Behavioral and neural mechanisms by which prior experience impacts subsequent learning

https://doi.org/10.1016/j.nlm.2017.11.008Get rights and content

Highlights

  • Prior behavioral experience has a profound effect on future learning.

  • Prior experience affects later learning through a variety of neural mechanisms.

  • The time course of facilitation varies across studies.

  • A metaplasticity-like priming mechanism might be an essential component of the memory trace.

Abstract

Memory is often thought about in terms of its ability to recollect and store information about the past, but its function likely rests with the fact that it permits adaptation to ongoing and future experience. Thus, the brain circuitry that encodes memory must act as if stored information is likely to be modified by subsequent experience. Considerable progress has been made in identifying the behavioral and neural mechanisms supporting the acquisition and consolidation of memories, but this knowledge comes largely from studies in laboratory animals in which the training experience is presented in isolation from prior experimentally-controlled events. Given that memories are unlikely to be formed upon a clean slate, there is a clear need to understand how learning occurs upon the background of prior experience. This article reviews recent studies from an emerging body of work on metaplasticity, memory allocation, and synaptic tagging and capture, all of which demonstrate that prior experience can have a profound effect on subsequent learning. Special attention will be given to discussion of the neural mechanisms that allow past experience to affect future learning and to the time course by which past learning events can alter subsequent learning. Finally, consideration will be given to the possible significance of a non-synaptic component of the memory trace, which in some cases is likely responsible for the priming of subsequent learning and may be involved in the recovery from amnestic treatments in which the synaptic mechanisms of memory have been impaired.

Introduction

The neurobiological study of learning and memory has made significant progress in identifying the cellular and molecular mechanisms that support the acquisition and consolidation of long-term memory (Helmstetter et al., 2008, Johansen et al., 2011, Kandel, 2012). In addition, the essential neural circuitry underlying many of the model systems used to study learning and memory has been identified (Davis, 1997, LeDoux, 2000, Thompson and Kim, 1996, Tovote et al., 2015). However, one domain in which we have a relatively poor understanding of learning and memory function is how prior experience affects subsequent learning. This is a product of the fact that many neurobiological studies of memory employ experimental designs wherein the learning event is short-lasting and presented in isolation from prior experimentally-controlled events. This standard approach has its benefits in that the learning event can be clearly defined and controlled by the experimenter, however it comes at the expense of understanding how prior experience affects subsequent learning. Outside of the laboratory memory formation does not occur in a vacuum (Dudai, 2009), but instead occurs upon prior and ongoing experience. Understanding how past experience impacts later learning is essential for a better understanding of learning and memory processes.

Although much of the extant work on the biological basis of memory has not considered how prior experience affects subsequent memory formation, there is an evolving literature that has revealed that the prior history of an organism has a profound effect on future learning. This literature has fallen under the rubrics of synaptic tagging and capture, metaplasticity, and memory allocation (Hulme et al., 2013, Rogerson et al., 2014, Viola et al., 2014). While they have been labeled using different nomenclature, what they share in common is that they all describe conditions by which prior behavioral experience can influence subsequent learning. In what follows, I will describe findings from behavioral studies of metaplasticity, synaptic tagging and capture, and memory allocation. Special emphasis will be placed on comparing both the behavioral and neurobiological mechanisms that permit past events to influence subsequent learning. By doing so, I hope to offer insight into the processes that govern whether prior experience affects subsequent learning. While the focus of this review will be limited, the reader should note that a larger literature exists that describes a similar tendency for past events to influence subsequent learning. This includes the effects of stress on subsequent learning (Kim and Yoon, 1998, Schmidt et al., 2013), reactivation-dependent modification of memory (Finnie & Nader, 2012), and assimilation of new information into existing schemas (McKenzie and Eichenbaum, 2011, Tse et al., 2007, Tse et al., 2011).

Section snippets

Prior behavioral experience regulates subsequent learning

If the goal of the study of learning and memory is to understand how organisms adapt to ongoing and future experience, then experimental paradigms used in the laboratory must allow for the rigorous examination of how prior experience affects subsequent memory formation. While much of prior work examining the neurobiological mechanisms of learning have not taken this important consideration into account, recent studies on metaplasticity, synaptic tagging and capture, and memory allocation have

Neural mechanisms by which prior experience facilitates subsequent learning

Discussion of the neural mechanisms involved in behavioral studies of metaplasticity, memory allocation, and synaptic tagging and capture is complicated by the fact that in many of the experiments the nature of initial experience differs greatly across studies (e.g. cued fear conditioning versus spatial exploration), and in most cases, the antecedent and subsequent events also differ within experiments. Moreover, in the behavioral studies of synaptic tagging and capture the temporal order of

