Previous studies have shown that the formation of new memories can be influenced by prior experience. This includes work using Pavlovian fear conditioning in rodents that has shown that an initial fear conditioning experience can become associated with and facilitate the acquisition of new fear memories, especially when they occur close together in time. However, most of the prior studies used only males as subjects, resulting in questions about the generalizability of the findings from this work. Here we tested whether prior contextual fear conditioning would facilitate later learning of cued fear conditioning in both male and female rats, and if there were differences based on the interval between the two conditioning episodes. Our results showed that levels of cued fear were not influenced by prior contextual fear conditioning or by the interval between training; however, females showed lower levels of cued fear. Freezing behavior in the initial training context differed by sex, with females showing lower levels of contextual fear, and by the type of initial training, with rats given delayed shock showing higher levels of fear than rats given immediate shock during contextual fear conditioning. These results indicate that contextual fear conditioning does not prime subsequent cued fear conditioning and that female rats express lower levels of cued and contextual fear conditioning than males.

G protein-gated inwardly rectifying K (GIRK) channels mediate the postsynaptic inhibitory effect of many neurotransmitters in the hippocampus and are implicated in neurological disorders characterized by cognitive deficits. Here, we show that enhancement or suppression of GIRK channel activity in dorsal CA1 pyramidal neurons disrupted novel object recognition in mice, without impacting open field activity or avoidance behavior. Contextual fear learning was also unaffected, but extinction of contextual fear was disrupted by suppression of GIRK channel activity in male mice. Thus, the strength of GIRK channel activity in dorsal CA1 pyramidal neurons regulates select cognitive task performance in mice.

Memory updating is essential for integrating new information into existing representations. However, this process could become maladaptive in conditions like post-traumatic stress disorder (PTSD), when fear memories generalize to neutral contexts. Previously, we have shown that contextual fear memory malleability in rats requires activation of M1 muscarinic acetylcholine receptors in the dorsal hippocampus. Here, we investigated the involvement of this mechanism in the transfer of contextual fear memories to other contexts using a novel fear memory updating paradigm. Following brief reexposure to a previously fear conditioned context, male rats ( = 8-10/group) were placed into a neutral context to evaluate the transfer of fear memory. We also infused the selective M1 receptor antagonist pirenzepine into the dorsal hippocampus before memory reactivation to try to block this effect. Results support the hypothesis that fear memory can be updated with novel contextual information, but only if rats are reexposed to the originally trained context relatively recently before the neutral context; evidence for transfer was not seen if the fear memory reactivation was omitted or if it occurred 6 h before neutral context exposure. The transferred fear persisted for 4 weeks, and the effect was blocked by M1 antagonism. These findings strongly suggest that fear transfer requires reactivation and destabilization of the original fear memory. The novel preclinical model introduced here, and its implication of muscarinic receptors in this process, could therefore inform therapeutic strategies for PTSD and similar conditions.

Safety signals reinforce instrumental avoidance behavior in nonhuman animals. However, there are no conclusive demonstrations of this phenomenon in humans. Using human participants in an avoidance task, Experiments 1-3 and 5 were conducted online to assess the reinforcing properties of safety signals, and Experiment 4 was conducted in the laboratory. Participants were trained with CSs+ and CSs-, and they could avoid an aversive outcome during presentations of the CSs+ by pressing their space bar at a specific time. If successful, the aversive outcome was not presented but instead a safety signal was. Participants were then tested-whilst on extinction-with two new ambiguous test CSs. If participants made an avoidance response, one of the test CSs produced the trained safety signal and the other was a control. In Experiments 1 and 4, the control was followed by no signal. In Experiment 2, the control was followed by a signal that differed in one dimension (color) with the trained safety signal, and in Experiment 3, the control differed in two dimensions (shape and color) from the trained safety signal. Experiment 5 tested the reinforcing properties of the safety signal using a choice procedure and a new response during test. We observed that participants made more avoidance responses to the ambiguous test CSs when followed by the trained signal in Experiments 1, 3, 4, and 5 (but not in Experiment 2). Overall, these results suggest that trained safety signals can reinforce avoidance behavior in humans.

