In the first part of this work, we describe a completely new mechanism that determines memory allocation in neuronal networks: a lateral inhibition between GCs that limits the number of neurons of the cellular engram of contextual fear memory. Interestingly, lateral inhibition affects the stability of the memory trace by determining the size of the cellular engram.
What are the determinants that limit the size of the emerging active ensembles in the DG during memory formation?
One factor is to attribute to the number of the upstream principal cells of the EC which is several folds lower than the number of GCs (Schmidt et al., 2012). This anatomical characterization may confer the DG the ability to “orthogonalize” and discriminate the information by distributing it to small and specific population of cells as proposed by models of pattern separation and completion (Leutgeb et al., 2007; Deng et al., 2013;
Guzman et al., 2016). Another factor is the sparse activity of GCs, mainly due to their intrinsic properties (i.e. relatively hyperpolarized membrane potential (Lopez-Rojas et al., 2016; Lopez-Rojas and Kreutz, 2016) as well as to dendritic filtering (Krueppel et al., 2011;
Kamijo et al., 2014). The physiological outcome is that, to become active, a GC needs many concomitant synaptic inputs (Krueppel et al., 2011).
On top of these factors, we now can add the mechanism revealed by the present study, the lateral inhibition among GCs. Specifically, this inhibitory interaction helps to maintain low levels of neuronal excitation in cells not immediately active during memory formation (Treves and Rolls, 1994). One of the principal reasons for so many mechanisms aiming at keeping such low neuronal excitation of GCs is that they allow sparse coding. Different studies suggest that in associative memories, sparse coding in the hippocampus is important to increase storage capacity and to disambiguate similar information (Olshausen and Field, 2004; Diamantaki et al., 2016).
How do active ensembles acquire engram properties?
Recent studies have reported that memory can be allocated to specific population of neurons by altering their neuronal activity during memory encoding (Yiu et al., 2014; Han et al., 2007). These studies reveal that there are cell autonomous mechanisms (i.e.
regulation of cellular excitability), that determine how the brain allocates memory to ensemble of cells. Our study reveals a network mechanism of memory allocation in the DG. Indeed, in the first experiment where we artificially and randomly selected an ensemble of GCs using optogenetics, we interfered with the formation of a natural cellular engram since mice could not recall the conditioned context using the context derived information. This result suggests that memory allocation is very unlikely to be uniquely a cell-autonomous phenomenon and that the activity of neighboring cells is indeed relevant for cellular engram formation. We next showed that our interference with memory allocation did not disrupt memory formation but rather created an artificial cellular engram since mice could not retrieve the fear memory by environmental stimuli but could retrieve it when the light was switched on (Figure 20B and E).
Our optogenetic manipulation conferred engram properties, a mnemonic trace, to the active ensemble. How this is possible and what are the molecular mechanisms, must be demonstrated with further experiments. We can however speculate that our optogenetic 10 Hz stimulation during training may assign engram properties to GCs ensemble through synaptic plasticity and via network connectivity. As LTP at mossy fiber synapses is believed to be mediated by a pre-synaptic mechanism (Zalutsky and Nicoll, 1990; Staubli et al., 1990; Xiang et al., 1994), it is possible that our 10 Hz stimulation may facilitate the release of neurotransmitters at these synapses and favor LTP (Nicoll and Schmitz, 2005;
Gundlfinger et al., 2010). Thus, we facilitate connectivity specifically of the optogenetic stimulated cellular engram. At the same time, we force dendritic depolarization of GCs and eventually also favoring LTP at perforant path synapses from the EC onto GCs (Jaffe et al., 1992; Sabatini and Svoboda, 2000). Accordingly, the contextual information of the environment (CS) would be represented in the ensemble of ChR2+ expressing neurons. In addition, stimulation of the ChR2 cellular ensemble may activate downstream targets such as the BLA known to participate in the CS-US association thus supporting the linking of the contextual information (CS) with the shocks (US) (Herry et al., 2008; Pape and Pare, 2010; Herry and Johansen, 2014; Grewe et al., 2017). It is however important to highlight that changes in reactivation of the ensembles due to rapid uncoupling of the context and the fear response by the artificial stimulation may cause memory extinction and reduced optogenetic memory retrieval (Figure S2F). This phenomenon has also been observed with a naturally-labelled cellular engram (Ramirez et al., 2013). In our study we used a continuous 10 Hz stimulation protocol to best represent what is normally observed in in vivo spikes generated by GCs during SE (Haggerty and Ji, 2015; Passecker et al., 2011).
Indeed, studies that performed in vivo recordings of GCs activity during spatial exploration
showed a firing frequency of around 7-8 Hz and the fraction of neurons that respond is around 9 % (GoodSmith et al., 2017). Thus, despite our manipulations were designed to emulate what has been shown in these observational studies, they may not faithfully mimic naturalistic network activity of the DG during memory encoding and recall.
