Comparison of conventional and rapid-acting antidepressants in a rodent probabilistic reversal learning task.
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ABSTRACT:
SUBMITTER: Wilkinson MP
PROVIDER: S-EPMC7085917 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A growing number of epidemiological and experimental studies has established that circadian disruption is strongly associated with psychiatric disorders, including major depressive disorder (MDD). This association is becoming increasingly relevant considering that modern lifestyles, social zeitgebers (time cues) and genetic variants contribute to disrupting circadian rhythms that may lead to psychiatric disorders. Circadian abnormalities associated with MDD include dysregulated rhythms of sleep, temperature, hormonal secretions, and mood which are modulated by the molecular clock. Rapid-acting antidepressants such as subanesthetic ketamine and sleep deprivation therapy can improve symptoms within 24 h in a subset of depressed patients, in striking contrast to conventional treatments, which generally require weeks for a full clinical response. Importantly, animal data show that sleep deprivation and ketamine have overlapping effects on clock gene expression. Furthermore, emerging data implicate the circadian system as a critical component involved in rapid antidepressant responses via several intracellular signaling pathways such as GSK3β, mTOR, MAPK, and NOTCH to initiate synaptic plasticity. Future research on the relationship between depression and the circadian clock may contribute to the development of novel therapeutic strategies for depression-like symptoms. In this review we summarize recent evidence describing: (1) how the circadian clock is implicated in depression, (2) how clock genes may contribute to fast-acting antidepressants, and (3) the mechanistic links between the clock genes driving circadian rhythms and neuroplasticity.
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Project description:Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population readout of a set of probabilistic spatial computations.
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Project description:Purpose of reviewKetamine produces rapid (within hours) antidepressant actions, even in patients considered treatment resistant, and even shows promise for suicidal ideation. Here, we review current research on the molecular and cellular mechanisms of ketamine and other novel rapid-acting antidepressants, and briefly explore gender differences in the pathophysiology and treatment of MDD.Recent findingsKetamine, an NMDA receptor antagonist, increases BDNF release and synaptic connectivity, opposing the deficits caused by chronic stress and depression. Efforts are focused on the development of novel rapid agents that produce similar synaptic and rapid antidepressant actions, but without the side effects of ketamine. The impact of gender on the response to ketamine and other rapid-acting antidepressants is in early stages of investigation.SummaryThe discovery that ketamine produces rapid therapeutic actions for depression and suicidal ideation represents a major breakthrough and much needed alternative to currently available medications. However, novel fast acting agents with fewer side effects are needed, as well as elucidation of the efficacy of these rapid-acting antidepressants for depression in women.
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Project description:Reversal learning paradigms are widely used assays of behavioral flexibility with their probabilistic versions being more amenable to studying integration of reward outcomes over time. Prior research suggests differences between initial and reversal learning, including higher learning rates, a greater need for inhibitory control, and more perseveration after reversals. However, it is not well-understood what aspects of stimulus-based reversal learning are unique to reversals, and whether and how observed differences depend on reward probability. Here, we used a visual probabilistic discrimination and reversal learning paradigm where male and female rats selected between a pair of stimuli associated with different reward probabilities. We compared accuracy, rewards collected, omissions, latencies, win-stay/lose-shift strategies, and indices of perseveration across two different reward probability schedules. We found that discrimination and reversal learning are behaviorally more unique than similar: Fit of choice behavior using reinforcement learning models revealed a lower sensitivity to the difference in subjective reward values (greater exploration) and higher learning rates for the reversal phase. We also found latencies to choose the better option were greater in females than males, but only for the reversal phase. Further, animals employed more win-stay strategies during early discrimination and increased perseveration during early reversal learning. Interestingly, a consistent reward probability group difference emerged with a richer environment associated with longer reward collection latencies than a leaner environment. Future studies should systematically compare the neural correlates of fine-grained behavioral measures to reveal possible dissociations in how the circuitry is recruited in each phase. