Divergent spatial codes in retrosplenial cortex and hippocampus support multi-scale representation of complex environments

  1. Célia Laurent
  2. Nada El Mahmoudi
  3. David M. Smith
  4. Francesca Sargolini
  5. Pierre-Yves Jacob

  • Curated by eLife

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    eLife Assessment

    This valuable study reports results showing how different neurons in the dysgranular retrosplenial cortex code spatial orientation. Specifically, the paper reports that some neurons maintain tuning for a single head direction across multi-compartmental environments, while other neurons are tuned to different head directions that reflect the geometry within each compartment. The study was viewed as likely to expand the field's understanding of directional tuning of neurons, but incomplete evidence was provided to support the conclusions.

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Abstract

In everyday life, mammals navigate through environments composed of multiple interconnected spaces. Understanding how the brain encodes space in such complex settings is essential to uncover the mechanisms that support flexible navigation in the real world.

In this study, we investigated how the retrosplenial cortex (RSC) and the hippocampus (HPC) encode spatial information in multi-room environments by recording neuronal activity in rats exploring environments composed of two or four connected rooms. These environments varied both in their structural layout and in their sensory features, allowing us to disentangle the influence of environmental geometry from that of local sensory cues.

We found that two types of directional coding coexist within the RSC: classical head direction cells maintained a stable preferred firing direction across all rooms, while multidirectional cells expressed room-specific directional tuning that followed the geometric structure of the environment (e.g., 180° or 90° rotations). In addition, non-directional RSC neurons displayed room-specific spatial firing patterns that repeated across rooms following geometric transformations, similar to the activity observed in multidirectional cells. In contrast, hippocampal place cells either remapped between rooms or showed simple translational repetition, without preserving any geometric alignment.

Taken together, these findings reveal a functional dissociation between retrosplenial and hippocampal spatial codes. The RSC supports a structured, multi-scale representation of space, segmenting the environment into locally anchored reference frames embedded within a coherent global geometry. The HPC, by contrast, encodes room-specific representations independently for each compartment. This division may support flexible navigation in complex environments by integrating geometry-based spatial segmentation and unification in the RSC with context-specific encoding in the HPC, thereby enabling multi-level spatial coding across interconnected spaces.

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  1. eLife

    eLife Assessment

    This valuable study reports results showing how different neurons in the dysgranular retrosplenial cortex code spatial orientation. Specifically, the paper reports that some neurons maintain tuning for a single head direction across multi-compartmental environments, while other neurons are tuned to different head directions that reflect the geometry within each compartment. The study was viewed as likely to expand the field's understanding of directional tuning of neurons, but incomplete evidence was provided to support the conclusions.

  2. eLife

    Reviewer #1 (Public review):

    Summary:

    The dysgranular retrosplenial cortex (RSD) and hippocampus both encode information related to an animal's navigation through space. Here, the authors study the different ways in which these two brain regions represent spatial information when animals navigate through interconnected rooms. Most importantly, they find that the RSD contains a small fraction of neurons that encode properties of interconnected rooms by firing in different head directions within each room. This direction is shifted by 180 degrees in 2-room environments, and by 90 degrees in 4-room environments. While it cannot be definitively proven that this encoding is not just related to the presence of exits (doors) in each room, this is a noteworthy finding and will motivate further study in more complex and well-controlled environments to understand this coding scheme in the RSD. The recordings and analyses used to identify these multi-directional cells are mostly solid. Additional conclusions regarding the rotational symmetry across rooms seen in the RSD neurons that do not encode direction (representing the majority of RSD neurons) remain incomplete, given the evidence presented thus far. The differences between RSD and hippocampus encoding of space are clear and consistent with prior observations.

    Strengths:

    (1) Use of tetrode recordings from the RSD to identify multi-direction cells that only encode one direction in each room, but shift the preferred direction by either 180 or 90 degrees depending on the number of rooms in the environment.

    (2) Solid controls to show that this multi-direction encoding is stable over time and across some environmental manipulations.

    (3) Convincing evidence that these multi-direction cells can co-exist with single-direction head direction cells in the RSD (as both cell types can be simultaneously recorded).

    (4) Convincing evidence for clear differences between directional and spatial encoding in the RSD versus hippocampus, consistent with prior observations.

    Weaknesses:

    (1) The paper mostly uses the term "retrosplenial cortex", but it is important to clarify that the study is only focused on the dysgranular retrosplenial cortex (RSD; Brodmann Area 30) and not the granular retrosplenial cortex (Brodmann Area 29). These are two distinct regions (despite the similar names), each with distinct connectivity and distinct behavioral encoding and function, so it is important to clarify in the abstract and title that the present study is solely about the RSD to prevent confusion in the literature.

    (2) The proportion of each observed cell type is not clearly stated, although it is clear that the multi-directional cells are in the minority. Having the proportion of well-isolated neurons in distinct sessions that encode each type of information (e.g., multi vs single direction encoding) would greatly aid the interpretation of the result and help the field know how common each cell type is in the RSD.

