Author response: Selection of distinct populations of dentate granule cells in response to inputs as a mechanism for pattern separation in mice (2013)

Full text Figures and data Side by side Abstract eLife digest Introduction Results Discussion Materials and methods References Decision letter Author response Article and author information Metrics Abstract The hippocampus is critical for episodic memory and computational studies have predicted specific functions for each hippocampal subregion. Particularly, the dentate gyrus (DG) is hypothesized to perform pattern separation by forming distinct representations of similar inputs. How pattern separation is achieved by the DG remains largely unclear. By examining neuronal activities at a population level, we revealed that, unlike CA1 neuron populations, dentate granule cell (DGC) ensembles activated by learning were not preferentially reactivated by memory recall. Moreover, when mice encountered an environment to which they had not been previously exposed, a novel DGC population—rather than the previously activated DGC ensembles that responded to past events—was selected to represent the new environmental inputs. This selection of a novel responsive DGC population could be triggered by small changes in environmental inputs. Therefore, selecting distinct DGC populations to represent similar but not identical inputs is a mechanism for pattern separation. https://doi.org/10.7554/eLife.00312.001 eLife digest Being able to keep memories of similar events separate in your mind is an essential part of remembering. If you use the same carpark every day, recalling where you left your car this morning is challenging, not because you have to remember an event from long ago, but because you have to distinguish between many similar memories. Keeping memories distinct is one of the functions of a subregion of the hippocampus called the dentate gyrus. The process of taking complex memories and converting them into representations that are less easily confused is known as pattern separation. Exactly how the dentate gyrus achieves this, however, is unclear. Computational models predict that a different population of dentate gyrus cells will be active when an animal is in different environments. However, previous experiments have instead shown that the same population of cells is active in multiple environments, and that cells distinguish between environments by firing at different rates. Now, Deng et al. have added to our understanding of pattern separation. The researchers used a type of genetically modified mouse in which it is possible to identify or ‘tag' the activity of a population of hippocampal neurons at multiple time points. They placed each mouse in a box and noted which hippocampal neurons were active as the animal learned about its new environment. After several such learning episodes, the animal received a mild electric shock inside the box. When it was returned to the box the next day, the mouse remembered receiving the shock, enabling the researchers to note which neurons were active during the retrieval process. Deng et al. found that in a subregion of the hippocampus called CA1, the particular neurons that were active during the initial learning episode were also likely to be active when the animals remembered receiving the shock. However, this was not the case for the dentate gyrus: in this subregion, distinct groups of cells were active during learning and during retrieval. Moreover, exposing the mice to two subtly different environments activated two distinct groups of cells in the dentate gyrus. The work of Deng et al. reveals that memory retrieval does not always involve reactivation of the same neurons that were active during encoding. More importantly, the results indicate that the dentate gyrus performs pattern separation by using distinct populations of cells to represent similar but non-identical memories. Overall the findings add to our understanding of the mechanisms that underpin memory formation. https://doi.org/10.7554/eLife.00312.002 Introduction During learning and memory, the hippocampus, a key structure for episodic memory, receives information from the cortex through multiple parallel pathways to each of its main subregions, including the dentate gyrus (DG), CA3 and CA1 (Squire, 1992; Rolls and Kesner, 2006; Rolls, 2010). The DG receives excitatory inputs from entorhinal cortex (EC) layer II neurons via the perforant pathway and relays the information to CA3 through mossy fibers. The CA3 in turn projects