NPAS4 refines spatial and temporal firing in CA1 pyramidal neurons

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1. 

   eLife

   Jul 2, 2026

   eLife Assessment

   This important study shows that NPAS4, a gene that is switched on by neural activity, enhances the spatial and temporal precision of hippocampal neurons during navigation. These findings, based on selective and sparse gene deletion, are supported by convincing evidence. However, the experiments were performed entirely in animals exposed to long-term environmental enrichment, which leaves open the question of whether the same effects would emerge under standard housing conditions. This study will be of interest to neuroscientists studying neuronal circuits and spatial coding.

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2. 

   eLife

   Jul 2, 2026

   Reviewer #1 (Public review):

   Summary:

   NPAS4 is an activity-dependent transcription factor that regulates inhibitory synapses onto active pyramidal neurons. In this study, the authors examined whether this molecular mechanism influences neural coding in awake animals. To accomplish this, they generated a sparse, CA1-specific NPAS4 knockout in mice and compared knockout neurons with neighboring wild-type neurons recorded from the same animals during navigation. They found that, although neurons lacking NPAS4, which received diminished somatic inhibition and enhanced dendritic inhibition, still encoded location, their spatial firing was less precise: place fields were broader and less stable, showed weaker firing within the field, and exhibited more firing outside the field. KO neurons also exhibited poorer temporal organization with …

   Reviewer #1 (Public review):

   Summary:

   NPAS4 is an activity-dependent transcription factor that regulates inhibitory synapses onto active pyramidal neurons. In this study, the authors examined whether this molecular mechanism influences neural coding in awake animals. To accomplish this, they generated a sparse, CA1-specific NPAS4 knockout in mice and compared knockout neurons with neighboring wild-type neurons recorded from the same animals during navigation. They found that, although neurons lacking NPAS4, which received diminished somatic inhibition and enhanced dendritic inhibition, still encoded location, their spatial firing was less precise: place fields were broader and less stable, showed weaker firing within the field, and exhibited more firing outside the field. KO neurons also exhibited poorer temporal organization with weaker coupling to theta oscillations and reduced phase precession, two signatures of precise spike timing in the hippocampus. Overall, the study suggests that NPAS4 links the balance of somatic and dendritic inhibition to the quality of circuit-level coding by refining the spatial and temporal precision of neuronal firing.

   Strengths:

   Using a sparse CA1-specific knockout, the authors compared NPAS4-deficient neurons with neighboring wild-type neurons within the same animal and network. This is a significant advantage because it minimizes confounding factors arising from global circuit disruption, providing a clearer comparison of genotypes. Furthermore, the rigorous optogenetic tagging strategy used to distinguish KO from WT neurons in vivo makes the single-cell comparisons much more convincing. Electrophysiological recordings from intermingled WT and KO neurons enable precise spike-timing measurements relative to a shared local field potential, which would be challenging to obtain with calcium imaging.

   Weaknesses:

   Rather than an acute manipulation, the authors rely on a chronic, sparse knockout, and NPAS4 had been deleted for at least one month before recording. Consequently, while the paper demonstrates a robust long-term phenotype, it is less definitive about the immediate causal sequence by which NPAS4 induction alters inhibition and reshapes spatial and temporal coding. Furthermore, the study focuses on single-neuron coding during navigation and does not test whether the observed degradation in coding precision leads to corresponding impairments in learning or memory in the same animals. In the discussion, the authors suggest that NPAS4 may be especially important for ripple-associated activity during sleep; however, the paper does not test this possibility.

