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eLife. 2016; 5: e14592.
PMCID: PMC4927294

Anatomical organization of presubicular head-direction circuits

Howard Eichenbaum, Reviewing editor
Howard Eichenbaum, Boston University, United States;

Abstract

Neurons coding for head-direction are crucial for spatial navigation. Here we explored the cellular basis of head-direction coding in the rat dorsal presubiculum (PreS). We found that layer2 is composed of two principal cell populations (calbindin-positive and calbindin-negative neurons) which targeted the contralateral PreS and retrosplenial cortex, respectively. Layer3 pyramidal neurons projected to the medial entorhinal cortex (MEC). By juxtacellularly recording PreS neurons in awake rats during passive-rotation, we found that head-direction responses were preferentially contributed by layer3 pyramidal cells, whose long-range axons branched within layer3 of the MEC. In contrast, layer2 neurons displayed distinct spike-shapes, were not modulated by head-direction but rhythmically-entrained by theta-oscillations. Fast-spiking interneurons showed only weak directionality and theta-rhythmicity, but were significantly modulated by angular velocity. Our data thus indicate that PreS neurons differentially contribute to head-direction coding, and point to a cell-type- and layer-specific routing of directional and non-directional information to downstream cortical targets.

DOI: http://dx.doi.org/10.7554/eLife.14592.001

Research Organism: Rat

Introduction

The initial observation made by Ranck and Taube (Ranck, 1984; Taube et al., 1990a; 1990b) that neurons in the dorsal portion of the rat presubiculum (PreS; classically referred to as ‘postsubiculum’) are tuned to the head-direction (HD) of the animal, represents a milestone discovery for the neural representation of direction. Together with place cells (O'Keefe and Dostrovsky, 1971; O'keefe and Nadel, 1978), grid cells (Hafting et al., 2005) and border cells (Savelli et al., 2008; Solstad et al., 2008; Lever et al., 2009), HD cells are thought to be part of an internal representation of self-location in the mammalian brain, and hence support spatial navigation and cognition (Valerio and Taube, 2012; Gibson et al., 2013).

The discovery of HD cells was followed by many years of investigation, aimed at elucidating the subcortical and cortical networks involved in the generation and processing of HD information (Taube, 2007; see Yoder and Taube, 2014; Geva-Sagiv et al., 2015 for review). According to current views, HD signals are generated subcortically and relayed to parahippocampal cortices via dorsal thalamic nuclei (Taube, 1995; Goodridge and Taube, 1997). The PreS receives a major projection from dorsal thalamic nuclei (Shipley and Sorensen, 1975; Thompson and Robertson, 1987; Shibata, 1993), contains the highest proportion of sharp HD cells among parahippocampal cortices (Boccara et al., 2010; Winter et al., 2015a) and contributes a major projection to the medial entorhinal cortex (MEC) (Caballero‐Bleda and Witter, 1993; 1994; Honda and Ishizuka, 2004). Thus, the PreS represents a major gateway of HD information into the entorhinal-hippocampal circuit. Notably, HD inputs to MEC where most grid cells have been observed (Sargolini et al., 2006; Boccara et al., 2010) have recently received great attention following experimental evidence pointing to HD signals as critical contributors to grid cell firing - in line with predictions from path-integration models (Burak and Fiete, 2006; McNaughton et al., 2006; Bush and Burgess, 2014). HD inputs to entorhinal grid cells could be ‘un-masked’ by removing excitatory feedback from the hippocampus (Bonnevie et al., 2013), and grid cell firing was disrupted following inactivation of HD signals (Winter et al., 2015a). Thus, theoretical and experimental evidence provide support for a ‘HD-to-grid’ transformation, and thus point to HD signals as critical components of the ‘cognitive’ grid-representation of space. However, despite this progress at the computational and systems level, direct anatomical evidence has been lacking. Specifically, while a previous study has indicated that HD inputs reach the MEC (Tukker et al., 2015), it is currently unknown how these projections are anatomically organized, and whether the morphological/electrophysiological diversity of PreS neurons (Funahashi and Stewart, 1997; Simonnet et al., 2013; Abbasi and Kumar, 2013) is related to in-vivo function. These represent major limitations for understanding how parahippocampal circuits are functionally organized, and how anatomically-identified circuits support spatial cognitive functions.

In the present work we address these issues by a combined anatomical and physiological approach. Specifically, we provide evidence for a layer- and cell-type specific representation of HD in the rat PreS, and resolve the anatomical organization of long-range HD inputs to the MEC.

Results

Cellular organization of the superficial layers of the rat PreS

We first investigated the cytoarchitectonic and cellular organization of PreS circuits. In the present study, we targeted the dorsal PreS (Figure 1A and Figure 1—figure supplement 1), and its borders could be reliably assessed by cytoarchitectonic criteria and neuroanatomical markers (Figure 1—figure supplement 2). The neuronal marker NeuN and calbindin revealed a prominently modular organization of PreS layer 2 (L2; Figure 1B; see also Ding and Rockland, 2001; Honda and Ishizuka, 2004) while layer 3 (L3) had a more homogenous appearance (NeuN staining; Figure 1B). In L2, calbindin immunoreactivity (Fujise et al., 1995) revealed two distinct principal cell populations - calbindin-positive and calbindin-negative neurons - which represented ~33% and 67% of the total neurons within this layer, respectively (n = 916 calbindin-positive out of 2793 NeuN-positive neurons; Figure 1B). Similarly to the organization of MEC (Varga et al., 2010; Kitamura et al., 2014; Ray et al., 2014; Fuchs et al., 2016), calbindin-positive PreS L2 neurons were also arranged in clusters, and their dendrites bundled together and formed tent-like structures in layer 1 (L1; Figure 1B).

Figure 1.
Anatomical organization and projection targets of superficial PreS neurons.

The PreS is known to project to many downstream cortical and subcortical targets, with the projection to MEC representing the most prominent output (Shipley and Sørensen, 1975; van Groen and Wyss, 1990b; Caballero‐Bleda and Witter, 1993; 1994; Honda and Ishizuka, 2004; Honda et al., 2008). We next explored the cellular and laminar specificity of this cortical output by injecting the retrograde neuronal tracer Cholera-toxin subunit B (CTB) in MEC. In line with previous work (Caballero‐Bleda and Witter, 1993; Honda and Ishizuka, 2004), we found that the PreS projection to MEC is layer-specific, since the large majority of retrogradely-labelled neurons was found in ipsilateral (and contralateral; not shown) PreS L3 (Figure 1C,D; 4497 total counted neurons, n = 4 brains). On the other hand, labeling in L2 was sparse, with very few neurons contributing to this pathway (Figure 1D), all of which were calbindin-negative (not shown).

