Psychopharmacology
November 5, 2025
Milad Soltanzadeh, Wang Zheng, Shona G. Allohverdi et al.
1 citation
RationaleKetamine and psilocybin have demonstrated therapeutic potential for mental disorders, including major depressive disorder, yet they engage distinct mechanisms of action. Ketamine, a dissociative hallucinogen, acts by blocking N-methyl-D-aspartate receptors (NMDAR), whereas psilocybin primarily targets serotonin receptors. These divergent mechanisms are reflected in their...
Research Square
September 26, 2024
Shona G. Allohverdi, Milad Soltanzadeh, André Schmidt et al.
Abstract Ketamine and psilocybin show potential as therapies for various mental illnesses, including major depressive disorder. However, further investigation into their neural mechanisms is required to understand their effects on the brain. By combining computational modelling with electroencephalography (EEG), we examine the effects of ketamine and psilocybin on hierarchical sensory...
PLoS One
2024
Josh Martin, Fatemeh Gholamali Nezhad, Alice Rueda et al.
2 citations
Ketamine has recently attracted considerable attention for its rapid effects on patients with major depressive disorder, including treatment-resistant depression (TRD). Despite ketamine's promising results in treating depression, a significant number of patients do not respond to the treatment, and predicting who will benefit remains a challenge. Although its antidepressant effects are known to...
Frontiers in Psychiatry
June 30, 2023
Colleen E. Charlton, Povilas Karvelis, Roger S McIntyre et al.
7 citations
Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine’s anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and...
Frontiers in Psychiatry
June 30, 2023
Colleen E. Charlton, Povilas Karvelis, Roger S McIntyre et al.
7 citations
Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine’s anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and...
Frontiers in Psychiatry
June 30, 2023
Colleen E. Charlton, Povilas Karvelis, Roger S McIntyre et al.
7 citations
Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine’s anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and...
Frontiers in Psychiatry
June 30, 2023
Colleen E. Charlton, Povilas Karvelis, Roger S McIntyre et al.
7 citations
Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine’s anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and...
Neuropsychopharmacology
April 25, 2023
Peter Bedford, Daniel J. Hauke, Zheng Wang et al.
43 citations
Abstract Psychedelics have emerged as promising candidate treatments for various psychiatric conditions, and given their clinical potential, there is a need to identify biomarkers that underlie their effects. Here, we investigate the neural mechanisms of lysergic acid diethylamide (LSD) using regression dynamic causal modelling (rDCM), a novel technique that assesses whole-brain effective...
Journal of Neuroscience
June 19, 2020
Lilian Weber, Andreea O. Diaconescu, Christoph Mathys et al.
82 citations
The auditory mismatch negativity (MMN) is significantly reduced in schizophrenia. Notably, a similar MMN reduction can be achieved with NMDA receptor (NMDAR) antagonists. Both phenomena have been interpreted as reflecting an impairment of predictive coding or, more generally, the "Bayesian brain" notion that the brain continuously updates a hierarchical model to infer the causes of its sensory...
Cerebral Cortex
August 8, 2012
André Schmidt, Andreea O. Diaconescu, Michael Kometer et al.
110 citations
This paper presents a model-based investigation of mechanisms underlying the reduction of mismatch negativity (MMN) amplitudes under the NMDA-receptor antagonist ketamine. We applied dynamic causal modeling and Bayesian model selection to data from a recent ketamine study of the roving MMN paradigm, using a cross-over, double-blind, placebo-controlled design. Our modeling was guided by a...