The human brain is able to remember experiences that occurred at specific places and times, such as a birthday party held at a particular restaurant. A part of the brain known as the hippocampus helps to store these episodic memories, but how exactly is not fully understood.

Within the hippocampus are specialized neurons known as place cells which ‘label’ locations with unique patterns of brain activity. When we revisit a place, such as the restaurant, place cells recall the stored pattern of brain activity allowing us to recognize the familiar location.

It has been shown that a new negative experience at a familiar place – for example, if we went back to the restaurant and had a terrible meal – triggers place cells to update the brain activity label associated with the location. However, it remains uncertain whether this re-labelling assists in storing the memory of the unpleasant experience.

To investigate, Blair et al. used a technique known as calcium imaging to monitor place cells in the hippocampus of freely moving rats. The rats were given a new experience – a mild foot shock – at a previously explored location. Tiny cameras attached to their heads were then used to record the activity of hundreds of place cells before and after the shock.

Initially, the rats remembered the aversive experience and avoided the location where they had been shocked. Over time, the rats began to return to the location; however, their place cells displayed different patterns of activity compared to their previous visits before the shock.

To test whether this change in place cell activity corresponded with new memories, another group of rats were administered a mild amnesia-inducing drug before the shock, causing them to forget the experience. These rats did not avoid the shock site or show any changes in place cell activity when they revisited it.

These findings imply that new events cause place cells to alter their ‘label’ for a location only if the event is remembered, not if it is forgotten. This indicates that alterations in place cell activity patterns may play a role in storing memories of unpleasant experiences. Having a better understanding of how episodic memories are stored could lead to better treatments for diseases that impair memory, such as Alzheimer’s disease and age-related dementia.

The rodent hippocampus contains place cells that fire selectively during visits to specific locations in space (O’Keefe and Dostrovsky, 1971). When place cells were first discovered, they were hypothesized to encode ‘cognitive maps’ that store stable long-lasting memories for the spatial geometry of familiar environments (O’Keefe and Nadel, 1978). Supporting this view, electrophysiology studies showed that place cells can retain stable positional tuning across repeated visits to the same environment (Lever et al., 2002). However, methodological limitations of single-unit electrophysiology made it challenging to consistently record the same population of place cells across long time spans, and thus to investigate the duration of time over which place cell tuning properties remained stable.

Recent advances in in vivo calcium imaging have made it possible to perform longitudinal studies of place cell tuning over days or weeks of experience. Such studies suggest that place cells in mice (Ziv et al., 2013; Cai et al., 2016; Kinsky et al., 2018; Keinath et al., 2022) and to a lesser extent in rats (Wirtshafter and Disterhoft, 2022) can change their spatial tuning properties (i.e., ‘remap’) with the mere passage time (see also Mankin et al., 2012). This phenomenon suggests that place cells may not simply encode spatial maps of environmental geometry, but also encode mnemonic information about accumulated past experiences that have occurred within an environment (Leutgeb et al., 2005; Colgin et al., 2008; Mankin et al., 2012; Ziv et al., 2013; Cai et al., 2016; Sanders et al., 2020). If so, then the rate at which place cells remap over time within a given environment may be proportional to the rate at which an animal stores new episodic memories of events that are linked to that environment.

If the rate of place remapping reflects the rate of hippocampal memory storage, then motivationally significant events (such as encounters with appetitive or aversive stimuli) that are preferentially stored to episodic memory might be expected to accelerate the rate of place cell remapping within environments where such events occur. Consistent with this view, studies have shown that place cells remap in response to behaviorally significant events (Breese et al., 1989; Bostock et al., 1991; Hollup et al., 2001; Colgin et al., 2008; Dupret et al., 2010; Alvernhe et al., 2011; Mamad et al., 2017). Numerous studies have shown that when an aversive stimulus is encountered in an environment, place cells respond by remapping their firing fields in that environment (Moita et al., 2003; Moita et al., 2004; Wang et al., 2012; Wang et al., 2015; Kim et al., 2015; Mamad et al., 2019; Schuette et al., 2020; Ormond et al., 2023), but it is not well understood whether such remapping plays a role in storing memories of aversive experiences.

Here, we investigated the role of place cell remapping in memory by using the MiniLFOV (Guo et al., 2023), a recently developed large-field-of-view version of the UCLA Miniscope (Cai et al., 2016; Aharoni and Hoogland, 2019), to image population activity of CA1 place cells in freely behaving rats as they acquired and extinguished a spatial avoidance learning task. The task was performed on a rectangular maze where rats ran stereotyped linear trajectories, allowing the speed and direction of running behavior to be closely matched during sessions conducted before acquisition versus after extinction of avoidance learning. In agreement with prior studies, we observed that avoidance learning induced place cell remapping in an environment where footshock was encountered compared with control conditions where (1) rats encountered a neutral barrier instead of an aversive footshock or (2) rats received footshock after injections of the muscarinic ACh receptor (mAChR) antagonist scopolamine at a dose (1 mg/kg) that disrupted long-term retention of avoidance without acutely impairing immediate avoidance or spatial tuning of place cells. Remapping after avoidance learning was similarly prevalent in subpopulations of shock-responsive and non-responsive place cells, and in contrast with some prior findings (Mamad et al., 2019), remapping did not alter the spatial distribution of place fields on the maze (i.e., there was no net migration of place fields toward or away from the shocked location). These findings add to a large body of evidence showing that place cell remapping occurs in response to aversive events, and also provide new evidence that remapping occurs preferentially under conditions where aversive encounters are remembered rather than forgotten, consistent with the hypothesis that place cell remapping may play a role in storing memories of aversive encounters.

Male (n = 7) and female (n = 8) Long–Evans rats underwent survival surgery to inject 1.2 uL of AAV9-Syn-GCamp7s (AddGene) in the hippocampal CA1 layer; ~2 wk later, a 1.8-mm-diameter GRIN lens stack (~0.5 pitch) was unilaterally implanted to image CA1 neurons. A baseplate was attached to the skull for mounting the miniscope, and then rats began a regimen of running one 15 min session per 48 hr on a 250 × 125 cm rectangular maze (Figure 1A). Rats earned 20 mg chocolate pellets by alternating between two rewarded corners. On each trial, rats were free to choose a direct short path (250 cm) or an indirect long path (500 cm) to reach the next reward. During early sessions, rats learned to prefer the short over the long path (Figure 1C and D). Upon reaching criterion for short path preference (>2 rewards/min, and twice as many short paths to long paths), rats began receiving drug-free shock, scopolamine shock, or barrier training sessions (Figure 1B).

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Between- versus within-session place cell stability

A large-field-of-view version of the UCLA Miniscope (‘MiniLFOV’; Guo et al., 2023) was used to image neurons in the hippocampal CA1 layer through the implanted GRIN lens during maze sessions (Figure 2A). Although the GRIN lens caused some flattening and compression of stratum oriens (Figure 2—figure supplement 1), this did not appear to cause significant disruptions of CA1 activity since spatial tuning properties of place cells were stable and intact (see below).

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Calcium activity was analyzed only during traversals of the short path since the long path was undersampled after rats had learned to prefer the short path. Analysis was further restricted to beeline trials during which the rat ran directly from one reward zone to the other on the short path, without any pause or change in direction (Figure 2B, Video 1); this assured that imaging data came from periods of active locomotion when place cells exhibit reliable spatial tuning, and that the rats’ behavior during imaging was similar across all experimental sessions and conditions. To further control for possible confounding effects of behavior differences between sessions (see Figure 2—figure supplement 2), beeline trials were randomly subsampled using an algorithm (see ‘Methods’) that minimized trial count and running speed differences between the drug-free and scopolamine conditions (Figure 2C). Spatial tuning was then analyzed and compared during these behaviorally homogeneous trials. To analyze spatial tuning, the short path was subdivided into 23 spatial bins (each 10.8 cm wide). Two spatial tuning curves (one per running direction) were derived for each neuron. Cell activity was measured in units of active frames per second (Af/s), defined as the mean number of imaging frames per second during which a neuron generated at least one inferred spike. A neuron was classified as a place cell if its LR or RL tuning curve (or both) met defined criteria for minimum Af/s, spatial selectivity, and spatial stability within a session (see ‘Methods’). About 1/3 of place cell tuning curves met the criteria for spatial selectivity only in the LR direction, 1/3 only in the RL direction, and 1/3 in both directions (Figure 2E). It should be noted that since we used a ubiquitous synapsin promoter to drive expression of GcaMP7s, some neurons classified as place cells might have been CA1 interneurons rather than pyramidal cells.

Video 1

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To analyze acute effects of scopolamine on CA1 place cell activity, data from drug-free or scopolamine shock sessions was compared against data from pre-training baseline sessions (always drug-free) given 48 hr earlier. The drug-free condition only included rats (n = 9) that retained avoidance of the short path 48 hr aftershock training, whereas the scopolamine condition only included rats (n = 7) that failed to avoid the short path 48 hr aftershock training (indicating that the drug had blocked avoidance learning). A 2 × 2 ANOVA on the number of place cells detected per session (Figure 2D, left) found no effect of training condition (F_1,14 = 0.03, p=0.87) or session (F_1,14 = 0.014, p=0.92), and no interaction (F_1,14 = 2.1, p=0.17). A similar ANOVA on the percentage of imaged cells per session that were classified as place cells (Figure 2D, right) found no effect of training condition (F_1,14 = 0.07, p=0.79), but place cell percentages were lower during training than pre-training sessions (F_1,14 = 5.1, p=0.04); this reduction was greater in the scopolamine than drug-free condition, resulting in a marginal interaction effect (F_1,14 = 4.4, p=0.0539). An analysis of how spatial tuning varied with the size and location of cell contours revealed that contours of non-place cells tended to be slightly but significantly smaller (p<0.01) and nearer to the lens center (p<0.05) than contours of place cells (Figure 2—figure supplement 3A).