Specificity of the cellular engram
One of the characteristics of the cellular engram is the specificity or principle of content, where a cellular engram must contain information about a particular experience, thus being specific for a distinct memory (Josselyn et al., 2015; Guan et al., 2016). In our experiments, the specificity (i.e. context of the conditioning) is supported by the fact that lateral inhibition triggered by the active ensemble of neurons coding for the memory suppresses neighboring neurons preventing alternative ensembles from coding for the same context. Thus, the information of the conditioning context will be exclusively assigned to active ensemble of neurons, acquiring specificity. Our results reveal however that mice could not retrieve the memory by natural cues although the memory has been formed (Figure 20B and D). How is this possible? An aspect to consider is the size of the ChR2+ population. In our study, we labelled with ChR2 a population of GCs that consisted of around 13% of the total population of the dorsal DG. During our SE experiments, we revealed a GCs population of around 8% that were positive for c-fos. This last population, that receive strong synaptic input from the EC, is naturally formed and contains all the context and sensory information necessary for correct memory formation. If we take these populations together, which are relatively small, the chances for a neuron to belong simultaneously to both pools are negligible (around 1%). In our experiments, the optogenetic manipulation prevents the formation of a natural ensemble that could guide recall by natural cues since c-fos staining is almost absent in ChR2- GCs (Figure 19D and S2E). Accordingly, context information would be direct and exclusively represented by ChR2+ GCs whose activity, transmitted to downstream target like the amygdala, would be associated with information from the US. On the other hand, optogenetic activation of GCs may cause homeostatic reductions of neuronal activity (Goold and Nicoll, 2010) and inputs form contextual cues may not be able to reactivate the ChR2+ ensemble, preventing natural recall.
Neuronal competition during memory formation and recall
The present work reveals that GCs are in competition between each other to become part of the cellular engram. This is also true for other brain regions (Han et al., 2007).
Moreover, our results show that acute modulation of neuronal activity during training bidirectionally affects the size of the cellular engram through a network mechanism.
Indeed, increasing the number of GCs belonging to the active ensemble resulted in a bigger cellular engram and correlated with increased memory recall, while decreasing the active ensemble’s size had the opposite effect (Figure S6E). During memory formation, active neurons inhibit the recruitment of neighboring cells confining mostly to engram neurons strong synaptic input from the EC. Interestingly, mechanisms determining the recruitment of neurons during memory formation seems to resemble those occurring during memory recall. In other words, acute modification of neuronal activity during memory encoding, either with optogenetic or chemogenetic, determines the size and the identity of neurons activated during memory recall 1 week later (Figure 21D). If this is the case, it could be very likely that some forms of long-term plasticity implemented during memory formation may determine neuronal selection during recall. According to synaptic plasticity models, the straightening of synapses through LTP is thought to be the ground floor for memory formation (Nabavi et al., 2014). Our results suggest that these mechanisms are in play during the formation and reactivation of cellular engrams.
Interestingly, we have shown that there is a correlation between the size of the cellular engram and memory performance (Figure S6E). However, a recent study has shown that this may not be the case in the BLA during cued fear conditioning (Morrison et al., 2016).
This suggests that different mechanisms of cellular engram regulation may occur in the DG and the BLA in line with the differential role in memory and the diverse connectivity of local inhibitory circuits that regulate engram formation in these two brain areas (Savanthrapadian et al., 2014). Indeed, we know that these brain areas are very different anatomically and functionally, where the network connectivity between excitatory cells and interneurons is very diverse (Savanthrapadian et al., 2014; Wolff et al., 2014). Concerning future investigations of the DG cellular engram, it would be interesting to know whether there are minimal and maximal values in the size of the cellular engram that determine correct memory function. Do other mechanisms exist (i.e. synaptic plasticity, genes expression and regulation,…) that help to maintain cellular engram size constant regardless of the nature and/or salience of the experience to be stored? Are more salient events recruiting more cells in the cellular engram? Is there a relationship between memory stability and the precision of the memory performance?
How is lateral inhibition among GCs mediated?
