Distributional coding of associative learning in discrete populations of midbrain dopamine neurons.

Midbrain dopamine neurons are thought to play key roles in learning by conveying the difference between expected and actual outcomes. Recent evidence suggests diversity in dopamine signaling, yet it remains poorly understood how heterogeneous signals might be organized to facilitate the role of downstream circuits mediating distinct aspects of behavior. Here, we investigated the organizational logic of dopaminergic signaling by recording and labeling individual midbrain dopamine neurons during associative behavior. Our findings show that reward information and behavioral parameters are not only heterogeneously encoded but also differentially distributed across populations of dopamine neurons. Retrograde tracing and fiber photometry suggest that populations of dopamine neurons projecting to different striatal regions convey distinct signals. These data, supported by computational modeling, indicate that such distributional coding can maximize dynamic range and tailor dopamine signals to facilitate specialized roles of different striatal regions.

Distinct Hippocampal Oscillation Dynamics in Trace Eyeblink Conditioning Task for Retrieval and Consolidation of Associations.

Trace eyeblink conditioning (TEBC) has been widely used to study associative learning in both animals and humans. In this paradigm, conditioned responses (CRs) to conditioned stimuli (CS) serve as a measure for retrieving learned associations between the CS and the unconditioned stimuli (US) within a trial. Memory consolidation, that is, learning over time, can be quantified as an increase in the proportion of CRs across training sessions. However, how hippocampal oscillations differentiate between successful memory retrieval within a session and consolidation across TEBC training sessions remains unknown. To address this question, we recorded local field potentials (LFPs) from the rat dorsal hippocampus during TEBC and investigated hippocampal oscillation dynamics associated with these two functions. We show that transient broadband responses to the CS were correlated with memory consolidation, as indexed by an increase in CRs across TEBC sessions. In contrast, induced alpha (8-10 Hz) and beta (16-20 Hz) band responses were correlated with the successful retrieval of the CS-US association within a session, as indexed by the difference in trials with and without CR.

The role of uncertainty in regulating associative change.

Rescorla (2000, 2001) interpreted his compound test results to show that both common and individual error terms regulate associative change such that the element of a conditioned compound with the greater prediction error undergoes greater associative change than the one with the smaller prediction error. However, it has recently been suggested that uncertainty, not prediction error, is the primary determinant of associative change in people (Spicer et al., 2020, 2022). The current experiments use the compound test in a continuous outcome allergist task to assess the role of uncertainty in associative change, using two different manipulations of uncertainty: outcome uncertainty (where participants are uncertain of the level of the outcome on a particular trial) and causal uncertainty (where participants are uncertain of the contribution of the cue to the level of the outcome). We replicate Rescorla's compound test results in the case of both associative gains (Experiment 1) and associative losses (Experiment 3) and then provide evidence for greater change to more uncertain cues in the case of associative gains (Experiments 2 and 4), but not associative losses (Experiments 3 and 5). We discuss the findings in terms of the notion of theory protection advanced by Spicer et al., and other ways of thinking about the compound test procedure, such as that proposed by Holmes et al. (2019). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Encoding of Predictive Associations in Human Prefrontal and Medial Temporal Neurons During Pavlovian Appetitive Conditioning.

Pavlovian conditioning is thought to involve the formation of learned associations between stimuli and values, and between stimuli and specific features of outcomes. Here, we leveraged human single neuron recordings in ventromedial prefrontal, dorsomedial frontal, hippocampus, and amygdala while patients of both sexes performed an appetitive Pavlovian conditioning task probing both stimulus-value and stimulus-stimulus associations. Ventromedial prefrontal cortex encoded predictive value along with the amygdala, and also encoded predictions about the identity of stimuli that would subsequently be presented, suggesting a role for neurons in this region in encoding predictive information beyond value. Unsigned error signals were found in dorsomedial frontal areas and hippocampus, potentially supporting learning of non-value related outcome features. Our findings implicate distinct human prefrontal and medial temporal neuronal populations in mediating predictive associations which could partially support model-based mechanisms during Pavlovian conditioning.

Older adults' name-face association learning is facilitated for names with high-frequency first syllables.