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3. 

   eLife

   Jul 2, 2026

   Reviewer #2 (Public review):

   Summary:

   The manuscript by Payne and colleagues examines how cell-autonomous loss of the activity-dependent transcription factor NPAS4 reshapes spatial and temporal coding in CA1 pyramidal neurons of behaving mice. The work builds on the Bloodgood lab's established framework in which NPAS4 reorganizes inhibition along the somatodendritic axis of CA1 pyramidal cells, principally by regulating CCK+ basket cell synapses, and asks whether this transcriptionally driven reconfiguration of inhibition propagates into the spike-train statistics that underlie hippocampal function. The combination of sparse Cre delivery with channelrhodopsin-mediated optotagging in Npas4 fl/fl:Ai32 mice is technically elegant, as it permits within-animal comparisons of intermingled wild-type and knockout pyramidal neurons sharing a …

   Reviewer #2 (Public review):

   Summary:

   The manuscript by Payne and colleagues examines how cell-autonomous loss of the activity-dependent transcription factor NPAS4 reshapes spatial and temporal coding in CA1 pyramidal neurons of behaving mice. The work builds on the Bloodgood lab's established framework in which NPAS4 reorganizes inhibition along the somatodendritic axis of CA1 pyramidal cells, principally by regulating CCK+ basket cell synapses, and asks whether this transcriptionally driven reconfiguration of inhibition propagates into the spike-train statistics that underlie hippocampal function. The combination of sparse Cre delivery with channelrhodopsin-mediated optotagging in Npas4 fl/fl:Ai32 mice is technically elegant, as it permits within-animal comparisons of intermingled wild-type and knockout pyramidal neurons sharing a common LFP, which is a significant analytical advantage for spike-timing analyses and for controlling network-level confounds. The reported phenotype is internally consistent and converges on a coherent story: knockout neurons exhibit broader and less stable place fields, lower signal-to-noise within fields, increased out-of-field activity, weaker theta-phase coupling, and shallower phase precession slopes, with the temporal deficits at least partly explained by enlargement of the spatial receptive field.

   Strengths:

   Several aspects of the work deserve explicit recognition. The validation of the optotagging strategy is thorough, including the high-power stimulation control to corroborate WT classification and the post hoc histological alignment of GFP+ density with electrophysiologically identified KO fractions. The decision to test NPAS4 function in adult mice maintained in long-term enriched environments addresses an important gap, since most prior work has focused on juveniles or short-term induction paradigms. The acute slice recordings recapitulating the somatodendritic inhibition phenotype reassure the reader that the in vivo measurements are interpreted against a known synaptic substrate. The analytical framework, especially the difference maps across epochs and the linear regression decomposition of phase precession slope into genotype, field size, and theta modulation strength, is rigorous and goes beyond simple group-level comparisons. The conceptual contribution, namely the demonstration that an activity-dependent transcription factor can be tied to single-neuron coding properties in vivo, is meaningful, although it is fair to note that the direction of the effect, given that the CCK to place cell link and the NPAS4 to CCK link have each been established in prior independent studies, is largely along the lines one would predict.

   Weaknesses:

   The most consequential concern, in my view, is the experimental context in which the entire study is conducted. Every animal is housed in an enriched environment for two to three months, and Figure 1A itself shows that NPAS4 expression in CA1 is essentially undetectable in standard-environment conditions and only emerges with enrichment. This raises the question of whether the manuscript is in fact describing the function of NPAS4 in general, or the function of NPAS4 specifically as recruited by chronic enrichment. The paper, in its current framing, elides this distinction and presents the EE state as if it were the baseline, which it is not. EE is known to alter hippocampal connectivity, the dynamics of place cell ensembles, and the expression of many activity-dependent genes; the CCK to pyramidal cell connectivity that the authors invoke as the mechanistic anchor is also dense in standard housing, so the absence of detectable NPAS4 in SE conditions raises the further conceptual problem of how NPAS4-negative neurons would normally be innervated by CCK+ basket cells in the first place. A direct comparison of WT and KO neurons in standard-environment animals, even on a smaller scale, would discriminate between two very different interpretations, namely that NPAS4 has a constitutive role in tuning CA1 firing versus that it is specifically engaged by enrichment-driven activity and contributes to an EE-specific reorganization of coding. Recent work, including Chiaruttini and colleagues (2025), reports baseline NPAS4 expression in CA1, so the SE result in Figure 1A may itself underestimate normal expression and deserves further scrutiny. Without an SE comparison, the generality of the conclusions cannot be assessed, and the title and abstract risk overstating the scope of the findings, particularly when one considers that NPAS4 is also induced by contextual fear conditioning and other paradigms, which would predict context-specific effects rather than a uniform refinement function.

