Perceptual pathways to hallucinogenesis

Sheldon, Andrew D.; Kafadar, Eren; Fisher, Victoria; Greenwald, Maximillian; Aitken, Fraser; Negreira, Alyson; Woods, Scott W.; Powers, Albert R.

doi:10.1016/j.schres.2022.02.002

“…The experimental paradigm was comprised of the determination of the nociceptive threshold (method of limits and QUEST) and probabilistic Pavlovian conditioning with a visual cue (main body of the NPP-task; Fig. 1a) as inspired and utilized in the works of Powers et al 35,37,38 .…”

Section: Mechanical Pain Detection Protocolmentioning

confidence: 99%

A novel computational approach to pain perception modelling within a Bayesian framework using quantitative sensory testing

Drusko

¹

,

Baumeister

²

,

Christensen

³

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Pain perception can be studied as an inferential process in which prior information influences the perception of nociceptive input. To date, there are no suitable psychophysical paradigms to measure this at an individual level. We developed a quantitative sensory testing paradigm allowing for quantification of the influence of prior expectations versus current nociceptive input during perception. Using a Pavlovian-learning task, we investigated the influence of prior expectations on the belief about the varying strength of association between a painful electrical cutaneous stimulus and a visual cue in healthy subjects (N = 70). The belief in cue-pain associations was examined with computational modelling using a Hierarchical Gaussian Filter (HGF). Prior weighting estimates in the HGF model were compared with the established measures of conditioned pain modulation (CPM) and temporal summation of pain (TSP) assessed by cuff algometry. Subsequent HGF-modelling and estimation of the influence of prior beliefs on perception showed that 70% of subjects had a higher reliance on nociceptive input during perception of acute pain stimuli, whereas 30% showed a stronger weighting of prior expectations over sensory evidence. There was no association between prior weighting estimates and CPM or TSP. The data demonstrates relevant individual differences in prior weighting and suggests an importance of top-down cognitive processes on pain perception. Our new psychophysical testing paradigm provides a method to identify individuals with traits suggesting greater reliance on prior expectations in pain perception, which may be a risk factor for developing chronic pain and may be differentially responsive to learning-based interventions.

show abstract

“…This seeming contradiction is often resolved through appeals to hierarchy: delusions may represent aberrations at lower level processing, while hallucinations reflect aberrations at higher levels ( 118 ). Separation across the processing hierarchy may also be paired with separation over time: PE-mediated belief formation may itself lead to the solidification of inappropriate beliefs and subsequent hallucination formation, at least in a subgroup of individuals with psychosis ( 130 ).…”

Section: Computational Frameworkmentioning

confidence: 99%

A computational lens on menopause-associated psychosis

Fisher

¹

,

Ortiz

²

,

Powers

³

2022

Self Cite

View full text Add to dashboard Cite

Psychotic episodes are debilitating disease states that can cause extreme distress and impair functioning. There are sex differences that drive the onset of these episodes. One difference is that, in addition to a risk period in adolescence and early adulthood, women approaching the menopause transition experience a second period of risk for new-onset psychosis. One leading hypothesis explaining this menopause-associated psychosis (MAP) is that estrogen decline in menopause removes a protective factor against processes that contribute to psychotic symptoms. However, the neural mechanisms connecting estrogen decline to these symptoms are still not well understood. Using the tools of computational psychiatry, links have been proposed between symptom presentation and potential algorithmic and biological correlates. These models connect changes in signaling with symptom formation by evaluating changes in information processing that are not easily observable (latent states). In this manuscript, we contextualize the observed effects of estrogen (decline) on neural pathways implicated in psychosis. We then propose how estrogen could drive changes in latent states giving rise to cognitive and psychotic symptoms associated with psychosis. Using computational frameworks to inform research in MAP may provide a systematic method for identifying patient-specific pathways driving symptoms and simultaneously refine models describing the pathogenesis of psychosis across all age groups.

show abstract

“…Separation across the processing hierarchy may also be paired with separation over time: PEmediated belief formation may itself lead to the solidification of inappropriate beliefs and subsequent hallucination formation, at least in a subgroup of individuals with psychosis (119).…”

Section: Positive Symptomsmentioning

confidence: 99%

A Computational Lens on Menopause-Associated Psychosis

Fisher¹,

Powers²

2022

Preprint

0

View full text Add to dashboard Cite

Psychotic episodes are debilitating disease states that can cause extreme distress and impair functioning. There are sex differences that drive the onset of these episodes. One difference is that, in addition to a risk period in adolescence and early adulthood, women approaching the menopause transition experience a second period of risk for new-onset psychosis. One leading hypothesis explaining this menopause-associated psychosis (MAP) is that estrogen decline in menopause removes a protective factor against processes that contribute to psychotic symptoms. However, the neural mechanisms connecting estrogen decline to these symptoms are still not well understood. Using the tools of computational psychiatry, links have been proposed between symptom presentation and potential algorithmic and biological correlates. These models connect changes in signaling with symptom formation by evaluating changes in information processing that are not easily observable (latent states). In this manuscript, we contextualize the observed effects of estrogen (decline) on neural pathways implicated in psychosis. We then propose how estrogen could drive changes in latent states giving rise to cognitive and psychotic symptoms associated with psychosis. Using computational frameworks to inform research in MAP may provide a systematic method for identifying patient-specific pathways driving symptoms and simultaneously refine models describing the pathogenesis of psychosis across all age groups.

show abstract

Perceptual pathways to hallucinogenesis

Cited by 12 publications

References 172 publications

A novel computational approach to pain perception modelling within a Bayesian framework using quantitative sensory testing

A novel computational approach to pain perception modelling within a Bayesian framework using quantitative sensory testing

A computational lens on menopause-associated psychosis

A Computational Lens on Menopause-Associated Psychosis

Contact Info

Product

Resources

About