Abstract:

The error-driven learning theory believes that the reinforcement brought by the stimulus must be surprising or unpredictable for the individual to form learning. The mismatch between the expected consequence of behavior and the actual result, known as prediction error (PE), is the driving factor of learning, according to this theory. The Rescorla & Wagner model, the Pearce-Hall model, and the temporal difference (TD) model are the three most common models for calculating prediction error. The RW model and the TD model, in particular, have had a significant impact on the research of prediction error-driven learning and memory. Under different learning models, prediction error is classified as reward or punishment prediction error (RPE or PPE); positive or negative prediction error; and singed or unsigned prediction error (SPE or UPE). As a type of salience, PE is different from other types of saliences. Salience includes stimulus novelty, valence evaluation, stimulus rareness and other salience. Physical salience, surprise (unexpected novelty), and expected novelty are all types of novelty, but only unexpected novelty can promote dopamine release; physical salience with no direct rewards can only cause a short spike in dopamine. Prediction error, on the other hand, are mostly related to the recognition, result perception, and valence evaluation processes.

A large body of work investigated the role of prediction error in the formation and updating of fear memory. Firstly, prediction error is considered to be a necessary factor in the process of fear acquisition. Negative PE is the source of successful fear extinction. Secondly, under the framework of Reconsolidation Interference of conditioned fear memory, prediction error is demonstrated as a necessary condition of memory destabilization. Prediction error plays a key role in fear memory reconsolidation: (1) PE during memory reactivation is an important boundary condition for memory destabilization; (2) PE is a necessary but not sufficient condition for the triggering of reconsolidation. The degree of prediction error determines whether or not the memory can become unstable. PE's role in memory updating has progressed from a qualitative to a quantitative examination, which has become an important measure of such research development; (3) The size of PE required for memory destabilization is proportional to the memory’s original strength. Thus, it is critical to take both sides into account when evaluating a retrieval manipulation. We propose an integrated model of retrieval boundary conditions and memory features for the reconsolidation of fear memories based on these studies and previous models.

However, until recently, the neural mechanism underlying the involvement of prediction error in fear memory update has remained largely elusive. Recent work has revealed the brain areas involved mainly include the amygdala, ventrolateral peri-aqueduct gray matter (vlPAG), hippocampus, and prefrontal cortex (PFC). The PFC, in particular, is a distinct area that may distinguish the fear extinguish with or without reconsolidation. While a range of neurotransmitters are linked to the role of PE in memory destabilization in terms of neuromodulation in brain circuits, the most significant of which is dopaminergic. However, glutamate’s participation in the same process is also worth mentioning.

We propose that in the future direction of the research on fear memory updating, further exploration should be made on quantitative research based on the PE calculation model, integrating the interaction between PE and other boundary conditions, and investigating the role of different types of saliences in memory reconsolidation. Importantly, multidisciplinary methods are urgently need to be used to investigate the neural and molecular mechanisms of PE's role in fear memory renewal. Individual differences in the effects of PE, on the other hand, must be investigated in order to facilitate the translation of studies from bench to bedside.

Key words: prediction error, fear conditioning, memory updating, reconsolidation, reconsolidation interference paradigm