Neurobiology of Learning and Memory最新文献

The ability to form long-term memories begins in early infancy. However, little is known about the specific mechanisms that guide memory formation during this developmental stage. We demonstrate the emergence of a long-term memory for a novel voice in three-month-old infants using the EEG mismatch response (MMR) to the word “baby”. In an oddball-paradigm, a frequent standard, and two rare deviant voices (novel and mother) were presented before (baseline), and after (test) familiarizing the infants with the novel voice and a subsequent nap. Only the mother deviant but not the novel deviant elicited a late frontal MMR (∼850  ms) at baseline, possibly reflecting a long-term memory representation for the mother’s voice. Yet, MMRs to the novel and mother deviant significantly increased in similarity after voice familiarization and sleep. Moreover, both MMRs showed an additional early (∼250  ms) frontal negative component that is potentially related to deviance processing in short-term memory. Enhanced spindle activity during the nap predicted an increase in late MMR amplitude to the novel deviant and increased MMR similarity between novel and mother deviant. Our findings indicate that the late positive MMR in infants might reflect emergent long-term memory that benefits from sleep spindles.

Reinforcement learning, crucial for behavior in dynamic environments, is driven by rewards and punishments, modulated by dopamine (DA) changes. This study explores the dopaminergic system’s influence on learning, particularly in Parkinson’s disease (PD), where medication leads to impaired adaptability. Highlighting the role of tonic DA in signaling the valence of actions, this research investigates how DA affects response vigor and decision-making in PD. DA not only influences reward and punishment learning but also indicates the cognitive effort level and risk propensity in actions, which are essential for understanding and managing PD symptoms.

In this work, we adapt our existing neurocomputational model of basal ganglia (BG) to simulate two reversal learning tasks proposed by Cools et al. We first optimized a Hebb rule for both probabilistic and deterministic reversal learning, conducted a sensitivity analysis (SA) on parameters related to DA effect, and compared performances between three groups: PD-ON, PD-OFF, and control subjects.

In our deterministic task simulation, we explored switch error rates after unexpected task switches and found a U-shaped relationship between tonic DA levels and switch error frequency. Through SA, we classify these three groups. Then, assuming that the valence of the stimulus affects the tonic levels of DA, we were able to reproduce the results by Cools et al.

As for the probabilistic task simulation, our results are in line with clinical data, showing similar trends with PD-ON, characterized by higher tonic DA levels that are correlated with increased difficulty in both acquisition and reversal tasks.

Our study proposes a new hypothesis: valence, signaled by tonic DA levels, influences learning in PD, confirming the uncorrelation between phasic and tonic DA changes. This hypothesis challenges existing paradigms and opens new avenues for understanding cognitive processes in PD, particularly in reversal learning tasks.

Cue-potentiated feeding (CPF) describes instances where food intake is increased by exposure to conditioned cues associated with food, often in the absence of hunger. CPF effects have been reported in a range of experimental protocols developed by researchers working across diverse fields spanning behavioural neuroscience, social psychology and ecology. Here we review the evolution of research on cue-potentiated feeding in animal models to identify important behavioural parameters and key neural circuits and pharmacological systems underlying the effect. Overall, evidence indicates that social, discrete and contextual stimuli can be used to elicit CPF effects across multiple species, though effects are often subtle and sensitive to procedural variables. While regular exposure to food cues is thought to be a key risk factor for overeating in so-called ‘obesogenic’ environments, further work is needed to identify whether CPF promotes positive energy balance and weight gain over the longer term. We suggest several methodological and conceptual areas for inquiry to elucidate the contribution of CPF to the regulation of food choice and energy intake.

Although early studies were able to demonstrate a negative impact of stress on working memory performance, present research findings are heterogeneous. Numerous further studies found no effects or even improved performance, with the direction of these stress effects likely depending on the underlying biological mechanisms. The aim of this study was to investigate receptor-specific effects, as part of the stress-induced cortisol response, on working memory performance. Healthy, male participants (N=318, mean age 25.4 ± 5.1y) were exposed to the Trier Social Stress Test (TSST), a social-evaluative stress manipulation, or a non-stress control condition after they had received either spironolactone (blockade of the mineralocorticoid receptor, MR) or mifepristone (blockade of the glucocorticoid receptor, GR) or a placebo. Both substances are potent antagonists with high affinity for the respective receptors. To assess working memory, we implemented the n-back task subsequent to stress exposure, number of correct responses and reaction times served as outcome measures. We did not find effects of stress on working memory for any outcome measure, i.e. correct responses and reaction times. Yet, post hoc tests revealed that the group that received mifepristone exhibited longer reaction times under medium load conditions when compared to the placebo group, which might be an indication of the GR’s involvement in task performance. We conclude that working memory performance is not affected by acute stress, at least under these prevalent conditions.

Humans and animals can quickly learn a new strategy when a previously-rewarding strategy is punished. It is difficult to model this with reinforcement learning methods, because they tend to perseverate on previously-learned strategies − a hallmark of impaired response to punishment. Past work has addressed this by augmenting conventional reinforcement learning equations with ad hoc parameters or parallel learning systems. This produces reinforcement learning models that account for reversal learning, but are more abstract, complex, and somewhat detached from neural substrates. Here we use a different approach: we generalize a recently-discovered neuron-level learning rule, on the assumption that it captures a basic principle of learning that may occur at the whole-brain-level. Surprisingly, this gives a new reinforcement learning rule that accounts for adaptation and lose-shift behavior, and uses only the same parameters as conventional reinforcement learning equations. In the new rule, the normal reward prediction errors that drive reinforcement learning are scaled by the likelihood the agent assigns to the action that triggered a reward or punishment. The new rule demonstrates quick adaptation in card sorting and variable Iowa gambling tasks, and also exhibits a human-like paradox-of-choice effect. It will be useful for experimental researchers modeling learning and behavior.