Our experiments reveal that there is a lateral inhibition between GCs. Activation of a small fraction of GCs triggers an inhibitory response in neighboring GCs (Figure 23). This is however unexpected since GCs are mainly excitatory and we observed very strong activation of GABAergic inputs in neighboring GCs. How is this possible? We have revealed that the lateral inhibition is possible through a di-synaptic loop mediated by GABAergic cells. Two major classes of GABAergic neurons in the DG may perform such inhibition: the PV+ and SST+ INs. However, our results suggest a selective role for SST+
cells but could not find an apparent role for PV+ INs. Dendritic lateral inhibition is not a unique characteristic of the DG and in fact it has also been observed in the cerebral cortex (Kapfer et al., 2007; Silberberg and Markram, 2007). In this case, the lateral inhibition is also mediated by SST+ cells that correlate activity of cortical excitatory neurons (Berger et al., 2010) and silence excitatory transmission (Urban-Ciecko et al., 2015). It has also been shown that SST+ cells fire at high rates during movement (Katona et al., 2014) which may provide inhibition necessary to lower DG activity levels and help to prevent increase in their activity (Figure 24B). According to this idea, as SST+ INs activity is already high at basal conditions, increasing their activity may have smaller effects on their memory functions than silencing them (Figure 24B). Many studies corroborate the idea that dendrite GABAergic synapses shunt excitatory afferents thus allowing SST+ INs to modulate synaptic plasticity, intracellular signaling and gene expression, all primary elements required for memory formation (Chiu et al., 2013; Chalifoux and Carter, 2010).
SST+ INs mediate DG cellular engram formation
Our chemogenetic manipulation has a temporal limitation which does not allow us to exclude that SST+ INs may play a pivotal role in memory formation beyond the encoding phase. As reported by chemogenetic studies using DREAD receptors, the effect of CNO in the brain can last for several hours after its administration (Alexander et al., 2009; Roth, 2016). Thus, it is very likely that our manipulation of SST+ cells may persist in the consolidation phase of memory. If this is the case, cellular engram size could also be affected during this phase of memory. For these reasons, further experimental evidence is needed to determine whether SST+ INs have a role in memory consolidation. Another aspect that has been shown is that neuronal activity regulates IEGs levels in SST+ INs (Figure S4). This modulation can affect gene expression that ultimately may control memory-related plasticity also in SST+ cells by altering their connectivity as previously shown by Spiegel and colleagues (Spiegel et al., 2014).
Do PV+ INs alter the size of the cellular engram?
Our results reveal that PV+ INs manipulation during contextual memory formation did not alter the size of the cellular engram or memory function. Previous studies have shown that PV+ INs acute modulation during encoding does not prevent fear memory formation (Lovett-Barron et al., 2014). However, PV+ INs may contribute to memory formation and to information storage by adapting network plasticity to previous experience (Donato et al., 2013). Wolff et al. (2014), have demonstrated that in the BLA, manipulation of PV+ INs affect cued-fear memory performance through inhibition of SST+ cells and subsequent disinhibition of principal neurons. Contrary to the BLA, in the DG, PV+ to SST+
connectivity is very rare as suggested by the anatomical segregation of these two INs subtypes in different layers (Per Andersen et al., 2007; Savanthrapadian et al., 2014).
Taken together, if in BLA, PV+ cells control memory formation through inhibition of SST+
INs and subsequent disinhibition of principal neurons’ dendrites, in the DG such mechanism is not supported due to the low connectivity between these types of cells. This may explain why in the DG, PV+ INs are not regulating memory formation. However, our results could not exclude a possible role for PV+ INs in shaping the cellular engram due to temporal resolution of the manipulations of these populations of cells. Indeed, other studies have revealed that PV+ hippocampal INs are dispensable during memory formation (Lovett-Barron et al., 2014) but required during later phases of memory process, in particular during consolidation (Karunakaran et al., 2016). Altogether, the brain area studied, the temporal resolution of the manipulation and the type of manipulation are all factors that may be determinant to establish a role for a specific population of cells in the cellular engram that could alter specific mnemonic functions.
Our study and others (Cai et al., 2016; Rashid et al., 2016) reveal that lateral inhibition is a crucial mechanism for cellular engram allocation and correct memory function. Rashid et al. (2016) have revealed that excitatory inhibitory balance between ensemble of neurons is mediated by a form of lateral inhibition in the amygdala, seemingly mediated by PV+ INs, that is used as a mechanism to link (coallocate) memories for events occurring close in time and to distinguish (disallocate) memories occurring farther apart in time. This mechanism is believed to occur also during memory recall when new memories can be linked with old memories. If this is the case, it is very likely that altered lateral inhibition may be associated with pathologies related to memory dysfunction. Many studies report that abnormalities of GABAergic circuits are at the core of brain pathologies such as schizophrenia (Lewis et al., 2005; Marin, 2012), epilepsy (Cossart et al., 2001), Alzheimer
(Verret et al., 2012; Palop and Mucke, 2016) and PSTD (Michels et al., 2014; Sun et al., 2016). With concern to memory related brain pathologies, it is believed that network alterations in oscillatory activities known to be orchestrated by interneurons are at the core mechanisms of such dysfunctions. Thus, the lateral inhibition circuit revealed in the present study may put the basis for future investigation aiming at understanding the molecular and cellular basis of pathological memory deficits with the hope to develop and propose rational therapies.