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Project description:RATIONALE:Reward-related impairments are common in major depressive disorder (MDD) and may contribute to the loss of interest in pleasurable activities. A novel approach to studying reward-related decision-making are effort-based tasks; however, direct comparisons between delayed-onset and rapid-acting antidepressants (ADs) have not yet been carried out. OBJECTIVES:To investigate the effects of conventional delayed-onset ADs versus rapid-acting ADs, ketamine and scopolamine, on effort-related choice behaviour. METHODS:Female Lister hooded rats were trained in an operant effort for reward task (EfRT) where animals choose between working for a high value-high effort reward and consuming low value-low effort chow. Using a within-subject study design, animals were then tested following acute treatment with different monoaminergic ADs, and the rapid-acting ADs ketamine or scopolamine. RESULTS:Consistent with previous findings, we found choice behaviour was sensitive to dopaminergic manipulations. We observed that pre-feeding altered choice behaviour and that the use of high or low value reward differentially affected behaviour. Monoamine re-uptake inhibitors and rapid-acting ADs resulted in similar, general patterns of reduced motivation without any evidence for specific effects, and we did not observe any clear differences between these classes of antidepressant. CONCLUSIONS:Motivational changes induced by dopaminergic manipulations and pre-feeding differentially affect effort choice behaviour. However, both conventional delayed-onset ADs and ketamine and scopolamine appear to have detrimental effects on motivation in this task at the higher doses tested without any evidence of specificity for effort-related choice behaviour, in contrast to their specificity in tasks which look at more cognitive aspects of reward processing.
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Project description:Cognitive flexibility helps us to navigate through our ever-changing environment and has often been examined by reversal learning paradigms. Performance in reversal learning can be modeled using computational modeling which allows for the specification of biologically plausible models to infer psychological mechanisms. Although such models are increasingly used in cognitive neuroscience, developmental approaches are still scarce. Additionally, though most reversal learning paradigms have a comparable design regarding timing and feedback contingencies, the type of feedback differs substantially between studies. The present study used hierarchical Gaussian filter modeling to investigate cognitive flexibility in reversal learning in children and adolescents and the effect of various feedback types. The results demonstrate that children make more overall errors and regressive errors (when a previously learned response rule is chosen instead of the new correct response after the initial shift to the new correct target), but less perseverative errors (when a previously learned response set continues to be used despite a reversal) adolescents. Analyses of the extracted model parameters of the winning model revealed that children seem to use new and conflicting information less readily than adolescents to update their stimulus-reward associations. Furthermore, more subclinical rigidity in everyday life (parent-ratings) is related to less explorative choice behavior during the probabilistic reversal learning task. Taken together, this study provides first-time data on the development of the underlying processes of cognitive flexibility using computational modeling.
| S-EPMC7848134 | biostudies-literature
Project description:In reversal learning tasks, the behavior of humans and animals is often assumed to be uniform within single experimental sessions to facilitate data analysis and model fitting. However, behavior of agents can display substantial variability in single experimental sessions, as they execute different blocks of trials with different transition dynamics. Here, we observed that in a deterministic reversal learning task, mice display noisy and sub-optimal choice transitions even at the expert stages of learning. We investigated two sources of the sub-optimality in the behavior. First, we found that mice exhibit a high lapse rate during task execution, as they reverted to unrewarded directions after choice transitions. Second, we unexpectedly found that a majority of mice did not execute a uniform strategy, but rather mixed between several behavioral modes with different transition dynamics. We quantified the use of such mixtures with a state-space model, block Hidden Markov Model (block HMM), to dissociate the mixtures of dynamic choice transitions in individual blocks of trials. Additionally, we found that blockHMM transition modes in rodent behavior can be accounted for by two different types of behavioral algorithms, model-free or inference-based learning, that might be used to solve the task. Combining these approaches, we found that mice used a mixture of both exploratory, model-free strategies and deterministic, inference-based behavior in the task, explaining their overall noisy choice sequences. Together, our combined computational approach highlights intrinsic sources of noise in rodent reversal learning behavior and provides a richer description of behavior than conventional techniques, while uncovering the hidden states that underlie the block-by-block transitions.