   A closely related concern is the meaning of the knockout itself. Even under EE, only a few percent of CA1 pyramidal neurons express detectable NPAS4 at any given moment (Figure 1A), yet the AAV strategy deletes the gene in 30 to 60 percent of pyramidal neurons. In effect, the majority of cells classified as KO in this study would not have been expressing the protein under the relevant conditions, so the population that is statistically driving the WT versus KO differences must include a non-trivial fraction of neurons in which the deletion has no protein-level consequence. This dilutes the expected effect and raises a more interesting biological question: are the observed phenotypes carried by the few KO neurons that would have expressed NPAS4, or do they emerge from a constitutive function of the gene that is broader than the IHC signal suggests? An additional, related possibility is that NPAS4 expression segregates non-uniformly across functional classes, for example, concentrating in cells with particular firing-rate or spatial-tuning profiles, in which case the "KO" label is binary at the level of the manipulation but graded at the level of biological consequence. Stratifying the KO population by some proxy of activity history, or relating the magnitude of the phenotype to per-cell measures of recent firing, would help address this. As written, the manuscript treats the KO designation as homogeneous, while the underlying biology is almost certainly not.

   A third concern, more conventionally statistical, is the treatment of cells as independent observations. The analyses rely almost uniformly on Kolmogorov-Smirnov tests applied to individual units pooled across animals, but cells recorded in the same animal share not only a common subject but a common network, since WT and KO neurons here are intermingled in the same CA1 microcircuit. Cell numbers per animal range widely, so a mixed-effects framework treating animal as a random factor, or a hierarchical bootstrap, would clarify which effects are robust against animal-level and session-level variability and protect against pseudo-replication. This concern is particularly acute for the smaller effects in Figure 2C-E, where the cumulative distributions overlap substantially, and the differences could plausibly be driven by a small number of mice or sessions. In several figures, the individual dots in supplementary panels are not labeled by animal or session, and that information would be useful for assessing how much of each effect is carried by which subset of the cohort.

   The absence of a Cre/ChR2 expression control is a separate gap. The comparison throughout the manuscript pits Cre+ ChR2+ neurons (NPAS4 KO) against neighboring non-transduced neurons (WT). This is internally elegant, but leaves open the possibility that part of the phenotype arises from chronic ChR2 expression or constitutive Cre activity rather than from NPAS4 loss, especially given that most of the readouts are subtle. A small companion cohort of Ai32 mice without the floxed Npas4 allele, injected with the same AAV and processed through identical optotagging and electrophysiology pipelines, would address this definitively and is, in my view, a near-essential addition.

   Several of the downstream phenotypes would benefit from stratified comparisons that hold first-order properties constant. Many of the downstream differences (stability across epochs, theta coupling, phase precession) could, in principle, be inherited from the upstream difference in firing rate, since the high-firing and high-spatial-information cells in the WT pool are likely contributing disproportionately to the group statistics. The authors do perform firing-rate-matched controls in Figure S4D-G, which is helpful, but the analysis should be extended in two ways: a parallel stratification by spatial information for the stability analyses in Figure 4, and matched comparisons of theta coupling (Figure 5) and phase precession (Figure 6) on neurons drawn from overlapping firing-rate and spatial-information distributions. The regression decomposition for phase precession is a step in this direction and shows that field size, not genotype, is the dominant predictor of slope; this finding, in my reading, deserves more prominent framing in the discussion than it currently receives, since it implies that the temporal precision phenotype is largely downstream of the spatial one rather than a parallel deficit.

