1
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Powers A, Angelos PA, Bond A, Farina E, Fredericks C, Gandhi J, Greenwald M, Hernandez-Busot G, Hosein G, Kelley M, Mourgues C, Palmer W, Rodriguez-Sanchez J, Seabury R, Toribio S, Vin R, Weleff J, Woods S, Benrimoh D. A computational account of the development and evolution of psychotic symptoms. Biol Psychiatry 2024:S0006-3223(24)01584-1. [PMID: 39260466 DOI: 10.1016/j.biopsych.2024.08.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 08/08/2024] [Accepted: 08/13/2024] [Indexed: 09/13/2024]
Abstract
The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing a compensatory relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.
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Affiliation(s)
- Albert Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
| | - P A Angelos
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Alexandria Bond
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Emily Farina
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Carolyn Fredericks
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jay Gandhi
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Maximillian Greenwald
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | | | - Gabriel Hosein
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Megan Kelley
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Catalina Mourgues
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - William Palmer
- Yale University Department of Psychology, New Haven, CT, USA
| | | | - Rashina Seabury
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Silmilly Toribio
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Raina Vin
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jeremy Weleff
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Scott Woods
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - David Benrimoh
- Department of Psychiatry, McGill University, Montreal, Canada
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2
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Raymond N, Trotti R, Oss E, Lizano P. Lesion network guided neuromodulation to the extrastriate visual cortex in Charles Bonnet syndrome reduces visual hallucinations: A case study. Cortex 2024; 178:245-248. [PMID: 39053348 PMCID: PMC11349469 DOI: 10.1016/j.cortex.2024.06.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 05/28/2024] [Accepted: 06/03/2024] [Indexed: 07/27/2024]
Affiliation(s)
- Nicolas Raymond
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Rebekah Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Emma Oss
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA.
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3
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Powers A, Angelos P, Bond A, Farina E, Fredericks C, Gandhi J, Greenwald M, Hernandez-Busot G, Hosein G, Kelley M, Mourgues C, Palmer W, Rodriguez-Sanchez J, Seabury R, Toribio S, Vin R, Weleff J, Benrimoh D. A computational account of the development and evolution of psychotic symptoms. ARXIV 2024:arXiv:2404.10954v1. [PMID: 38699166 PMCID: PMC11065053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing an adaptive relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.
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Affiliation(s)
- Albert Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Philip Angelos
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Alexandria Bond
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Emily Farina
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Carolyn Fredericks
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jay Gandhi
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Maximillian Greenwald
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | | | - Gabriel Hosein
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Megan Kelley
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Catalina Mourgues
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - William Palmer
- Yale University Department of Psychology, New Haven, CT USA
| | | | - Rashina Seabury
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Silmilly Toribio
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Raina Vin
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jeremy Weleff
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - David Benrimoh
- Department of Psychiatry, McGill University, Montreal, Canada
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Schmid FR, Kriegleder MF. Explanatory power by vagueness. Challenges to the strong prior hypothesis on hallucinations exemplified by the Charles-Bonnet-Syndrome. Conscious Cogn 2024; 117:103620. [PMID: 38104388 DOI: 10.1016/j.concog.2023.103620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/30/2023] [Accepted: 12/06/2023] [Indexed: 12/19/2023]
Abstract
Predictive processing models are often ascribed a certain generality in conceptually unifying the relationships between perception, action, and cognition or the potential to posit a 'grand unified theory' of the mind. The limitations of this unification can be seen when these models are applied to specific cognitive phenomena or phenomenal consciousness. Our article discusses these shortcomings for predictive processing models of hallucinations by the example of the Charles-Bonnet-Syndrome. This case study shows that the current predictive processing account omits essential characteristics of stimulus-independent perception in general, which has critical phenomenological implications. We argue that the most popular predictive processing model of hallucinatory conditions - the strong prior hypothesis - fails to fully account for the characteristics of nonveridical perceptual experiences associated with Charles-Bonnet-Syndrome. To fill this explanatory gap, we propose that the strong prior hypothesis needs to include reality monitoring to apply to more than just veridical percepts.
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Affiliation(s)
- Franz Roman Schmid
- Vienna Cognitive Science Hub, University of Vienna, Austria; Vienna Doctoral School in Cognition, Behavior and Neuroscience, University of Vienna, Austria.
