BACKGROUND: Altered sensory processing in migraine has been demonstrated by several studies in unimodal, and especially visual, tasks. While there is some limited evidence hinting at potential alterations in multisensory processing among migraine sufferers, this aspect remains relatively unexplored. This study investigated the interictal cognitive performance of migraine patients without aura compared to matched controls, focusing on associative learning, recall, and transfer abilities through the Sound-Face Test, an audiovisual test based on the principles of the Rutgers Acquired Equivalence Test.
METHODS: The performance of 42 volunteering migraine patients was compared to the data of 42 matched controls, selected from a database of healthy volunteers who had taken the test earlier. The study aimed to compare the groups\' performance in learning, recall, and the ability to transfer learned associations.
RESULTS: Migraine patients demonstrated significantly superior associative learning as compared to controls, requiring fewer trials, and making fewer errors during the acquisition phase. However, no significant differences were observed in retrieval error ratios, generalization error ratios, or reaction times between migraine patients and controls in later stages of the test.
CONCLUSIONS: The results of our study support those of previous investigations, which concluded that multisensory processing exhibits a unique pattern in migraine. The specific finding that associative audiovisual pair learning is more effective in adult migraine patients than in matched controls is unexpected. If the phenomenon is not an artifact, it may be assumed to be a combined result of the hypersensitivity present in migraine and the sensory threshold-lowering effect of multisensory integration.

Pavlovian conditioning is typically distinguished from sensitization but a Pavlovian conditional stimulus (CS) also results in sensitization. A Pavlovian CS can sensitize responding to a probe stimulus that is related to the unconditional stimulus (US) or to the US itself. Pavlovian sensitization has been studied in the defensive, sexual, and feeding systems. In Pavlovian sensitization, the focus is not on a conditional response (CR) directly elicited by the CS but on the response mode that is activated by the CS. Activation of a response mode increases the probability of particular responses and also increases reactivity to various stimuli. Pavlovian sensitization reflects this increased stimulus reactivity. Pavlovian sensitization helps uncover successful learning in situations where a conventional CR does not occur. Pavlovian sensitization also encourages broadening our conceptions of Pavlovian conditioning to include changes in afferent processes. Implications for biological fitness and for basic and translational research are discussed.

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 Ca2+ 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.

Pairing a palatable flavor (US) with an initially neutral flavor cue (CS) results in an acquired conditioned preference for the latter. Two main associations have been proposed to explain the acquisition of flavor preferences: Flavor-Flavor and Flavor-Nutrient learning. Although the hedonic reaction triggered by US consumption has also been suggested as a possible additional component underlying acquired flavor preference, this issue has received little attention. Here we explored whether the amount of training to the CS-US compound can favor the formation of a Flavor-Hedonic reaction association using rats as subjects and sucrose as the US. We expected that the more exposure to the CS-US compound, the stronger the S-R type association. Since S-R associations are not sensitive to devaluation procedures, we used a Sensory-Specific Satiety procedure to devalue the US after conditioning and then measured preferences for the CS. On Experiment 1 with a short restrictive training (classic procedure), preference for the CS was decreased after devaluation of the US compared to the control condition. On Experiment 2, with short unrestrictive training, preference for the CS was again weakened. Experiment 3 with a long unrestrictive training, rats expressed preference for the CS regardless of the devaluation procedure. These results suggest that, as with an instrumental paradigm, extensive training in flavor preference learning undermines the US devaluation effect.