For tuning curves that met the criteria for spatial selectivity in each session, four tuning properties were analyzed: peak Af/s rate, out-of-field Af/s rate, tuning width, and spatial information content (see ‘Methods’). For each rat and each session, median values of these tuning properties were taken over all LR and RL tuning curves that met spatial selectivity criteria (Figure 2—figure supplement 4); 2 × 2 mixed ANOVAs were then performed on the resulting rate medians for each of the four tuning properties (Figure 2F). There were large main effects of session (pre-training vs. training) for all four tuning properties, which were driven by correspondingly large differences in behavior sampling and running speed (Figure 2C). However, there were no main effects of training condition (drug-free vs. scopolamine) or interactions between training condition and session (Figure 2F), indicating that none of the four tuning properties differed during training sessions given drug-free versus on scopolamine.

The place field recurrence ratio was defined as ${RR=N}_R/N_T$ , where $N_R$ is the number of place fields that recurred during the pre-training and training sessions, and $N_T$ is the total number of recurring and non-recurring place fields detected during both sessions combined (see ‘Methods’). Mean $RR$ values were lower (independent ${\displaystyle t_{14}=2.15,\mathrm{p}=0.0497}$) during scopolamine (40.7 ± 8.8%) than drug-free (50.7 ± 3.9%) training sessions, consistent with the findings reported above that the proportion of neurons classified as place cells during the training session was lower on scopolamine than drug-free (Figure 2D, right). It was observed that contours of recurring place cells tended to be slightly but significantly smaller (p<0.01) and nearer to the lens center (p<0.01) than contours of non-recurring place cells (see Figure 2—figure supplement 3B and C).

To investigate how scopolamine affected population coding by recurring place cells, two heatmaps (one per running direction, denoted $H_{LR}^{pre}$ and $H_{RL}^{pre}$) were created from pre-training tuning curves of recurring place cells (Figure 2H, Figure 2—figure supplement 5). Additionally, two heatmaps per running direction were created from data collected during the first ($H_{LR}^{trn1}$ , $H_{RL}^{trn1}$) and second ($H_{LR}^{trn2}$ , $H_{RL}^{trn2}$) half of each training session’s subsampled beeline trials, all of which occurred prior to shock delivery. Between-session population vector correlation matrices (one per running direction) were derived for each rat (Figure 2—figure supplement 5) with matrix entries given by ${\rho }_{i,j}^{btwn}=R(H_i^{pre},H_j^{trn1})$, where $H_i^{pre}$ and $H_j^{trn1}$ denote population vectors in columns i and j of the pre-training and trn1 heatmaps, respectively, and $R$ is the Pearson correlation coefficient. Within-session population vector correlation matrices were derived in a similar manner with matrix entries given by ${\rho }_{i,j}^{wthn}=R(H_i^{trn1},H_j^{trn2})$, where $H_i^{trn1}$ and $H_j^{trn2}$ denote population vectors in columns i and j of the trn1 and trn2 heatmaps, respectively. When population vector correlation matrices were averaged together across running directions and rats (Figure 2I), high mean ${\rho }_{}^{wthn}$ values were observed along diagonals of within-session correlation matrices for both the drug-free and scopolamine conditions. By contrast, lower mean ${\rho }_{}^{btwn}$ values were observed along diagonals of between-session correlation matrices, in accordance with prior studies showing that place cell population vectors become decorrelated over time (Mankin et al., 2012; Ziv et al., 2013; Cai et al., 2016; Keinath et al., 2022). To quantify this decorrelation, a place tuning stability score (S) was computed as S = median(${\rho }_1^{LR}-{\rho }_{off}^{LR}$ , ${\rho }_2^{LR}-{\rho }_{off}^{LR}$ ,..., ${\rho }_K^{LR}-{\rho }_{off}^{LR}$ , ${\rho }_1^{RL}-{\rho }_{off}^{RL}$ , ${\rho }_2^{RL}-{\rho }_{off}^{RL}$ ,..., ${\rho }_K^{RL}-{\rho }_{off}^{RL}$), where ${\rho }_{off}^{LR}$ and ${\rho }_{off}^{RL}$ are mean off-diagonal $\rho$ values and ${\rho }_i^{LR}$ and ${\rho }_i^{RL}$ are individual peri-diagonal $\rho$ values for bins in the rat’s LR and RL correlation matrices (see ‘Methods’). A 2 × 2 mixed ANOVA on S scores with training condition (drug-free vs. scopolamine) as an independent factor and time interval (between vs. within session) as a repeated factor found no main effect of training condition (F_1,14 = 1.73, p=0.21), but there was a large main effect of time interval (F_1,14 = 71.5, p=7.1e^-7) and a significant interaction (F_1,14 = 8.1, p=0.0132). Uncorrected post hoc comparisons confirmed that this was because scopolamine injections reduced between- (t₁₄ = 3.1, S_DF < S_SCP p=0.0084) but not within- (t₁₄ = 0.83, S_DF < S_SCP p=0.42) session population vector correlations (Figure 2I, center). Hence, even though scopolamine did not acutely disrupt spatial tuning of CA1 neurons (Figure 2F), the drug reduced the percentage of recurring place cells and degraded the between-session (but not within-session) similarity of recurring place cell population vectors (Figure 2H and I). Similar disruption of between- but not within-session place cell stability has been previously reported in aged rats (Barnes et al., 1997).

Disruption of between-session place cell stability by scopolamine was similar in male and female rats (Figure 2—figure supplement 6). Cross-session stability of population vectors was completely abolished in control analyses (see ‘Methods’) where inferred spikes were circularly shifted against position tracking data during each individual beeline trial of the pre-training reference session (Figure 2—figure supplement 7). When analyses of Figure 2 were repeated on scopolamine rats (n = 2) that retained avoidance despite the injection, population vector similarity was not degraded between pre-training and training sessions, suggesting that impairment of between-session place tuning stability was related to impairment of avoidance learning (Figure 2—figure supplement 8). When the analyses were repeated on drug-free rats (n = 2) that failed to retain avoidance despite being trained drug free, between- and within-session population vector similarity were indistinguishable from drug rats that retained avoidance (Figure 2—figure supplement 8), implying that failure to acquire avoidance in these rats was not attributable to any noticeable deficiency in the fidelity of the hippocampal place code during training.

Induction of place cell remapping by aversive learning

Training-induced place cell remapping was analyzed in the same subset of rats shown in Figure 2. To measure remapping, post-extinction CA1 population vectors were compared against the 48 hr pre-acquisition baseline session. For the drug-free shock condition, post-extinction population vectors were sampled from the first session aftershock training during which the rat met criterion (>2 rewards/min, and twice as many short paths as long paths) for extinction of short path avoidance (Figure 3A, left); this was the earliest post-training session with adequate sampling of the short path. For the scopolamine shock condition, post-extinction population vectors were sampled from the session given 8 d (i.e., four sessions including the training session) after the pre-training session (Figure 3A, center); this matched the modal intersession interval for the drug-free condition, so that confounds would not arise from measuring remapping across different time intervals for the drug-free versus scopolamine conditions. Likewise, for the barrier control condition, post-extinction population vectors were also sampled 8 d after the pre-training session; one barrier training rat became startled due to external factors and stopped running early in the 8 d post-training session, so the 6 d session was used instead (Figure 3A, right).

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To control for potential confounds from between-session behavior differences, beeline trials were subsampled using an algorithm (see ‘Methods’) that equalized the number of trials from pre- and post-extinction sessions in each rat (Figure 3B, left), while also minimizing running speed differences between sessions and training conditions (Figure 3B). Spatial tuning was analyzed during subsampled trials, and a 3 × 2 mixed ANOVA on the number of place cells detected during each session (Figure 3C, left) yielded no effect of training condition (F_2,19 = 0.43, p=0.66) or session (F_1,19 = 0.01, p=0.92), and no interaction effect (F_2,19 = 1.57, p=0.24). A similar ANOVA on the percentage of imaged cells per session classified as place cells also yielded no significant effects (training condition: F_2,19 = 0.14, p=0.87; session: F_1,19 = 0.56, p=0.46; interaction: F_2,19 = 1.28, p=0.3). The place field recurrence ratio ($RR$) between pre- and post-extinction sessions also did not differ among training conditions (Figure 3C, right; one-way ANOVA: ${\displaystyle F_{2,19}=.65,\mathrm{p}=0.53}$).

To investigate whether shock-induced remapping occurred, a pair of heatmaps (pre and post) was created from tuning curves of recurring place cells in each running direction (LR and RL) for each training condition (Figure 3D). As in prior calcium imaging studies (Ziv et al., 2013), place fields tended to be more densely concentrated near the ends of the short path than in the middle (Figure 3E). Heatmap pairs were used to derive two population vector correlation matrices per rat, $P_{LR}$ and $P_{RL}$ (Figure 3—figure supplement 1). When $P_{LR}$ and $P_{RL}$ were averaged across rats, a gap of low correlation appeared in the center of the diagonal for the drug-free shock condition (Figure 3F, left), which was not seen in the scopolamine shock (Figure 3F, middle) or barrier (Figure 3F, right) conditions, suggesting that drug-free shock training induced more remapping of the short path than scopolamine shock or barrier training, in accordance with prior studies (Moita et al., 2003; Moita et al., 2004; Wang et al., 2012; Mamad et al., 2019; Schuette et al., 2020; Ormond et al., 2023).