   The place field stability analysis is interesting but somewhat under-analyzed. The authors show that KO fields shift toward the field entrance more rapidly than WT fields and propose that this reflects an accelerated or dysregulated Mehta-effect-like dynamic. The framing is attractive, but the analysis does not establish that the shifts are systematic in the same way the classical Mehta effect is. An alternative reading is that the elevated out-of-field firing creates spurious local maxima that the peak-finding procedure occasionally classifies as field shifts, especially when in-field firing is reduced. A control analysis using a fixed reference window around the original peak, rather than re-identifying the peak each epoch, would help distinguish a genuine plasticity-like shift from instability driven by noise. The behavior of the WT population in epoch 4 also raises a question: would the drift intensify over longer recording windows, and to what extent is the apparent drift imposed by the repetitive structure of the task itself, in which animals are effectively running on a constrained linear /circular track that may impose drift-like dynamics across the population independently of genotype?

   A final note on mechanism. The manuscript leans on prior work showing that NPAS4 regulates CCK+ basket cell synapses, and uses this as the mechanistic anchor for the coding deficits. The connection is reasonable but remains indirect within this study, since the authors do not measure CCK+ interneuron activity, perisomatic inhibition, or local circuit dynamics in the same animals. The discussion already acknowledges some of this, but the speculative framing of dendritic versus somatic inhibition contributions could be tightened, especially given that competing inhibitory sources (PV+ basket cells, axo-axonic cells, OLM interneurons) also shape the spatial and temporal features measured here. A more cautious mechanistic framing, distinguishing what is demonstrated from what is inferred from prior work, would be appropriate.

   In summary, this is an ambitious and technically demanding study that makes a meaningful contribution by linking activity-dependent transcriptional regulation of inhibition to the spatial and temporal organization of CA1 spike trains in awake, behaving mice. The within-animal optotagging design is a real strength, the phenotype is internally consistent across multiple coding metrics, and the conceptual implications for how experience tunes single-neuron coding are significant. The principal concerns, namely the unaddressed enrichment confound that pervades the entire dataset, the conceptual ambiguity around what a KO designation actually means at the cell level when only a small fraction of CA1 neurons express the protein, the statistical treatment of nested observations from a shared microcircuit, the missing transgene control, the absence of stratified comparisons by firing rate and spatial information for the secondary phenotypes, and the somewhat overreaching mechanistic framing of the discussion, are all addressable, and if handled carefully would substantially strengthen the manuscript. With these revisions, the work would be a valuable contribution to the literature on how the molecular memory of activity shapes circuit-level coding.

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4. 

   eLife

   Jul 2, 2026

   Author response:

   We appreciate the time and attention to our manuscript and the feedback from the reviewers, who were overall supportive of the work. Both reviewers validated the technical approach we used to differentiate the wild-type (WT) and knockout (KO) neurons noting: “The combination of sparse Cre delivery with channel rhodopsin-mediated optotagging in Npas4 fl/fl:Ai32 mice is technically elegant” and “the rigorous optogenetic tagging strategy used to distinguish KO from WT neurons in vivo makes the single-cell comparisons much more convincing.” Furthermore, they note the consistency of the reported results, stating: “The reported phenotype is internally consistent and converges on a coherent story”.

   Both reviewers also pointed out several concerns or points of improvement for the manuscript. Below, we first offer several …

   Author response:

   We appreciate the time and attention to our manuscript and the feedback from the reviewers, who were overall supportive of the work. Both reviewers validated the technical approach we used to differentiate the wild-type (WT) and knockout (KO) neurons noting: “The combination of sparse Cre delivery with channel rhodopsin-mediated optotagging in Npas4 fl/fl:Ai32 mice is technically elegant” and “the rigorous optogenetic tagging strategy used to distinguish KO from WT neurons in vivo makes the single-cell comparisons much more convincing.” Furthermore, they note the consistency of the reported results, stating: “The reported phenotype is internally consistent and converges on a coherent story”.