to CA1, which sends back-projections to deep layers of the EC, forming the classic tri-synaptic pathway (EC→DG→CA3→CA1). CA3 also receives direct inputs from EC through the perforant pathway and there are extensive interconnections among CA3 neurons via recurrent collateral fibers. In addition to inputs from CA3, CA1 receives inputs directly from EC layer III neurons through the temporoammonic pathway, forming a monosynaptic pathway (EC→CA1). In this complex neural network, each pathway and each subregion is likely to carry out specific functions during learning and memory. Based on these network connections and the anatomical characteristics of each subregion, theories about specific functions of the individual hippocampal subregions in learning and memory have been proposed by computational modeling (Rolls and Kesner, 2006; Rolls, 2010). In particular, the DG is postulated to function as a pattern separator by de-correlating inputs from EC (Marr, 1971) because of its sparse activity and its considerably larger population of neurons compared to the EC and CA3. The pattern separation function of the DG is supported by accumulating evidence from behavioral studies, reporting that animals with lesions or blocked plasticity in the DG were impaired in discriminating similar spatial and contextual information (Gilbert et al., 2001; McHugh et al., 2007; Goodrich-Hunsaker et al., 2008; Nakashiba et al., 2012). Nevertheless, how the DG achieves the pattern separation function remains elusive. In vivo physiological recordings of dentate granule cells (DGCs) have shown that changes in environmental inputs only evoke the rate remapping of DGCs but not the global remapping predicted by computational models (Leutgeb et al., 2007). Through the powerful mossy fiber synapses, outputs of the DG are passed to the downstream recurrent network in CA3, which is hypothesized to be the site for memory storage (Treves and Rolls, 1994). Computational studies have suggested that it is advantageous to have two extrinsic afferent systems for the autoassociative network in CA3—one with strong synapses for memory formation and the other with associatively modifiable synapses for memory retrieval (Treves and Rolls, 1992). Therefore, it has been speculated that the mossy fiber inputs from the DG may be particularly suitable for memory formation, whereas the direct inputs from EC may be responsible for information recall. On the other hand, CA1 is considered to be a feed forward neural network and is the main output region for the hippocampus (Rolls and Kesner, 2006; Rolls, 2010). Experimental evidence from genetic and physiological studies has demonstrated the importance of CA1 for both memory formation and retrieval (Riedel et al., 1999; Dupret et al., 2010; Goshen et al., 2011). Because the large size of the DGC population is a key factor for the computational hypothesis of pattern separation, we utilized TetTag transgenic mice to examine the population neuronal activity of the dorsal DG to test whether DGCs undergo global remapping at the population level. To examine the specificity of the responsiveness of the DGCs, population activity in CA1 was also analyzed. Our results revealed a novel mechanism for pattern separation in the DG: the selection of distinct DGC populations to represent different contextual information. In addition, we observed that memory recall preferentially reactivated the neuronal population involved in learning in CA1 but not in the DG, suggesting that, in a complex neural network, memory recall may not reinstate the activities in every pathway involved in memory formation. Results Using TetTag transgenic mice to examine neuronal activity at a population level We studied the population activity of neurons in the hippocampus by examining the transient expression of immediate early genes (IEGs, such as Fos, Arc and Egr1), which is commonly used as an indicator of recent neuronal activity (Guzowski et al., 2005). To compare the activities in the same neuronal population in response to two events at sequential time points, we used TetTag bi-transgenic mice in which neuronal activities at a given time window can be persistently labeled (Figure 1A, Figure 1—figure supplement 1; Reijmers et al., 2007). In these mice, neuronal activity can activate the Fos promoter and induce the expression of tetracycline-controlled transactivator (tTA) from the Fos-tTA transgene. In the absence of doxycycline (dox), a drug that binds to tTA and prevents tTA from binding to the tetracycline responsive