To statistically analyze this remapping effect, a place tuning stability score S was derived for each rat by the methods described above. Boxplots in Figure 3H (top row) show each rat’s median and range of S values from all peridiagonal bins in $P_{LR}$ and $P_{RL}$ combined. Bar graphs (Figure 3H, top left) for mean stability scores, ${\displaystyle \overline{S}}$, for each training condition differed significantly between drug-free, scopolamine, and barrier conditions (one-way ANOVA: ${\displaystyle F_{2,19}=9.7,\mathrm{p}=0.0012}$); uncorrected post hoc t-tests confirmed that this was because ${\displaystyle \overline{S}}$ was lower in the drug-free shock than scopolamine shock (${\displaystyle t_{14}=4.3,\mathrm{p}=0.0007}$) or barrier (${\displaystyle t_{13}=2.2,\mathrm{p}=0.0498}$) conditions, which differed only marginally from one another (${\displaystyle t_{11}=1.98,\mathrm{p}=0.0834}$). Hence, drug-free avoidance training and extinction induced more place cell remapping than the scopolamine shock or barrier training conditions; this remapping occurred at all locations on the short path but a 3 × 3 repeated-measures ANOVA with training condition (drug-free shock, scopolamine shock, barrier) and track zone (left safe, center shock, right safe; bottom 3 rows of Figure 3H) as factors suggested that remapping was most pronounced in the center zone where shocks occurred than at L and R ends of the track where no shocks occurred (Figure 3H, bottom; ${\displaystyle F_{2,40}=3.0,\mathrm{p}=0.0596}$). Induction of remapping by avoidance training and extinction did not differ in male versus female rats, nor did the impairment of remapping by scopolamine (Figure 3—figure supplement 2). When the analyses of Figure 3 were repeated on scopolamine rats (n = 2) that successfully retained avoidance despite the injection, the drug was less effective at inducing place cell remapping (Figure 3—figure supplement 3), suggesting (but not proving) that impairment of remapping was causally related to impairment of avoidance learning. When the analyses were repeated on drug-free rats (n = 2) that failed to retain avoidance despite being trained drug free (Figure 3—figure supplement 2), one rat showed less and the other showed more place tuning stability across the entire length of the track when compared against rats that retained avoidance.

Kolmogorov–Smirnov tests found that place field density distributions (accumulated over all rats) did not change significantly between the pre versus post sessions in any training condition, including the drug-free shock condition (Figure 3E, left). Hence, remapping did not cause place fields to migrate toward or away from the shock zone (Figure 3—figure supplement 4), in contrast with prior reports that remapping can cause place fields to migrate toward locations where aversive stimuli are encountered (Mamad et al., 2019). All place cell remapping effects and differences among training conditions were abolished when remapping analyses were performed on shuffled data (Figure 3—figure supplement 5).

To analyze the extent of remapping caused by aversive learning, the rat’s position on the track was decoded from place cell calcium activity (see ‘Methods’). The decoder was trained on data from one session (pre- or post-extinction) and tested on data from the other session. The decoding error in a given position bin was measured as the median of the absolute difference (in cm) between the rat’s actual versus predicted position over all visits to that bin. Wilcoxon signed-rank tests compared decoding errors obtained with shuffled versus non-shuffled population vectors; a decoding accuracy index (DAI) was then derived for each bin, with DAI = 0 corresponding to p=0.01 for more accurate decoding from unshuffled than shuffled population vectors (see ‘Methods’). When mean DAI values were compared among training conditions, significant differences were detected only in two bins at the center of the track (in the shock zone) where decoding in the drug-free shock condition was significantly less accurate (p<0.05) than in scopolamine shock and barrier training conditions combined (asterisks in Figure 3D, bottom). In accordance with results from population vector correlation analysis, these decoding results support the conclusion that drug-free shocks induced more remapping of the center zone than shocks while on scopolamine or from barrier training.

Shock-evoked responses of place cells

Shock-induced place cell remapping has been observed in prior studies (Moita et al., 2003; Moita et al., 2004; Wang et al., 2012; Schuette et al., 2020), but the cellular and synaptic mechanisms of such remapping are not well understood. Individual CA1 neurons can form new place fields at locations where they are artificially stimulated or inhibited (Bittner et al., 2015; Geiller et al., 2022), and since some CA1 place cells are naturally responsive to shocks (Moita et al., 2003; Moita et al., 2004), it is possible that individual CA1 neurons might gain or lose place fields at locations where they respond to shocks. If so, then this might partly account for remapping at the population level. If shock-evoked responses of CA1 neurons are involved in remapping, then blockade of remapping by scopolamine could be related to effects of the drug upon these shock-evoked responses. To investigate this, each place cell imaged during a training session was classified as shock-responsive if its Af/s rate was significantly higher (p<0.01) during entries to the electrified than non-electrified shock zone; otherwise, it was classified as non-responsive to shocks (see ‘Methods).

The mean percentage of shock-responsive cells per rat (Figure 4A, left column) was 35.5 ± 2.3% for drug-free training and 29.6 ± 3.3% for scopolamine training; these percentages did not differ significantly (independent $t_{14}=$ 1.58; p=0.13). Pre-shock baseline Af/s rates (Figure 4A, middle column) were higher for shock-responsive than non-responsive place cells in both the drug-free ($t_{1931}=$ 9.3; p<0.0001) and scopolamine ($t_{1034}=$ 4.34; p<0.0001) conditions, which was attributable to the fact that in both conditions, place field peaks for shock-responsive and non-responsive cells tended to be segregated on the ‘approach’ and ‘departure’ sides of the shock zone, respectively (Figure 4A, right column). Thus, as rats approached the shock zone in either running direction, shock-responsive cells were more likely than non-responsive cells to be active in their place fields just before shock zone entry.

Figure 4

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To compare remapping by shock-responsive versus non-responsive CA1 neurons, analyses were performed on place cells that recurred during pre- and post-extinction sessions and were also active during the training session (so that each cell could be classified as responsive or non-responsive to shocks). Pre- and post-extinction heatmaps were derived from tuning curves of shock-responsive (Figure 4B) and non-responsive (Figure 4C) place cells. LR and RL tuning curves were combined together in each heatmap, with RL (but not LR) tuning curves reflected on the horizontal so that the rat’s running direction was oriented from left to right in all rows; hence, columns to the left or right of center in each heatmap denoted locations where rats were approaching or departing the shock zone, respectively. From these heatmaps, shock-responsive and non-responsive population vector correlation matrices were derived for the drug-free ($P_{shk+}^{DF}$ , $P_{shk-}^{DF}$) and scopolamine ($P_{shk+}^{SCOP}$ , $P_{shk-}^{SCOP}$) conditions. A gap of low population vector correlation values in the center of $P_{shk+}^{DF}$ but not $P_{shk+}^{SCOP}$ (Figure 4B) and of $P_{shk-}^{DF}$ but not $P_{shk-}^{SCOP}$ (Figure 4C) indicated that drug-free shocks induced remapping of the center zone in both shock-responsive and non-responsive place cell populations, whereas scopolamine shocks failed to induce remapping in either population. Confirming this, a series of independent t-tests was performed on clusters of peri-diagonal bins arrayed along diagonals of $P_{shk+}^{DF}$ versus $P_{shk+}^{SCOP}$ , and $P_{shk-}^{DF}$ versus $P_{shk-}^{SCOP}$ (see ‘Methods’); resulting significance values (line graphs in Figure 4B and C) dipped well below p<0.01 in the center region of the track (but not at the ends), indicating that drug-free shocks caused shock-responsive and non-responsive place cells to remap the center zone more than scopolamine shocks.

Place cell remapping has been shown to occur at locations where animals experience aversive events such as shocks, predator odors, or attacks (Moita et al., 2003; Moita et al., 2004; Wang et al., 2012; Wang et al., 2015; Kim et al., 2015; Mamad et al., 2019; Schuette et al., 2020; Ormond et al., 2023), but it is not well understood whether such remapping plays a functional role in storing memories for aversive encounters. Here we investigated this question by using a large-field-of-view version of the UCLA Miniscope (Guo et al., 2023) to image population activity of CA1 place cells in rats as they acquired and extinguished a spatial avoidance learning task. We found that significantly more place cell remapping was induced under experimental conditions where aversive encounters were remembered (drug-free shocks) than under control conditions where they were forgotten (shock training on scopolamine), or where a neutral rather than aversive path-blocking stimulus was encountered (barrier training). While these results do not definitively prove that place cell remapping is causally necessary for storing memories of aversive encounters, they provide correlational evidence that remapping occurs selectively under conditions where a stimulus occurs and is subsequently remembered rather than forgotten.

All experimental procedures were approved by the Chancellor’s Animal Research Committee of the University of California, Los Angeles, in accordance with the US National Institutes of Health (NIH) guidelines, protocol #2017-038. Raw data files and Matlab analysis code are openly available at https://github.com/tadblair/tadblair or https://doi.org/10.5068/D1ZT2S.

Source data and code for reproducing the figures are available at: https://github.com/tadblair/tadblair or https://doi.org/10.5068/D1ZT2S.

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Decision letter after peer review:

Thank you for submitting your article "Disruption of place cell remapping by scopolamine during aversive learning" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Liset M de la Prida as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Laura Colgin as the Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: Alexandra T Keinath (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

This paper describes results obtained from multi-cellular imaging of CA1 cells using large-field-of-view miniscopes in rats performing a shock avoidance task. By exploiting behavioral (barriers) and pharmacological (scopolamine) manipulations, the authors explore cell remapping dynamics during aversive learning. We very much value using large-field-of-view miniscope imaging to provide place cell data from rats, thus favoring inter-species comparisons. We also appreciate the inclusion of an appropriate set of control analyses and experiments to exclude potential confounds, especially when it comes to comparison between groups. While all reviewers agreed that the work will be of interest, there were also some concerns requiring substantial revision.

