Prior Learning of Relevant Nonaversive Information Is a Boundary Condition for Avoidance Memory Reconsolidation in the Rat Hippocampus

Abstract

Reactivated memories can be modified during reconsolidation, making this process a potential therapeutic target for posttraumatic stress disorder (PTSD), a mental illness characterized by the recurring avoidance of situations that evoke trauma-related fears. However, avoidance memory reconsolidation depends on a set of still loosely defined boundary conditions, limiting the translational value of basic research. In particular, the involvement of the hippocampus in fear-motivated avoidance memory reconsolidation remains controversial. Combining behavioral and electrophysiological analyses in male Wistar rats, we found that previous learning of relevant nonaversive information is essential to elicit the participation of the hippocampus in avoidance memory reconsolidation, which is associated with an increase in theta- and gamma-oscillation power and cross-frequency coupling in dorsal CA1 during reactivation of the avoidance response. Our results indicate that the hippocampus is involved in memory reconsolidation only when reactivation results in contradictory representations regarding the consequences of avoidance and suggest that robust nesting of hippocampal theta-gamma rhythms at the time of retrieval is a specific reconsolidation marker. Posttraumatic stress disorder (PTSD) is characterized by maladaptive avoidance responses to stimuli or behaviors that represent or bear resemblance to some aspect of a traumatic experience. Disruption of reconsolidation, the process by which reactivated memories become susceptible to modifications, is a promising approach for treating PTSD patients. However, much of what is known about fear-motivated avoidance memory reconsolidation derives from studies based on fear conditioning instead of avoidance-learning paradigms. Using a step-down inhibitory avoidance task in rats, we found that the hippocampus is involved in memory reconsolidation only when the animals acquired the avoidance response in an environment that they had previously learned as safe and showed that increased theta- and gamma-oscillation coupling during reactivation is an electrophysiological signature of this process.

On the Boundary Conditions of Avoidance Memory Reconsolidation: An Attractor Network Perspective

“…To simulate the main experimental protocol of Radiske et al (2017), we used the schema shown in Figure 2A, where each session corresponds to the respective input pattern shown in Figure 2B. The first stage is the storage of the non-related memory by the input Inr in all networks (notice that the activated neurons in this pattern do not overlap with those in the other patterns).…”

“…Specifically, it is defined by Ir = Is + (Ins -Is)f(#), where #  [#min = 0, #max = 10] -the "pattern number"is related to the duration of the nonreinforced reexposure session, and f(#) = 1 / (1 + e (#max / 2) -# ) is a function representing the ratio between input patterns Ins and Is and varies monotonically between 0 and 1 (Osan et al, 2011). To simulate a 40-second reexposure session (Radiske et al, 2017), we used # = 3.1, which corresponds to Ir closer to the aversive memory ( Figure 2B).…”

“…The latency values are truncated at the ceiling of 500 s, i.e., the maximum duration of the reexposure session in Radiske et al (2017).…”

“…Therefore, investigating the boundary conditions leading to the reconsolidation or extinction of aversive memories is especially important to help developing better strategies for the treatment of anxiety and fear-related disorders (Dębiec and Ledoux, 2004;Kindt et al, 2009;Lee et al, 2005). Some already known boundary conditions are the strength of the aversive memory storage (Forcato et al, 2014;Suzuki et al, 2004;Taylor et al, 2009;Wang et al, 2009), the time elapsed between the storage and the aversive memory reactivation (Baratti et al, 2008;Forcato et al, 2013;Inda et al, 2011;Milekic and Alberini, 2002), and, more recently, the previous knowledge of the context/stimulus as non-aversive (Radiske et al, 2017). However, the results of the literature that define them are controversial (Nader and Hardt, 2009), suggesting the necessity of a broad parametric mapping that adequately defines the actual existence of the boundary conditions already discovered.…”

“…To that end, we considered the computational approach of the attractor network model developed by Osan et al (2011), which was previously used to explain experimental findings regarding freezing behavior of rodents submitted to paradigms of contextual fear memory consolidation, reconsolidation, and extinction. Here, we use such a model to gain theoretical insights into the experimental results of Radiske et al (2017), which showed that the prior non-aversive learning of the context where the animals experience the shock (i.e., the IA box) is a boundary condition for the reconsolidation of the avoidance memory.…”