promoter (tetO), the resulting tTA can activate the expression of the tau-LacZ marker from the transgene: tetO-tau-lacZ:tTA*. At the same time, a tetracycline-insensitive form of transactivator (tTA*: tTA containing H100Y point mutation) is also expressed, allowing the persistent tau-LacZ expression irrespective of dox treatment. Thus, if the mice are removed from dox treatment for an initial experience and euthanized shortly after a second experience, the activity of the same neuronal ensemble in response to these two sequential experiences can be assessed by examining the expressions of tau-LacZ and IEGs, which correspond to neuronal activities of the first and second experiences, respectively. Figure 1 with 3 supplements see all Download asset Open asset Induction of tag (tau-LacZ) expression by removing dox treatment. (A) A brief cartoon illustrating the TetTag transgenic system. (B) and (E) Experimental designs. Dox treatment is illustrated by blue shading. (C) and (D) There are few neurons in either CA1 (C) or the DG (D) (outlined by DAPI [blue]) expressing LacZ marker (green) if mice are kept on a dox diet until enriched environment (EE) exposure. Samples are also stained with FOS (red). Each channel in the inset (outlined by the square) is presented below the corresponding overall image, with arrows indicating the LacZ-positive neurons. (F) and (G) In mice that were removed from dox treatment 2 days before EE exposure, many LacZ-positive neurons can be observed in both CA1 (F) and the DG (G). In both subregions, many tagged neurons are also co-stained with FOS. The scale bar in (D) represents 50 μm for (C, D, F, and G). https://doi.org/10.7554/eLife.00312.003 First, we tested whether expression of tau-LacZ markers in the hippocampus of TetTag mice could be regulated by dox. We exposed mice to an enriched environment under either a dox-on or dox-off condition (Figure 1B,E, see ‘Materials and methods') and found that removing dox treatment effectively induced tau-LacZ expression in neurons of the DG and CA1 (Figure 1B–G, Figure 1—figure supplement 2A–B), with most of the LacZ-positive neurons displaying typical morphologies of granule cells and pyramidal neurons in the DG and CA1, respectively (Figure 1F,G). Furthermore, many LacZ-positive cells also co-expressed FOS, with over 70% and 85% of LacZ-positive cells expressing FOS in the DG and CA1, respectively, suggesting that the expression of LacZ did not affect the expression of IEGs in the same neuron (Figure 1F,G, Figure 1—figure supplement 3A). It was also notable that the efficiency of tagging was low, compared to the endogenous FOS labeling, particularly in the CA1 region. A low efficiency of tagging was also observed in basolateral amygadala (Reijmers et al., 2007). This low and variable induction efficiency across brain regions was possibly caused by low penetrance and variable expressivity of the transgenes, a common problem for transgenic mice. To test if the tagged population represents activities in the general population, we measured the intensity of FOS staining in the LacZ-positive and LacZ-negative neurons. In both DG and CA1, the FOS intensity was similar between LacZ-positive and LacZ-negative populations (Figure 1—figure supplement 3B–E). Therefore, it was likely that LacZ tagged neurons were representatives of the activated population, although we could not formally rule out the possibility that only a specific population of activated neurons (e.g. the population with the highest activities) could be tagged. The induction efficiency was even lower in CA3 with few neurons tagged (Figure 1—figure supplement 2), preventing further analysis in this region. We next tested the activity-dependent expression of tau-LacZ markers in TetTag mice. After removing them from dox treatment, we exposed some mice to a fear conditioning chamber (ctxA, Figure 2—figure supplement 4) and kept others in their home cage (HC) (‘Materials and methods'). While LacZ-positive neurons could be readily detected in both CA1 and the DG in the HC mice (Figure 2A,B), substantially more LacZ tagged neurons were observed in the ctxA mice in both CA1 and the DG (Figure 2C–F; t-test, in CA1, HC, 1.5 ± 0.5%, n = 4; ctxA, 5.1 ± 0.5%, n = 3; p<0.007; in the DG, HC, 1.9 ± 0.7%; ctxA, 6.9 ± 1.0%; p<0.016). Therefore, the dox-regulated and activity-dependent expression of LacZ in both the DG and CA1 suggested the feasibility of studying neuronal activities at a population level in these hippocampal subregions using TetTag mice. Figure 2 with 1 