A point of discussion was whether the results of scopolamine are novel and specific enough to support claiming a direct effect on memory processes. There were also concerns regarding additional methodological controls which are required. We feel they can be addressed with additional analyses and experiments. In a consultation session, we agreed the following revisions are required before a definitive recommendation can be made:

1) Control experiments for scopolamine are required. These include:

a) A control is needed to show that the injection procedures do not impair general behaviour (e.g. motivation, attention, level of stress) as well as other forms of learning;

b) Consider effects in the absence of shock learning. To be able to claim that the effects of scopolamine are specific to aversive learning, a control with either no learning or appetitive learning (e.g. of a reward location, which also involves place field reorganization in some cases) would be useful. We feel that acknowledging the systemic/brain-wide/unspecific effect of scopolamine is not enough and you should provide some additional evidence of specificity.

c) Consider behavioral side effects of a systemic approach. Similarly, consider that functional effects of scopolamine (power and coordination of theta oscillations brain-wide) can additionally provide an explanatory value of the effects. Some of these are discussed but some others need support.

2) Additional control analyses are required, including:

a) Population vector analysis should be tested against shuffled distributions.

b) Population-level analysis in terms of the percentage of cells meeting place-cell criteria across manipulations; the equivalency of place cell measures when including all principal cells, not just those meeting (same-session) pre-selection criteria.

c) There are also some issues with the different pre-/post-training timing (8 days vs 6 days after pre-training) used in remapping effects with/without scopolamine that require clarification.

3) Clarification regarding LFOV:

a) Using large GRIN lenses may bring undesired histological damage and we wonder whether flattening the dorsal hippocampus may have consequences on functional readouts.

b) Given improvements in LFOV imaging with your approach, we wonder whether center/periphery ROI imaging may be or may not be affected. Given individual variability of imaging ROIs per rat, we would like to see this more carefully addressed.

4) Regarding impact and novelty, you may consider the following suggestions:

a) We discussed whether the above revisions may offer a chance to reinforce the novelty of your observations, by presenting pharmacological and behavioral (barriers) experiments as manipulations to better focus on the study of place cell remapping dynamics during aversive learning in rats. Actually, the abstract poorly integrates barrier results, which we feel should be mentioned. The authors may consider whether by highlighting/refocusing around some of these angles their manuscript would gain additional impact and broader interest.

b) Consider also tuning the title accordingly if required. Please, note that the title and/or the abstract should provide an indication of the biological system under study.

c) We also discussed whether using LFOV imaging in rats is an important addition to your paper and we would ask you to consider expanding the value of the approach when it comes to imaging from larger brains such as in rats versus mice. We feel in addressing questions regarding GRIN lenses and image aberration you may find the opportunity to highlight this better.

Please see the comments from each reviewer for more details.

Reviewer #1 (Recommendations for the authors):

Here is a list of comments for the authors to improve their work:

1. The body of the analysis is centered on the evaluation of population vector correlation matrices between behavioral phases and conditions. To build them, the authors rely on tuning curve heatmaps calculated from place cells in a reference condition (pre). One major problem with population tuning curves is that their typical 'diagonal' shape is very sensitive to noise so all curves and derived analysis should be tested against shuffled distribution as well. This affects data in Figure 2H,I; Figure 3D-F; Figure 4B,C.

2. The authors nicely control for their main figure analysis using the subset of scopolamine-treated rats that retained avoidance, but they do not provide data on the similarly important group of drug-free rats that DO NOT retain avoidance. They may help to provide additional controls for all main figure analyses as well. In addition, the paper would benefit from examining whether remapping indices can explain the behavioral performance of all rats, without resorting to categorizing them by performance level (i.e. using correlation analysis and/or predictive model analysis).

3. Using large GRIN lenses for large-field-of-view is a major strength of the paper when applied to imaging from the rat hippocampus. However, this can yield undesired histological damage. For instance, pushing the lens against the alveus for image flattening results in a reduction of the stratum oriens and atrophy of basal dendrites. This is inevitable and should not be considered by the authors as a criticism, but worth mentioning/controlling for effects. Are any of the behavioral and/or functional readouts correlated with some histological damage?

4. Similarly, there is natural variability in imaging from cells at the center/periphery of the GRIN, which differ in aberration effects. Since there is a different contribution across animals another useful control is to evaluate the consistency of conclusions for data obtained from center/periphery within and between animals. This would also help to set standards for the field, especially for LFOV imaging. Importantly, there is poor information on how the ROIs are defined, what methods are used for segmentation and how imaging from different sessions are treated (same ROIs, different ROIs, etc…), and what signals are evaluated dF/F with/without denoising, models of spike inference, etc…

Reviewer #2 (Recommendations for the authors):

Here are some detailed cpmmrnts.

1) Please add page and line numbers to ease review.

2) Given that several of the rats did the drug-free shock learning twice, how were these data analysed? Was only one of the sessions per rat chosen to contribute to the analysis, if yes, how?

3) Was there an influence of the order of sessions on the results (e.g. scopolamine during the first shock session, the second one, after a barrier session or not)?

4) Any analysis of the number of trials, if comparing across sessions of different durations, should be done on a number of trials/minute to allow for cross-sessions comparisons (e.g. Sup Figure 2 A).

5) Analysis of remapping: remapping is not the same as instability. It corresponds to a consistent activation of place fields in specific locations, that change (in a consistent manner) in a different condition, with the activity pattern, mostly reinstated when coming back to the original condition. Otherwise, changes in place cell firing that are not consistent or reproducible are considered drift or instability of the spatial firing. It is unclear if the current paradigm and analysis tests remapping and not simply instability.

6) In the 'Scopolamine does not disrupt place cell responses to shock' section: individual place cells are considered to 'respond' to the shock if their activity increases during entry into the shock zone. However, place cells can also respond by decreasing their activity, or even changing their place field shape or location, but this is not analysed.

7) Given that place cells can modulate their firing spontaneously with time (mentioned by the authors), any analysis of place cells between two different conditions where time has elapsed should have as a control a similar comparison, without the parameter of interest being changed, but with approximately the same amount of time passed or at least number of sessions (as the authors do in one of their analyses).

8) Nomenclature: In general, it would be good to avoid the use of abbreviations as much as possible, including in the figures, to help readability. Also, the different terms used (mostly condition or session names) can be confusing and there may be errors in figures or legends that make the interpretation difficult. The use of pretraining, training, and post in some instances, but pre10 post 5 in others (within the same session), is also a bit confusing. Perhaps the 10 min part of the shock training sessions that is pre-shock should be called the normal session and then the shock session would be called the shock session (or barrier session), without lumping both in the same session. Also, there are 2 forms of training: training to choose the shortest path, then training of the shock – and then extinction of the shock learning. Perhaps the authors could find a more intuitive and consistent way to name their sessions. What is 'post-extinction' (e.g. in 'post-extinction CA1 population vectors)? Is it referring to the activity during the extinction sessions? Or during the sessions that followed the extinction sessions, which according to Figure 2B will always be a shock session? It seems that this is sometimes called post-training (e.g. Figure 1J) and sometimes post-extinction (e.g. Figure 1J, legend). Is the place field recurrence rate (Figure 2G) the same as place field recurrence ratio (in results)? Do subsampled and down sampled mean the same here?

9) Related to this, in several instances the axis labels or legends of a figure are not self-sufficient and could be enhanced with more information about the measure that is shown (e.g.: Figure 1J: how is %baseline computed?).

10) The graph in Figure 1B seems to show that after each shock session, the rats have 1 extinction session. But in the main text, it is said that 'rats continued to run standard sessions on the maze every 48h until they reached the avoidance extinction criterion", which seems to assume that this would take several sessions. It seems that the graph should be adapted to reflect how many sessions were run. It is not clear what happens after the barrier sessions – do the rats move on to the shock learning sessions immediately? Does the '3s' mean that they do instead of the barrier session 3 times, or maybe extinction sessions?

11) It is a bit unclear what the -48/+48 measure means on some of the figure axes and in text. Does that mean that what is compared is data from 4 days apart? Or just 2 days apart? If it's the latter, shouldn't the measure be 0-48h or -24/+24?

12) Rejecting specific trials from the analysis does not change the behaviour of the rats during data collection; it only makes the analysis more balanced. The sentence "This assured that rats were behaving as similarly as possible during data collection in all sessions" should be rewritten to reflect this.

13) Figure 2E could show proportions out of the total number of putative pyramidal cells analysed, not just out of detected place cells, to see if the percentage of active place cells changes.

14) Tuning curve 'sequences' (showing the tuning curves of all cells ordered according to peak firing) are used in many of the plots, but it is unclear what information to take from them. Reorganizing the figures to emphasize the quantification of the results might be useful and perhaps removing some of the sequence plots unless they convey a specific message or can be used as an example.

15) Related to this, most of the figures are really small. Focusing on the ones that provide quantitative results (i.e. less 'tuning curves' plots) and making those bigger would probably help the reader.

16) Descriptions of some specific procedures could be added in the methods (listed in no specific order):

a) How were the beeline trials selected?

b) How were putative spikes extracted/reconstructed from the calcium imaging signal (deconvolution?)?

c) How was the injection procedure performed, and where were the rats kept after it? Were there any observable effects on the behaviour?

d) what was the weight/age of the rats at the start of the experiment?

e) what is the statistical significance threshold chosen?

f) how were the shocks delivered and calibrated? Did they not generate artefacts in the imaging?

17) The difference between past findings and the novelty of the present study could be explained better (for example, Sun et al. 2021 seems very relevant to the current study but is practically not discussed, also, Wu et al. (2017) [Hippocampal awake replay in fear memory retrieval. Nature Neuroscience 20, 571-580] and Girardeau et al. (2017) [Hippocampal awake replay in fear memory retrieval. Nature Neuroscience] seem like they should be discussed).