Older adults have even greater difficulty learning name-face associations than young adults, although many variables reflecting properties of the names have been shown to affect young and older adults' name learning similarly. Older adults' name-face association learning was compared for names with high-frequency (HF) first syllables versus names with low-frequency (LF) first syllables. Twenty-eight adults ages 65 to 80 learned five names with HF first syllables and five names with LF first syllables in association with 10 new faces over repeated testing rounds with feedback. Participants learned more name-face associations when the names had HF first syllables than LF first syllables. Findings indicate that older adults benefit from increased frequency of phonological segments within a word on a task other than word retrieval and are consistent with a theoretical framework that accounts for learning new name-face associations, the effects of linguistic properties of the names, and ageing.

Stimulus-outcome associations are required for the expression of specific Pavlovian-instrumental transfer.

A series of experiments employed a specific Pavlovian-instrumental transfer (PIT) task in rats to determine the capacity of various treatments to undermine two outcome-specific stimulus-outcome (S-O) associations. Experiment 1 tested a random treatment, which involved uncorrelated presentations of the two stimuli and their predicted outcomes. This treatment disrupted the capacity of the outcome-specific S-O associations to drive specific PIT. Experiment 2 used a negative-contingency treatment during which the predicted outcomes were exclusively delivered in the absence of their associated stimulus. This treatment spared specific PIT, suggesting that it left the outcome-specific S-O associations relatively intact. The same outcome was obtained in Experiment 3, which implemented a zero-contingency treatment consisting of delivering the predicted outcomes in the presence and absence of their associated stimulus. Experiment 4 tested a mixed treatment, which distributed the predicted outcomes at an equal rate during each stimulus. This treatment disrupted the capacity of the outcome-specific S-O associations to drive specific PIT. We suggest that the mixed treatment disrupted specific PIT by generating new and competing outcome-specific S-O associations. By contrast, we propose that the random treatment disrupted specific PIT by undermining the original outcome-specific S-O associations, indicating that these associations must be retrieved to express specific PIT. We discuss how these findings inform our theoretical understanding of the mechanisms underlying this phenomenon. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A simple semi-automated home-tank method and procedure to explore classical associative learning in adult zebrafish.

The zebrafish is a laboratory species that gained increasing popularity the last decade in a variety of subfields of biology, including toxicology, ecology, medicine, and the neurosciences. An important phenotype often measured in these fields is behaviour. Consequently, numerous new behavioural apparati and paradigms have been developed for the zebrafish, including methods for the analysis of learning and memory in adult zebrafish. Perhaps the biggest obstacle in these methods is that zebrafish is particularly sensitive to human handling. To overcome this confound, automated learning paradigms have been developed with varying success. In this manuscript, we present a semi-automated home tank-based learning/memory test paradigm utilizing visual cues, and show that it is capable of quantifying classical associative learning performance in zebrafish. We demonstrate that in this task, zebrafish successfully acquire the association between coloured-light and food reward. The hardware and software components of the task are easy and cheap to obtain and simple to assemble and set up. The procedures of the paradigm allow the test fish to remain completely undisturbed by the experimenter for several days in their home (test) tank, eliminating human handling or human interference induced stress. We demonstrate that the development of cheap and simple automated home-tank-based learning paradigms for the zebrafish is feasible. We argue that such tasks will allow us to better characterize numerous cognitive and mnemonic features of the zebrafish, including elemental as well as configural learning and memory, which will, in turn, also enhance our ability to study neurobiological mechanisms underlying learning and memory using this model organism.

The effect of hippocampal subfield damage on rapid temporal integration through statistical learning and associative inference.

