TY - JOUR

T1 - Statistical Learning and Inference Is Impaired in the Nonclinical Continuum of Psychosis

AU - Dzafic, Ilvana

AU - Randeniya, Roshini

AU - Harris, Clare D.

AU - Bammel, Moritz

AU - Garrido, Marta I.

N1 - Publisher Copyright: Copyright © 2020 the authors

PY - 2020/8/26

Y1 - 2020/8/26

N2 - Our perceptions result from the brain's ability to make inferences, or predictive models, of sensory information. Recently, it has been proposed that psychotic traits may be linked to impaired predictive processes. Here, we examine the brain dynamics underlying statistical learning and inference in stable and volatile environments, in a population of healthy human individuals (N = 75; 36 males, 39 females) with a range of psychotic-like experiences. We measured prediction error responses to sound sequences with electroencephalography, gauged sensory inference explicitly by behaviorally recording sensory statistical learning errors, and used dynamic causal modeling to tap into the underlying neural circuitry. We discuss the findings that were robust to replication across the two experiments (Discovery dataset, N = 31; Validation dataset, N = 44). First, we found that during stable conditions, participants demonstrated greater precision in their predictive model, reflected in a larger prediction error response to unexpected sounds, and decreased statistical learning errors. Moreover, individuals with attenuated prediction errors in stable conditions were found to make greater incorrect predictions about sensory information. Critically, we show that greater errors in statistical learning and inference are related to increased psychotic-like experiences. These findings link neurophysiology to behavior during statistical learning and prediction formation, as well as providing further evidence for the idea of a continuum of psychosis in the healthy, nonclinical population.

AB - Our perceptions result from the brain's ability to make inferences, or predictive models, of sensory information. Recently, it has been proposed that psychotic traits may be linked to impaired predictive processes. Here, we examine the brain dynamics underlying statistical learning and inference in stable and volatile environments, in a population of healthy human individuals (N = 75; 36 males, 39 females) with a range of psychotic-like experiences. We measured prediction error responses to sound sequences with electroencephalography, gauged sensory inference explicitly by behaviorally recording sensory statistical learning errors, and used dynamic causal modeling to tap into the underlying neural circuitry. We discuss the findings that were robust to replication across the two experiments (Discovery dataset, N = 31; Validation dataset, N = 44). First, we found that during stable conditions, participants demonstrated greater precision in their predictive model, reflected in a larger prediction error response to unexpected sounds, and decreased statistical learning errors. Moreover, individuals with attenuated prediction errors in stable conditions were found to make greater incorrect predictions about sensory information. Critically, we show that greater errors in statistical learning and inference are related to increased psychotic-like experiences. These findings link neurophysiology to behavior during statistical learning and prediction formation, as well as providing further evidence for the idea of a continuum of psychosis in the healthy, nonclinical population.

KW - Educational science

KW - inference

KW - prediction error

KW - psychosis continuum;

KW - statistical learning

KW - volatility

KW - Psychology

UR - http://www.scopus.com/inward/record.url?scp=85090078723&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/0a7b4f87-20d4-3de4-8e4e-656560eb95fd/

U2 - 10.1523/JNEUROSCI.0315-20.2020

DO - 10.1523/JNEUROSCI.0315-20.2020

M3 - Journal articles

C2 - 32690617

VL - 40

SP - 6759

EP - 6769

JO - The Journal of Neuroscience

JF - The Journal of Neuroscience

SN - 0270-6474

IS - 35

ER -