18) How were the A>0.6 threshold and A<0.31 threshold chosen?

19) The authors have selected for analyses of the 'control' (non-scopolamine) group only rats that learn to avoid the shock zone, and for analyses of the 'test' (scopolamine) group the rats that do not learn. Possibly related to this, it seems that the different groups have different behaviours in the pre-scopolamine session. I believe this is not the right approach; instead, if anything, the groups that are going to be compared should be equalized in as many parameters as possible at least prior to the manipulation of interest. If anything, the variability within each group should be used to assess the correlation between remapping/ instability of place cells and performance.

Reviewer #3 (Recommendations for the authors):

On the whole, I very much enjoyed reading this work, I found the results to be quite interesting and the presentation to be clear. I have only one question that can be addressed with further analysis. An essential claim of the manuscript is that the spatial codes measured during the drug-free and scopolamine shock sessions are equivalent in terms of within-session quality (and I appreciated all of the subsampling controls to match gross behavioral measures), yet I think this is only shown to be the case for 'place cells' which were preselected on the basis of various within-session measures. Can you confirm that: (1) the percentage of cells meeting place-cell criteria is equivalent across the two manipulations (not just the raw number of cells), and that (2) the equivalency of these measures holds when including all principal cells, not just those meeting (same-session) preselection criteria? I would be convinced about this claim if this were the case.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

The manuscript has been improved but there are some remaining issues that need to be addressed. Please, check the reviewers' comments and correct/make changes to address the remaining comments. Regarding R2 comments (previous comment 6) asking for additional analysis, please feel free to make a decision on whether this can be addressed textually.

Reviewer #2 (Recommendations for the authors):

Hippocampal place cell remapping occurs with memory storage of aversive experiences.

Tracking no: 29-05-2022-RA-eLife-80661R1

The scientific approach and interpretation of this revised manuscript have been substantially updated (mostly in the introduction and discussion) and appear much more straightforward and supported by the results. The authors have answered most of my comments and added a behavioural-only control for the injection procedure, which is very useful (although the results for the control group might need some clarification, see comment below). Overall, I find the manuscript to be much improved and the results very interesting.

Comments related to previous comments:

Previous Comment 4: Normalizing trial counts: Currently, the data shown in Figure 2 – supplement 2 in the 'trn' group is taken from 10 minutes of behaviour, while data in the other groups are obtained from 15-minute sessions. Thus, the figure gives the impression of the trial number decreasing between the pre and trn sessions, but this is due (at least partially) to the shorter session duration for trn. This is why I was suggesting using trials/min in order to see if the rats still run fewer trials for an identical duration. If the authors prefer to keep the absolute number of trials as a measure, I suggest adding in the figure itself a clear mention of the duration of data included in each group to avoid misunderstandings.

Previous Comment 5 Analysis of remapping vs instability: I believe the authors have actually done an analysis that answers this, by computing the within-session correlation of rate maps (showing that the cells are still spatially stable) in Figure 2I, by showing that the spatial information is similar between the pre and trn sessions even in the scopolamine condition, together with computing the pre vs post correlations; thus no action is needed.

Previous Comment 6 Response to shock by increased firing vs decreased firing: My suggestion would be to detect all active place fields contacting the shock zone in the pre10 session part, and analyze their firing in the post5 or subsequent session part. Using an active place field should prevent the low baseline problem described by the authors.

Previous Comment 16.e Choice of significance threshold: Sorry if the previous comment was unclear – I meant that the methods should specify which is the threshold for statistical significance chosen to be used throughout the manuscript to decide when a test result that produces a p-value is deemed significant vs not, e.g. 'tests were considered significant at p<0.05'.

New Comment 1 (NC1): Thank you for adding a behavioural control with injection of saline. I have some comments related to this new figure (Figure 1 – Supplementary figure 1):

a) Is data in the 'Shock' session from the entire 15 min or only the first 10 min pre-shock? I recommend showing separately pre10 and post5 to get a better understanding of the effects.

b) If all the data were included: why is it that the saline rats do not seem to avoid the shock zone during the shock session (compare pre and shock data in B or C)? This should be discussed in the main text.

c) Separating the data in the graph would also allow us to replicate the effect seen in the implanted rats where scopolamine rats avoid the short path even before the shock session. Does this effect underlie an increase in impulsivity, or impairment of decision-making, possibly linked to a decrease in general attention? Are such side-effects of the scopolamine known? Perhaps these types of possible side effects of the scopolamine could be added to the relevant discussion (e.g. in around L 596).

d) Ideally, some measure of general activity (average speed or total distance covered for the whole session, not just included trials) should be shown in the same way as the existing figures to further assess the effects of the scopolamine, injection procedures and shock on activity.

e) Why is the 'shock' session not called 'trn' as in Figure 2 Supplement 2?

NC2: L 24, L 52 (and also L 503) "We conclude that place cell remapping occurs in response to motivationally significant (rather than neutral) stimuli that are remembered rather than merely perceived and forgotten"; "studies have shown that place cells remap in response to behaviorally significant events": this is partially correct, however, these sentences and the corresponding one in the discussion imply that only behaviourally significant events can cause place cell remapping. But place cells also remap in response to events of low/no behavioural significance, e.g. a change in the odour/colour of the environment (Anderson and Jeffery 2003, J Neurosci; Jeffery et al., 2003) or events of intermediary behavioural relevance like the introduction of barriers in the absence of a navigation task (Rivard et al., 2004, Journal of General Physiology, Muller and Kubie, 1987, J Neurosci). These studies generally observe partial remapping (of a sub-population of the place cells) while perhaps the remapping in the shock condition in the current study is more global (but to test this, additional analysis of place fields away from the shock zone would be necessary). For these reasons, I suggest reformulating/removing the references to "motivationally significant (rather than neutral) stimuli" to perhaps focus on the remembered vs non-remembered aspect. Perhaps the salience of an event influences the degree of remapping throughout the place cell population… but that hasn't really been demonstrated by the current study.

NC3: L508 +: "Hippocampal place fields tend to be preferentially concentrated at locations where rodents spend large amounts of time […]" : this is not always the case (see for example Hok et al., 2007, J Neurosci; Pfieffer, 2022, J Neurosci), and might depend on specific task demands and behavioural stereotypy (reviewed in Nyberg et al., 2022). I suggest adding a clarification that the goal overrepresentation phenomenon is not ubiquitous and might depend on the task and navigational strategy.

NC4: L 536 'indicating that place fields shifted towards and away from the shocked location in equal proportions': could the authors point to a result showing this, instead of fields, for example, changing their size or firing rate?

Essential revisions:

A point of discussion was whether the results of scopolamine are novel and specific enough to support claiming a direct effect on memory processes. There were also concerns regarding additional methodological controls which are required. We feel they can be addressed with additional analyses and experiments. In a consultation session, we agreed the following revisions are required before a definitive recommendation can be made:

1) Control experiments for scopolamine are required. These include:

a) A control is needed to show that the injection procedures do not impair general behaviour (e.g. motivation, attention, level of stress) as well as other forms of learning;

We have run an additional saline-only control group (along with additional scopolamine groups) to demonstrate that scopolamine does impair avoidance learning compared against saline-injected controls. As shown in the Supplement to Figure 1, rats receiving saline alone show significantly greater post-training avoidance of the short path than rats receiving scopolamine.

b) Consider effects in the absence of shock learning. To be able to claim that the effects of scopolamine are specific to aversive learning, a control with either no learning or appetitive learning (e.g. of a reward location, which also involves place field reorganization in some cases) would be useful.

We believe that the barrier control condition, in which rats were exposed to a neutral barrier rather than an aversive shock, is sufficient to address this concern. However, we agree with this and other reviewers that insufficient attention was given to this control in the original manuscript, so it is now mentioned in the abstract and considered more prominently in the introduction and discussion.

We feel that acknowledging the systemic/brain-wide/unspecific effect of scopolamine is not enough and you should provide some additional evidence of specificity.

We have added a paragraph to the discussion (ll. 665-678) in which it is explained why the main conclusions of our study (namely, that place cell cell remapping is related to storage of memories for aversive events) do not depend upon whether or not scopolamine’s pharmacological actions were localized to the hippocampus (as almost certainly they were not).

c) Consider behavioral side effects of a systemic approach. Similarly, consider that functional effects of scopolamine (power and coordination of theta oscillations brain-wide) can additionally provide an explanatory value of the effects. Some of these are discussed but some others need support.

These considerations have been thoroughly integrated into the discussion. We acknowledge that scopolamine likely affected hippocampal and non-hippocampal circuits (ll. 665-678) and discuss the drug’s acute effects upon behavior and place cell activity (ll.561-612), including citation of prior work on how mAChRs modulate theta oscillations (ll.580-589).

2) Additional control analyses are required, including:

a) Population vector analysis should be tested against shuffled distributions.

New analyses show that all of the effects reported in the paper are abolished when the analyses are performed on shuffled data (Supplement 7 to Figure 2; Supplement 4 to Figure 3). Running this control analysis helped us to identify a minor flaw in the population vector correlation metric from the original manuscript (see reply to referee #1 comments below); this flaw has been corrected throughout the main text and figures by using a new population vector correlation metric referred to as place tuning stability (S). All previously reported effects survive the correction of converting to this slightly modified correlation measure.

b) Population-level analysis in terms of the percentage of cells meeting place-cell criteria across manipulations; the equivalency of place cell measures when including all principal cells, not just those meeting (same-session) pre-selection criteria.