    (3) The authors state that "MDCs [multi-directional cells] never exhibited multidirectional activity within a single room" - but many of the single room examples from the 4-room environment (shown in Figures 2E and 2F) reveal multi-peaked directional encoding. This suggests that the multi-direction encoding may be more compatible with encoding some property of the number of exits rather than relative room orientations.

    (4) The spatial rotation analyses of non-directional cell analyses are considered incomplete. This is impacted by the slower speed at the doors and hence altered firing rates (as evidenced in spatial rate plots). The population rate is not relevant as the correlational analyses are done on a single cell level. Since some cells fire more with increasing speed and others fire less, that will necessarily result in a population rate map that minimizes firing rate differences near the doorway, where the animals move more slowly. But on a single cell level, that reduced speed is having a big effect, as evidenced by individual rate map examples, and the rooms will need to be rotated to obtain a higher correlation by overlapping the doorway regions. This does not necessarily say anything about spatial coding across the two or four interconnected rooms being rotationally symmetric, and it would appear difficult to draw any conclusions related to spatial encoding from those analyses.

  3. eLife

    Reviewer #2 (Public review):

    Summary:

    Laurent et al. perform in vivo electrophysiological recordings in the retrosplenial cortex of rats foraging in multi-compartment environments with either identical or unique visual features. The authors characterize two types of directional signals in the area that they have previously reported: classic head direction cells anchored to the global allocentric reference frame and multi-direction cells (MDCs), which have a rotationally preserved directional field anchored to local compartments. The primary finding of this work is that MDCs seem sensitive to local environmental geometry rather than visual context. They also show that MDC tuning persists in the absence of hippocampal place field repetition, further dissociating the RSC local directional signal from the broader allocentric representation of space. A novel observation is that RSC non-directional spatial signals are anchored to the local environment, which could and should be explored further. While the data is solid and the analyses are mostly appropriate, the primary findings are incremental, and more interesting novel claims are not explored in detail or not explicitly tested.

    Strengths:

    The environmental manipulations clearly demonstrate that tuning is not modulated by complex visual information.

    The finding that RSC two-dimensional spatial responses are stable and anchored to environmental features is novel and can be further explored in future work.

    Weaknesses:

    The observation that BDCs and MDCs are insensitive to visual context builds upon the author's previous work (and replicates aspects of Zhang et al., 2022) but leaves many open questions that are not addressed with the current set of experiments. Specifically, what exactly are MDCs anchoring to? The primary theory is that they anchor to environmental geometry, but there are no explicit experimental manipulations to test this theory. It is important to note that 2- and 4-compartment environments share many features, including the same cardinal axes, making any differences/similarities in these two conditions difficult to interpret.

    The main finding presented with respect to BDC/MDs tuning is that they are not sensitive to visual context as manipulated by distinct visual patterns on the wall and floor in multicompartment environments. One could argue that the individual rooms are, in actuality, quite similar in low-level visual features - each possesses a large white background square visual feature on a single wall with a fixed relationship to the door(s). How can the authors rule out that i) BDC/MDC responses are modulated by these low-level features rather than geometry and/or ii) that the rats are not paying attention to any visual features at all? There is no task requiring them to indicate which room they are in. Furthermore, the doorways themselves are prominent visual features that are present in each context. It would be interesting to see if MDC/BDC tuning persisted in a square room where the number of doorways was manipulated to rule out this possibility.

    A strong possibility is that the rotational symmetry of both MDCs and non-directional spatial neurons is related to i) door-related firing, 2) stereotyped movement, and 3) stereotyped directional sampling. In Supplemental Figure 8, the authors begin to address this by comparing a 'population ratemap' to a 'population speed map.' I do not think this is sufficient and is difficult to interpret. Instead, the authors should assess whether MDC and BDCs fire more at doorways and what the overlap is with the speed-modulated cells they report. Moreover, they should assess whether the spatial speed profile itself is rotationally symmetric within each session. It would also be useful to look at the confluence of the variables simultaneously using some form of regression analysis. The authors could generate a directional predictor that captures the main response property of these cells and see if it accounts for greater variability in spiking than speed or x,y position. Finally, rotationally symmetric directional sampling biases could arise from the doors being present on the same two walls in each room. The authors should assess whether MDC tuning is still present if directional sampling is randomly downsampled to match directional observations in each compartment.

    Recent work has demonstrated that neurons with egocentric corner or boundary tuning are observed in RSC. The authors do not address whether egocentric tuning contributes to MDC signals. An explicit analysis of the relationship and potential overlap of MDC and egocentric populations is warranted.

    Many of the MDCs presented in the main figures are not especially compelling. This includes alterations to MDC tuning in Figure 2, which is a key datapoint. The authors should show significantly more (if not all) examples of MDCs in each environment. It would similarly be useful to see all/more examples of non-directional spatially tuned neurons with rotationally symmetric firing patterns.

    "One might hypothesize that specific environmental cues, such as door orientation or landmark positioning, drive these tuning shifts. However, our results argue against this interpretation. In four-room environments, each room had multiple entry points, yet MDCs never exhibited multidirectional activity within a single room."

