The mechanisms underlying conditioning of phantom percepts differ between those with hallucinations and synesthesia.

There are many different kinds of 'phantom' percepts but it is unknown whether they are united by common mechanisms. For example, synaesthesia (e.g., numbers evoking colour) and hallucinations appear conceptually and phenomenologically similar: both result in a percept that does not have an environmental correlate. Here, people with synaesthesia (n = 66) performed a conditioned hallucinations paradigm known to be sensitive to hallucination susceptibility, and we asked whether synaesthetes would show the same behavioural profile as hallucinators in this task. Repeated pairing of checkerboards with tones, and gratings with colours encourages the participant to draw on prior knowledge when asked to report on the presence of the difficult-to-detect target stimulus. Synaesthetes show increased modelled expectancies for the stimulus association across the board, resulting in a higher number of detections at all stimulus intensities. This is in contrast to the pattern observed in hallucinators, who weigh their prior beliefs more strongly than controls, giving rise to more conditioned hallucinations. Results indicate that fundamentally different perceptual processes may be at the core of these seemingly similar experiences.

Conditioned Hallucinations and Prior Overweighting Are State-Sensitive Markers of Hallucination Susceptibility.

BACKGROUND: 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 overreliance on priors (i.e., prior overweighting) during perception in select samples of individuals with hallucinations, corresponding to increased precision of prior expectations over incoming sensory evidence. However, the clinical utility of this observation depends on the extent to which it reflects static symptom risk or current symptom state. METHODS: To determine whether task performance and estimated prior weighting relate to specific elements of symptom expression, a large, heterogeneous, and deeply phenotyped sample of hallucinators (n = 249) and nonhallucinators (n = 209) performed the conditioned hallucination (CH) task. RESULTS: We found that CH rates predicted stable measures of hallucination status (i.e., peak frequency). However, CH rates were more sensitive to hallucination state (i.e., recent frequency), significantly correlating with recent hallucination severity and driven by heightened reliance on past experiences (priors). To further test the sensitivity of CH rate and prior weighting to symptom severity, a subset of participants with hallucinations (n = 40) performed a repeated-measures version of the CH task. Changes in both CH frequency and prior weighting varied with changes in auditory hallucination frequency on follow-up. CONCLUSIONS: These results indicate that CH rate and prior overweighting are state markers of hallucination status, potentially useful in tracking disease development and treatment response.

Perceptual pathways to hallucinogenesis.

Recent advances in computational psychiatry have provided unique insights into the neural and cognitive underpinnings of psychotic symptoms. In particular, a host of new data has demonstrated the utility of computational frameworks for understanding how hallucinations might arise from alterations in typical perceptual processing. Of particular promise are models based in Bayesian inference that link hallucinatory perceptual experiences to latent states that may drive them. In this piece, we move beyond these findings to ask: how and why do these latent states arise, and how might we take advantage of heterogeneity in that process to develop precision approaches to the treatment of hallucinations? We leverage specific models of Bayesian inference to discuss components that might lead to the development of hallucinations. Using the unifying power of our model, we attempt to place disparate findings in the study of psychotic symptoms within a common framework. Finally, we suggest directions for future elaboration of these models in the service of a more refined psychiatric nosology based on predictable, testable, and ultimately treatable information processing derangements.

Measuring Voluntary Control Over Hallucinations: The Yale Control Over Perceptual Experiences (COPE) Scales.

