ReviewGABAergic interneurons: The orchestra or the conductor in fear learning and memory?
Introduction
Fear conditioning is not only a fundamental form of learning that enables animals to detect and defend themselves from dangerous situations but also one of the most intensely studied paradigms for associative memory (Fanselow and Wassum, 2015). Its acquisition involves exposure to an innocuous conditioned stimulus (CS, i.e. auditory tone) in conjunction with an intrinsically aversive unconditioned stimulus (US, i.e. foot-shock). When reencountered, the CS serves as a reminder of imminent threat and promotes the expression of behaviors such as avoidance, freezing, and aggression. Although such reactions are essential for survival, their dysregulation features prominently in conditions like phobia (Berardi et al., 2012), panic disorder (Lueken et al., 2014, Michael et al., 2007, Tuescher et al., 2011) and PTSD (Blechert et al., 2007, Grillon and Morgan, 1999, Jovanovic and Norrholm, 2011, Milad et al., 2009, Rabinak et al., 2017, Shvil et al., 2014).
Fear memories are thought to be formed through experience-dependent plasticity, which is responsible for the formation of a neural trace of CS-US pairing (McKernan and Shinnick-Gallagher, 1997, Rogan et al., 1997, Rumpel et al., 2005, Sigurdsson et al., 2007, Tsvetkov et al., 2002, Arruda-Carvalho and Clem, 2014, Clem and Huganir, 2010, Clem and Huganir, 2013, Clem and Schiller, 2016). A number of plausible mechanisms have been suggested to mediate this process, ranging from potentiation and growth of synaptic connections to epigenetic regulation (Josselyn et al., 2015). However, a general consensus has been that memory storage is the purview of excitatory projection neurons (PNs). PNs are an ideal substrate for long-term memory because they vary widely in their response properties and are highly interconnected within distributed brain networks, in which they are responsible for the propagation of excitatory activity. Furthermore, they possess a postsynaptic compartment that appears anatomically, biochemically, and molecularly tailored for input-selective synaptic strengthening (Hao and Oertner, 2012, Segal, 2017). However, while excitatory PNs are critical for memory formation and retrieval, mounting evidence suggests that their activity is highly orchestrated by interactions with local GABAergic interneurons.
Although they are far outnumbered by excitatory PNs in brain areas that play key roles in fear memory, such as the amygdala, hippocampus, and prefrontal cortex, interneurons mediate overwhelming inhibition through dense and redundant connections onto excitatory PNs (Fishell and Rudy, 2011, Karnani et al., 2014). Synthesis and release of GABA is a shared property of these cells, but they have long been known to exhibit a pronounced diversity of dendritic morphology, postsynaptic axonal targets, firing characteristics, and protein expression patterns (DeFelipe et al., 2013). Emerging evidence indicates that these properties also correlate with discrete stimulus responses and functional roles for different subpopulations, with profound consequences for excitatory PN activity (Karnani et al., 2014). Such data imply that, contrary to early thinking, inhibitory interneurons do not simply act as passive gain regulators but also actively shape network activity. The existence of synaptic connections between interneurons further expands this computational capacity by permitting both inhibition and disinhibition of excitatory PNs.
A major reason why interneurons have been the subject of so few memory studies was the lack of sophisticated technology for identifying and manipulating genetically-defined cell types. However, memory models have also deemphasized interneurons in part because their unique structural and molecular features suggested that they are ill-equipped to express conventional forms of plasticity (McBain and Kauer, 2009). For example, Hebbian synaptic strengthening, heralded as a central mechanism in memory formation, relies on NMDA-receptor mediated Ca2+ entry into dendritic spines and activation of Ca2+/calmodulin-dependent protein kinase II (CaMKII). However, interneurons are typically devoid of dendritic spines as well as CaMKII, and many have negligible NMDA receptor-mediated currents (Mahanty and Sah, 1998, Matta et al., 2013). Nevertheless, it is now clear that, similar to excitatory PNs, inhibitory interneurons exhibit diverse forms of synaptic potentiation and depression in response to artificial stimulation (Cohen et al., 2016, Huang et al., 2013, Mahanty and Sah, 1998, Owen et al., 2013, Pelkey et al., 2005, Woodin et al., 2003), raising the possibility that inhibitory microcircuit plasticity could also be a mechanism underlying long-term memory.
In this review, we discuss emerging evidence that inhibitory interneurons make critical contributions to stimulus processing and memory storage in fear learning. We will devote particular attention to the role of genetically-defined inhibitory populations, whose selective interrogation is now enabled by transgenic mouse lines that express cell-specific Cre and Flp recombinases. We will conclude with a summary of working principles and an outlook on future studies.
Section snippets
Regulation of CS and US processing by inhibitory microcircuits
With the advent of tools to study genetically-defined neuronal populations in the behaving animal, inhibitory microcircuits that play critical roles in acquisition and expression of emotional memory have been defined in auditory cortex (Letzkus et al., 2011), medial prefrontal cortex (Courtin et al., 2014), central amygdala (Ciocchi et al., 2010, Haubensak et al., 2010, Li et al., 2013, Penzo et al., 2015), basolateral amygdala (Wolff et al., 2014), and hippocampus (Lovett-Barron et al., 2014,
Molecular and anatomical evidence for interneuron plasticity in emotional learning
As increasingly sophisticated experiments uncover roles for inhibitory interneurons in emotional stimulus processing, the question of whether learning modifies inhibitory microcircuits remains largely unexplored. The most abundant evidence for such plasticity is derived from biochemical and anatomical analyses, which have relied on in situ hybridization or immunolabeling to reveal changes in the expression level of inhibitory neuronal markers and structural remodeling of synaptic contacts.
Learning-induced plasticity of inhibitory microcircuit transmission
The first description of activity-dependent plasticity of interneuron transmission (Buzsaki and Eidelberg, 1982) was published nine years after the discovery of long-term potentiation (Bliss and Lomo, 1973). Over subsequent decades long-lasting changes in inhibition have been observed after electrical stimulation of interneurons in the amygdala, striatum, cortex, and hippocampus (Kullmann et al., 2012). Furthermore, synaptic plasticity of cortical interneurons is a well-characterized mechanism
Concluding remarks
As studies continue to unravel the function of interneurons in fear learning, it is becoming increasingly clear that these cells make critical contributions to memory acquisition and expression. Not only do interneurons coordinate local network dynamics underlying CS and US processing, but they also exhibit changes in molecular composition, morphology, and synaptic transmission in conjunction with memory storage. Such data imply that interneurons may play an integral role in memory storage and
Acknowledgements
This work was supported by the following grants from the National Institutes of Health:MH105414 (RLC) and EY026053 (RLC).
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2022, NeuronCitation Excerpt :Synaptic inhibition is thought to facilitate these processes in part through rhythmic entrainment of PN firing (Headley and Paré, 2017). However, evidence suggests that both learning and recall also rely on synaptic interactions between INs that promote PN firing through disinhibition, for example, when the recruitment of one IN subtype leads to a corresponding suppression of another (Artinian and Lacaille, 2018; Letzkus et al., 2015; Lucas and Clem, 2018). Because they modulate large groups of PNs, such complex outcomes of GABAergic transmission could endow discrete subsets of INs with unique influence over memory networks.