PMID- 37793581 OWN - NLM STAT- MEDLINE DCOM- 20231106 LR - 20231106 IS - 1873-7528 (Electronic) IS - 0149-7634 (Linking) VI - 154 DP - 2023 Nov TI - Storm on predictive brain: A neurocomputational account of ketamine antidepressant effect. PG - 105410 LID - S0149-7634(23)00379-2 [pii] LID - 10.1016/j.neubiorev.2023.105410 [doi] AB - For the past decade, ketamine, an N-methyl-D-aspartate receptor (NMDAr) antagonist, has been considered a promising treatment for major depressive disorder (MDD). Unlike the delayed effect of monoaminergic treatment, ketamine may produce fast-acting antidepressant effects hours after a single administration at subanesthetic dose. Along with these antidepressant effects, it may also induce transient dissociative (disturbing of the sense of self and reality) symptoms during acute administration which resolve within hours. To understand ketamine's rapid-acting antidepressant effect, several biological hypotheses have been explored, but despite these promising avenues, there is a lack of model to understand the timeframe of antidepressant and dissociative effects of ketamine. In this article, we propose a neurocomputational account of ketamine's antidepressant and dissociative effects based on the Predictive Processing (PP) theory, a framework for cognitive and sensory processing. PP theory suggests that the brain produces top-down predictions to process incoming sensory signals, and generates bottom-up prediction errors (PEs) which are then used to update predictions. This iterative dynamic neural process would relies on N-methyl-D-aspartate (NMDAr) and alpha-amino-3-hydroxy-5-methyl-4-isoxazole-propionic receptors (AMPAr), two major component of the glutamatergic signaling. Furthermore, it has been suggested that MDD is characterized by over-rigid predictions which cannot be updated by the PEs, leading to miscalibration of hierarchical inference and self-reinforcing negative feedback loops. Based on former empirical studies using behavioral paradigms, neurophysiological recordings, and computational modeling, we suggest that ketamine impairs top-down predictions by blocking NMDA receptors, and enhances presynaptic glutamate release and PEs, producing transient dissociative symptoms and fast-acting antidepressant effect in hours following acute administration. Moreover, we present data showing that ketamine may enhance a delayed neural plasticity pathways through AMPAr potentiation, triggering a prolonged antidepressant effect up to seven days for unique administration. Taken together, the two sides of antidepressant effects with distinct timeframe could constitute the keystone of antidepressant properties of ketamine. These PP disturbances may also participate to a ketamine-induced time window of mental flexibility, which can be used to improve the psychotherapeutic process. Finally, these proposals could be used as a theoretical framework for future research into fast-acting antidepressants, and combination with existing antidepressant and psychotherapy. CI - Copyright (c) 2023 The Authors. Published by Elsevier Ltd.. All rights reserved. FAU - Bottemanne, Hugo AU - Bottemanne H AD - Paris Brain Institute - Institut du Cerveau (ICM), UMR 7225 / UMRS 1127, Sorbonne University / CNRS / INSERM, Paris, France; Sorbonne University, Department of Philosophy, Science Norm Democracy Research Unit, UMR, 8011, Paris, France; Sorbonne University, Department of Psychiatry, Pitie-Salpetriere Hospital, Assistance Publique-Hopitaux de Paris (AP-HP), Paris, France. Electronic address: hugo.bottemanne@sorbonne-universite.fr. FAU - Berkovitch, Lucie AU - Berkovitch L AD - Saclay CEA Centre, Neurospin, Gif-Sur-Yvette Cedex, France; Department of Psychiatry, GHU Paris Psychiatrie et Neurosciences, Service Hospitalo-Universitaire, Paris, France. FAU - Gauld, Christophe AU - Gauld C AD - Department of Child Psychiatry, CHU de Lyon, F-69000 Lyon, France; Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS & Universite Claude Bernard Lyon 1, F-69000 Lyon, France. FAU - Balcerac, Alexander AU - Balcerac A AD - Paris Brain Institute - Institut du Cerveau (ICM), UMR 7225 / UMRS 1127, Sorbonne University / CNRS / INSERM, Paris, France; Sorbonne University, Department of Neurology, Pitie-Salpetriere Hospital, Assistance Publique-Hopitaux de Paris (AP-HP), Paris, France. FAU - Schmidt, Liane AU - Schmidt L AD - Paris Brain Institute - Institut du Cerveau (ICM), UMR 7225 / UMRS 1127, Sorbonne University / CNRS / INSERM, Paris, France. FAU - Mouchabac, Stephane AU - Mouchabac S AD - Paris Brain Institute - Institut du Cerveau (ICM), UMR 7225 / UMRS 1127, Sorbonne University / CNRS / INSERM, Paris, France; Sorbonne University, Department of Psychiatry, Saint-Antoine Hospital, Assistance Publique-Hopitaux de Paris (AP-HP), Paris, France. FAU - Fossati, Philippe AU - Fossati P AD - Paris Brain Institute - Institut du Cerveau (ICM), UMR 7225 / UMRS 1127, Sorbonne University / CNRS / INSERM, Paris, France; Sorbonne University, Department of Philosophy, Science Norm Democracy Research Unit, UMR, 8011, Paris, France. LA - eng PT - Journal Article PT - Review DEP - 20231002 PL - United States TA - Neurosci Biobehav Rev JT - Neuroscience and biobehavioral reviews JID - 7806090 RN - 690G0D6V8H (Ketamine) RN - 0 (Antidepressive Agents) RN - 0 (Receptors, N-Methyl-D-Aspartate) SB - IM MH - Humans MH - *Ketamine/pharmacology MH - *Depressive Disorder, Major/drug therapy MH - Antidepressive Agents/pharmacology/therapeutic use MH - Brain/metabolism MH - Signal Transduction MH - Receptors, N-Methyl-D-Aspartate/metabolism OTO - NOTNLM OT - Antidepressant OT - Bayesian brain OT - Bayesian inference OT - Belief OT - Ketamine OT - Neural oscillations OT - Predictive coding OT - Predictive processing OT - Rapid acting antidepressant EDAT- 2023/10/05 01:00 MHDA- 2023/11/06 06:43 CRDT- 2023/10/04 19:14 PHST- 2023/04/22 00:00 [received] PHST- 2023/08/24 00:00 [revised] PHST- 2023/09/26 00:00 [accepted] PHST- 2023/11/06 06:43 [medline] PHST- 2023/10/05 01:00 [pubmed] PHST- 2023/10/04 19:14 [entrez] AID - S0149-7634(23)00379-2 [pii] AID - 10.1016/j.neubiorev.2023.105410 [doi] PST - ppublish SO - Neurosci Biobehav Rev. 2023 Nov;154:105410. doi: 10.1016/j.neubiorev.2023.105410. Epub 2023 Oct 2.