Glutamatergic Contribution to Probabilistic Reasoning and Jumping to Conclusions in Schizophrenia: A Double-Blind, Randomized Experimental Trial

Strube, Wolfgang; Marshall, Louise; Quattrocchi, Graziella; Little, Simon; Cimpianu, Camelia Lucia; Ulbrich, Miriam; Schneider‐Axmann, Thomas; Falkai, Peter; Hasan, Alkomiet; Bestmann, Sven

doi:10.1016/j.biopsych.2020.03.018

Cited by 14 publications

(16 citation statements)

References 65 publications

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“…Relation between premature commitments and decision uncertainty. Similar "jumping to conclusions" effects have already been described, but in participants or conditions associated with high decision confidence 14,15 , something which stands at odds with the increased decision uncertainty observed here under ketamine (Fig. 2).…”

Section: Coding Imbalancesupporting

confidence: 83%

“…Indeed, hypofunction of NMDA receptors has been proposed to destabilize the attractor-like dynamics observed in these circuits, by altering the strength of recurrent synaptic connectivity. At the cognitive level, this synaptic alteration is thought to impair inference in a way that can trigger decision biases 13 , "jumping to conclusions" 14,15 , but also deficits in confidence 16 . Together, this theoretical work confers a central role to NMDA receptors in the computational precision of neural circuits implementing cognitive inference.…”

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confidence: 99%

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Premature commitment to uncertain decisions during human NMDA receptor hypofunction

et al. 2022

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Making accurate decisions based on unreliable sensory evidence requires cognitive inference. Dysfunction of n-methyl-d-aspartate (NMDA) receptors impairs the integration of noisy input in theoretical models of neural circuits, but whether and how this synaptic alteration impairs human inference and confidence during uncertain decisions remains unknown. Here we use placebo-controlled infusions of ketamine to characterize the causal effect of human NMDA receptor hypofunction on cognitive inference and its neural correlates. At the behavioral level, ketamine triggers inference errors and elevated decision uncertainty. At the neural level, ketamine is associated with imbalanced coding of evidence and premature response preparation in electroencephalographic (EEG) activity. Through computational modeling of inference and confidence, we propose that this specific pattern of behavioral and neural impairments reflects an early commitment to inaccurate decisions, which aims at resolving the abnormal uncertainty generated by NMDA receptor hypofunction.

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Section: Coding Imbalancesupporting

confidence: 83%

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confidence: 99%

Premature commitment to uncertain decisions during human NMDA receptor hypofunction

et al. 2022

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“…A candidate mechanism is N -methyl- d -aspartate receptor (NMDAR) hypofunction 56 , 57 as a recent pharmacological study suggests that NMDAR functioning is linked to probabilistic reasoning during the beads task. 58 If this relationship can be confirmed, treatment response prediction to pharmacological interventions targeting glutamate metabolism (eg, d-serine or glycine), may be a promising avenue of research. Furthermore, future research is required to assess, whether model parameters allow stratifying patients for clinical trials using Metacognitive Training or similar interventions.…”

Section: Discussionmentioning

confidence: 99%

Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training

Hauke

Röth

Karvelis

et al. 2022

Schizophrenia Bulletin

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Background and Hypothesis In a complex world, gathering information and adjusting our beliefs about the world is of paramount importance. The literature suggests that patients with psychotic disorders display a tendency to draw early conclusions based on limited evidence, referred to as the jumping-to-conclusions bias, but few studies have examined the computational mechanisms underlying this and related belief-updating biases. Here, we employ a computational approach to understand the relationship between jumping-to-conclusions, psychotic disorders, and delusions. Study Design We modeled probabilistic reasoning of 261 patients with psychotic disorders and 56 healthy controls during an information sampling task—the fish task—with the Hierarchical Gaussian Filter. Subsequently, we examined the clinical utility of this computational approach by testing whether computational parameters, obtained from fitting the model to each individual’s behavior, could predict treatment response to Metacognitive Training using machine learning. Study Results We observed differences in probabilistic reasoning between patients with psychotic disorders and healthy controls, participants with and without jumping-to-conclusions bias, but not between patients with low and high current delusions. The computational analysis suggested that belief instability was increased in patients with psychotic disorders. Jumping-to-conclusions was associated with both increased belief instability and greater prior uncertainty. Lastly, belief instability predicted treatment response to Metacognitive Training at the individual level. Conclusions Our results point towards increased belief instability as a key computational mechanism underlying probabilistic reasoning in psychotic disorders. We provide a proof-of-concept that this computational approach may be useful to help identify suitable treatments for individual patients with psychotic disorders.

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“…This connotation is known as the “NMDAR hypofunction hypothesis” [ 34 ]. Numerous findings indicate that SCZ is induced by NMDAR hypofunction using drug treatments [ 35 , 36 , 37 , 38 , 39 ]. Indeed, hypoactivity of NMDA and brain-derived neurotrophic factor (BDNF)/glial-cell derived neurotrophic factor (GDNF) receptors via gut microbiota alterations in central nervous system disorders including schizophrenia has also been reported [ 40 , 41 , 42 ].…”

Section: A Tridimensional Relationship Of Gut Microbial Diversity Neu...mentioning

confidence: 99%

Modulation of Gut Microbial Diversity through Non-Pharmaceutical Approaches to Treat Schizophrenia

Munawar

Ahmad

Anwar

et al. 2022

IJMS

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Schizophrenia (SCZ) is a psychotic syndrome with well-defined signs and symptoms but indecisive causes and effective treatment. Unknown underpinning reasons and no cure of the disease profoundly elevate the risk of illness. Gut microbial dysbiosis related metabolic dysfunction is providing a new angle to look at the potential causes and treatment options for schizophrenia. Because of the number of side effects, including gut dysbiosis, of traditional antipsychotic drugs, new alternative therapeutic options are under consideration. We propose that non-pharmacotherapy using biotherapeutic products could be a potent treatment to improve cognitive impairment and other symptoms of schizophrenia. Use of live microorganisms (probiotics), fibers (prebiotics), and polyphenols alone or in a mixture can maintain gut microbial diversity and improve the two-way relationship of the gut microbiota and the central nervous system. Fiber and polyphenol induced management of gut microbiota may positively influence the gut–brain axis by increasing the level of brain-derived neurotrophic factors involved in schizophrenia. Furthermore, we endorse the need for comprehensive clinical assessment and follow-up of psychobiotic (pro and prebiotics) treatment in mental illness to estimate the level of target recovery and disability reduction in schizophrenia.

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Glutamatergic Contribution to Probabilistic Reasoning and Jumping to Conclusions in Schizophrenia: A Double-Blind, Randomized Experimental Trial

Abstract: contribution to probabilistic reasoning and jumping-to-conclusions in schizophrenia: a double blind, randomized experimental trial., Biological Psychiatry (2020), doi:

Cited by 14 publications

References 65 publications

Premature commitment to uncertain decisions during human NMDA receptor hypofunction

Premature commitment to uncertain decisions during human NMDA receptor hypofunction

Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training

Modulation of Gut Microbial Diversity through Non-Pharmaceutical Approaches to Treat Schizophrenia

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