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Piarulli A, Vanneste S, Nemirovsky IE, Kandeepan S, Maudoux A, Gemignani A, De Ridder D, Soddu A. Tinnitus and distress: an electroencephalography classification study. Brain Commun 2023; 5:fcad018. [PMID: 36819938 PMCID: PMC9927883 DOI: 10.1093/braincomms/fcad018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/08/2022] [Accepted: 01/27/2023] [Indexed: 02/04/2023] Open
Abstract
There exist no objective markers for tinnitus or tinnitus disorders, which complicates diagnosis and treatments. The combination of EEG with sophisticated classification procedures may reveal biomarkers that can identify tinnitus and accurately differentiate different levels of distress experienced by patients. EEG recordings were obtained from 129 tinnitus patients and 142 healthy controls. Linear support vector machines were used to develop two classifiers: the first differentiated tinnitus patients from controls, while the second differentiated tinnitus patients with low and high distress levels. The classifier for healthy controls and tinnitus patients performed with an average accuracy of 96 and 94% for the training and test sets, respectively. For the distress classifier, these average accuracies were 89 and 84%. Minimal overlap was observed between the features of the two classifiers. EEG-derived features made it possible to accurately differentiate healthy controls and tinnitus patients as well as low and high distress tinnitus patients. The minimal overlap between the features of the two classifiers indicates that the source of distress in tinnitus, which could also be involved in distress related to other conditions, stems from different neuronal mechanisms compared to those causing the tinnitus pathology itself.
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Affiliation(s)
| | | | - Idan Efim Nemirovsky
- Western Institute for Neuroscience, Physics & Astronomy Department, University of Western Ontario, London, ON N6A 3K7, Canada
| | - Sivayini Kandeepan
- Department of Physics, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka
| | - Audrey Maudoux
- Robert Debré University Hospital, APHP, Paris 75019, France
| | - Angelo Gemignani
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa 56124, Italy
| | | | - Andrea Soddu
- Correspondence to: Andrea Soddu Physics & Astronomy Department Western Institute for Neuroscience University of Western Ontario 1151 Richmond Street, London, ON N6A 3K7, Canada E-mail:
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daSilva Morgan K, Schumacher J, Collerton D, Colloby S, Elder GJ, Olsen K, Ffytche DH, Taylor JP. Transcranial Direct Current Stimulation in the Treatment of Visual Hallucinations in Charles Bonnet Syndrome: A Randomized Placebo-Controlled Crossover Trial. Ophthalmology 2022; 129:1368-1379. [PMID: 35817197 DOI: 10.1016/j.ophtha.2022.06.041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE To investigate the potential therapeutic benefits and tolerability of inhibitory transcranial direct current stimulation (tDCS) on the remediation of visual hallucinations in Charles Bonnet syndrome (CBS). DESIGN Randomized, double-masked, placebo-controlled crossover trial. PARTICIPANTS Sixteen individuals diagnosed with CBS secondary to visual impairment caused by eye disease experiencing recurrent visual hallucinations. INTERVENTION All participants received 4 consecutive days of active and placebo cathodal stimulation (current density: 0.29 mA/cm2) to the visual cortex (Oz) over 2 defined treatment weeks, separated by a 4-week washout period. MAIN OUTCOME MEASURES Ratings of visual hallucination frequency and duration following active and placebo stimulation, accounting for treatment order, using a 2 × 2 repeated-measures model. Secondary outcomes included impact ratings of visual hallucinations and electrophysiological measures. RESULTS When compared with placebo treatment, active inhibitory stimulation of visual cortex resulted in a significant reduction in the frequency of visual hallucinations measured by the North East Visual Hallucinations Interview, with a moderate-to-large effect size. Impact measures of visual hallucinations improved in both placebo and active conditions, suggesting support and education for CBS may have therapeutic benefits. Participants who demonstrated greater occipital excitability on electroencephalography assessment at the start of treatment were more likely to report a positive treatment response. Stimulation was found to be tolerable in all participants, with no significant adverse effects reported, including no deterioration in preexisting visual impairment. CONCLUSIONS Findings indicate that inhibitory tDCS of visual cortex may reduce the frequency of visual hallucinations in people with CBS, particularly individuals who demonstrate greater occipital excitability prior to stimulation. tDCS may offer a feasible intervention option for CBS with no significant side effects, warranting larger-scale clinical trials to further characterize its efficacy.
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Affiliation(s)
- Katrina daSilva Morgan
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.
| | - Julia Schumacher
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Daniel Collerton
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sean Colloby
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Greg J Elder
- Northumbria Sleep Research, Department of Psychology, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom
| | - Kirsty Olsen
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Dominic H Ffytche
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
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Irizarry R, Sosa Gomez A, Tamayo Acosta J, Gonzalez Diaz L. Charles Bonnet Syndrome in the Setting of a Traumatic Brain Injury. Cureus 2022; 14:e29293. [PMID: 36147864 PMCID: PMC9482793 DOI: 10.7759/cureus.29293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/18/2022] [Indexed: 11/05/2022] Open
Abstract
Traumatic brain injuries are often associated with a broad range of neuropsychiatric sequelae, for which no straightforward treatment approach is established. Historically, the treatment of traumatic brain injuries has been tailored towards the symptoms presented by the patient. In this paper, we present the case of a 42-year-old male with a past medical history significant for retinitis pigmentosa who suffered a traumatic brain injury and subsequently developed visual hallucinations consistent with Charles Bonnet syndrome.
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