| S-EPMC10501641 | biostudies-literature
Project description:Efforts to develop efficacious antidepressant agents with novel mechanisms have been largely unsuccessful since the 1950's until the discovery of ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist that produces rapid and sustained antidepressant actions even in treatment-resistant patients. This finding has ushered in a new era for the development of novel rapid-acting antidepressants that act at the NMDA receptor complex, but without dissociative and psychotomimetic side effects of ketamine. Here, we review the current state of rapid-acting antidepressant drug development, including NMDA channel blockers, glycine site agents, and allosteric modulators, as well as ketamine stereoisomers and metabolites. In addition, we focus on the neurobiological mechanisms underlying the actions of these diverse agents and discuss evidence of convergent mechanisms including increased brain-derived neurotrophic factor signaling, increased synthesis of synaptic proteins, and most notably increased GluR1 and synaptic connectivity in the medial prefrontal cortex. These convergent mechanisms provide insight for potential additional novel targets for drug development (e.g., agents that increase synaptic protein synthesis and plasticity). Importantly, the convergent effects on synapse formation and plasticity also reverse the well-documented neuronal and synaptic deficits associated with stress and depression, and thereby target the underlying pathophysiology of major depressive disorder.
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Project description:Impulsivity is defined as a trait-like tendency to engage in rash actions that are poorly thought out or expressed in an untimely manner. Previous research has found that impulsivity relates to deficits in decision making, in particular when it necessitates executive control or reward outcomes. Reinforcement learning (RL) relies on the ability to integrate reward or punishment outcomes to make good decisions, and has recently been shown to often recruit executive function; as such, it is unsurprising that impulsivity has been studied in the context of RL. However, how impulsivity relates to the mechanisms of RL remains unclear. We aimed to investigate the relationship between impulsivity and learning in a reward-driven learning task with probabilistic feedback and reversal known to recruit executive function. Based on prior literature in clinical populations, we predicted that higher impulsivity would be associated with poorer performance on the task, driven by more frequent switching following unrewarded outcomes. Our results did not support this prediction, but more advanced, trial-history dependent analyses revealed specific effects of impulsivity on switching behavior following consecutive unrewarded trials. Computational modeling captured group-level behavior, but not impulsivity results. Our results support previous findings highlighting the importance of sensitivity to negative outcomes in understanding how impulsivity relates to learning, but indicate that this may stem from more complex strategies than usually considered in computational models of learning. This should be an important target for future research.
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Project description:RATIONALE:Dysregulation of the serotonin (5-HT) system is a pathophysiological component in major depressive disorder (MDD), a condition closely associated with abnormal emotional responsivity to positive and negative feedback. However, the precise mechanism through which 5-HT tone biases feedback responsivity remains unclear. 5-HT2C receptors (5-HT2CRs) are closely linked with aspects of depressive symptomatology, including abnormalities in reinforcement processes and response to stress. Thus, we aimed to determine the impact of 5-HT2CR function on response to feedback in biased reinforcement learning. METHODS:We used two touchscreen assays designed to assess the impact of positive and negative feedback on probabilistic reinforcement in mice, including a novel valence-probe visual discrimination (VPVD) and a probabilistic reversal learning procedure (PRL). Systemic administration of a 5-HT2CR agonist and antagonist resulted in selective changes in the balance of feedback sensitivity bias on these tasks. RESULTS:Specifically, on VPVD, SB 242084, the 5-HT2CR antagonist, impaired acquisition of a discrimination dependent on appropriate integration of positive and negative feedback. On PRL, SB 242084 at 1 mg/kg resulted in changes in behaviour consistent with reduced sensitivity to positive feedback. In contrast, WAY 163909, the 5-HT2CR agonist, resulted in changes associated with increased sensitivity to positive feedback and decreased sensitivity to negative feedback. CONCLUSIONS:These results suggest that 5-HT2CRs tightly regulate feedback sensitivity bias in mice with consequent effects on learning and cognitive flexibility and specify a framework for the influence of 5-HT2CRs on sensitivity to reinforcement.
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