The time course by which prior experience affects subsequent learning

Early on in the experimental analysis of learning and memory it became apparent that the interval of time between learning trials is a critical factor in determining whether information is committed to long-term memory (Carew et al., 1972, Ebbinghaus, 1885/1913, Fanselow and Tighe, 1988, Josselyn et al., 2001, Philips et al., 2013). Trials distributed over longer periods of time produce better learning compared to trials spaced closely together, thus it is not unexpected that the interval of

A priming mechanism as a component of the memory trace

The data reviewed here suggest that there might be at least two mechanisms by which prior experience is able to impact later learning. The first is a mechanism whereby facilitation occurs when one event takes place within the time window of molecular consolidation engaged by a separate experience, akin to synaptic tagging and capture. The second type being the product of a longer lasting priming mechanism, possibly associated with learning related changes in intrinsic neuronal membrane

Conclusions

The studies reviewed here make it clear that prior experience has a profound effect on subsequent learning. The propensity of prior experience to influence later learning likely reflects an essential mechanism in the brain that balances the need to maintain the stability of networks that store information with the requirement that those networks also exist in a plastic state that allows them to adapt to future stimulation (Abraham & Robins, 2005). Given that memories are not formed in isolation

Acknowledgements

The author reports no biomedical financial interests or potential conflicts of interest. This work was supported by funds from Stony Brook University.

References (97)

  • J.P. Johansen et al.

    Molecular mechanisms of fear learning and memory

    Cell

    (2011)
  • J.J. Kim et al.

    Stress: Metaplastic effects in the hippocampus

    Trends in Neurosciences

    (1998)
  • S. McKenzie et al.

    Consolidation and reconsolidation: Two lives of memories?

    Neuron

    (2011)
  • D. Moncada et al.

    Phosphorylation state of CREB in the rat hippocampus: A molecular switch between spatial novelty and spatial familiarity?

    Neurobiology of Learning and Memory

    (2006)
  • R.G. Morris

    NMDA receptors and memory encoding

    Neuropharmacology

    (2013)
  • R.G. Parsons et al.

    Mechanisms underlying long-term fear memory formation from a metaplastic neuronal state

    Neurobiology of Learning and Memory

    (2016)
  • G.T. Philips et al.

    Pattern and predictability in memory formation: From molecular mechanisms to clinical relevance

    Neurobiology of Learning and Memory

    (2013)
  • V. Rau et al.

    Stress-induced enhancement of fear learning: An animal model of posttraumatic stress disorder

    Neuroscience and Biobehavioral Reviews

    (2005)
  • M.J. Sanders et al.

    Pre-training prevents context fear conditioning deficits produced by hippocampal NMDA receptor blockade

    Neurobiology of Learning and Memory

    (2003)
  • Y. Sano et al.

    CREB regulates memory allocation in the insular cortex

    Current Biology

    (2014)
  • M.V. Schmidt et al.

    Stress-induced metaplasticity: From synapses to behavior

    Neuroscience

    (2013)
  • M. Sehgal et al.

    Learning to learn – Intrinsic plasticity as a metaplasticity mechanism for memory formation

    Neurobiology of Learning and Memory

    (2013)
  • H.K. Titley et al.

    Toward a neurocentric view of learning

    Neuron

    (2017)
  • E. Tsvetkov et al.

    Fear conditioning occludes LTP-induced presynaptic enhancement of synaptic transmission in the cortical pathway to the lateral amygdala

    Neuron

    (2002)
  • H. Viola et al.

    The tagging and capture hypothesis from synapse to memory

    Progress in Molecular Biology and Translational Science

    (2014)
  • A.P. Yiu et al.

    Neurons are recruited to a memory trace based on relative neuronal excitability immediately before training

    Neuron

    (2014)
  • W.C. Abraham

    Metaplasticity: Tuning synapses and networks for plasticity

    Nature Reviews Neuroscience

    (2008)
  • W.C. Abraham et al.

    Heterosynaptic metaplasticity in the hippocampus in vivo: A BCM-like modifiable threshold for LTP

    Proceedings of the National Academy of Sciences of the United States of America

    (2001)
  • F. Ballarini et al.

    Memory in elementary school children is improved by an unrelated novel experience

    PLoS ONE

    (2013)
  • F. Ballarini et al.

    Behavioral tagging is a general mechanism of long-term memory formation

    Proceedings of the National Academy of Sciences of the United States of America

    (2009)
  • D.M. Bannerman et al.

    Distinct components of spatial learning revealed by prior training and NMDA receptor blockade

    Nature

    (1995)
  • D.E. Berman et al.

    Memory extinction, learning anew, and learning the new: Dissociations in the molecular machinery of learning in cortex

    Science

    (2001)
  • D.E. Berman et al.

    Specific and differential activation of mitogen-activated protein kinase cascades by unfamiliar taste in the insular cortex of the behaving rat

    Journal of Neuroscience

    (1998)
  • D.J. Cai et al.

    A shared neural ensemble links distinct contextual memories encoded close in time

    Nature

    (2016)
  • T.J. Carew et al.