Activity-regulated cytoskeleton-associated protein (Arc) plays a crucial role in synaptic plasticity, a process integral to learning and memory. Arc transcription is induced within a few minutes of stimulation, making it a useful marker for neuronal activity. However, the specific neuronal activity patterns that initiate Arc transcription have remained elusive due to the inability to observe mRNA transcription in live cells in real time. Using a genetically encoded RNA indicator (GERI) mouse model that expresses endogenous Arc mRNA tagged with multiple GFPs, we investigated Arc transcriptional activity in response to various electrical field stimulation patterns. The GERI mouse model was generated by crossing the Arc-PBS knock-in mouse, engineered with binding sites in the 3' untranslated region (UTR) of Arc mRNA, and the transgenic mouse expressing the cognate binding protein fused to GFP. In dissociated hippocampal neurons, we found that the pattern of stimulation significantly affects Arc transcription. Specifically, theta-burst stimulation consisting of high-frequency (100 Hz) bursts delivered at 10 Hz frequency induced the highest rate of Arc transcription. Concurrently, the amplitudes of nuclear calcium transients also reached their peak with 10 Hz burst stimulation, indicating a correlation between calcium concentration and transcription. However, our dual-color single-cell imaging revealed that there were no significant differences in calcium amplitudes between Arc-positive and Arc-negative neurons upon 10 Hz burst stimulation, suggesting the involvement of other factors in the induction of Arc transcription. Our live-cell RNA imaging provides a deeper insight into the complex regulation of transcription by activity patterns and calcium signaling pathways.

"Pavlovian" or "motivational" biases are the phenomenon that the valence of prospective outcomes modulates action invigoration: the prospect of reward invigorates actions, while the prospect of punishment suppresses actions. Effects of the valence of prospective outcomes are well established, but it remains unclear how the magnitude of outcomes ("stake magnitude") modulates these biases. In this preregistered study ( = 55), we manipulated stake magnitude (high vs. low) in an orthogonalized Motivational Go/NoGo Task. We tested whether higher stakes (a) strengthen biases or (b) elicit cognitive control recruitment, enhancing the suppression of biases in motivationally incongruent conditions. Confirmatory tests showed that high stakes slowed down responding, especially in motivationally incongruent conditions. However, high stakes did not affect whether a response was made or not, and did not change the magnitude of Pavlovian biases. Reinforcement-learning drift-diffusion models (RL-DDMs) fit to the data suggested that response slowing was best captured by stakes prolonging the non-decision time. There was no effect of the stakes on the response threshold (as in typical speed-accuracy trade-offs). In sum, these results suggest that high stakes slow down responses without affecting the expression of Pavlovian biases in behavior. We speculate that this slowing under high stakes might reflect heightened cognitive control, which is however ineffectively used, or reflect positive conditioned suppression, i.e., the interference between goal-directed and consummatory behaviors, a phenomenon previously observed in rodents that might also exist in humans. Pavlovian biases and slowing under high stakes may arise in parallel to each other.

One characteristic of long-term memory is the existence of an inverted U-shaped response to increasing intervals between training sessions, and consequently, an optimal spacing that maximizes memory formation. Current models of this spacing effect focus on specific molecular components and their interactions. Here, we computationally study the underlying network architecture, in particular, the potential of motif dynamics in qualitatively capturing the spacing effect in a manner that is independent of the animal model, biomolecular components, and the timescales involved. We define a common training and test protocol, and computationally identify network topologies that can qualitatively replicate the experimentally observed characteristics of the spacing effect. For 41 motifs derived from fundamental network architectures such as autoregulation, feedback, and feedforward motifs, we tested their capacity to manifest the spacing effect in terms of an inverted U-shaped response curve, using different combinations of stimulation protocols, response metrics, and kinetic parameters. Our findings indicate that positive feedback motifs where the stimulus enhances conversion reaction in the loop replicate the spacing effect across all response metrics, while feedforward motifs exhibit a metric-specific spacing effect. For some parameter combinations, linear cascades of activation and conversion reactions were found sufficient to qualitatively exhibit spacing effect characteristics.

Incubation of craving is a phenomenon describing the intensification of craving for a reward over extended periods of abstinence from reinforcement. Animal models use instrumental markers of craving to reward cues to examine incubation, while human paradigms rely on subjective self-reports. Here, we characterize an animal-inspired, novel human paradigm that showed strong positive relationships between self-reports and instrumental markers of craving for favored palatable foods. Further, we found consistent nonlinear relationships with time since last consumption and self-reports, and preliminary patterns between time and instrumental responses. These findings provide a novel approach to establishing an animal-inspired human model of incubation.