Percentage of cells meeting place cell criteria are now reported in Figure 2D (right graph) and 3C (middle graph).

c) There are also some issues with the different pre-/post-training timing (8 days vs 6 days after pre-training) used in remapping effects with/without scopolamine that require clarification.

This appears to be a reference to an issue raised in a comment from referee #2. As explained in our reply to that comment below, we have controlled for this; the amount of time that elapses between sessions is identical for all analyses in Figure 2 (48 h) and very nearly so for all analyses in Figures 3 and 4, where all but 3 rats had identical intervals of 8d.

3) Clarification regarding LFOV:

a) Using large GRIN lenses may bring undesired histological damage and we wonder whether flattening the dorsal hippocampus may have consequences on functional readouts.

We agree that the issue of tissue compression is a concern for GRIN lens experiments, but no more so for our current study than for numerous other studies that have used similar methods in mice and rats. We do not convinced that histological damage can be quantified in a reliable way from the micrographs, but we have acknowledged this issue by adding a sentence to the Results section (ll. 151-154):

“Although the GRIN lens caused some flattening and compression of stratum oriens (Supplementary Figure 1), we do not believe this caused significant disruptions of CA1 activity since spatial tuning properties of place cells were quite similar to those reported in prior studies of rats without lens implants.”

b) Given improvements in LFOV imaging with your approach, we wonder whether center/periphery ROI imaging may be or may not be affected. Given individual variability of imaging ROIs per rat, we would like to see this more carefully addressed.

Supplement 3 to Figure 2 now shows how spatial tuning and between-session recurrence of place cells depends upon the size (area in pixels) and eccentricity (distance from lens center) of cell contours in the imaging plane. Although there are small statistically significant effects of contour size and eccentricity upon the percentage of cells classified as place cells (and also on the probability that a place cell will recur from one session to the next), we not believe that these small effects or are of much interest or that they are likely to have impacted the outcome of our other analysis, for reasons discussed in the caption.

4) Regarding impact and novelty, you may consider the following suggestions:

a) We discussed whether the above revisions may offer a chance to reinforce the novelty of your observations, by presenting pharmacological and behavioral (barriers) experiments as manipulations to better focus on the study of place cell remapping dynamics during aversive learning in rats. Actually, the abstract poorly integrates barrier results, which we feel should be mentioned. The authors may consider whether by highlighting/refocusing around some of these angles their manuscript would gain additional impact and broader interest.

b) Consider also tuning the title accordingly if required. Please, note that the title and/or the abstract should provide an indication of the biological system under study.

c) We also discussed whether using LFOV imaging in rats is an important addition to your paper and we would ask you to consider expanding the value of the approach when it comes to imaging from larger brains such as in rats versus mice. We feel in addressing questions regarding GRIN lenses and image aberration you may find the opportunity to highlight this better.

We are grateful for these suggestions and have made structural revisions to address them. The abstract (as well as the introduction and discussion) now address the barrier result and its importance for interpreting the findings. The title, introduction, and discussion have been thoroughly revised to shift emphasis away from implying that the scopolamine effects were end-goal of the study, and toward depiction of the scopolamine manipulation as a means to the more fundamental end of elucidating the role of remapping in storing memories of aversive experiences.

Please see the comments from each reviewer for more details.

Reviewer #1 (Recommendations for the authors):

Here is a list of comments for the authors to improve their work:

1. The body of the analysis is centered on the evaluation of population vector correlation matrices between behavioral phases and conditions. To build them, the authors rely on tuning curve heatmaps calculated from place cells in a reference condition (pre). One major problem with population tuning curves is that their typical 'diagonal' shape is very sensitive to noise so all curves and derived analysis should be tested against shuffled distribution as well. This affects data in Figure 2H,I; Figure 3D-F; Figure 4B,C.

The requested controls against shuffled distributions are now reported in Supplement 7 to Figure 2 and Supplement 4 to Figure 3, which show results after circularly shifting inferred spikes against position tracking data during each beeline trial. When deconvolved spikes were shuffled prior to the analysis, spatial tuning and remapping effects were abolished, as expected. It is worth noting that in the course of performing this control analysis, we became aware of a minor flaw in the population vector correlation measure that we used in the original manuscript; this flaw has been corrected in the revised paper without major impact upon the reported results. Briefly, the flaw was as follows. We previously measured population vector correlations by taking the median R value in bins near the diagonal of the population vector correlation matrix. However, when running our analyses on shuffled distributions, we realized that this measure can become large not only when place cells exhibit similar spatial tuning across sessions, but also when non-place cells fire at similar baseline rates across the entire track during both sessions. The proper control for this is to subtract away the mean off-diagonal r-values (which tend to be small for place cells and large for non-place cells) in each individual correlation matrix before taking the median. Making this correction to our metric produced almost no differences from the outcomes of our population vector correlation analyses, because the analyses were already being performed upon tuning curves of place cells that had been selected for their spatial firing properties, and thus for the fact that they already had near-zero mean r-values off the diagonal (hence, subtracting these near-zero means under the new measure had minimal effect upon analysis outcomes). It does become important to perform this correction in the requested analyses of population vector correlation matrices computed from shuffled spike trains, since these matrices can have large values on the diagonal in the absence of spatial tuning. We thank the referee for proposing the shuffle control and thereby helping us to improve our population vector correlation measure.

2. The authors nicely control for their main figure analysis using the subset of scopolamine-treated rats that retained avoidance, but they do not provide data on the similarly important group of drug-free rats that DO NOT retain avoidance. They may help to provide additional controls for all main figure analyses as well. In addition, the paper would benefit from examining whether remapping indices can explain the behavioral performance of all rats, without resorting to categorizing them by performance level (i.e. using correlation analysis and/or predictive model analysis).

In the original manuscript, the results for drug free rats that did not retain avoidance were included in Supplementary Figures 4-7 (in the revised manuscript, these results are shown in Supplement 8 to Figure 2 and Supplement 3 to Figure 3). However, the reviewer is correct to point out that these results were not previously mentioned in the main text. We have addressed this by adding sentences to the main text that describe results for drug free rats that did not retain avoidance along with results for the scopolamine rats that did retain avoidance.

3. Using large GRIN lenses for large-field-of-view is a major strength of the paper when applied to imaging from the rat hippocampus. However, this can yield undesired histological damage. For instance, pushing the lens against the alveus for image flattening results in a reduction of the stratum oriens and atrophy of basal dendrites. This is inevitable and should not be considered by the authors as a criticism, but worth mentioning/controlling for effects. Are any of the behavioral and/or functional readouts correlated with some histological damage?

We agree that the issue of tissue compression is a concern for GRIN lens experiments, but no more so for our current study than for numerous other studies that have used similar methods in mice and rats. We do not convinced that histological damage can be quantified in a reliable way from the micrographs, but we have acknowledged this issue by adding a sentence to the Results section (ll. 151-154):

“Although the GRIN lens caused some flattening and compression of stratum oriens (Supplementary Figure 1), we do not believe this caused significant disruptions of CA1 activity since spatial tuning properties of place cells were quite similar to those reported in prior studies of rats without lens implants.”

4. Similarly, there is natural variability in imaging from cells at the center/periphery of the GRIN, which differ in aberration effects. Since there is a different contribution across animals another useful control is to evaluate the consistency of conclusions for data obtained from center/periphery within and between animals. This would also help to set standards for the field, especially for LFOV imaging.

Supplement 3 to Figure 2 now shows how spatial tuning and between-session recurrence of place cells depends upon the size (area in pixels) and eccentricity (distance from lens center) of cell contours in the imaging plane. Although there are small statistically significant effects of contour size and eccentricity upon the percentage of cells classified as place cells (and also on the probability that a place cell will recur from one session to the next), we not believe that these small effects or are of much interest or that they are likely to have impacted the outcome of our other analysis, for reasons discussed in the caption.

Importantly, there is poor information on how the ROIs are defined, what methods are used for segmentation and how imaging from different sessions are treated (same ROIs, different ROIs, etc…), and what signals are evaluated dF/F with/without denoising, models of spike inference, etc…

We have addressed this by specifying the requested information more clearly in the methods section (ll. 808-840; as noted therein, exact parameters for the analysis may be found in the scripts provided on Github). We have also updated Figure 2A (upper right quadrant) to more clearly illustrate an example of how cell contours align across sessions.

Reviewer #2 (Recommendations for the authors):

Here are some detailed comments.

1) Please add page and line numbers to ease review.

The revision is paginated and line numbered.

2) Given that several of the rats did the drug-free shock learning twice, how were these data analysed? Was only one of the sessions per rat chosen to contribute to the analysis, if yes, how?

Only one rat (the female shown in the bottom row of Figure 2B) received two drugfree shocks, and the second drug-free shock session was not included in the analysis. To avoid confusion, the second drug-free shock session is no longer shown in Figure 2 B (since no data from this animal was used after the extinction session that is still plotted in the Figure). We thank the reviewer for catching this.

3) Was there an influence of the order of sessions on the results (e.g. scopolamine during the first shock session, the second one, after a barrier session or not)?

A ranksum test yielded no significant effect of training session order on results within either the drug free or scopolamine shock conditions; this is now indicated by ‘ns’ labels underneath the horizontal axis in Figure 1H, right panel.

4) Any analysis of the number of trials, if comparing across sessions of different durations, should be done on a number of trials/minute to allow for cross-sessions comparisons (e.g. Sup Figure 2 A).

It is not clear to us why the referee is recommending this. The goal of beeline trial filtering is to assure that behavior sampling of the short path (total time spent in each bin) is as similar as possible across analyzed sessions; this mandates equalizing the TOTAL NUMBER of beeline trials per session, not trials per unit time. Hence, the primary reason for showing panel A in Supplement 2 to Figure 2 (formerly Sup Figure 2A to which the referee refers) is to show what pre-subsampled trial counts look like when they are NOT normalized by time, and thereby demonstrate why it was necessary to equalize trial counts by subsampling beeline trials. If the graph were normalized by time, then the information the graph is intended to convey would be lost.

