Why is the Rescorla-Wagner model so influential?

Fear conditioning: Insights into learning, memory and extinction and its relevance to clinical disorders

Fear, whether innate or learned, is an essential emotion required for survival. The learning, and subsequent memory, of fearful events enhances our ability to recognise and respond to threats, aiding adaptation to new, ever-changing environments. Considerable research has leveraged associative learning protocols such as contextual or auditory forms of fear conditioning in rodents, to understand fear learning, memory consolidation and extinction phases of memory. Such assays have led to detailed characterisation of the underlying neurocircuitry and neurobiology supporting fear learning processes. Given fear processing is conserved across rodents and humans, fear conditioning experiments provide translational insights into fundamental memory processes and fear-related pathologies. This review examines associative learning protocols used to measure fear learning, memory and extinction, before providing an overview on the underlying complex neurocircuitry including the amygdala, hippocampus and medial prefrontal cortex. This is followed by an in-depth commentary on the neurobiology, particularly synaptic plasticity mechanisms, which regulate fear learning, memory and extinction. Next, we consider how fear conditioning assays in rodents can inform our understanding of disrupted fear memory in human disorders such as post-traumatic stress disorder (PTSD), anxiety and psychiatric disorders including schizophrenia. Lastly, we critically evaluate fear conditioning protocols, highlighting some of the experimental and theoretical limitations and the considerations required when conducting such assays, alongside recent methodological advancements in the field. Overall, rodent-based fear conditioning assays remain central to making progress in uncovering fundamental memory phenomena and understanding the aetiological mechanisms that underpin fear associated disorders, alongside the development of effective therapeutic strategies.

From British Associationism to the Hippocampal Cognitive Map: A Personal View From a Ringside Seat at the Cognitive/PDP Revolution

The mandate for this special issue of Hippocampus was to provide a few examples of one's own work in a relatively personal context. Accordingly, I will discuss some of my own work here, but will also provide a broader arc of ideas and discoveries within which the efforts of myself and many others have taken place. This history begins with the associationists, who proposed that the human mind could be understood, in part, as a compounding of simple associations between contiguously occurring items and events. This idea was taken up by the behaviorist traditions, which made significant progress toward refining this simple idea. Subsequently, as interest turned toward neural mechanisms, Donald Hebb provided a foundational proposal for how synaptic changes could provide for this associative learning. The associationist view was, however, challenged by gestaltists who took a more wholistic, cognitive approach. Stunning support was provided for Tolman's cognitive map idea with the discovery of place cells in the hippocampus, and the subsequent treatise provided in O'Keefe and Nadel's The Hippocampus as a Cognitive Map. I propose that, ultimately, this associationist versus cognitive debate was settled by the development of the Parallel Distributed Processing (PDP) approach, which incorporated Hebbian synapses into large, neural-like networks, which could accomplish complex cognitive tasks. My own work took place within the framework provided by O'Keefe and Nadel. One aspect of my work followed Jim Ranck's discovery of Head Direction cells. Tad Blair and others in my lab traced a brainstem circuit, which we proposed could explain the origins of the directional code. In other work, I investigated cells in the subicular region. These provided a contrast to the hippocampal place cells in that each subicular cell kept the same spatial pattern across different environments, whereas the hippocampal cells formed a different map for each context.

Multiple and subject-specific roles of uncertainty in reward-guided decision-making

Decision-making in noisy, changing, and partially observable environments entails a basic tradeoff between immediate reward and longer-term information gain, known as the exploration-exploitation dilemma. Computationally, an effective way to balance this tradeoff is by leveraging uncertainty to guide exploration. Yet, in humans, empirical findings are mixed, from suggesting uncertainty-seeking to indifference and avoidance. In a novel bandit task that better captures uncertainty-driven behavior, we find multiple roles for uncertainty in human choices. First, stable and psychologically meaningful individual differences in uncertainty preferences actually range from seeking to avoidance, which can manifest as null group-level effects. Second, uncertainty modulates the use of basic decision heuristics that imperfectly exploit immediate rewards: a repetition bias and win-stay-lose-shift heuristic. These heuristics interact with uncertainty, favoring heuristic choices under higher uncertainty. These results, highlighting the rich and varied structure of reward-based choice, are a step to understanding its functional basis and dysfunction in psychopathology.

What do you learn from a single cue? Dimensional reweighting and cue reassociation from experience with a newly unreliable phonetic cue

In language comprehension, we use perceptual cues to infer meanings. Some of these cues reside on perceptual dimensions. For example, the difference between bear and pear is cued by a difference in voice onset time (VOT), which is a continuous perceptual dimension. The present paper asks whether, and when, experience with a single value on a dimension behaving unexpectedly is used by the learner to reweight the whole dimension. We show that learners reweight the whole VOT dimension when exposed to a single VOT value (e.g., 45 ms) and provided with feedback indicating that the speaker intended to produce a /b/ 50% of the time and a /p/ the other 50% of the time. Importantly, dimensional reweighting occurs only if 1) the 50/50 feedback is unexpected for the VOT value, and 2) there is another dimension that is predictive of feedback. When no predictive dimension is available, listeners reassociate the experienced VOT value with the more surprising outcome but do not downweight the entire VOT dimension. These results provide support for perceptual representations of speech sounds that combine cues and dimensions, for viewing perceptual learning in speech as a combination of error-driven cue reassociation and dimensional reweighting, and for considering dimensional reweighting to be reallocation of attention that occurs only when there is evidence that reallocating attention would improve prediction accuracy (Harmon, Z., Idemaru, K., & Kapatsinski, V. 2019. Learning mechanisms in cue reweighting. Cognition, 189, 76-88.).