supplement see all Download asset Open asset Activity-dependent induction of tag (tau-LacZ) expression. (A) and (B) The expressions of LacZ marker (green) in CA1 (A) and DG (B) of the mice in the home cage (HC) group. The overall anatomies are highlighted by the DAPI staining (blue). (C) and (D) The expressions of LacZ marker in CA1 (C) and the DG (D) of the mice in the context A (ctxA) group. (E) and (F) Quantification demonstrates that the numbers of LacZ-positive neurons are significantly higher in the ctxA group compared to the HC group in both CA1 (E) and the DG (F). The scale bar in (D) represents 100 μm for panels (A–D). Asterisk indicates statistically significant difference between groups. Data are shown as mean ± SEM. https://doi.org/10.7554/eLife.00312.007 Preferential reactivation of CA1 neuronal population involved in learning by memory recall To study the activity of neuronal populations in the DG and CA1 during event learning and subsequent memory recall, we used a contextual fear conditioning paradigm combining contextual pre-exposure and immediate foot shock (Fanselow, 1990, 2000, 2010). This is a task in which the hippocampus has been demonstrated to be critically involved in forming a conjunctive representation of the conditioning context during pre-exposure (Barrientos et al., 2002; Rudy et al., 2002; Stote and Fanselow, 2004). We chose this task because the formation of the contextual memory, which is dependent on the hippocampus, can be temporally separated from the subsequent context-shock association, which presumably relies mostly on the function of amygdala (Rudy and O'Reilly, 2001; Rudy et al., 2002; Reijmers et al., 2007; Han et al., 2009). With dox treatment removed, we pre-exposed one group of mice (preA, n = 12) to the fear conditioning chamber (context A) to tag the activated neurons (LacZ+) in contextual learning (Figure 3A, Figure 2—figure supplement 1). After the last pre-exposure (on day 5), mice were put back on dox treatment to prevent further tagging. 2 days later, mice were subjected to immediate shock in the conditioning chamber and their conditioned fear memory was tested 1 day after immediate shock. Mice were perfused shortly after the memory test for neuronal activity analysis. For comparison, another group of mice (preC, n = 11) was subjected to the identical protocol except that they were pre-exposed to an environment (context C, Figure 2—figure supplement 1) that was completely different from the conditioning chamber. Because the mice associated contextual information during pre-exposure with the subsequent aversive stimulus (i.e. foot shock) in this protocol, it was not surprising that preA mice but not preC mice displayed a high level of freezing behavior when the mice were tested for their conditioned response in context A (Figure 3B; t-test, t21 = 3.424, p<0.0026). Figure 3 with 2 supplements see all Download asset Open asset Memory recall preferentially reactivates the neuron population in response to learning in CA1 but not in the DG. (A) The pre-exposure-immediate shock paradigm for contextual fear conditioning. Dox treatment is illustrated by blue shading. Contextual learning mainly takes place during pre-exposure in the absence of dox treatment. LacZ and IEGs (FOS or EGR1) are regarded as indicators of learning-induced activity and retrieval-induced activity, respectively. Dox treatment is illustrated by blue shading. (B) preA mice display significantly more freezing behavior than preC mice. (C) and (D) During pre-exposure, the proportions of LacZ-positive neurons in either CA1 (C) or the DG (D) are not significantly different between preA and preC mice. (E) During the retrieval test, preferential reactivation of the LacZ-positive population in CA1 is revealed by quantifying the percentage of FOS-positive neurons in the total population (activation rate) and the percentage of LacZ-FOS double-positive cells in the LacZ-positive population (reactivation rate). (F) There is no preferential reactivation of LacZ-positive DGCs in preA mice, whereas LacZ-positive DGCs are significantly less likely to be reactivated in preC mice compared to preA mice. The reactivation rate is not significantly different from the activation rate in preA mice but is significantly lower than the activation rate in preC mice. (G) Reactivation indexes suggesting the differential reactivations of learning-induced neuronal ensembles by recall in CA1 and the DG (ANOVA: region x group interaction, F1,1 = 5.016, p<0.037; main region effect, F1,21 = 