    Long-term habituation of a defensive withdrawal reflex in aplysia

    Science

    (1972)
  • S. Chen et al.

    Reinstatement of long-term memory following erasure of its behavioral and synaptic expression in Aplysia

    eLife

    (2014)
  • R.L. Clem et al.

    Ongoing in vivo experience triggers synaptic metaplasticity in the neocortex

    Science

    (2008)
  • A.S. Cohen et al.

    Facilitation of long-term potentiation by prior activation of metabotropic glutamate receptors

    Journal of Neurophysiology

    (1996)
  • S.I. Cohen-Matsliah et al.

    A novel role for extracellular signal-regulated kinase in maintaining long-term memory-relevant excitability changes

    Journal of Neuroscience

    (2007)
  • S.I. Cohen-Matsliah et al.

    A novel role for protein synthesis in long-term neuronal plasticity: Maintaining reduced postburst afterhyperpolarization

    Journal of Neuroscience

    (2010)
  • M. Davis

    Neurobiology of fear responses: The role of the amygdala

    Journal of Neuropsychiatry and Clinical Neurosciences

    (1997)
  • Y. Dong et al.

    CREB modulates excitability of nucleus accumbens neurons

    Nature Neuroscience

    (2006)
  • Y. Dudai

    Predicting not to predict too much: How the cellular machinery of memory anticipates the uncertain future

    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences

    (2009)
  • S.M. Dudek et al.

    Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-methyl-D-aspartate receptor blockade

    Proceedings of the National Academy of Sciences of the United States of America

    (1992)
  • J.E. Dunsmoor et al.

    Emotional learning selectively and retroactively strengthens memories for related events

    Nature

    (2015)
  • H.E. Ebbinghaus

    Memory: A contribution to experimental psychology

    (1885/1913)
  • M.S. Fanselow

    Factors governing one-trial contextual conditioning

    Animal Learning & Behavior

    (1990)
  • M.S. Fanselow et al.

    Contextual conditioning with massed versus distributed unconditional stimuli in the absence of explicit conditional stimuli

    Journal of Experimental Psychology: Animal Behavior Processes

    (1988)
  • Cited by (20)

    • Persistence of Spatial Memory Induced by Spaced Training Involves a Behavioral-Tagging Process

      2022, Neuroscience
      Citation Excerpt :

      Finally, our results are also consistent with the phenomenon of metaplasticity, a term used to describe the way in which synaptic plasticity can be regulated by prior synaptic activity (Abraham and Bear, 1996; Schmidt et al., 2013). Thus, the effect of the history of the animal on synaptic plasticity could impact on subsequent learning and memory abilities (Parsons, 2018). In this framework, the amount of AMPA receptor subunits and other proteins in the synapse at the moment of retraining could be considered a metaplastic change derived from the first training.

    • Pre-adolescent stress disrupts adult, but not adolescent, safety learning

      2021, Behavioural Brain Research
      Citation Excerpt :

      Transient increases in synaptic integration in these circuits may therefore enable safety learning in adolescents, while the deleterious effects of pre-adolescent CUS exposure may create lasting impairments in safety learning by disrupting circuit maturation [65,66]. Although interpretation of the present study has been limited to preclinical studies, our findings emphasize the importance of considering both age and prior experience when determining the appropriate course of clinical treatment [67–69]. Our findings suggest it is worth exploring in clinical studies whether stressed adolescents might benefit from using safety signals, as a novel way to mitigate fear when other methods (e.g., fear extinction [8–10]) are otherwise limited and ineffective.

    • Hippocampal network oscillations as mediators of behavioural metaplasticity: Insights from emotional learning

      2018, Neurobiology of Learning and Memory
      Citation Excerpt :

      Evidence suggests that neuronal metaplasticity, i.e., adaptive change that occur via setting the threshold for induction of synaptic plasticity (Abraham & Bear, 1996), may be an important mechanisms of such adaptation. Indeed, several lines of evidence suggest that metaplasticity occurs in vivo (Hulme, Jones, & Abraham, 2013) and supports adaptive changes during distinct emotional memory phases in a time- and brain region-specific manner (Parsons & Davis, 2012; Parsons, 2017; Parsons, Walker, & Davis, 2016). In support of these findings, the concept of metaplasticity has been broadened from synaptic level to adaptive plasticity at the level of neural systems referred as “behavioural metaplasticity” (Schmidt et al., 2013).

    • Facilitation of fear learning by prior and subsequent fear conditioning

      2018, Behavioural Brain Research
      Citation Excerpt :

      This includes the effects of stress on learning, that has been the topic of considerable study [7], and various well-characterized conditioning phenomena [8–10]. In more recent years studies have started to describe additional conditions by which recent experience can affect the acquisition of memory [11]. One line of research includes a set of behavioral findings that confirm many of the predictions of the synaptic tagging and capture model [12].

    View all citing articles on Scopus
    View full text