We next sought to explore the projection targets of the two principal cell populations (calbindin-positive and calbindin-negative neurons) in PreS L2. We found that these two cell types could be differentiated according to contralateral cortical projection targets: CTB injections in PreS resulted in dense cellular labeling in contralateral PreS L2 (Figure 1E; see also Figure 1—figure supplement 3A–Dvan Groen and Wyss, 1990a; Honda et al., 2008), where the majority of retrogradely-labelled neurons was calbindin-positive (~76%, Figure 1F; 159 total counted L2 neurons, n = 3 brains) and arranged in clusters (Figure 1E). The cellular specificity of this labeling pattern was reversed by tracer injections in the superficial layers of retrosplenial (RS) cortex area 29 (Sugar et al., 2011; Boccara et al., 2015; Sugar and Witter, 2016) whose rostral border with PreS could be reliably identified based on the differential expression of calbindin, wolframin and zinc (Figure 1—figure supplement 2). CTB injections centered on this area resulted in intense cellular labeling in the contralateral homotypical area (Figure 1G and Figure 1—figure supplement 3E–H). Within PreS, most retrogradelly-labelled neurons were found within L2 (Figure 1—figure supplement 3E–H), the majority of which were calbindin-negative (~86%, Figure 1G; 896 total counted L2 neurons, n = 4 brains).

Altogether, these results indicate that the superficial layers of PreS (L2 and L3) can be differentiated according to cytoarchitectonic organization, cellular composition and cortical projection targets.

Identified HD cells in the rat PreS

We next sought to investigate how HD activity, the predominant firing pattern observed among PreS neurons (Taube et al., 1990a; Boccara et al., 2010), relates to cellular and circuit heterogeneity of the superficial PreS layers. To this end, we took advantage of a head-fixed preparation (see Zugaro et al., 2001; 2002; Shinder and Taube, 2011; 2014 for review) and recorded spiking activity from single neurons in awake rats during passive rotation. Animals were head-fixed on a rotating platform and body-centered rotations were manually performed by the experimenter (see Video 1). Within the same recording, animals were rotated both clockwise and counterclockwise (average number of inversions, 6.6 ± 4.7; n = 310 recordings) and average accelerations (1.3 ± 0.8 rad/s2), decelerations (−1.1 ± 0.7 rad/s2) and angular velocities (1.1 ± 0.4 rad/s) were within the physiological ranges reported by previous studies (Blair and Sharp, 1995; Taube, 1995; Stackman and Taube, 1997; Shinder and Taube, 2011). The main advantage of the head-fixed preparation - mechanical stability - allowed us to perform a large number of juxtacellular recordings from single PreS neurons (n = 310) and thus explore the cellular basis of the HD representation via juxtacellular labeling and cell identification (see below).

Video 1.

Representative recording of a HD cell from the rat PreS.

The video shows a recording of a PreS HD in a rat during passive rotation. A polar plot (showing total spike count as a function of HD; upper right corner) and a high-pass filtered spike trace (bottom) are displayed.

DOI: http://dx.doi.org/10.7554/eLife.14592.006

In line with previous studies using similar head-restraining procedures, as well as freely moving animals (Taube et al., 1990a; Taube, 1995; Tukker et al., 2015), sharp HD-selective responses were very common among PreS neurons and could be reliably assessed by on-line monitoring of spiking activity (see Materials and methods and Video 1). To quantify head-directionality of spiking responses, we computed the HD index (Boccara et al., 2010), while statistical significance was assessed with a shuffling test (Boccara et al., 2010; Tukker et al., 2015). Neurons were defined as HD cells if the HD index was larger than the 95th percentile of the shuffled distribution (see Materials and methods). A large proportion of PreS neurons met these criteria (186 out of 310; ~60%; see also Boccara et al., 2010; Tukker et al., 2015; Figure 2A,B), with the fraction ‘strong’ HD cells (HD index >0.8 and p<0.01; 121/310, ~39%) being within the range of previous studies from freely-behaving rodents (Taube et al., 1990a; 1990b; Boccara et al., 2010; Tukker et al., 2015). A minority of weak but statistically-significant HD responses were contributed by fast-spiking (FS) interneurons (Figure 2A; see below). Firing in HD cells was stable over time, as assessed by Pearson’s correlation coefficient of HD tuning curves computed for the two halves of each recording session (mean correlation coefficient, 0.79 ± 0.21; n = 181 HD cells) and preferred firing directions were homogeneously distributed over a 360 degrees angle (Figure 2C; Taube et al., 1990a; Taube, 1995). During passive rotation, average and peak firing rates of HD cells (3.4 ± 4.2 Hz and 15.4 ± 12.6 Hz, respectively; n = 186) were also within the range reported during free behavior (Taube et al., 1990a; 1990b; Blair and Sharp, 1996). Thus, in line with previous work, the basic properties (e.g. distribution of preferred firing directions, HD strength, stability, average and peak firing rates) and abundance of PreS HD cells recorded under passive rotation appeared to be very similar to the ones recorded in freely-moving animals. To further confirm that bona fide HD cells can be recorded under passive rotation, in a subset of recordings (n = 4) we sequentially monitored the activity of the same HD cells during head-fixation and free-behavior. To achieve this, we used miniaturized recording equipment (Tang et al., 2014), which allowed us to release the rats from head-fixation while maintaining the juxtacellular recording during free movement. As shown in the representative recording in Figure 2D, the general tuning properties of the HD cells were very similar between passive-rotation and free behavior (Figure 2E; mean correlation coefficient of the HD tuning curves, 0.68 ± 0.20, p<0.05; n = 4).

Figure 2.
HD tuning of PreS neurons.

Based on these results, we took advantage of this preparation for exploring the anatomical organization of HD circuits. In a subset of the recorded neurons, juxtacellular labeling was performed for obtaining cell identification. Representative recordings from identified HD cells are shown in Figure 3. These neurons were identified as L3 pyramidal cells, with relatively simple apical dendrites reaching L1 and basal dendrites largely confined within L3 (Figure 3A and E). Spikes from these identified neurons were sharply tuned to the direction the animal was facing during passive rotation (Figure 3B and F) with spikes occurring within a narrow directional angle (HD Index = 0.98, p=0.001; and HD Index = 0.97, p=0.004; for Figure 3C and G, respectively). HD firing was stable, as assessed by the Pearson’s correlation coefficients of HD tuning between the two halves of the recording sessions (0.99 and 0.93 for Figure 3D and H, respectively).

Figure 3.
Identified HD cells in PreS layer 3.

In total, we successfully labeled and recovered 54 PreS neurons (48 principal cells and 6 interneurons; see also Figure 2—figure supplement 1) during passive rotation. Of these, 27 (50%) were classified as HD cells. The majority of identified HD cells were located in L3 (n = 18), the rest in deep layers (L46; n = 9). No HD cell was recovered in L2. All principal neurons whose morphology could be assessed (see Materials and methods) were classified as pyramidal (21 out of 21 in L3; 4 out of 8 in deep layers) or multipolar neurons (4 out of 8 in deep layers). These data thus indicate that, within the superficial PreS layer, HD responses are preferentially contributed by L3 pyramidal neurons.