   Both reviewers also pointed out several concerns or points of improvement for the manuscript. Below, we first offer several scientific and methodological clarifications that we believe resolve a number of the reviewers' concerns. We then outline which remaining points we plan to address through revision, and which fall outside the scope of the current study.

   Scientific Clarifications:

   Request for a standard housing control. Both of the reviewers brought up the long-term enrichment paradigm (EE) we opted to use for this study and expressed interest in seeing data from standard housed (SE) animals. This is an approach the lab has taken in its slice physiology work [1-3], where comparing EE and SE conditions has revealed important differences between cellular phenotype. However, the in vivo experiments described here differ in a key way: obtaining these recordings requires extensive handling, training, and daily transport between the vivarium, home cage, and behavior room. These experimental steps themselves constitute the kind of novel, salient experience known to induce NPAS4, making a true SE comparison unattainable within this paradigm. In our experiment, mice were housed in EE as a supplemental, well-established strategy to induce NPAS4 in CA1 pyramidal neurons but we believe the behavior alone would be sufficient. We will describe this more clearly in the text of the manuscript.

   Consistent with this view, place fields recorded from wild-type mice in other studies using SE but undergoing comparable handling and training procedures, are similar in size, spatial information, and stability to the WT place fields we reported here [4,5]. As part of our revisions, we will consider statistical comparisons between our WT neurons and those reported in other studies to quantitatively assess whether a difference exists.

   More broadly, we note that the existing literature on NPAS4 induction does not, to our knowledge, establish a baseline level of NPAS4 expression in CA1 pyramidal neurons in the complete absence of behavioral experience. Reports of NPAS4 expression in CA1 have generally relied on animals exposed to some form of salient or novel experience [3,6,7], consistent with our framework that NPAS4 induction reflects behaviorally-driven activity rather than a constitutive baseline.

   Expression profile of NPAS4. Reviewer #2 brought up a concern about the extent of the NPAS4 expression, referring to the IHC results in Figure 1A stating: “Even under EE, only a few percent of CA1 pyramidal neurons express detectable NPAS4 at any given moment (Figure 1A), yet the AAV strategy deletes the gene in 30 to 60 percent of pyramidal neurons. In effect, the majority of cells classified as KO in this study would not have been expressing the protein under the relevant conditions.” We wish to clarify two points here. First, in the experimental paradigm used to obtain the IHC results, mice were exposed to enrichment for only 90 minutes while in the in vivo physiology paradigm, mice were housed in an enriched environment (with frequent toy changes to ensure novelty) for weeks. Thus, NPAS4 is almost certainly expressed in a much larger percentage of WT neurons in mice that were kept in chronic enrichment and used for the in vivo studies. Second, while the NPAS4 protein is only expressed in cells for several hours following neuronal activity, it initiates an inhibitory synapse phenotype that persists long-term. Thus, even though a small percentage of neurons are NPAS4+ in the IHC results, it is likely that a much larger percentage of them have expressed NPAS4 in the past and now show the inhibitory synapse phenotype. Evidence for this comes from the slice physiology results in Figure 1C (and see similar results from adolescents [1-3]) in which animals were housed in enrichment long-term and differences between inhibition persisted in nearly every WT/KO comparison.

   We also recognize the related possibility that NPAS4 expression may not be uniform across the pyramidal cell population, but may instead concentrate in particular functional subtypes, such as cells with higher firing rates or stronger spatial tuning. As part of our revisions, we plan to test this directly by stratifying the KO population by firing rate and relating it to the magnitude of the observed phenotype. Taken together, we believe that while only a small fraction of CA1 pyramidal neurons are NPAS4+ at any given moment, a much larger fraction have experienced NPAS4 induction and the accompanying synaptic reorganization over the timescale of chronic enrichment making the WT/KO comparison in this study substantially less diluted than the IHC snapshot alone would suggest.