24.49, p<0.0001; main group effect, F1,21 = 50.10, p<0.0001). Asterisk indicates statistically significant difference between groups. Hash indicates statistically significant difference from chance. Data are shown as mean ± SEM (ns: no significant difference; HC: home cage; sac: sacrifice). https://doi.org/10.7554/eLife.00312.009 To investigate the activities in neuron populations of the DG and CA1, we concurrently examined the expression of tau-LacZ and the expression of IEGs to evaluate the neuronal activities during contextual pre-exposure and during memory recall test, respectively (Figure 3—figure supplement 1, see ‘Materials and methods'). We focused our analysis on the dorsal hippocampus, because this region has been shown to be tightly associated with learning and memory. For technical convenience, FOS and EGR1 were used as markers to assess the recall-activated neurons in CA1 and the DG, respectively, and we designated the percentage of IEG positive neurons in the total numbers of neurons quantified as the activation rate (‘Materials and methods'). To measure the proportion of the neurons that were activated by the recall test in the neuronal population that was previously activated during pre-exposure, we quantified the percentage of LacZ+IEG double positive neurons in the LacZ tagged population (designated as the reactivation rate). We were not able to detect a significant difference in either CA1 or the DG in the percentage of LacZ positive neurons in the total numbers of neurons quantified between preA and preC mice (Figure 3C,D; t-test, CA1: t21 = 0.5005, p>0.62; DG: t21 = 0.8504, p>0.40), suggesting that contexts A and C had equivalent simulating effects. To investigate how the neurons involved in memory formation responded to subsequent memory recall, we compared the reactivation rates to the corresponding activation rates. In CA1, whether or not the neurons that were activated during pre-exposure were preferentially activated again by the recall test in context A depended on the identity of the pre-exposure context (Figure 3E; ANOVA: group x activity rates interaction, F1,1 = 11.60, p<0.0027; main effect of activity rates, F1,21 = 44.04, p<0.0001; main effect of group, F1,21 = 8.238, p<0.0092). Because both groups of mice were tested in context A, there was no significant difference in the activation rate between preA and preC mice, as expected (Figure 3E, Bonferroni post test, In the reactivation rate of preA mice was significantly higher than that of preC mice (Figure 3E, Bonferroni post test, indicating that a previous learning experience neuronal at the time of memory recall. In preA mice, which pre-exposure and in context A, the reactivation rate was significantly higher than the activation rate (Figure 3E, Bonferroni post test, suggesting that CA1 neurons that were activated during learning were preferentially reactivated by subsequent memory recall. By in preC mice, neurons to context C during pre-exposure were not preferentially activated by the subsequent test in context A (Figure 3E, Bonferroni post test, activation rate reactivation rate in preC mice, suggesting that preferential reactivation of the CA1 neuron population involved in memory formation depended on retrieval of the same memory We further quantified the of this reactivation by a reactivation which the reactivation rate by the corresponding activation rate (‘Materials and methods'). In CA1, the reactivation in preA but not preC mice was significantly (Figure one t-test, = = p<0.0001; = with the of preA mice significantly higher than that of preC mice (Figure t-test, t21 = data to that the CA1 neuronal ensemble that is responsible for contextual learning is likely for the recall of the same memory The of this with previous that that CA1 is involved in both memory formation and retrieval (Riedel et al., 1999; Goshen et al., further our of using TetTag mice for population neuronal activity study in the of distinct populations of DGCs to represent different events in the DG In to CA1, memory recall did not induce the preferential reactivation of the population of DGCs that was activated during as by the similar activation rate and reactivation rate in preA mice (Figure ANOVA: group x activity rates interaction, F1,1 = no main effect of activity rates, F1,21 = main effect of group, F1,21 = Bonferroni post test, activation rate reactivation rate in To our in preC mice, the reactivation rate of DGCs was significantly lower than the activation rate (Figure Bonferroni post test, indicating that the