In our dataset, a subset of recordings could be classified as FS (n = 20) based on spike-width and firing rate criteria (Taube et al., 1990a; Tukker et al., 2015) which were confirmed by cell identification (n = 3; Figure 2—figure supplement 1A). In line with previous work from freely-moving rats (Tukker et al., 2015) we found that a minority of FS interneurons (3 out of 20) contributed weak HD responses (Figure 2—figure supplement 1B), which were stable between the two halves of the recording sessions (mean correlation coefficient, 0.73 ± 0.30, p<0.05; n = 3). The majority of FS interneurons (13 out of 20) were significantly modulated by angular velocity (see Materials and methods) and fired at higher rates during rotation compared to resting periods (Figure 2—figure supplement 1C). Theta rhythmicity was very sparse among FS interneurons (Figure 2—figure supplement 1D,E); yet classical ‘theta-cells’ were observed within the PreS (as in Taube et al., 1990a; Blair and Sharp, 1996), and one of them was identified as a paravalbumin-positive interneuron (Figure 2—figure supplement 1E). PreS interneurons were thus modulated by rotational movement and were on average only weakly tuned to HD and entrained by the theta rhythm.

Long-range axonal projections of identified PreS HD cells

We next sought to explore the long-range organization of HD circuits within parahippocampal cortices. We thus performed a subset of experiments, where animals were sacrificed ~4 to 12 hrs following juxtacellular labeling to ensure long-range filling of axonal projections. In the present work, we focus on projections reaching the MEC, as this projection represents the most prominent output of PreS neurons (Caballero‐Bleda and Witter, 1993; Honda and Ishizuka, 2004).

A representative experiment is shown in Figure 4. Here, the morphology of 2 identified HD cells has been reconstructed (Figure 4A); these were pyramidal neurons located in L3 with apical dendrites reaching the pial surface of PreS. These cells sent an axon to the angular bundle; in few instances, the axon split in two branches, one of which travelled caudo-medially (see below) and the other one rostrally (Figure 4B, asterisk; see also Abbasi and Kumar, 2013) [although the latter branches were not traced further in the present study, we speculate they might target the contralateral MEC, in line with double-retrograde experiments showing partial overlap between contra- and ipsilateral projecting L3 PreS neurons (not shown)]. Caudally-travelling axonal branches often made a sharp turn within the angular bundle before exiting into the deep layers of MEC, where sparse axonal branching could be typically observed. Most axons branched upon entry into L3 and displayed a high density of small axonal varicosities (Figure 4B,C). Few branches coursed through L2 and extended within the deep portion of L1, where larger boutons could typically be observed (Figure 4C).

Figure 4.
Long-range axonal projections of identified PreS HD cells to MEC.

In total, 8 long-range axonal projections from identified HD cells could be recovered (median HD index, 0.9; range 0.64–0.96, n = 8; Figure 4D). All of them reached the ipsilateral MEC where they generally showed a layer-specific distribution: compared to L2/1 and deep layers, most axonal length was observed within MEC L3 (total axonal length, 2.19 ± 3.38 mm in L3 versus 0.44 ± 0.57 mm in L1, L2 and deep layers; n = 8, p=0.025; Figure 4D). The layer-selective branching pattern of the reconstructed single axons is in line with anterograde tracing experiments, which showed that most PreS afferents are observed within MEC L3 (Caballero‐Bleda and Witter, 1993; Honda and Ishizuka, 2004; and data not shown). Altogether, our data provide an anatomical demonstration that the MEC receives HD inputs from upstream PreS L3 neurons, and that HD inputs are arranged according to layer-specific gradients within the MEC.

HD selectivity and morphological properties of L3 and L2 neurons

The distribution of identified HD cells appeared to follow a layer-specific distribution, since most neurons were recovered in L3 (18/25 identified HD cells) and none in L2. To further investigate this issue, we sought to target juxtacellular recordings to L2. Since this layer is a relatively thin cortical structure - which makes ‘blind’ juxtacellular targeting particularly challenging- we first explored whether there are electrophysiological signatures of PreS L2, which could enable its selective targeting by juxtacellular procedures. To this end, we employed extracellular recording techniques and monitored multi-unit spiking and local field potential (LFP) activity during electrode penetrations orthogonal to the PreS layers. We found that in awake animals (and to some extent also in anesthetized animals; not shown) L2 could be reliably localized based on two extracellular signatures; first, we often observed an increase in multi-unit spiking activity upon entry into L2, which could possibly result from the relatively higher cellular density within this layer (Figure 1B). Second, the transition from L2 to L1 could always be reliably identified, due to the sharp cessation of spiking activity occurring upon entry into L1. Indeed in 4 out of 4 experiments, where electrode locations were confirmed relative to electrolytic lesions (see Materials and methods), we could reliably identify the location of PreS L2 (not shown), indicating that these electrophysiological signatures could be used to successfully target PreS L2.

We thus took advantage of these electrophysiological signatures for targeting juxtacellular recordings to PreS L2. During individual electrode penetrations, multiple consecutive neurons could be typically recorded juxtacellularly across PreS layers. While HD cells were commonly found before the cortical depth of L2 -assessed by prior extracellular mapping- neurons sampled within L2 discharged independently from the direction the rat was facing during passive rotation. These observations were confirmed by juxtacellular labeling, as shown in two representative recordings from identified L2 neurons (Figure 5). The basal dendrites of the first neuron, which was calbindin-positive (Figure 5A), were largely confined within L2, while the apical dendritic branches covered a large territory within L1. This neuron fired irrespectively of the direction the animal was facing during passive rotation (Figure 5B,C; p=0.35). The second neuron also displayed basal dendrites largely confined to L2, a multipolar apical dendritic tree extending into L1, and was calbindin-negative (Figure 5D). This neuron was also not tuned to HD (Figure 5E,F; p=0.67). In both neurons (Figure 5A,D) an axon could be traced within the angular bundle: these axons however followed a different route compared to L3 pyramidal cells (Figure 4), as they travelled medially (rather than laterally) within the angular bundle - possibly towards contralateral projection targets, in line with tracing experiments (Figure 1E–G).

Figure 5.
Non-directional spiking patterns of identified L2 PreS neurons.