   Timeline of NPAS4 expression and synaptic reorganization. Reviewer #1 pointed out that this study only examines the effects of NPAS4-deletion on longer timescales (weeks to months after the virus expression and subsequent knockout) stating “[the study] is less definitive about the immediate causal sequence by which NPAS4 induction alters inhibition and reshapes spatial and temporal coding”. The reviewer is correct, the temporal relationship between NPAS4 expression, changes in synaptic inhibition, and changes in neuronal firing are important outstanding questions in the field. Currently, we lack molecular tools that would enable us to clearly test these relationships but with our existing, albeit limited information, we have the following working model.

   When an animal is placed into a new context, a subset of CA1 pyramidal neurons will fire action potentials in a spatially refined manner. This activity will drive NPAS4 expression in those neurons, resulting in protein expression that persists for a couple of hours before the protein is degraded.

   Following expression, NPAS4 will bind to various sites in the genome and initiate a genetic program which results in changes in inhibition recruiting CCK basket cell synapses to the soma and destabilizing CCK dendritic synapses. The exact mechanism behind this reorganization of inhibition is unknown, but the phenotype likely emerges over the course of several hours following NPAS4 expression and persists for days following the stimulus that induced NPAS4.

   While our chronic knockout approach does not allow us to resolve the precise timing of events in this sequence, it does allow us to ask a distinct and complementary question: what is the long-term consequence for a neuron that has never been able to execute this program? Our results demonstrate that NPAS4-deficient neurons which cannot initiate NPAS4-dependent inhibitory reorganization regardless of their activity history show systematic degradation in spatial and temporal coding precision. This establishes that the NPAS4-dependent inhibitory phenotype has lasting and functionally meaningful consequences for in vivo information encoding, a question that shorter-timescale or acute manipulations would not be well-positioned to address. Resolving the immediate causal sequence between NPAS4 induction, synaptic reorganization, and changes in firing will be an important goal for future work as new molecular tools become available.

   Behaviors that drive NPAS4 expression. Reviewer #2 pointed out that “NPAS4 is also induced by contextual fear conditioning and other paradigms which would predict context-specific effects rather than a uniform refinement function.” They are correct NPAS4 is expressed in response to different behavioral paradigms, including fear conditioning and environmental enrichment. However, the subregion in which NPAS4 is induced depends critically on the behavioral paradigm. When mice are exposed to contextual fear conditioning, NPAS4 expression is robust in CA3 and the dentate gyrus but negligible in CA1 [6]. This is consistent with the known activity patterns of these subregions: CA3 neurons are strongly recruited during contextually-dependent associative learning, while CA1 neurons are more reliably driven by exposure to novelty and respond in a spatially-refined manner. Consistent with this, studies using fear conditioning have focused on behavioral discrimination and synaptic changes in CA3 and granule cells [6]. To our knowledge no study has examined the relationship between fear conditioning, NPAS4, and CA1 pyramidal neuron function. Whether behavioral paradigms beyond environmental enrichment and spatial navigation can induce NPAS4 in CA1, and what consequences that might have for pyramidal neuron firing, are interesting questions for future work.

   We also wish to address the conceptual framing underlying this concern. In CA1, we do not believe that “context-specific effects” are separable from a “uniform refinement function.” CA1 pyramidal neurons respond in a context-dependent manner. When a mouse is placed onto a linear track, there is a subset of neurons that will increase their activity over the course of that exposure. But within this subset, individual neurons will also show spatially-refined responses firing action potentials as the animal runs through the corresponding place field. The spatial precision NPAS4 confers is always nested within context-dependent mechanisms NPAS4 refines whatever representation a neuron is already computing, rather than overriding the context-dependency of that representation. We therefore do not view these as competing frameworks.

