have limited spatial resolution for understanding specific brain mechanisms.

Humans develop a constellation of different representations of the external environment, even in the face of the same sensory exposure. According to the Bayesian framework, these differentiations could be grounded in a different weight assigned to prior knowledge vs. new external inputs in predictive inference. Since recent advances in computational psychiatry suggest that autism (ASD) and schizophrenia (SSD) lie on the two diametric poles of the same predictive continuum, the adoption of a specific inferential style could be routed by dispositional factors related to autistic and schizotypal traits. However, no studies have directly investigated the role of ASD-SSD dimension in shaping the neuro-behavioral markers underlying perceptual inference.

We used a probabilistic detection task while simultaneously recording EEG to investigate whether neurobehavioral signatures related to prior processing were diametrically shaped by ASD and SSD traits in the general population (n = 80). We found that the position along the ASD-SSD continuum directed the predictive strategies adopted by the individuals in decision-making. While proximity to the positive schizotypy pole was associated with the adoption of the predictive approach associated to the hyper-weighting of prior knowledge, proximity to ASD pole was related to strategies that favored sensory evidence in decision-making. These findings revealed that the weight assigned to prior knowledge is a marker of the ASD-SSD continuum, potentially useful for identifying individuals at-risk of developing mental disorders and for understanding the mechanisms contributing to the onset of symptoms observed in ASD and SSD clinical forms.