The physiological differences between PreS L2 and L3 neurons are summarized in Figure 6. All identified L2 and L3 neurons included in the analysis displayed ‘regular’ firing patterns and broad spike waveforms (Figure 2—figure supplement 1A); the neurons where morphology could be assessed displayed pyramidal or ‘pyramidal-like’ morphologies (see Materials and methods; Figure 6A) and spiny dendrites (Figure 6B) - features classically associated with principal (glutamatergic) cell identity. Both the strength of HD modulation (Figure 6C) and the proportion of HD cells were significantly lower in L2 compared to L3 (0/11 in L2 versus 18/25 in L3, p<0.001, Fisher’s Exact Test). Notably, while average firing rates did not differ (L2, 2.5 ± 2.5 Hz; L3, 2.4 ± 2.6 Hz; p=0.245), spiking rhythmicity in the theta-frequency range (4–12 Hz) as assessed by a standard ‘theta index’ (Yartsev et al., 2011) was more prominent among L2 than L3 neurons (Figure 6D,E; we note that in our head-fixed preparation, theta activity presumably reflects immobility-related type-II theta [Shin, 2010, Tai et al., 2012] since animals were not actively moving during passive rotation). In line with previous work from freely-moving animals (Taube et al., 1990a; Boccara et al., 2010; Tukker et al., 2015), theta-rhythmicity was very sparse among principal neurons (Figure 6E), and the only statistically-significant theta-rhythmic discharges (as assessed by a shuffling procedure; see Materials and methods) were selectively contributed by L2 cells (4 out of 4). Theta-rhythmic spiking patterns were contributed by both calbindin-positive and calbindin-negative neurons (Figure 6E), and average theta-indices did not differ significantly between the two cell classes (calbindin-positive, 2.3 ± 2.3, n = 3; calbindin-negative, 3.8 ± 2.5, n = 6; p=0.54; we note however that the small dataset of identified calbindin-positive neurons prevents rigorous assessment of structure-function relationships). The electrophysiological differences between L2 and L3 neurons were not accounted for by biases in rotational parameters, since average angular velocities (L2, 0.96 ± 0.31 rad/s; L3, 0.96 ± 0.33 rad/s; p=0.8), accelerations (L2, 1.41 ± 0.82 rad/s2; L3, 1.24 ± 0.89 rad/s2; p=0.4) and decelerations (L2, −1.27 ± 0.74 rad/s2; L3, -1.12 ± 0.81 rad/s2; p=0.3) were not significantly different between L2 (n = 11) and L3 (n = 25) recordings. Notably, the spike waveforms of L2 neurons differed significantly from that of L3 cells (Figure 6F), as they showed on average a significantly longer duration (as assessed by spike half-width) and more pronounced negativity (Figure 6G). Altogether, these data indicate that PreS L2 and L3 neurons can be differentiated according to spike waveform features, HD modulation and temporal spiking properties within the theta-frequency range (see Figure 6 and Figure 6—source data 1).

Figure 6.
Morphological and electrophysiological properties of L2 and L3 PreS neurons.

The present data thus reveal a cell-type and layer specificity of the HD representation within PreS circuits. Together with the different projection targets of L2 and L3 neurons (Figure 1), these data point to different routing of directional and non-directional information from the superficial PreS layers to downstream cortical areas (see Figure 6—figure supplement 1).

Discussion

The PreS is widely recognized as a key structure in the cortical representation of HD. Here we show that the superficial layers of the rat PreS are composed of molecularly- and morphologically-distinct principal cell populations, which can be differentiated according to long-range projection targets. Temporal and directional firing properties are differentially distributed among these neurons, with L3 pyramidal cells being predominantly modulated by HD, and L2 neurons’ spiking being largely unaffected by HD but significantly entrained by theta oscillations. These findings closely resemble the cytoarchitectonic and functional architecture of the MEC; specifically, also in MEC (i) calbindin-positive neurons are clustered and project (at least to some extent) to the contralateral homologue area (Varga et al., 2010; Fuchs et al., 2016), and (ii) L2 and L3 neurons differ in morphological, electrophysiological, functional properties and projection targets (Kitamura et al., 2014; Ray et al., 2014). Notably, both Pres and MEC have been shown to contain the same types of spatially-modulated neurons, albeit in different proportions (Boccara et al., 2010). The common basic architecture of PreS and MEC circuits could point to similar mechanisms supporting the generation of spatial firing within these areas, as proposed by previous authors (Boccara et al., 2010).

Our experimental design, based on passive rotation of head-fixed rats (see Materials and methods) was optimized for selectively targeting HD cells. Our experiments confirmed earlier work which indicated that HD responses are largely preserved under these conditions (Zugaro et al., 2001; 2002; Shinder and Taube, 2011; 2014). Indeed, the abundance and general properties of PreS HD neurons were very similar to the ones reported from freely-moving animals, thus pointing to a largely intact HD system which is uncoupled from voluntary animal locomotion (see also Winter et al., 2015b). Our approach thus enabled efficient identification and labeling of HD neurons (Figure 3) but prevented assessment of spatial firing properties. Hence, the spatial firing patterns of the ‘non-directional’ L2 neurons remain to be established. We note that the lack of directionality in PreS L2 might be due to the lack of HD inputs from the dorsal thalamus, in line with tracing experiments indicating that thalamic inputs largely avoid PreS L2 (van Groen and Wyss, 1990b; 1995Shibata, 1993). An intriguing possibility is that L2 neurons could contribute the spatial signals which have been previously recorded among PreS units (i.e. grid and border cells; Boccara et al., 2010; Winter et al., 2015b). Based on the known correlation between spiking theta-rhythmicity and grid activity (Boccara et al., 2010; Brandon et al., 2011; Koenig et al., 2011) and the fact that under our recording configuration, theta-rhythmic responses were almost exclusively contributed by L2 PreS neurons (Figure 6D,E), we speculate that L2 could be the principal source of grid activity in PreS - as it is the case in MEC (Boccara et al., 2010). Future approaches involving either juxtacellular labeling (Tang et al., 2014) or genetic targeting in freely-moving animals will be required for testing this hypothesis.

Reconstructions of long-range axonal projections from functionally-identified PreS HD cells provided direct anatomical evidence that the MEC receives HD inputs, complementing earlier evidence (Tukker et al., 2015) and in line with predictions from computational models (Burak and Fiete, 2006; McNaughton et al., 2006; Bush and Burgess, 2014). HD inputs are thought to be critically involved in the generation of grid activity; the long-range HD circuits we describe in the present study (Figure 4) could provide –together with the parasubiculum (Tang et al., 2016) - one source for HD inputs into the grid system. The distribution of axonal length and axonal varicosities (Figure 4C,D) indicated that most synaptic contacts are likely to occur within MEC L3. Although axonal-bouton distribution is typically in large agreement with connectivity inferred by direct methods, it remains to be established whether MEC L3 neurons are indeed the prime recipient of HD inputs (see Canto et al., 2012). An intriguing observation is that the representation of HD appears to be much sparser in MEC L3 (Giocomo et al., 2014; Tang et al., 2015) compared to its presynaptic inputs structure (i.e. PreS L3), arguing against a simple feed-forward inheritance of HD coding. It will be crucial to resolve the signal transformation occurring in MEC L3 (Tang et al., 2015) for understanding the layer specific contribution of MEC circuits to spatial coding.