5) Analysis of remapping: remapping is not the same as instability. It corresponds to a consistent activation of place fields in specific locations, that change (in a consistent manner) in a different condition, with the activity pattern, mostly reinstated when coming back to the original condition. Otherwise, changes in place cell firing that are not consistent or reproducible are considered drift or instability of the spatial firing. It is unclear if the current paradigm and analysis tests remapping and not simply instability.

It is unclear what remedy, if any, the referee is requesting to address this concern.

6) In the 'Scopolamine does not disrupt place cell responses to shock' section: individual place cells are considered to 'respond' to the shock if their activity increases during entry into the shock zone. However, place cells can also respond by decreasing their activity, or even changing their place field shape or location, but this is not analysed.

Prior to submitting the original manuscript we did perform an analysis of inhibitory responses to shock. The problem with such an analysis is that statistical power for detecting excitatory versus inhibitory responses is highly asymmetric; the majority of place cells have a low baseline spike rate at the shocked location, so an immense number of trials would be required to detect a shock-evoked decrease of the spike rate from the already low baseline rate. Consequently, very few cell can be categorized as inhibited by shock, but whether this reflects an actual paucity of shock inhibition or a statistical power problem is impossible to determine.

7) Given that place cells can modulate their firing spontaneously with time (mentioned by the authors), any analysis of place cells between two different conditions where time has elapsed should have as a control a similar comparison, without the parameter of interest being changed, but with approximately the same amount of time passed or at least number of sessions (as the authors do in one of their analyses).

Yes, we have controlled for this. The amount of time that elapses between sessions is identical for all analyses in Figure 2 (48 h) and very nearly so for all analyses in Figures 3 and 4 (mode of 8d).

8) Nomenclature: In general, it would be good to avoid the use of abbreviations as much as possible, including in the figures, to help readability. Also, the different terms used (mostly condition or session names) can be confusing and there may be errors in figures or legends that make the interpretation difficult. The use of pretraining, training, and post in some instances, but pre10 post 5 in others (within the same session), is also a bit confusing. Perhaps the 10 min part of the shock training sessions that is pre-shock should be called the normal session and then the shock session would be called the shock session (or barrier session), without lumping both in the same session. Also, there are 2 forms of training: training to choose the shortest path, then training of the shock – and then extinction of the shock learning. Perhaps the authors could find a more intuitive and consistent way to name their sessions. What is 'post-extinction' (e.g. in 'post-extinction CA1 population vectors)? Is it referring to the activity during the extinction sessions? Or during the sessions that followed the extinction sessions, which according to Figure 2B will always be a shock session? It seems that this is sometimes called post-training (e.g. Figure 1J) and sometimes post-extinction (e.g. Figure 1J, legend). Is the place field recurrence rate (Figure 2G) the same as place field recurrence ratio (in results)? Do subsampled and down sampled mean the same here?

We sympathize with the referee’s confusion over these issues and have endeavored to clarify them throughout the revised manuscript.

9) Related to this, in several instances the axis labels or legends of a figure are not self-sufficient and could be enhanced with more information about the measure that is shown (e.g.: Figure 1J: how is %baseline computed?).

This has been clarified in the caption for panel J of Figure 1 which now reads:

“J) Left: Extinction curves over the first 3 post-extinction sessions; number of rewards earned on the short path is measured as a percentage of baseline (48 h before training; thin lines: individual rats, thick lines: per session median).”

10) The graph in Figure 1B seems to show that after each shock session, the rats have 1 extinction session. But in the main text, it is said that 'rats continued to run standard sessions on the maze every 48h until they reached the avoidance extinction criterion", which seems to assume that this would take several sessions. It seems that the graph should be adapted to reflect how many sessions were run. It is not clear what happens after the barrier sessions – do the rats move on to the shock learning sessions immediately? Does the '3s' mean that they do instead of the barrier session 3 times, or maybe extinction sessions?

This has been clarified by adding the following to the caption for panel B of Figure 1:

“The number of sessions in ACQ and EXT boxes varied per rat, depending on how many sessions it took individual subjects to reach behavioral criteria.”

11) It is a bit unclear what the -48/+48 measure means on some of the figure axes and in text. Does that mean that what is compared is data from 4 days apart? Or just 2 days apart? If it's the latter, shouldn't the measure be 0-48h or -24/+24?

4 days apart. To clarify this, the label “time from training session” has been added to the horizontal axis of Figure 1H.

12) Rejecting specific trials from the analysis does not change the behaviour of the rats during data collection; it only makes the analysis more balanced. The sentence "This assured that rats were behaving as similarly as possible during data collection in all sessions" should be rewritten to reflect this.

The statement has been rewritten as follows (ll. 884-887):

“This assured that rats were behaving as similarly as possibly during analyzed data segments from all sessions.”

13) Figure 2E could show proportions out of the total number of putative pyramidal cells analysed, not just out of detected place cells, to see if the percentage of active place cells changes.

Percentage of cells meeting place cell criteria are now reported in Figure 2D (right graph) and 3C (middle graph).

14) Tuning curve 'sequences' (showing the tuning curves of all cells ordered according to peak firing) are used in many of the plots, but it is unclear what information to take from them. Reorganizing the figures to emphasize the quantification of the results might be useful and perhaps removing some of the sequence plots unless they convey a specific message or can be used as an example.

We have retained the heatmap plots because they show al data from individual cells and therefore provide readers with important validation of the size and quality of the dataset that was analyzed in the other summary graphs.

15) Related to this, most of the figures are really small. Focusing on the ones that provide quantitative results (i.e. less 'tuning curves' plots) and making those bigger would probably help the reader.

We believe that the sizing of our figures conforms with current practice for publishing calcium imaging data in peer reviewed journals, but we will be happy to consider any figure reformatting guidance from the editorial staff if the paper is accepted for publication.

16) Descriptions of some specific procedures could be added in the methods (listed in no specific order): a) How were the beeline trials selected?

This is explained in great detail in the Methods section (ll. 879-944).

b) How were putative spikes extracted/reconstructed from the calcium imaging signal (deconvolution?)?

This is now explained in the Methods (ll. 834-840).

c) How was the injection procedure performed, and where were the rats kept after it? Were there any observable effects on the behaviour?

Injection methods are now explained in the Methods (ll. 794-798). Behavior effects are detailed in Results (ll. 112-146) and Discussion (ll. 561-612).

d) what was the weight/age of the rats at the start of the experiment?

This is now stated in the Methods (ll. 724-727).

e) what is the statistical significance threshold chosen?

It is unclear to what analysis this question is referring.

f) how were the shocks delivered and calibrated? Did they not generate artefacts in the imaging?

Shock delivery apparatus and procedures are now explained in the Methods (ll. 731-737). Shocks did not generate artefacts in the imaging. Unlike electrophysiological recordings, calcium imaging is not susceptible to shock artefacts. The housing of the miniscope is made of non-conductive plastic and is therefore electrically insulated from the rat and the shock current.

17) The difference between past findings and the novelty of the present study could be explained better (for example, Sun et al. 2021 seems very relevant to the current study but is practically not discussed, also, Wu et al. (2017) [Hippocampal awake replay in fear memory retrieval. Nature Neuroscience 20, 571-580] and Girardeau et al. (2017) [Hippocampal awake replay in fear memory retrieval. Nature Neuroscience] seem like they should be discussed).

We have added references to the Wu et al. (2017) and Girardeau et al. (2017) studies in the context of our discussion about how shock-induced remapping affects the spatial distribution of place fields (l. 522-24). We have also added new references to recently published work by Wirtshafter and Disterhoft (2022) and Ormond et al. (2023) that has come out during the time we have been working on revisions.

18) How were the A>0.6 threshold and A<0.31 threshold chosen?

As explained in the Methods (ll. 873-877), these values were chosen because they were the cutoff thresholds for the top and bottom quartiles, respectively, of the percentage of trials on which rats chose the short path.

19) The authors have selected for analyses of the 'control' (non-scopolamine) group only rats that learn to avoid the shock zone, and for analyses of the 'test' (scopolamine) group the rats that do not learn. Possibly related to this, it seems that the different groups have different behaviours in the pre-scopolamine session. I believe this is not the right approach; instead, if anything, the groups that are going to be compared should be equalized in as many parameters as possible at least prior to the manipulation of interest. If anything, the variability within each group should be used to assess the correlation between remapping/ instability of place cells and performance.

We report an analysis of correlation between remapping measures and behavioral performance in Panel H of Supplement 8 to Figure 2.

Reviewer #3 (Recommendations for the authors):

On the whole, I very much enjoyed reading this work, I found the results to be quite interesting and the presentation to be clear. I have only one question that can be addressed with further analysis. An essential claim of the manuscript is that the spatial codes measured during the drug-free and scopolamine shock sessions are equivalent in terms of within-session quality (and I appreciated all of the subsampling controls to match gross behavioral measures), yet I think this is only shown to be the case for 'place cells' which were preselected on the basis of various within-session measures. Can you confirm that: (1) the percentage of cells meeting place-cell criteria is equivalent across the two manipulations (not just the raw number of cells),

Percentage of cells meeting place cell criteria are now reported in Figure 2D (right graph) and 3C (middle graph).

and that (2) the equivalency of these measures holds when including all principal cells, not just those meeting (same-session) preselection criteria? I would be convinced about this claim if this were the case.

The within-session quality measures to which the referee is referring (place field width, spatial info, peak in-field firing rate, mean out-of-field firing rate) are measures that can only be applied to cells with verified spatial tuning, so we are unsure what the referee means by requesting that these measures be performed on “all principle cells…not just those meeting preselection criteria.”