Flexible decision-making requires a balance between exploring features of an environment and exploiting prior knowledge. Behavioral flexibility is typically measured by how long it takes subjects to consistently make accurate choices after reward contingencies switch or task rules change. This measure, however, only allows for tracking flexibility across multiple trials, and does not assess the degree of flexibility. Plus, although increases in decision-making accuracy are strong indicators of learning, other decision-making behaviors have also been suggested as markers of flexibility, such as the on-the-fly decision reversals known as vicarious trial and error (VTE) or switches to a different, but incorrect, strategy. We sought to relate flexibility, learning, and neural activity by comparing choice history-derived evaluation of strategy use with changes in decision-making accuracy and VTE behavior while recording from the medial prefrontal cortex (mPFC) in rats. Using a set-shifting task that required rats to repeatedly switch between spatial decision-making strategies, we show that a previously developed strategy likelihood estimation procedure could identify putative learning points based on decision history. We confirm the efficacy of learning point estimation by showing increases in decision-making accuracy aligned to the learning point. Additionally, we show increases in the rate of VTE behavior surrounding identified learning points. By calculating changes in strategy likelihoods across trials, we tracked flexibility on a trial-by-trial basis and show that flexibility scores also increased around learning points. Further, we demonstrate that VTE behaviors could be separated into indecisive and deliberative subtypes depending on whether they occurred during periods of high or low flexibility and whether they led to correct or incorrect choice outcomes. Field potential recordings from the mPFC during decisions exhibited increased beta band activity on trials with VTE compared to non-VTE trials, as well as increased gamma during periods when learned strategies could be exploited compared to prelearning, exploratory periods. This study demonstrates that increased behavioral flexibility and VTE rates are often aligned to task learning. These relationships can break down, however, suggesting that VTE is not always an indicator of deliberative decision-making. Additionally, we further implicate the mPFC in decision-making and learning by showing increased beta-based activity on VTE trials and increased gamma after learning.

Synaptic potentiation has been linked to learning in sensory cortex, but the connection between this potentiation and increased sensory-evoked neural activity is not clear. Here, we used longitudinal in vivo Ca imaging in the barrel cortex of awake mice to test the hypothesis that increased excitatory synaptic strength during the learning of a whisker-dependent sensory-association task would be correlated with enhanced stimulus-evoked firing. To isolate stimulus-evoked responses from dynamic, task-related activity, imaging was performed outside of the training context. Although prior studies indicate that multiwhisker stimuli drive robust subthreshold activity, we observed sparse activation of L2/3 pyramidal (Pyr) neurons in both control and trained mice. Despite evidence for excitatory synaptic strengthening at thalamocortical and intracortical synapses in this brain area at the onset of learning-indeed, under our imaging conditions thalamocortical axons were robustly activated-we observed that L2/3 Pyr neurons in somatosensory (barrel) cortex displayed only modest increases in stimulus-evoked activity that were concentrated at the onset of training. Activity renormalized over longer training periods. In contrast, when stimuli and rewards were uncoupled in a pseudotraining paradigm, stimulus-evoked activity in L2/3 Pyr neurons was significantly suppressed. These findings indicate that sensory-association training but not sensory stimulation without coupled rewards may briefly enhance sensory-evoked activity, a phenomenon that might help link sensory input to behavioral outcomes at the onset of learning.

How does repeated stimulation of mechanoafferents affect feeding motor neurons? Monosynaptic connections from a mechanoafferent population in the buccal ganglia to five motor followers with different functions were examined during repeated stimulus trains. The mechanoafferents produced both fast and slow synaptic outputs, which could be excitatory or inhibitory. In contrast, other mechanoafferents produce only fast excitation on their followers. In addition, patterns of synaptic connections were different to the different motor followers. Some followers received both fast excitation and fast inhibition, whereas others received exclusively fast excitation. All followers showed strong decreases in fast postsynaptic potential (PSP) amplitude within a stimulus train. Fast and slow synaptic connections were of net opposite signs in some followers but not in others. For one follower, synaptic contacts were not uniform from all subareas of the mechanoafferent cluster. Differences in properties of the buccal ganglia mechanoafferents and other mechanoafferents may arise because the buccal ganglia neurons innervate the interior of the feeding apparatus, rather than an external surface, and connect to motor neurons for muscles with different motor functions. Fast connection patterns suggest that these synapses may be activated when food slips, biasing the musculature to release food. The largest slow inhibitory synaptic PSPs may contribute to a delay in the onset of the next behavior. Additional functions are also possible.