The cellular and circuit organization of PreS is likely optimized for subserving a specific function during navigation and episodic memory. Inactivation and lesion studies have indicated that the PreS might be critically involved in the stability of spatial representations (Taube et al., 1992; Goodridge and Taube, 1997; Calton et al., 2003; Taube, 2007) by binding visual landmark information to the HD representation (Vogt and Miller, 1983; McNaughton et al., 1991; Goodridge and Taube, 1995; Knierim et al., 1995; Taube, 2007). In this context, the connection from PreS L2 to RS cortex (Figure 1G) – an area known to receive strong direct inputs from primary visual cortex (Ding, 2013) – could point to L2 as the site where visual information is processed and integrated into the PreS HD map. Future work will be required for dissecting the contribution of PreS and RS neurons to this computation, which is crucial for the stable expression of cognitive representations of space.

Materials and methods

Histological analysis, histochemistry and immunohistochemistry

At the end of each recording, the animal was euthanized with an overdose of pentobarbital and quickly perfused transcardially with 0.1 M phosphate-buffered saline followed by a 4% paraformaldehyde solution. Brains were removed from the skull, immersed in fixative for at least one day and cut with vibratome or cryostat (prior cryo-protection step in 30% sucrose) to obtain 50–70 μm thick parasagittal sections. To reveal the morphology of juxtacellularly labeled cells (i.e. filled with neurobiotin or biocytin, see below), brain slices were processed with streptavidin-546 or 488 (Life Technologies, UK). Immunohistochemical stainings for Calbindin (Monoclonal or Rabbit anti Calbindin D28-k, 1:2000; Swant, Switzerland), Paravalbumin (Monoclonal anti paravalbumin, 1:3000; Swant), Wolframin (Rabbit anti Wfs-1, 1:500; ProteinTech, UK) and NeuN (Anti-NeuN A60, 1:1000; Millipore, USA) were performed on free-floating sections. Immunohistochemical images were acquired by epifluorescence (Axio imager Zeiss) or confocal (Zeiss LSM 710) microscopy, and the analysis was performed with Neurolucida software (MBF bioscience). After fluorescence images were acquired, the neurobiotin/biocytin staining was converted into a dark DAB reaction product. Some sections underwent Ni2+-DAB enhancement protocol (Klausberger et al., 2003). Zinc staining was essentially performed as previously described (Danscher, 1981; Ichinohe and Rockland, 2004). Briefly, after perfusion with a solution containing sodium sulfide, brain sections were washed thoroughly with 0.1 M and 0.01 M phosphate buffer solutions. Sections were then developed by exposing them to a solution containing gum arabic, citrate buffer, hydroquinone and silver lactate for 60–120 min in the dark at room temperature. Development of reaction products was terminated by rinsing the sections in 0.01 M phosphate buffer and subsequently several times in 0.1 M phosphate buffer.

Retrograde neuronal labeling

Retrograde tracer solutions containing Cholera Toxin Subunit B- Alexa Fluor 488 or 546 conjugates (Life Technologies) (CTB; 0.8% w/vol in PB 0.1 M) were injected in 200-–250 g rats under ketamine/xylazine anesthesia. Briefly, animals were placed in a stereotaxic apparatus, and a small craniotomy (<1 mm2) was performed at the coordinates for targeting the MEC (see Burgalossi et al., 2011; Ray et al., 2014), dorsal PreS (lambda coordinates: 0.0 mm AP, 3.3 mm ML, −3.0 mm DV) or RS29 (lambda coordinates: −1.0 mm AP, 3.3 mm ML, −3.0 mm DV). Injections in RS29 (n = 4) were centered on, but not restricted to, the caudal portion of the RS29, bordering rostrally with the PreS. The border between PreS and RS29 were confirmed by calbindin staining (see Figure 1—figure supplement 2). We note that this region has been previously referred to as ‘area retrosplenialis 29e’ (Blackstad, 1956; Haug, 1976; Slomianka and Geneser, 1991) or ‘triangular region’ (Ding, 2013). PreS injections (n = 3) were centered on L2; to this end, prior to injection, PreS layer 2 was localized by electrophysiological mapping with low-resistance electrodes (1–3 MΩ), based on characteristic signatures of the multiunit spiking activity (see Results). Glass electrodes with a tip diameter of ~20–40 µm filled with CTB solution were then lowered into the target region. To avoid diffusion of the tracer during electrode penetration, the tip of the pipette was front-filled with a small amount of Ringer solution. Typically, small amounts of tracer solutions (~0.3–0.8 µl) were then slowly injected using positive pressure. After the injections, the pipettes were left in place for several minutes and slowly retracted. The craniotomy was closed by application of silicone (Kwik-cast, World Precision Instruments) and animals survived for 3–5 days before being euthanized and transcardially perfused. Both hemispheres were cut into 60–70 µm thick parasagittal slices and analyzed with epifluorescence and/or confocal microscopy. When necessary, immunochemical staining for calbindin was performed to outline the cytoarchitecture of the superficial PreS layers.

Analysis of anatomy data

Retrogradely-labeled PreS neurons (Figure 1C–G and Figure 1—figure supplement 3) and NeuN/calbindin-positive PreS L2 neurons (Figure 1B) were manually counted on z-stacks with the Neurolucida software. For tracing experiments, neurons were counted from six parasagittal sections encompassing the medio-lateral extent of the dorsal PreS. Neuronal reconstructions of juxtacellular labeled cells were performed manually with the Neurolucida software and displayed as 2-dimensional projections. The projection planes for the cells in Figure 5 were optimized (by rotation along the dorso-ventral plane) in order to obtain optimal display of apical dendritic branches. For displaying long-range axonal projections of PreS HD cells (Figure 4), PreS cells were registered relative to the parasagittal PreS section containing their somato-dendritic compartment, while axons were superimposed on the reconstruction of more lateral parasagittal sections containing MEC at a typical medio-lateral level (Figure 4D).

Juxtacellular recordings

Experimental procedures for obtaining juxtacellular recordings, signal acquisition and processing and animal tracking in awake, head-fixed animals were essentially performed as recently described (Diamantaki et al., 2016Houweling et al., 2010). Briefly, recordings were made from male Wistar rats (~150–250 g). Glass pipettes with resistance 4–6 MΩ were filled with extracellular (Ringer) solution containing in mM: 135 NaCl, 5.4 KCl, 5 HEPES, 1.8 CaCl2 and 1 MgCl2 (pH is adjusted to 7.2) plus Neurobiotin (1.5–3%; Vector Laboratories, UK) or Biocytin (1.5–3%; Sigma-Aldrich, Germany). Osmolarity was adjusted to 290–320 mOsm.