   The role of NPAS4 in shaping CCK synapses. Reviewer #2 made the point that “the CCK to pyramidal cell connectivity that the authors invoke as the mechanistic anchor is also dense in standard housing, so the absence of detectable NPAS4 in SE conditions raises the further conceptual problem of how NPAS4-negative neurons would normally be innervated by CCK+ basket cells in the first place.” We wish to clarify that NPAS4 is not necessary for the formation of CCK synapses onto CA1 pyramidal neurons there are likely a number of NPAS4-independent mechanisms that regulate this synaptic connectivity (for example, see [8]). Rather, we place NPAS4 in the role of an activity-dependent modulator that acts on top of this baseline connectivity: when NPAS4 is expressed in response to neuronal activity, it shifts the balance of CCK inhibitory input along the somatodendritic axis, increasing somatic and decreasing dendritic CCK synaptic strength [1,2]. The question is therefore not how CCK synapses are established in the absence of NPAS4, but rather how experience-dependent activity uses NPAS4 to fine-tune the distribution of those synapses and it is this fine-tuning that our study links to the precision of in vivo spatial and temporal coding.

   Methodological Clarifications:

   Clarification on how stability analysis was performed. Reviewer #2 requested additional analysis for the stability results: “A control analysis using a fixed reference window around the original peak, rather than re-identifying the peak each epoch, would help distinguish a genuine plasticity-like shift from instability driven by noise.” We wish to clarify that this is precisely the methodology that was used in the manuscript. For the stability analysis shown in Figures 4C-E, the activity was aligned to the peak activity in epoch 1 such that 0 always represents the location of the peak in epoch 1. This approach allows us to identify how that activity differs in subsequent epochs, namely whether it has shifted relative to the activity in epoch 1. We will make this more clear in the results and methods sections.

   Request for Ai32 control. Reviewer #2 made the point that “The comparison throughout the manuscript pits Cre+ ChR2+ neurons (NPAS4 KO) against neighboring non-transduced neurons (WT). This is internally elegant, but leaves open the possibility that part of the phenotype arises from chronic ChR2 expression or constitutive Cre activity rather than from NPAS4 loss, especially given that most of the readouts are subtle.” We agree this would be the ideal control and regret that it is no longer experimentally feasible, as the laboratory in which these experiments were conducted is no longer operating. However, we believe several features of the existing dataset make a ChR2 or Cre artifact unlikely. First, the effects of chronic ChR2 expression are not known to produce the specific pattern of phenotypes we observe in particular the redistribution of somatic versus dendritic inhibition, which is recapitulated independently in acute slice recordings from animals that did not undergo optotagging procedures (Figure 1C). Second, the phenotype we report is internally coherent across multiple independent metrics: place field size, stability, signal-to-noise ratio, theta coupling, and phase precession all shift in the same direction, in a manner consistent with a specific change in inhibitory synaptic balance rather than a nonspecific effect of transgene expression. Third, the sparse nature of the Cre expression means that KO and WT neurons share the same local network, same LFP, and same behavioral context any network-level effect of Cre or ChR2 would be expected to affect both populations similarly. We will add a discussion of these points to the manuscript.

   PSTH clarification (unit of opto-response). To quantify the opto-response, we treated each light-on + light-off period (a total of 2 seconds) as the one trial. We aligned the trials by the light-on period, binned the spikes by 1 msec bins, and then summed the responses across trials to produce a histogram. From this histogram we found the maximum response during light off (e.g. the 1 msec bin with the greatest response which should be reported as number of spikes). We subtracted this from the maximum response during light on. Thus, the unit of opto-response should be spike counts. We will clarify this in the text and figures.

   Use of male mice. Reviewer #1 rightfully pointed out that this study only used male mice. In this study, we only used mice that were larger than 20 grams to ensure the mice could carry the weight of the implanted drives while performing the behavior. As this genetic line of mice is on the smaller size, only male mice were above this weight threshold. Importantly, slice work conducted in the Blood good lab has not identified sex differences in NPAS4 phenotypes [3,9]. Future studies would benefit from the use of both male and female mice. We will state this more explicitly in the text and expand on the potential implications of excluding female mice from our study.