Auditory verbal hallucinations (AVH) frequently cause significant distress and dysfunction, and may be unresponsive to conventional treatments. Some voice-hearers report an ability to fully control the onset and offset of their AVH, making them significantly less disruptive. Measuring and understanding these abilities may lead to novel interventions to enhance control over AVH. Fifty-two voice-hearers participated in the pilot study. 318 participants with frequent AVH participated in the validation study. A pool of 59 items was developed by a diverse team including voice-hearers and clinicians. After the pilot study, 35 items were retained. Factorial structure was assessed with exploratory (EFA, n = 148) and confirmatory (CFA, n = 170) factor analyses. Reliability and convergent validity were assessed using a comprehensive battery of validated phenomenological and clinical scales. CFA on the final 18 items supported two factors for a Methods of Control Scale (5 items each, average ω = .87), and one factor for a Degree of Control Scale (8 items, average ω = .95). Correlation with clinical measures supported convergent validity. Degree of control was associated with positive clinical outcomes in voice-hearers both with and without a psychosis-spectrum diagnosis. Degree of control also varied with quality of life independently of symptom severity and AVH content. The Yale control over perceptual experiences (COPE) Scales robustly measure voice-hearers' control over AVH and exhibit sound psychometric properties. Results demonstrate that the capacity to voluntarily control AVH is independently associated with positive clinical outcomes. Reliable measurement of control over AVH will enable future development of interventions meant to bolster that control.

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

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.

Development of Voluntary Control Over Voice-Hearing Experiences: Evidence From Treatment-Seeking and Non-Treatment-Seeking Voice-Hearers.

Voluntary control over voice-hearing experiences is one of the most consistent predictors of functioning among voice-hearers. However, control over voice-hearing experiences is likely to be more nuanced and variable than may be appreciated through coarse clinician-rated measures, which provide little information about how control is conceptualized and developed. We aimed to identify key factors in the evolution of control over voice-hearing experiences in treatment-seeking (N = 7) and non-treatment-seeking (N = 8) voice-hearers. Treatment-seeking voice-hearers were drawn from local chapters of the Connecticut Hearing Voices Network, and non-treatment-seeking voice-hearers were recruited from local spiritually oriented organizations. Both groups participated in a clinical assessment, and a semi-structured interview meant to explore the types of control exhibited and how it is fostered. Using Grounded Theory, we identified that participants from both groups exerted direct and indirect control over their voice-hearing experiences. Participants that developed a spiritual explanatory framework were more likely to exert direct control over the voice-hearing experiences than those that developed a pathologizing framework. Importantly, despite clear differences in explanatory framework and distress because of their experiences, both groups underwent similar trajectories to develop control and acceptance over their voice-hearing experiences. Understanding these factors will be critical in transforming control over voice-hearing experiences from a phenomenological observation to an actionable route for clinical intervention.

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

Early intervention in psychotic spectrum disorders is critical for maximizing key clinical outcomes. While there is some evidence for the utility of intervention during the prodromal phase of the illness, efficacy of interventions is difficult to assess without appropriate risk stratification. This will require biomarkers that robustly help to identify risk level and are also relatively easy to obtain. Recent work highlights the utility of computer-based behavioral tasks for understanding the pathophysiology of psychotic symptoms. Computational modeling of performance on such tasks may be particularly useful because they explicitly and formally link performance and symptom expression. Several recent studies have successfully applied principles of Bayesian inference to understanding the computational underpinnings of hallucinations. Within this framework, hallucinations are seen as arising from an over-weighting of prior beliefs relative to sensory evidence. This view is supported by recently-published data from two tasks: the Conditioned Hallucinations (CH) task, which determines the degree to which participants use expectations in detecting a target tone; and a Sine-Vocoded Speech (SVS) task, in which participants can use prior exposure to speech samples to inform their understanding of degraded speech stimuli. We administered both of these tasks to two samples of participants at clinical high risk for psychosis (CHR; N = 19) and healthy controls (HC; N = 17). CHR participants reported both more conditioned hallucinations and more pre-training SVS detection. In addition, relationships were found between participants' performance on both tasks. On computational modeling of behavior on the CH task, CHR participants demonstrate significantly poorer recognition of task volatility as well as a trend toward higher weighting of priors. A relationship was found between this latter effect and performance on both tasks. Taken together, these results support the assertion that these two tasks may be driven by similar latent factors in perceptual inference, and highlight the potential utility of computationally-based tasks in identifying risk.