We used head-restrain and passive-rotation procedures following the work of Shinder and Taube (2011); (2014), i.e. animals were head-restrained onto a rotatable platform, which was rotated manually by the experimenter. For these experiments, animals were pre-implanted with a metal post and a recording chamber under ketamine/xylazine anesthesia. After a recovery period (~3–4 days) animals were slowly habituated to head-fixation and to the rotation of the apparatus. Habituation and recordings were performed under slightly-dimmed ambient illumination in the ‘cue-rich’ environment of the laboratory setting. Thus, both during habituation and recordings, the rats had visual access to proximal cues available in the immediate vicinity (e.g. computer screens, cold-light source, stereomicroscope) and distal cues (i.e. Faraday cage, ceiling, curtains), including the experimenter, which was always located in the same relative position during the passive rotation experiment. These cues were thus the most likely source of ‘anchoring’ stability to HD firing (see e.g. Knierim et al., 1995 for review). The stability of HD responses in the dark (i.e. in the absence of visual cues) has not been tested in the present study. Craniotomies (<1 mm2) were performed at the coordinates for targeting the dorsal PreS (0–0.5 mm posterior and 3–3.7 mm lateral from Lambda). Before juxtacellular recordings, mapping experiments with low-resistance electrodes (0.5–1 MΩ) were performed to precisely estimate the location of the PreS, and of PreS L2. In a subset of preliminary experiments, the location of L2 was confirmed by aligning Tungsten electrode tracks to anatomically-verified electrolytic lesions (n = 4), essentially as previously described (Beed et al., 2013).

Juxtacellular labeling was performed by using standard labeling protocols (Pinault, 1994; 1996) and modified procedures, which consisted in rapidly breaking the dielectric membrane resistance by short (1–2 ms) ‘buzz-like’ current pulses, which provided rapid access to cell entrainment by juxtacellular current injection (i.e. 200 ms square current pulses, Pinault, 1994; 1996). After cell labeling, animals were either immediately perfused for anatomical analysis, or returned to their home cage and perfused ~4–12 hr following labeling. In order to maximize axonal recovery, in some experiments multiple neurons were labeled; the sparse labeling typically allowed unequivocal assignment of the identified cells, based on positional coordinates and recording depth. In total, 54 neurons (48 principal cells and 6 interneurons) were labeled and recovered in PreS. In 36 out of 48 cases, the morphology of principal neurons could be assessed; in the remaining cases, morphology could not be assessed as only the soma and/or proximal dendrites were recovered. Cells were classified as ‘pyramidal’ if a pyramidal-shaped soma and at least a prominent apical dendrite could be identified. Non-pyramidal, ‘multipolar’ morphologies were classified based on the proximal dendritic arrangement and the lack of prominent apical dendrite(s). Within L2, principal cells generally displayed ‘pyramidal-like’ morphologies, with often multiple apical dendrites branching extensively within L1. Ten out of 11 L2 neurons were tested for calbindin expression (3 calbindin-positive and 7 calbindin-negative neurons). Identified neurons were classified as interneurons (n = 6) based on classical morphological features (e.g. thin, smooth and often ‘beaded’ dendrites; see Ascoli et al. (2008) for review). Two FS interneurons were tested for PV expression, and were positive (one neuron shown in Figure 2—figure supplement 1E). In 8 neurons, a long-range axon was traced till the ipsilateral MEC. The quality in axonal filling differed among the individual cases, and in general it cannot be assured whether even in the best-filled examples, thin axonal branches were missed due to incomplete filling. Nevertheless, the presence of axonal boutons (which were always associated with terminal axonal branching) within MEC (Figure 4) provides anatomical demonstration that HD inputs target MEC neurons with a bias for MEC L3 (Figure 4).

The juxtacellular voltage signal was acquired via an ELC-03XS amplifier (NPI Electronic), sampled at 20 kHz by a LIH 1600 data-acquisition interface (HEKA Electronic) under the control of PatchMaster 2.20 software (HEKA Electronic) or Spike2 v8.02 software and Power1401-3 data-acquisition interface (CED, UK). Extracellular signals were acquired via an EXT-HS-M amplifier (NPI Electronic); either broad-band (e.g. for LFP) or band-pass (i.e. for spikes) signals were acquired by filtering the extracellular signals via a DPA-2F2 filter unit (NPI Electronic). The orientation of the rat’s head was tracked using a LED placed on the back of the turntable, in line with the sagittal plane of the animal. Animal tracking was performed by acquiring a video (25 Hz frame rate) with the IC Capture Software (The Imaging Source).

Analysis of electrophysiology data

Spike signals from juxtacellular traces and a few extracellular units (n = 6) were isolated by using principal component analysis, essentially as previously described (Burgalossi et al., 2011). The bursting index (see Figure 6—source data 1) was defined as the sum of spikes with an ISI < 6 ms, divided by the number of spikes. A single white LED, positioned on the rotating apparatus, was used for extracting the HD angle and the angular velocity. The angular velocity was calculated based on smoothed X and Y coordinates of the tracking (averaged across a 600 ms rectangular sliding window). A linear velocity cutoff (1 cm/s) was applied for isolating periods of rest from rotational movement, and only spikes during movement were included in the theta, speed and HD analysis (see below).

The theta-index was computed as in Yartsev et al. (2011). Briefly, theta-rhythmicity of spiking was determined by first calculating the spike train's autocorrelation for each cell using a 10 ms bin size. The power spectrum obtained by calculating the Fourier Transformation on the autocorrelation was used to measure the modulation strength in the theta band (4–12 Hz). The theta index was defined as the average power within 1 Hz of the maximum of the autocorrelation function in the theta band divided by the average power between 1 and 50 Hz. Only recordings with >20 spikes were included in the theta-rhythmicity analysis (n = 10 L2 and n = 22 L3 neurons; Figure 6D,E). Statistical significance of theta-rhythmicity was evaluated with a shuffling test (essentially as described by Yartsev et al. (2011), which was performed on a cell-by-cell basis; for each trial of the shuffling procedure, individual spike times were randomly time-shifted. For each permutation, the theta-index was calculated and the procedure reiterated 1000 times. The significance value for each cell was assessed based on the resulting null distribution, i.e. a neuron was defined as significantly theta-rhythmic if the theta-index was >95th percentile of its corresponding null distribution.

Speed analysis was performed as in Kropff et al. (2015). Briefly, a speed score was defined as the Pearson’s product-moment correlation between the instantaneous firing rate and the rat’s instantaneous angular velocity. A neuron was defined as significantly modulated by angular velocity if its speed score was >95thof the null distribution, generated by a shuffling procedure (1000 permutations per cell) essentially as in Kropff et al. (2015). The firing rate and angular velocities were calculated with 40 ms bins, coinciding with the frames of the tracking camera. Angular acceleration and deceleration were calculated as α=dω/dt, where ω is the angular velocity and dt the time between two frames (40 ms). For calculating the number of inversions during passive rotation, an inversion was defined as a sign change of the difference between two consecutive angles, if larger than π radians.