INTRODUCTION: The hippocampus (HPC) supports integration of information across time, often indexed by associative inference (AI) and statistical learning (SL) tasks. In AI, an indirect association between stimuli that never appeared together is inferred, whereas SL involves learning item relationships by extracting regularities across experiences. A recent model of hippocampal function (Schapiro et al., 2017) proposes that the HPC can support temporal integration in both paradigms through its two distinct pathways. METHODS: We tested this models' predictions in four patients with varying degrees of bilateral HPC damage and matched healthy controls, with two patients with complementary damage to either the monosynaptic or trisynaptic pathway. During AI, participants studied overlapping paired associates (AB, BC) and their memory was tested for premise pairs (AB) and for inferred pairs (AC). During SL, participants passively viewed a continuous picture sequence that contained an underlying structure of triplets that later had to be recognized. RESULTS: Binomial distributions were used to calculate above chance performance at the individual level. For AI, patients with focal HPC damage were impaired at inference but could correctly infer pairs above chance once premise pair acquisition was equated to controls; however, the patient with HPC and cortical damage showed severe impairment at recalling premise and inferred pairs, regardless of accounting for premise pair performance. For SL, none of the patients performed above chance, but notably neither did most controls. CONCLUSIONS: Associative inference of indirect relationships can be intact with HPC damage to either hippocampal pathways or the HPC more broadly, provided premise pairs can first be formed. Inference may remain intact through residual HPC tissue supporting premise pair acquisition, and/or through extra-hippocampal structures supporting inference at retrieval. Clear conclusions about hippocampal contributions to SL are precluded by low performance in controls, which we caution is not dissimilar to previous amnesic studies using the same task. This complicates interpretations of studies claiming necessity of hippocampal contributions to SL and warrants the use of a common and reliable task before conclusions can be drawn.

Schema-congruency supports the formation of unitized representations: Evidence from event-related potentials.

The main goal of the present study was to investigate whether schema-based encoding of novel word pairs (i.e., novel compound words) supports the formation of unitized representations and thus, associative familiarity-based recognition. We report two experiments that both comprise an incidental learning task, in which novel noun-noun compound words were presented in semantically congruent contexts, enabling schema-supported processing of both constituents, contrasted with a schema-neutral condition. In Experiment 1, the effects of schema congruency on memory performance were larger for associative memory performance than for item memory performance in a memory test in which intact, recombined, and new compound words had to be discriminated. This supports the view that schema congruency boosts associative memory by promoting unitization. When contrasting event-related potentials (ERPs) for hits with correct rejections or associative misses, an N400 attenuation effect (520-676 ms) indicating absolute familiarity was present in the congruent condition, but not in the neutral condition. In line with this, a direct comparison of ERPs on hits across conditions revealed more positive waveforms in the congruent than in the neutral condition. This suggests that absolute familiarity contributes to associative recognition memory when schema-supported processing is established. In Experiment 2, we tested whether schema congruency enables the formation of semantically overlapping representations. Therefore, we included semantically similar lure compound words in the test phase and compared false alarm rates to these lures across conditions. In line with our hypothesis, we found higher false alarm rates in the congruent as compared to the neutral condition. In conclusion, we provide converging evidence for the view that schema congruency enables the formation of unitized representations and supports familiarity-based memory retrieval.

Optogenetic activation of dopamine D1 receptors in island cells of medial entorhinal cortex inhibits temporal association learning.

A critical feature of episodic memory formation is to associate temporally segregated events as an episode, called temporal association learning. The medial entorhinal cortical-hippocampal (EC-HPC) networks is essential for temporal association learning. We have previously demonstrated that pyramidal cells in the medial EC (MEC) layer III project to the hippocampal CA1 pyramidal cells and are necessary for trace fear conditioning (TFC), which is an associative learning between tone and aversive shock with the temporal gap. On the other hand, Island cells in MECII, project to GABAergic neurons in hippocampal CA1, suppress the MECIII input into the CA1 pyramidal cells through the feed-forward inhibition, and inhibit TFC. However, it remains unknown about how Island cells activity is regulated during TFC. In this study, we report that dopamine D1 receptor is preferentially expressed in Island cells in the MEC. Optogenetic activation of dopamine D1 receptors in Island cells facilitate the Island cell activity and inhibited hippocampal CA1 pyramidal cell activity during TFC. The optogenetic activation caused the impairment of TFC memory recall without affecting contextual fear memory recall. These results suggest that dopamine D1 receptor in Island cells have a crucial role for the regulation of temporal association learning.

Associative and predictive hippocampal codes support memory-guided behaviors.