   Future planned changes to manuscript:

   As the reviewers suggested, we intend to add the following analyses and make the following changes to the manuscript:

   Stratify key analyses (stability, theta coupling, phase precession) by FR to determine whether there is a dependency on the firing rate of cells.

   Apply hierarchical bootstrapping and add per-animal color-coding to supplementary figures to assess animal-level variability and protect against pseudoreplication.

   Add a circular-linear phase-position correlation analysis as an additional quantification of phase precession strength, complementing the existing slope-based analysis.

   Improve discussion around the temporal phenotype being downstream of the spatial one.

   Tighten mechanistic framing in the Discussion to more clearly distinguish what is demonstrated in this study from what is inferred from prior work, and to acknowledge the contributions of other inhibitory cell types.

   Minor changes and figure clarifications as noted by reviewers.

   Outside of the scope of this study or unable to be performed:

   There were several recommendations or points that the reviewers brought up that we do not have the resources to address. Nevertheless, we appreciate the reviewers noting these.

   SE control (as discussed above)

   Ai32 control (as discussed above)

   Behavioral consequences of NPAS4 knockout and the effects on learning and memory • Ripple analysis

   Drift observed in E4 and what this might look like over larger timescales

   Comparison between male and female mice to determine whether there are sex-dependence differences

   In conclusion, the reviewers recognized this as a well-designed and internally consistent study. We believe that many of the critiques including the request for a standard housing control, questions regarding the extent of NPAS4 expression across the pyramidal cell population, and points about the timeline of NPAS4 expression and synaptic reorganization are addressed by the clarifications provided in this response. We agree with many of the suggested analytical and textual changes and look forward to incorporating those into the revised manuscript.

   References:

   (1) Heinz, D. A., Cui, W., Cooper, K. L. & Bloodgood, B. L. Experience-induced NPAS4 reduces dendritic inhibition from CCK+ inhibitory neurons and enhances plasticity. J. Neurophysiol. 134, 361–371 (2025).

   (2) Hartzell, A. L. et al. NPAS4 recruits CCK basket cell synapses and enhances cannabinoid-sensitive inhibition in the mouse hippocampus. Elife 7, (2018).

   (3) Bloodgood, B. L., Sharma, N., Browne, H. A., Trepman, A. Z. & Greenberg, M. E. The activity dependent transcription factor NPAS4 regulates domain-specific inhibition. Nature 503, 121–125 (2013).

   (4) Sharif, F., Tayebi, B., Buzsáki, G., Royer, S. & Fernandez-Ruiz, A. Subcircuits of deep and superficial CA1 place cells support efficient spatial coding across heterogeneous environments. Neuron 109, 363–376.e6 (2021).

   (5) Quirk, C. R. et al. Precisely timed theta oscillations are selectively required during the encoding phase of memory. Nat. Neurosci. 24, 1614–1627 (2021).

   (6) Ramamoorthi, K. et al. Npas4 regulates a transcriptional program in CA3 required for contextual memory formation. Science 334, 1669–1675 (2011).

   (7) Chiaruttini, N. et al. ABBA+BraiAn, an integrated suite for whole-brain mapping, reveals brain-wide differences in immediate-early genes induction upon learning. Cell Rep. 44, 115876 (2025).

   (8) Früh, S. et al. Neuronal Dystroglycan Is Necessary for Formation and Maintenance of Functional CCK-Positive Basket Cell Terminals on Pyramidal Cells. J. Neurosci. 36, 10296–10313 (2016).

   (9) Lin, Y. et al. Activity-dependent regulation of inhibitory synapse development by Npas4. Nature 455, 1198–1204 (2008).

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5. 

   Version published to 10.64898/2026.03.22.713468 on bioRxiv

   Mar 22, 2026