Changes caused by learning that a food is inedible in were examined for fast and slow synaptic connections from the buccal ganglia S1 cluster of mechanoafferents to five followers, in response to repeated stimulus trains. Learning affected only fast connections. For these, unique patterns of change were present in each follower, indicating that learning differentially affects the different branches of the mechanoafferents to their followers. In some followers, there were increases in either excitatory or inhibitory connections, and in others, there were decreases. Changes in connectivity resulted from changes in the amplitude of excitation or inhibition, or as a result of the number of connections, or of both. Some followers also exhibited changes in either within or between stimulus train plasticity as a result of learning. In one follower, changes differed from the different areas of the S1 cluster. The patterns of changes in connectivity were consistent with the behavioral changes produced by learning, in that they would produce an increase in the bias to reject or to release food, and a decrease in the likelihood to respond to food.

To survive in changing environments, animals need to learn to associate specific sensory stimuli with positive or negative valence. How do they form stimulus-specific memories to distinguish between positively/negatively associated stimuli and other irrelevant stimuli? Solving this task is one of the functions of the mushroom body, the associative memory center in insect brains. Here we summarize recent work on sensory encoding and memory in the mushroom body, highlighting general principles such as pattern separation, sparse coding, noise and variability, coincidence detection, and spatially localized neuromodulation, and placing the mushroom body in comparative perspective with mammalian memory systems.

When animals learn the association of a conditioned stimulus (CS) with an unconditioned stimulus (US), later presentation of the CS invokes a representation of the US. When the expected US fails to occur, theoretical accounts predict that conditioned inhibition can accrue to any other stimuli that are associated with this change in the US. Empirical work with mammals has confirmed the existence of conditioned inhibition. But the way it is manifested, the conditions that produce it, and determining whether it is the opposite of excitatory conditioning are important considerations. Invertebrates can make valuable contributions to this literature because of the well-established conditioning protocols and access to the central nervous system (CNS) for studying neural underpinnings of behavior. Nevertheless, although conditioned inhibition has been reported, it has yet to be thoroughly investigated in invertebrates. Here, we evaluate the role of the US in producing conditioned inhibition by using proboscis extension response conditioning of the honeybee (). Specifically, using variations of a "feature-negative" experimental design, we use downshifts in US intensity relative to US intensity used during initial excitatory conditioning to show that an odorant in an odor-odor mixture can become a conditioned inhibitor. We argue that some alternative interpretations to conditioned inhibition are unlikely. However, we show variation across individuals in how strongly they show conditioned inhibition, with some individuals possibly revealing a different means of learning about changes in reinforcement. We discuss how the resolution of these differences is needed to fully understand whether and how conditioned inhibition is manifested in the honeybee, and whether it can be extended to investigate how it is encoded in the CNS. It is also important for extension to other insect models. In particular, work like this will be important as more is revealed of the complexity of the insect brain from connectome projects.

In 1998, a special edition of was published with a discrete focus of synthesizing the state of the field to provide an overview of the function of the insect mushroom body. While molecular neuroscience and optical imaging of larger brain areas were advancing, understanding the basic functioning of neuronal circuits, particularly in the context of the mushroom body, was rudimentary. In the past 25 years, technological innovations have allowed researchers to map and understand the in vivo function of the neuronal circuits of the mushroom body system, making it an ideal model for investigating the circuit basis of sensory encoding, memory formation, and behavioral decisions. Collaborative efforts within the community have played a crucial role, leading to an interactive connectome of the mushroom body and accessible genetic tools for studying mushroom body circuit function. Looking ahead, continued technological innovation and collaborative efforts are likely to further advance our understanding of the mushroom body and its role in behavior and cognition, providing insights that generalize to other brain structures and species.

Associative learning enables the adaptive adjustment of behavioral decisions based on acquired, predicted outcomes. The valence of what is learned is influenced not only by the learned stimuli and their temporal relations, but also by prior experiences and internal states. In this study, we used the fruit fly to demonstrate that neuronal circuits involved in associative olfactory learning undergo restructuring during extended periods of low-caloric food intake. Specifically, we observed a decrease in the connections between specific dopaminergic neurons (DANs) and Kenyon cells at distinct compartments of the mushroom body. This structural synaptic plasticity was contingent upon the presence of allatostatin A receptors in specific DANs and could be mimicked optogenetically by expressing a light-activated adenylate cyclase in exactly these DANs. Importantly, we found that this rearrangement in synaptic connections influenced aversive, punishment-induced olfactory learning but did not impact appetitive, reward-based learning. Whether induced by prolonged low-caloric conditions or optogenetic manipulation of cAMP levels, this synaptic rearrangement resulted in a reduction of aversive associative learning. Consequently, the balance between positive and negative reinforcing signals shifted, diminishing the ability to learn to avoid odor cues signaling negative outcomes. These results exemplify how a neuronal circuit required for learning and memory undergoes structural plasticity dependent on prior experiences of the nutritional value of food.