In total, we recorded n = 310 PreS neurons in awake, head-fixed rats during passive rotation, where all HD bins (n = 36) were visited at least once (as in Tukker et al., 2015). Recordings (or portions of recordings) were cellular damage was observed in the electrophysiology were excluded from the analysis (as in Pinault, 1996; Herfst et al., 2012). To quantify HD tuning, we divided the number of spikes by the occupancy for each HD bin. The HD index of a cell was defined as the average Rayleigh vector over all bins, essentially as previously described (Boccara et al., 2010; Tukker et al., 2015). Significance was evaluated with a shuffling test, which was performed on a cell-by-cell basis; for each trial of the shuffling procedure, the entire sequence of spikes was randomly time-shifted. For each permutation, the HD Index was calculated and the procedure reiterated 1000 times. The significance value for each cell was assessed based on the resulting null distribution, i.e. a neuron was defined as HD cell if the HD Index was > 95th percentile of its corresponding null distribution. For recordings in which each HD bin was sampled in each half of the recording (n = 181 out of 186 HD cells), we quantified the stability of the HD tuning by generating separate tuning curves for the first and second half of the recording time and calculating Pearson’s linear correlation coefficient.

For all experiments, sample sizes were estimated based on previously published data using similar procedures (Ray et al., 2014; Tang et al., 2014; 2015). Statistical significance was assessed by a two-sided Mann-Whitney nonparametric test with 95% confidence intervals.

Acknowledgements

We thank Alexandra Eritja for excellent assistance with anatomy experiments, Fereshteh Zarebidaki for contributing to anatomy experiments and data analysis, Thomas Klausberger and Erzsebet Borok for helpful advices on DAB-enhancement procedures, Maria Diamantaki, John Tukker and Robert Naumann for helpful comments on earlier versions of the manuscript.

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Funding Information

This paper was supported by the following grant:

  • http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft to Patricia Preston-Ferrer, Stefano Coletta, Markus Frey, Andrea Burgalossi.

Additional information

Competing interests

The authors declare that no competing interests exist.

Author contributions

PP-F, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article.

SC, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article.

MF, Analysis and interpretation of data, Drafting or revising the article.

AB, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article.

Ethics

Animal experimentation: All experimental procedures were performed according to the German guidelines on animal welfare and approved by the local institution in charge of experiments using animals (Regierungspraesidium Tuebingen, permit numbers CIN2/14, CIN5/14 and CIN8/14).

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2016; 5: e14592.

Decision letter

Howard Eichenbaum, Reviewing editor
Howard Eichenbaum, Boston University, United States;

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your work entitled "Anatomical Organization of Presubicular Head-Direction Circuits" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Howard Eichenbaum as the Reviewing Editor and Timothy Behrens as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Kate Jefferey (peer reviewer).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted a list of required and recommended changes and experiments that we feel must be considered if this work is to be published in eLife.

Head-direction (HD) cells form the building block of the navigation system. Unveiling their dynamics and circuitry is vital to further our understanding of how the cognitive map forms within the medial entorhinal cortex (MEC) and the hippocampus. In the present manuscript, Preston-Ferrer and colleagues present novel findings on the circuit underlying the processing of the HD information in the pre-subiculum (PreS), an important relay of the HD signal to the MEC. Using juxtacellular recordings from awake, head-restrained mice, the authors present data from a large amount of neurons and were able to reconstruct for identified HD cells in vivo their morphology, anatomy and axonal projections. The paper presents three levels of anatomical differentiation within the PreS: i) HD cells were identified within Layer 3, not Layer 2, ii) Layer 3 cells (including HD cells) project to the ipsilateral MEC, Layer 2 neurons project to the contralateral PreS; iii) Layer 2 showed more theta modulation than Layer 3 cells. These results are interesting but the data, in their present form, do not fully support the novel findings.

Major issues:

1) The authors have showed that Layer 3 cells project to the MEC, using both histological reconstruction and retrograde labeling. Based on the reconstruction of 8 identified HD cells, they show quite clearly that they target mainly the superficial layers of the MEC. This is one of the most important findings of the manuscript. Indeed, this is surprising and not really expected, as the authors admitted themselves, as (i) HD cells are more prominent in the deep layers of the MEC than in the superficial layers (where they are virtually absent) and (ii) a previous report (Tukker et al., 2015; but only one reconstructed axon was shown there) reported a projection from PreS layer 3 HD cell to the deep layers. Why haven't the author tried an anterograde labeling from the PreS to demonstrate definitively their claim? Do only HD cells from layer 3 project to the MEC or all cells from layer 3? (i.e. did the authors have reconstructed the axons of non-HD cells from PreS layer 3)? Did these 8 HD cells have strong HD index?

2) The authors did not adequately describe the apparatus used for the head-fixation. Were the animals free to run on a treadmill or on a wheel? If so, did the author had access to the speed of the animal? This is a clear limitation of the head-fixed experiment compared to freely moving juxtacellular recording (again, Tukker et al., 2015). The fact that Layer 2 neurons are theta modulated suggests that they may be modulated by speed, and that will be the demonstration of a nice functional and anatomical segregation between the HD and speed signals. Perhaps the authors should first try to correlate the firing rate with angular speed?

3) The higher theta rhythmicity in layer 2 was mostly explained by a few strongly theta modulated cells (Figure 7C). Is there any evidence that these cells were different from the others? Were they all excitatory pyramidal or stellate cells or is there a chance that some were interneurons? By the way, have the authors recorded from any interneurons in the course of this study?

Author response image 1.
Laminar organization of projections from the PreS to MEC.

4) Following up on the previous point, could the authors report more detailed descriptions of the cells they recorded within the two layers: average firing rate (partially reported in the text), peak firing rates for HD cells, waveform width, etc.

5) Is there a relationship between calbindin expression and theta rhythmicity? As the authors reported that these two classes of cells have different output, it will be interesting to show that they are also functionally segregated.

6) The experiments described were performed in head-fixed rats with passive rotation. Such an experimental design has been used before for thalamic recordings, which showed that head-direction cells can be observed under such conditions, but some differences seem to exist to free movement. Because the entire manuscript is based on this preparation, a control experiment for presubicular recordings in the set-up used here should be performed and some neurons should be recorded consecutively during passive rotation and free movement. Of course, this does not require the difficult juxta recording and labelling of the neurons, but could be done with tetrodes or silicon probes, which give more stable recordings and many cells can be recorded simultaneously. This experiment is well within the expertise of the authors and could be done relatively quickly. Importantly, it would give a quantitative measure how the same neurons fire according to head-direction in passive and free movement. This would answer if the same neurons are head-direction cells and how their head-direction tuning changes under both conditions.

7) In the Introduction the authors lay out their aim with: "Specifically, it is currently unknown how HDcells are anatomically organized within the PreS, and whether they project to MEC, as long speculated by computational models (see Giocomo et al., 2014 for review)." However, in a previous paper – the corresponding author of present manuscript was a co-auhor in this older paper – they say "[…]our data do indicate that at least a subset of the MEC-projecting pyramidal cells in layer 3 of the presubiculum is HD" (Tukker et al., J Neurosci 2015). A fair presentation of what has been achieved previously is necessary and should also be reflected in the significance statement.