DGC population to context C was significantly less likely to be activated by context A compared to the general DGC to activation rates that were not significantly different between preA and preC mice (Figure Bonferroni post test, the reactivation rate of preC mice was significantly lower than that of preA mice (Figure Bonferroni post test, Thus, than the DGC population to context C, preC mice activated a different population of DGCs in response to context results were further by the analysis of reactivation The reactivation was significantly higher in preA mice compared to that of preC mice (Figure t-test, t21 = with the in preC but not preA mice significantly below (Figure one t-test, = = = To these we the data in the DG by quantifying the activities in the of and similar results ‘Materials and Figure 3—figure supplement that the of the the all subsequent were out using this Furthermore, we the activation and reactivation rates in a of preA and preC mice, using the expression of FOS as the indicator for DGC activities in the recall results were using either FOS or EGR1 as activity indicators in the same of mice (Figure In these of the population activities of DGCs demonstrated that neurons in the DG and CA1 responded during memory CA1 pyramidal DGCs activated by learning an event were not preferentially reactivated by the same memory. distinct ensembles of DGCs were selected in response to different Figure Download asset Open asset results are in the activity analysis of DGCs using either FOS or EGR1 as IEG markers in the same of mice. (A) analysis using FOS as IEG marker and as neuronal marker demonstrates the selection of different populations of DGCs to represent different environmental inputs (ANOVA: group x activity rate interaction, F1,1 = Bonferroni post test, reactivation rate activation for preA mice, for preC n = n = (B) Reactivation from the analysis using FOS as IEG The in preC is significantly than preA = and the level t-test, = = whereas the in preA is not different from t-test, = = (C) analysis using EGR1 as IEG marker in the same of mice has similar activity pattern as by FOS (ANOVA: group x activity rate interaction, F1,1 = Bonferroni post test, reactivation rate activation for preA mice, for preC The numbers of DGCs in the granule cell layers were quantified from DAPI (D) Reactivation from the analysis using EGR1 as IEG The in preC is significantly than preA = and the level t-test, = = whereas the in preA is not different from t-test, = = Asterisk indicates statistically significant difference between groups. Hash indicates statistically significant difference from chance. Data are shown in mean ± SEM. To how these results could be by HC activity, an part of both and experiences, and whether the of the learned context was critical for population we a new with two of the previous First, one group of mice mice, n = 4) were kept in their HC to context during the dox-off window the other group was exposed to context A (ctxA, n = the was that the pre-exposed context for animals at the (Figure After all mice were put back on dox treatment, the HC mice were to context A, whereas ctxA mice were further into two groups and to either context A n = or C n = Figure Download asset Open asset home cage activity of context has a significant on reactivation in CA1 and DG. (A) The Dox treatment is illustrated by blue shading. (B) HC mice have a significantly lower of LacZ-positive cells in CA1 compared to ctxA mice. (C) Preferential reactivation of CA1 neurons to pre-exposure by only in mice but not HC or mice. (D) HC mice have a significantly lower of LacZ-positive cells in the DG compared to ctxA mice. (E) In HC and mice but not the reactivation rate is significantly lower than the corresponding activation rate in the DG, suggesting different populations of DGCs are selected in response to distinct experiences (F) reactivation indexes analysis. Asterisk indicates statistically significant difference between groups or rates. Hash indicates statistically significant difference from chance. Data are shown as mean ± SEM home cage; sac: sacrifice). with the findings in Figure to context A in higher of LacZ induction in both CA1 and DG (Figure t-test, HC ctxA, in CA1, = in DG, = In mice, which were pre-exposed and to the same the reactivation rates in CA1 were significantly higher than the activation rates, suggesting preferential activation of neurons that responded during pre-exposure by however, this preferential reactivation was not found in either HC or mice, experiences