Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework

Kafadar, Eren; Mittal, Vijay A.; Strauss, Gregory P.; Chapman, Hannah C.; Ellman, Lauren M.; Bansal, Sonia; Gold, James M.; Alderson-Day, Ben; Evans, Samuel; Moffatt, Jamie; Silverstein, Steven M.; Walker, Elaine F.; Woods, Scott W.; Corlett, Philip R.; Powers, Albert R.

doi:10.1016/j.schres.2020.04.017

Cited by 29 publications

(39 citation statements)

References 56 publications

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“…The CH task is a sensory-detection task using principles of psychometric thresholding and Pavlovian associative learning 17,18,[30][31][32][33] to induce auditory hallucinations 17,18 . Participants press buttons to indicate their detection of a target stimulus, a 1-kHz pure tone embedded in 70-dB SPL white noise and presented concurrently with a flashed white checkerboard on a black background (Fig.…”

Section: Auditory Conditioned Hallucinations (Ch) Taskmentioning

confidence: 99%

“…Here we present data from a large, heterogeneous, and deeply-phenotyped group of individuals with unusual perceptual experiences, including those with (AH+; N=249) and without (AH-; N=209) auditory hallucinations. Participants completed the Conditioned Hallucinations (CH) task, which has previously been shown to be sensitive to prior hyper-precision and propensity toward auditory hallucinations 17,18 . We again show that the CH task and estimated relative prior precision are sensitive to hallucination propensity.…”

Section: Introductionmentioning

confidence: 99%

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Conditioned hallucinations and prior hyper-precision are state-sensitive markers of hallucination susceptibility

Kafadar¹,

Fisher²,

Quagan³

et al. 2021

Preprint

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Recent advances in computational psychiatry have identified latent cognitive and perceptual states that predispose to psychotic symptoms. Behavioral data fit to Bayesian models have demonstrated an over-reliance on priors during perception in select samples of individuals with hallucinations. However, the clinical utility of this observation depends on whether it reflects static symptom risk or current symptom state. To determine whether task performance and estimated prior weighting related to specific elements of symptom expression, a large, heterogeneous, and deeply-phenotyped sample of hallucinators (N = 249) and non-hallucinators (N=209) performed the Conditioned Hallucination (CH) task. CH rates were sensitive to hallucination state, correlating with hallucination severity measures over the two days leading up to task completion and driven by heightened reliance on past experiences (priors). To further test this relationship, a subset of AH+ participants (N = 40) performed a repeated-measures version of the CH task. Changes in both CH frequency and relative prior precision varied with changes in AH frequency on follow-up. These results support the use of CH rate and prior hyper-precision as state markers of hallucination status, potentially useful in tracking disease development and treatment response.

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Section: Auditory Conditioned Hallucinations (Ch) Taskmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conditioned hallucinations and prior hyper-precision are state-sensitive markers of hallucination susceptibility

Kafadar¹,

Fisher²,

Quagan³

et al. 2021

Preprint

Self Cite

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“… 82 There are now a set of behavioral methods that are sensitive to individual differences in the proclivity to hear sounds in the absence of sounds and to perceive comprehensible speech when presented with highly degraded speech samples. 80 , 81 , 83 We hypothesize that measures from both of these “pathways” toward idiosyncratic percepts and beliefs are relevant for the prediction of conversion to psychosis.…”

Section: New Directions In the Understanding Of Symptom Mechanismsmentioning

confidence: 99%

Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience

Gold

Corlett

Strauss

et al. 2020

Schizophrenia Bulletin

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Abstract Research suggests that early identification and intervention with individuals at clinical high risk (CHR) for psychosis may be able to improve the course of illness. The first generation of studies suggested that the identification of CHR through the use of specialized interviews evaluating attenuated psychosis symptoms is a promising strategy for exploring mechanisms associated with illness progression, etiology, and identifying new treatment targets. The next generation of research on psychosis risk must address two major limitations: (1) interview methods have limited specificity, as recent estimates indicate that only 15%–30% of individuals identified as CHR convert to psychosis and (2) the expertise needed to make CHR diagnosis is only accessible in a handful of academic centers. Here, we introduce a new approach to CHR assessment that has the potential to increase accessibility and positive predictive value. Recent advances in clinical and computational cognitive neuroscience have generated new behavioral measures that assay the cognitive mechanisms and neural systems that underlie the positive, negative, and disorganization symptoms that are characteristic of psychotic disorders. We hypothesize that measures tied to symptom generation will lead to enhanced sensitivity and specificity relative to interview methods and the cognitive intermediate phenotype measures that have been studied to date that are typically indicators of trait vulnerability and, therefore, have a high false positive rate for conversion to psychosis. These new behavioral measures have the potential to be implemented on the internet and at minimal expense, thereby increasing accessibility of assessments.

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“…However, when CHR initiatives have incorporated performance-based assessments, they have often been traitlinked measures that are unlikely to be sensitive to, or predictive of, changes in mental status 4 . The incorporation of state-sensitive performance-based measures with established links to the pathophysiological mechanisms implicated in symptom genesis may allow for more objective and effective monitoring of changes in mental status that are predictive of an impending psychotic episode or a positive response to treatment 4,5 . While this approach to psychosis risk assessment is just emerging, there are already multiple studies of schizophrenia documenting that relatively brief and non-invasive behavioral and electrophysiological measures can tap into mechanisms thought to be involved in positive [6][7][8] , negative [9][10][11][12] , disorganized [13][14][15] or motor 16 symptoms, and that these measures are sensitive to changes in the severity level of the symptom cluster with which they are correlated 14,17,18 .…”

Section: Introductionmentioning

confidence: 99%

“…Findings from two recent magnetoencephalography (MEG) studies are consistent with the notion that predictive processes are engaged during the MFT 30,31 . A growing literature has linked alterations in predictive processing with positive symptoms in schizophrenia 5,[32][33][34] , suggesting that MFT performance among those at CHR for psychosis might be associated with severity of attenuated positive symptoms.…”

Section: Introductionmentioning

confidence: 99%

Increased face detection responses on the mooney faces test in people at clinical high risk for psychosis

et al. 2021

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Identifying state-sensitive measures of perceptual and cognitive processes implicated in psychosis may allow for objective, earlier, and better monitoring of changes in mental status that are predictive of an impending psychotic episode, relative to traditional self-report-based clinical measures. To determine whether a measure of visual perception that has demonstrated sensitivity to the clinical state of schizophrenia in multiple prior studies is sensitive to features of the at-risk mental state, we examined differences between young people identified as being at clinical high risk for psychosis (CHR; n = 37) and non-psychiatric matched controls (n = 29) on the Mooney Faces Test (MFT). On each trial of the MFT, participants report whether they perceive a face in a degraded face image. The CHR group reported perceiving a greater number of faces in both upright and inverted MFT stimuli. Consistent with prior work, males reported more faces on the MFT than females in both conditions. However, the finding of greater reported face perception among CHR subjects was robustly observed in the female CHR group relative to the female control group. Among male CHR participants, greater reported face perception was related to increased perceptual abnormalities. These preliminary results are consistent with a small but growing literature suggesting that heightened perceptual sensitivity may characterize individuals at increased clinical risk for psychosis. Further studies are needed to determine the contributions of specific perceptual, cognitive, and motivational mechanisms to the findings.

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Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework

Cited by 29 publications

References 56 publications

Conditioned hallucinations and prior hyper-precision are state-sensitive markers of hallucination susceptibility

Conditioned hallucinations and prior hyper-precision are state-sensitive markers of hallucination susceptibility

Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience

Increased face detection responses on the mooney faces test in people at clinical high risk for psychosis

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