Episodic memory involves learning and recalling associations between items and their spatiotemporal context. Those memories can be further used to generate internal models of the world that enable predictions to be made. The mechanisms that support these associative and predictive aspects of memory are not yet understood. In this study, we used an optogenetic manipulation to perturb the sequential structure, but not global network dynamics, of place cells as rats traversed specific spatial trajectories. This perturbation abolished replay of those trajectories and the development of predictive representations, leading to impaired learning of new optimal trajectories during memory-guided navigation. However, place cell assembly reactivation and reward-context associative learning were unaffected. Our results show a mechanistic dissociation between two complementary hippocampal codes: an associative code (through coactivity) and a predictive code (through sequences).

How associations become behavior.

The Rescorla and Wagner (1972) model is the first mathematical theory to explain associative learning in the presence of multiple stimuli. Its main theoretical construct is that of associative strength, but this is connected to behavior only loosely. We propose a model in which behavior is described by a collection of Poisson processes, each with a rate proportional to an associative strength. The model predicts that the time between behaviors follows an exponential or hypoexponential distribution. This prediction is supported by two data sets on autoshaped and instrumental behavior in rats.

Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation.

Associative learning is crucial for adapting to environmental changes. Interactions among neuronal populations involving the dorso-medial prefrontal cortex (dmPFC) are proposed to regulate associative learning, but how these neuronal populations store and process information about the association remains unclear. Here we developed a pipeline for longitudinal two-photon imaging and computational dissection of neural population activities in male mouse dmPFC during fear-conditioning procedures, enabling us to detect learning-dependent changes in the dmPFC network topology. Using regularized regression methods and graphical modeling, we found that fear conditioning drove dmPFC reorganization to generate a neuronal ensemble encoding conditioned responses (CR) characterized by enhanced internal coactivity, functional connectivity, and association with conditioned stimuli (CS). Importantly, neurons strongly responding to unconditioned stimuli during conditioning subsequently became hubs of this novel associative network for the CS-to-CR transformation. Altogether, we demonstrate learning-dependent dynamic modulation of population coding structured on the activity-dependent formation of the hub network within the dmPFC.

Chinese character unitization enhances item memory in addition to associative memory: Evidence from ERP and TFR.

While the effect of unitization on associative memory has been established, its effect on item memory remains debated. This study aimed to investigate the influence of unitization on item memory using Chinese characters to manipulate unitization and recording scalp EEG to elucidate the underlying neural mechanisms. In the learning phase, participants were asked to determine whether the character pairs presented could form a Chinese compound character. In the subsequent testing phase, participants performed item recognition and associative recognition tasks. Behavioral results revealed that unitization not only improved associative memory but also facilitated item memory. Event-related potential analysis indicated there were FN400 effect (related to familiarity) and LPC effect (related to recollection) during associative recognition after unitization, however, only the LPC effect was observed for the item recognition. More importantly, time-frequency analysis demonstrated stronger θ oscillations (associated with recollection) in the unitized condition compared to the non-unitized condition, which further partially mediated the reduction in RT during the item recognition. These results suggest that unitization enhances item memory through recollection, thereby leading to more confident recognition judgments, and that unitization does not impair item processing within an association but rather enables more precise and accurate processing.

Category relevance attenuates overshadowing in human predictive learning.

In situations in which multiple predictors anticipate the presence or absence of an outcome, cues compete to anticipate the outcome, resulting in a loss of associative strength compared to control conditions without additional cues. Critically, there are multiple factors modulating the magnitude and direction of such competition, although in some scenarios the effect of these factors remains unexplored. We sought to assess whether the relative salience of the elements in a compound of cues modulates the magnitude of the overshadowing effect in human predictive learning. Two separable categories (i.e., colors and symbols) were used in a predictive learning task. In Experiment 1, different groups of participants were granted with different time of exposure to a compound of cues belonging to different categories (color and symbol) to evaluate potential differences in the magnitude of overshadowing. Furthermore, we used posttest questionnaires to assess whether participants used either only one or both categories during training, and assessed if this impacted the magnitude of overshadowing. In general, overshadowing was not modulated by the time of exposition, except in the case of very short time of exposition with prominent learning about the most salient category. In Experiment 2, the relative salience of a category was biased via prior experience either with a biconditional discrimination or attending only the relevant category (either color or symbol). The previously relevant category was less prone to overshadowing, but not the alternative one. Results are discussed in light of attentional and configural theories of associative learning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Why is the Rescorla-Wagner model so influential?