In recent years, there have been significant advances in our understanding of the positive symptoms of schizophrenia, such as hallucinations and delusions. This progress has been significantly aided by the use of associative learning-based approaches in human subjects and preclinical animal models. Here, we first review experimental research focusing on the abnormal processing of absent stimuli using three different conditioning phenomena: conditioned hallucinations, mediated conditioning, and trace conditioning. We then review studies investigating the ability to reduce focal processing of physically present but informationally redundant stimuli using habituation, latent inhibition, and blocking. The results of these different lines of research are then summarized within the framework of Wagner\'s (1981) standard operating procedures model, an associative learning model with explicit reference to the internal representations of both present and absent stimuli. Within this framework, the central deficit associated with positive symptoms can be described as a failure to suppress the focal processing of both absent stimuli and present but irrelevant stimuli. This can explain the wide range of results obtained in different experimental settings. Finally, we briefly discuss the role of the hippocampus and its interaction with dopaminergic transmission in the emergence of such abnormal stimulus representations and learning. Overall, we hope that the theoretical framework and empirical findings offered by the associative learning approach will continue to facilitate and integrate analyses of schizophrenia conducted at the psychological and behavioral levels on the one hand, and at the neural and molecular levels on the other, by serving as a useful interface between them. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The ability to establish associations between environmental stimuli is fundamental for higher-order brain functions like state inference and generalization. Both the hippocampus and orbitofrontal cortex (OFC) play pivotal roles in this, demonstrating complex neural activity changes after associative learning. However, how precisely they contribute to representing learned associations remains unclear. Here, we train head-restrained mice to learn four \'odor-outcome\' sequence pairs composed of several task variables-the past and current odor cues, sequence structure of \'cue-outcome\' arrangement, and the expected outcome; and perform calcium imaging from these mice throughout learning. Sequence-splitting signals that distinguish between paired sequences are detected in both brain regions, reflecting associative memory formation. Critically, we uncover differential contents in represented associations by examining, in each area, how these task variables affect splitting signal generalization between sequence pairs. Specifically, the hippocampal splitting signals are influenced by the combination of past and current cues that define a particular sensory experience. In contrast, the OFC splitting signals are similar between sequence pairs that share the same sequence structure and expected outcome. These findings suggest that the hippocampus and OFC uniquely and complementarily organize the acquired associative structure.

Viral infections can be detrimental to the foraging ability of the western honey bee, Apis mellifera. The deformed wing virus (DWV) is the most common honey bee virus and has been proposed as a possible cause of learning and memory impairment. However, evidence for this phenomenon so far has come from artificially infected bees, while less is known about the implications of natural infections with the virus. Using the proboscis extension reflex (PER), we uncovered no significant association between a simple associative learning task and natural DWV load. However, when assessed through a reversal associative learning assay, bees with higher DWV load performed better in the reversal learning phase. DWV is able to replicate in the honey bee mushroom bodies, where the GABAergic signalling pathway has an antagonistic effect on associative learning but is crucial for reversal learning. Hence, we assessed the pattern of expression of several GABA-related genes in bees with different learning responses. Intriguingly, mushroom body expression of selected genes was positively correlated with DWV load, but only for bees with good reversal learning performance. We hypothesise that DWV might improve olfactory learning performance by enhancing the GABAergic inhibition of responses to unrewarded stimuli, which is consistent with the behavioural patterns that we observed. However, at higher disease burdens, which might be induced by an artificial infection or by a severe, natural Varroa infestation, this DWV-associated increase in GABA signalling could impair associative learning as previously reported by other studies.

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 Drosophila 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 Drosophila MB output pathways and update what is known about the plasticity of both pre- and postsynaptic compartments of Drosophila MB neurons.

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 Drosophila melanogaster 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.

How does the brain translate sensory information into complex behaviors? With relatively small neuronal numbers, readable behavioral outputs, and an unparalleled genetic toolkit, the Drosophila mushroom body (MB) offers an excellent model to address this question in the context of associative learning and memory. Recent technological breakthroughs, such as the freshly completed full-brain connectome, multiomics approaches, CRISPR-mediated gene editing, and machine learning techniques, led to major advancements in our understanding of the MB circuit at the molecular, structural, physiological, and functional levels. Despite significant progress in individual MB areas, the field still faces the fundamental challenge of resolving how these different levels combine and interact to ultimately control the behavior of an individual fly. In this review, we discuss various aspects of MB research, with a focus on the current knowledge gaps, and an outlook on the future methodological developments required to reach an overall view of the neurobiological basis of learning and memory.