The common fruit fly provides a powerful platform to investigate the genetic, molecular, cellular, and neural circuit mechanisms of behavior. Research in this model system has shed light on multiple aspects of brain physiology and behavior, from fundamental neuronal function to complex behaviors. A major anatomical region that modulates complex behaviors is the mushroom body (MB). The MB integrates multimodal sensory information and is involved in behaviors ranging from sensory processing/responses to learning and memory. Many genes that underlie brain disorders are conserved, from flies to humans, and studies in have contributed significantly to our understanding of the mechanisms of brain disorders. Genetic mutations that mimic human diseases-such as Fragile X syndrome, neurofibromatosis type 1, Parkinson's disease, and Alzheimer's disease-affect MB structure and function, altering behavior. Studies dissecting the effects of disease-causing mutations in the MB have identified key pathological mechanisms, and the development of a complete connectome promises to add a comprehensive anatomical framework for disease modeling. Here, we review models of human neurodevelopmental and neurodegenerative disorders via the effects of their underlying mutations on MB structure, function, and the resulting behavioral alterations.

The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.

Animal brains need to store information to construct a representation of their environment. Knowledge of what happened in the past allows both vertebrates and invertebrates to predict future outcomes by recalling previous experience. Although invertebrate and vertebrate brains share common principles at the molecular, cellular, and circuit-architectural levels, there are also obvious differences as exemplified by the use of acetylcholine versus glutamate as the considered main excitatory neurotransmitters in the respective central nervous systems. Nonetheless, across central nervous systems, synaptic plasticity is thought to be a main substrate for memory storage. Therefore, how brain circuits and synaptic contacts change following learning is of fundamental interest for understanding brain computations tied to behavior in any animal. Recent progress has been made in understanding such plastic changes following olfactory associative learning in the mushroom bodies (MBs) of A current framework of memory-guided behavioral selection is based on the MB skew model, in which antagonistic synaptic pathways are selectively changed in strength. Here, we review insights into plasticity at dedicated MB output pathways and update what is known about the plasticity of both pre- and postsynaptic compartments of MB neurons.

Binding of arbitrary information into distinct memory representations that can be used to guide behavior is a hallmark of relational memory. What is and is not bound into a memory representation and how those things influence the organization of that representation remain topics of interest. While some information is intentionally and effortfully bound-often the information that is consistent with task goals or expectations about what information may be required later-other information appears to be bound automatically. The present set of experiments sought to investigate whether spatial memory would be systematically influenced by the presence and absence of distinct categories of stimuli on a spatial reconstruction task. In this task, participants must learn multiple item-location bindings and place each item back in its studied location after a short delay. Across three experiments, participants made significantly more within-category errors (i.e., misassigning one item to the location of a different item from the same category) than between-category errors (i.e., misassigning one item to the location of an item from a different category) when categories were perceptually or semantically distinct. These data reveal that category information contributed to the organization of the memory representation and influenced spatial reconstruction performance. Together, these results suggest that categorical information can influence memory organization, and not always to the benefit of overall task performance.

Memory formation is contingent on molecular and structural changes in neurons in response to learning stimuli-a process known as neuronal plasticity. The initiation step of mRNA translation is a gatekeeper of long-term memory by controlling the production of plasticity-related proteins in the brain. The mechanistic target of rapamycin complex 1 (mTORC1) controls mRNA translation, mainly through phosphorylation of the eukaryotic initiation factor 4E (eIF4E)-binding proteins (4E-BPs) and ribosomal protein S6 kinases (S6Ks). mTORC1 signaling decreases throughout brain development, starting from the early postnatal period. Here, we discovered that in mice, the age-dependent decrease in mTORC1 signaling occurs selectively in excitatory but not inhibitory neurons. Using a gene conditional knockout (cKO) strategy, we demonstrate that either up- or downregulating the mTORC1-4E-BP2 axis in GAD65 inhibitory interneurons, but not excitatory neurons, results in long-term object recognition and object location memory deficits. Our data indicate that the mTORC1 pathway in inhibitory but not excitatory neurons plays a key role in memory formation.