The influence of the Rescorla-Wagner model cannot be overestimated, despite that (1) the model does not differ much computationally from its predecessors and competitors, and (2) its shortcomings are well-known in the learning community. Here we discuss the reasons behind its widespread influence in the cognitive and neural sciences, and argue that it is the constant search for general-process theories by learning scholars which eventually produced a model whose application spans many different areas of research to this day. We focus on the theoretical and empirical background of the model, the theoretical connections that it has with later developments across Marr's levels of analysis, as well as the broad variety of research that it has guided and inspired.

Chinese character unitization enhances recollection-based associative recognition: Evidence from fMRI.

Previous research has suggested that familiarity can enhance associative memory after unitization, but the cognitive mechanisms underlying unitization remain debated. To explore the neural mechanisms of associative memory after unitization in the absence of semantic relations, we used Chinese characters as stimuli and recorded participants' blood oxygen level-dependent signals during recognition. Behavioral results showed that after Chinese character unitization, not only the associative performance of recognition (Pr, hit rate minus false alarm rate) and general Pr but also the hit rate and correct rejection rate increased. Neuroimaging results revealed activation of the hippocampus and parahippocampal gyrus during associative recognition in both the unitized and the non-unitized condition, and hippocampal activation increased after unitization. However, activation of the perirhinal cortex was not observed in either condition. These findings, in contrast to those from previous studies on unitization, suggest that Chinese character unitization enhances recollection-based, rather than familiarity-based, associative recognition. This suggests that the encoding of semantic relations during unitization is critical for subsequent familiarity-based associative recognition.

Overshadowing, but not relative validity, between the elements of an outcome during human associative learning.

Overshadowing and relative validity constitute two phenomena that inspired the development of the Rescorla-Wagner model in 1972. They demonstrate that cues will interact with one another for an association with the presence or absence of an outcome. Here, three experiments sought to explore whether these two effects extended to outcomes using a food allergist paradigm with human participants. In Experiment 1 (overshadowing) participants received trials in which a cue was followed by a compound of two outcomes (A-O1O2). Test trials revealed that participants learned less about the A-O2 association than they did between a control cue C, which had been paired with O2 in isolation (C-O2) in training - thus demonstrating an outcome overshadowing effect. In Experiment 2 (relative validity) participants received true discrimination trials, in which A was paired with an O1O3 compound and B was paired with an O2O3 compound, and pseudo discrimination trials, in which C and D were paired on 50% of the trials with an O4O6 compound and on the remaining trials with an O5O6 compound. Consequently, O3 is less well predicted by A and B relative to O1 and O2, whereas O6 is equally well predicted by C and D relative to O4 and O5. Despite the relative validity of A and B for O3 being less than the relative validity of C and D for O6, the ratings of A and B for O3 were the same as C and D for O6. This failure to observe an outcome relative validity effect was reproduced in Experiment 3, which replicated Experiment 2, but with an adjustment made to the number of training trials given to participants. These results are discussed in terms of a real-time development of the Rescorla-Wagner model provided by Wagner (1981).

Hippocampal integration and separation processes with different temporal and spatial dynamics during learning for associative memory.

The hippocampus is known to be critically involved in associative memory formation. However, the role of the hippocampus during the learning of associative memory is still controversial; while the hippocampus is considered to play a critical role in the integration of related stimuli, numerous studies also suggest a role of the hippocampus in the separation of different memory traces for rapid learning. Here, we employed an associative learning paradigm consisting of repeated learning cycles. By tracking the changes in the hippocampal representations of associated stimuli on a cycle-by-cycle basis as learning progressed, we show that both integration and separation processes occur in the hippocampus with different temporal dynamics. We found that the degree of shared representations for associated stimuli decreased significantly during the early phase of learning, whereas it increased during the later phase of learning. Remarkably, these dynamic temporal changes were observed only for stimulus pairs remembered 1 day or 4 weeks after learning, but not for forgotten pairs. Further, the integration process during learning was prominent in the anterior hippocampus, while the separation process was obvious in the posterior hippocampus. These results demonstrate temporally and spatially dynamic hippocampal processing during learning that can lead to the maintenance of associative memory.