    I do not understand the logic here. Can the authors unpack this? Also, it is clear that some of the example cells have more than one peak in individual compartments. How is this quantified?

  4. eLife

    Reviewer #3 (Public review):

    Summary:

    The authors examine firing of dysgranular retrosplenial cortex (dRSC) neurons in relation to head orientation and location for rats exploring open-field environments. One environment utilized was a square arena with high walls that is split into two rectangular spaces connected by a doorway. Another environment is a square arena split into quadrants connected by doors near the center. For each, the different sub-spaces of the environments are either identical in terms of visual and tactile cues or different. For head direction neurons, the authors present one population where each neuron maintains a single tuning direction for the two or four sub-compartments of the two environments. A second population exhibits what is termed multi-directional firing, wherein neurons exhibit (overall) two or four head direction peaks in firing. For such neurons, firing in each of the sub-compartments is associated with only a single preferred direction, but the directions across compartments are shown to be at 180-degree (two-compartment environment) or 90-degree offsets. The offsets evidence tuning to the "same" orientation for the sub-compartments that are, in the global reference frame, oriented at 180 or 90 degree offsets. The results are similar whether or not the sub-compartments have the same or different tactile and visual cues. Thus, the first population is said to be global in its head direction tuning, while the second relates to each local environment in a way that is systematic across sub-compartments. Spatially-specific activity of another population of non-direction-tuned RSC neurons is examined, and comparisons of sub-compartment spatial firing maps suggest that spatial tuning in RSC also repeats across compartments when the firing maps for the compartments are rotated to match each other (as in physical space). Finally, a population of hippocampal "place" cells exhibited different location mapping across sub-compartments. The findings are interpreted to indicate that RSC can simultaneously map orientation in both local and global reference frames, possibly forming a mechanism whereby the sub-compartments' shared geometry (given by the boundary shapes and the door locations) can be related to each other and to the global space they share.

    Strengths:

    This paper addresses an interesting problem and expands how the field will think about directional tuning.

    Weaknesses:

    It is not clear that the experimental design allows for a clear interpretation of the data. Rates for preferred turning are low, as are ratemap correlations for spatially-tuned neurons.

    (1) It is concerning that the neurons with head direction tuning have fairly low peak firing rates (mean close to 5 Hz), where prior studies examining head direction tuning in dRSC found head direction-tuned neurons with peak rates more than an order of magnitude higher (100 Hz or more). Under circumstances where neurons are tuned well to variables other than head direction (for example, angular velocity of movement), weak head direction tuning may be observed if those other variables are not sampled equally across head directions. The manuscript contains no rigorous control for this possibility. One place to start to address this issue would be to map out variables such as angular velocity by head orientation, and to test whether such relationships also carry 90 and 180 degree offsets.

    (2) There is some question as to whether dRSC neurons (spatial or directional) following the sub-compartment "geometry" is appropriate in terms of interpreting the data. In the condition with sub-compartments carrying different tactile and visual cues, it seems that such cues pertain only to the floor of the environments. The distal visual space of the boundaries appears to be identical. One is left to wonder whether distinguishing environments according to boundary wall visual cues would lead to different results. The CA1 data does not help to rule this possibility out. A second reason to doubt the "shared geometry" interpretation is that there is no condition where sub-compartment geometry is varied. It is also the case that the sub-compartment doorways may stand as the only salient distal visual cue linking the environments. Local sensory cues and geometry seem not so disentangled in this study, but this is a major claim in the abstract.

    (3) There is some concern with the interpretation that the spatial tuning of some dRSC neurons repeats in rotated form across sub-compartments. The firing rate map correlations are very low on average (~0.2), and far lower than the population of CA1 having repeating fields across the same vs different visual/tactile cue conditions. The authors should define the chance level of ratemap correlation by shuffling neuron identities. Apologies if this is indeed the current approach, but it seems not to be (I was left a bit lost by the description in the methods). For any population of hippocampal place cells, the cross-neuron correlations of firing rate maps are typically not zero, and correlations at 0.2 would normally be evidence for remapping.

    (4) A somewhat picky point here that is not meant to claim that multi-compartment studies are not useful - the introduction states that real-world environments typically consist of multi-compartment rooms. This is certainly not true for rodents and is only sometimes true in humans.

    (5) The discussion lacks a consideration of how such dRSC output might impact the target structures of dRSC.

    (6) The discussion speaks to the idea that multi-directional neurons may aid in transitioning between contexts (sub-compartments). But it is notable that none of the multidirectional neurons have multi-directional tuning in all sub-compartments, but such firing was seen in the 2017 Nature Neuroscience study by Jacob/Jeffery. The discussion should address this difference and perhaps posit a means by which the firing of global and local head direction neurons can be related to each other to yield navigation that depends on both scales.

    (7) The authors should provide the size of the smoothing function for spatial firing rate maps.

    (8) The authors should devise a measure to define directional tuning in 4 directions (with 90-degree offsets).

    (9) Figures 2D and 2H - The offsets in preferred tuning across sub-compartments are rather variable.

  5. Version published to 10.1101/2024.08.22.609122 on bioRxiv