[Editors’ note: what follows is the authors’ response to the second round of review.]

Reviewer #2 (Recommendations for the authors):

Hippocampal place cell remapping occurs with memory storage of aversive experiences.

Tracking no: 29-05-2022-RA-eLife-80661R1

The scientific approach and interpretation of this revised manuscript have been substantially updated (mostly in the introduction and discussion) and appear much more straightforward and supported by the results. The authors have answered most of my comments and added a behavioural-only control for the injection procedure, which is very useful (although the results for the control group might need some clarification, see comment below). Overall, I find the manuscript to be much improved and the results very interesting.

Comments related to previous comments:

Previous Comment 4: Normalizing trial counts: Currently, the data shown in Figure 2 – supplement 2 in the 'trn' group is taken from 10 minutes of behaviour, while data in the other groups are obtained from 15-minute sessions. Thus, the figure gives the impression of the trial number decreasing between the pre and trn sessions, but this is due (at least partially) to the shorter session duration for trn. This is why I was suggesting using trials/min in order to see if the rats still run fewer trials for an identical duration. If the authors prefer to keep the absolute number of trials as a measure, I suggest adding in the figure itself a clear mention of the duration of data included in each group to avoid misunderstandings.

As explained in our reply to the referee’s original comment, retaining the nonnormalized scale is essential for conveying the information provided by the figure; we agree with the referee’s concerns about lack of clarity and have made the recommended changes by adding data durations to x-axis labels of the figure, along with a clarification of what these labels mean in the caption.

Previous Comment 5 Analysis of remapping vs instability: I believe the authors have actually done an analysis that answers this, by computing the within-session correlation of rate maps (showing that the cells are still spatially stable) in Figure 2I, by showing that the spatial information is similar between the pre and trn sessions even in the scopolamine condition, together with computing the pre vs post correlations; thus no action is needed.

Acknowledged.

Previous Comment 6 Response to shock by increased firing vs decreased firing: My suggestion would be to detect all active place fields contacting the shock zone in the pre10 session part, and analyze their firing in the post5 or subsequent session part. Using an active place field should prevent the low baseline problem described by the authors.

It would certainly be possible to skirt the problem of asymmetrical statistical power (noted in our prior reply) by performing such an analysis, but it is unclear to us that the results of such an analysis would be germane to the questions we are asking in the present study about whether shock responses are predictive of remapping responses. Analyzing inhibitory responses by the proposed method would only be possible for a subset of cells selected for the property of being active in the shock zone, a property that itself might be confounded with the dependent variable of interest: remapping. Moreover, some kind of inclusion threshold on statistical power would have to be formulated and justified to select cells by this criterion (the referee does not propose suggestions for how to do this). For these reasons, it is our view that the only question to which the proposed analysis could provide a meaningful answer would be “are there any place cells that show evidence of being inhibited by shock?” That question, although interesting, is not primary to the scope and focus of the present study.

Previous Comment 16.e Choice of significance threshold: Sorry if the previous comment was unclear – I meant that the methods should specify which is the threshold for statistical significance chosen to be used throughout the manuscript to decide when a test result that produces a p-value is deemed significant vs not, e.g. 'tests were considered significant at p<0.05'.

We have addressed this point by locating every statement about “significance” in the Results and Methods sections where threshold information was not provided in the text or figures; threshold information has been added on lines 215, 216, 235, 236, 460.

New Comment 1 (NC1): Thank you for adding a behavioural control with injection of saline. I have some comments related to this new figure (Figure 1 – Supplementary figure 1):

a) Is data in the 'Shock' session from the entire 15 min or only the first 10 min pre-shock? I recommend showing separately pre10 and post5 to get a better understanding of the effects.

We have clarified this by adding the duration of each session in minutes to the session labels above the plot in Figure 1 – supplementary figure 1B; the caption text has also been updated with the following text:

“shock session includes only data from the 10’ pre-shock period whereas all other days include data from the full 15’ session.”

b) If all the data were included: why is it that the saline rats do not seem to avoid the shock zone during the shock session (compare pre and shock data in B or C)? This should be discussed in the main text.

As noted above (see reply to ‘a’) shock session data only includes the pre-shock period, so there is no inconsistency to address here.

c) Separating the data in the graph would also allow us to replicate the effect seen in the implanted rats where scopolamine rats avoid the short path even before the shock session. Does this effect underlie an increase in impulsivity, or impairment of decision-making, possibly linked to a decrease in general attention? Are such side-effects of the scopolamine known? Perhaps these types of possible side effects of the scopolamine could be added to the relevant discussion (e.g. in around L 596).

We assume that when the referee says “scopolamine rats avoid the short path even before the shock session” they mean before the shock STIMULUS (not “session”). It is indeed the case that both implanted and non-implanted scopolamine rats show reduced preference for the short path prior to shock. “Separating the data in the graph” is not necessary to see this; in the existing version of Figure 1 – supplementary figure 1 (panels B and C) it can be seen that on the shock day, scopolamine rats show a greatly reduced preference for the short path compared with saline-injected rats. New statistics have been added to the figure caption to show that this effect is significant.

d) Ideally, some measure of general activity (average speed or total distance covered for the whole session, not just included trials) should be shown in the same way as the existing figures to further assess the effects of the scopolamine, injection procedures and shock on activity.

We have now included the measure of median running speed during beeline trials for this data as well in Supplement to Figure 1A (bottom) and the caption has been revised to reflect this (L 1076):

“A) Top: Mann-Whitney U tests found that 48 hour retention of avoidance behavior did not differ for males versus females in the drug-free or scopolamine shock conditions. Bottom: Median beeline running speeds per session.”

e) Why is the 'shock' session not called 'trn' as in Figure 2 Supplement 2?

We have changed the label from ‘shock’ to ‘trn’ for consistency with figures in the main text.

NC2: L 24, L 52 (and also L 503) "We conclude that place cell remapping occurs in response to motivationally significant (rather than neutral) stimuli that are remembered rather than merely perceived and forgotten"; "studies have shown that place cells remap in response to behaviorally significant events": this is partially correct, however, these sentences and the corresponding one in the discussion imply that only behaviourally significant events can cause place cell remapping. But place cells also remap in response to events of low/no behavioural significance, e.g. a change in the odour/colour of the environment (Anderson and Jeffery 2003, J Neurosci; Jeffery et al., 2003) or events of intermediary behavioural relevance like the introduction of barriers in the absence of a navigation task (Rivard et al., 2004, Journal of General Physiology, Muller and Kubie, 1987, J Neurosci). These studies generally observe partial remapping (of a sub-population of the place cells) while perhaps the remapping in the shock condition in the current study is more global (but to test this, additional analysis of place fields away from the shock zone would be necessary). For these reasons, I suggest reformulating/removing the references to "motivationally significant (rather than neutral) stimuli" to perhaps focus on the remembered vs non-remembered aspect. Perhaps the salience of an event influences the degree of remapping throughout the place cell population… but that hasn't really been demonstrated by the current study.

On lines 24 and 502, we have followed the referee’s suggestion by changing the wording to read:

“…remapping occurs selectively under conditions where a stimulus occurs and is subsequently remembered rather than forgotten…”

We have retained existing wording on line 52 in the citation of prior studies showing that “place cells remap in response to behaviorally significant events” because we believe this wording is accurate and it is clearly not intended as a statement about what is demonstrated in the current study. We agree with the referee’s point that “behavioral significance” may not be a core prerequisite for remapping, but the existing wording of the citation is fully compatible with this, especially since the Introduction explains that remapping can occur with the mere passage of time and that the rate of remapping may be proportional to the rate at which episodic memories are being stored.

NC3: L508 +: "Hippocampal place fields tend to be preferentially concentrated at locations where rodents spend large amounts of time […]" : this is not always the case (see for example Hok et al., 2007, J Neurosci; Pfieffer, 2022, J Neurosci), and might depend on specific task demands and behavioural stereotypy (reviewed in Nyberg et al., 2022). I suggest adding a clarification that the goal overrepresentation phenomenon is not ubiquitous and might depend on the task and navigational strategy.

“tend to be” has been replaced with “are sometimes observed to be”

NC4: L 536 'indicating that place fields shifted towards and away from the shocked location in equal proportions': could the authors point to a result showing this, instead of fields, for example, changing their size or firing rate?

To better support this conclusion, we have added another supplementary figure (Figure 3—figure supplement 4) to quantify the field shifts.

Author details

1. Garrett J Blair

   Department of Psychology, UCLA, Los Angeles, United States

   Present address

   Center for Neural Science, New York University, New York, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   gblair@ucla.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2724-8914

2. Changliang Guo

   1. David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States
   2. Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
   3. Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, United States

   Contribution

   Conceptualization, Software, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Shiyun Wang

   Department of Psychology, UCLA, Los Angeles, United States

   Contribution

   Collection of supplementary behavioral data

   Competing interests

   No competing interests declared

4. Michael S Fanselow

   1. Department of Psychology, UCLA, Los Angeles, United States
   2. Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, United States

   Contribution

   Conceptualization, Resources, Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3850-5966

5. Peyman Golshani

   1. David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States
   2. Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
   3. Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, United States

   Contribution

   Supervision, Funding acquisition, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

6. Daniel Aharoni

   1. David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States
   2. Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
   3. Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, United States

   Contribution

   Conceptualization, Resources, Software, Supervision, Funding acquisition, Validation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4931-8514

7. Hugh T Blair

   1. Department of Psychology, UCLA, Los Angeles, United States
   2. Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, United States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Writing – original draft, Project administration

   For correspondence

   tadblair@ucla.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8256-5109

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