8) For the presented data, it is key to define the exact border between layer 2 and layer 3, which is not trivial. This should be shown with clear examples and a better description on how exactly it was decided for neurons that were located close to the border.

9) How was the rotation speed compared between different experiments?

10) For the physiological identification of layer, a histological example of a lesion should be shown. Is it really possible to make such a small lesion to determine the border?

11) It would be useful to get a slightly better picture of where exactly in presubiculum the study was done, perhaps with a zoomed-out anatomical illustration, and location on an atlas, so that the exact region is more obvious for anyone who might want to pursue this further. The analysis is focused on MEC but the interconnections with RSC are also very important to understand, as the authors note in the discussion, and the impact statement could be adapted to include this. We would like to know more about which part of RSC (e.g. AP location, layer etc) was targeted and exactly what the labelling patterns were. We also need a lot more details about the behavioural manipulation – how was the animal rotated, with what angular acceleration and velocity, how many reversals, what visual cues were available, etc.

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

Thank you for submitting your article "Anatomical Organization of Presubicular Head-Direction Circuits" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Timothy Behrens as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Adrien Peyrache (Reviewer #1); Thomas Klausberger (Reviewer #2); Kate J Jeffery (Reviewer #3).

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

Summary:

The authors have taken great care in adequately addressing the concerns and questions of the referees. The additional experiments have significantly strengthened the manuscript.

Essential revisions:

1) The additional data and figures are particularly useful. Please include one of the sub-parts of Figure 1—figure supplement 1 (micrograph plus line drawing) in the main paper, to help the reader visualize the anatomy.

2) Please complete the presentation with a wiring diagram including the cell types, their properties, distribution and connections, summarizing the take-home message visually (akin to a graphical abstract).

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

Thank you for resubmitting your work entitled "Anatomical Organization of Presubicular Head-Direction Circuits" for further consideration at eLife. Your revised article has been favorably evaluated by Timothy Behrens (Senior editor), and a Reviewing editor in consultation with the reviewers.

The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

The reviewers found the article adequately revised but one reviewer had the following recommendations. The reviewer found the additional data and figures particularly useful and recommended that one of the sub-parts of Figure 1—figure supplement 1 (micrograph plus line drawing) be moved to the main paper to help the readers visualize the anatomy. Also this reviewer suggested that the authors add a wiring diagram including the cell types, their properties, distribution and connections, summarizing the take-home message visually (akin to a graphical abstract).

Major issues:

1) The authors have showed that Layer 3 cells project to the MEC, using both histological reconstruction and retrograde labeling. Based on the reconstruction of 8 identified HD cells, they show quite clearly that they target mainly the superficial layers of the MEC. This is one of the most important findings of the manuscript. Indeed, this is surprising and not really expected, as the authors admitted themselves, as (i) HD cells are more prominent in the deep layers of the MEC than in the superficial layers (where they are virtually absent) and (ii) a previous report (Tukker et al., 2015; but only one reconstructed axon was shown there) reported a projection from PreS layer 3 HD cell to the deep layers. Why haven't the author tried an anterograde labeling from the PreS to demonstrate definitively their claim?

First point; we agree with the Reviewers that the present findings are somewhat ‘surprising’, in light of the sparseness of strong head-directionality among MEC L3 neurons (Giocomo et al., 2012; Tang et al., 2015; but see Sargolini et al., 2006; Boccara et al., 2010). Our findings are however not incompatible with existing data since (i) as we pointed out in the discussion, our data do not exclude synapses being made on the apical dendrites of deep-layer neurons (see for example Canto and Witter, J Neurosc 2012) and (ii) grid cells from MEC L2/3 have indeed been shown to receive HD inputs (Bonnevie et al., 2013). These points are referred to in the discussion of the revised manuscript. Second point; we would like to specify that in our previous study (Tukker et al., 2015) a single axon ‘could be traced till the deep layers of MEC’, but did not terminate there (i.e. no terminal branching or axonal boutons were described). Hence, it is likely the single axon of Tukker et al. was en route towards L3 – as the present work (Figure 4), our new tracing experiments (see Author response image 1) and previous work indicates (Caballero-Bleda and Witter, 1993, Honda and Ishizuka, 2004). Third point; we have performed the anterograde tracing experiments suggested by the Reviewers (see Author response image 1). In line with our single axonal reconstructions, the large majority of axons and boutons were indeed observed within MEC L3 (Author response image 1).

Due to an already large supplementary material, we have not included these data in the revised manuscript. We however refer to this point in the Results section and cite the relevant literature (Caballero-Bleda and Witter, 1993,Honda and Ishizuka, 2004). If the Editor/Reviewers feel these data should be included in the revised manuscript, we will be happy to do so.

We have addressed this comment by specifying in the revised manuscript that ‘it remains to be established whether MEC L3 neurons are indeed the prime recipient of H D inputs (see Canto and Witter, 2012) (Discussion). In the results we state that ‘the layer-selective branching pattern of the reconstructed single axons is in line with anterograde tracing experiments, which showed that most Pre S afferents are observed within MEC L3 (Caballero Bleda and Witter, 1993, Honda and Ishizuka, 2004 an d data not shown)’

Do only HD cells from layer 3 project to the MEC or all cells from layer 3? (i.e. did the authors have reconstructed the axons of non-HD cells from PreS layer 3)? Did these 8 HD cells have strong HD index?

All axons which could be traced till MEC (n=8) carried a significant amount of HD (p <0.05; median H D index, 0.9; range 0.64 – 0.96). We note however that given the small dataset of identified long-range axons, it cannot be concluded that HD signals re the sole input reaching the downstream MEC.

We specify in the revised manuscript that ‘[…]8 long-range axon al projections from identified HD cells could be recovered (median HD index, 0.9; range 0.6 4 – 0.96, n= 8; Figure 4D)’ (Results).

2) The authors did not adequately describe the apparatus used for the head-fixation. Were the animals free to run on a treadmill or on a wheel? If so, did the author had access to the speed of the animal? This is a clear limitation of the head-fixed experiment compared to freely moving juxtacellular recording (again, Tukker et al., 2015). The fact that Layer 2 neurons are theta modulated suggests that they may be modulated by speed, and that will be the demonstration of a nice functional and anatomical segregation between the HD and speed signals. Perhaps the authors should first try to correlate the firing rate with angular speed?

First, we apologize for not having provided sufficient details about the passive-rotation procedures (see also response to comment 11 below). We have now added more information in the revised Methods, and provide a video of a representative HD cell recorded during passive rotation (Video 1).

Second, we specify that our rats were not on a treadmill, and hence we cannot correlate spiking activity to the animal translational movement. For clarity, we now state in the revised manuscript that under our preparation, theta-activity most likely reflects immobility-related type-II theta, as previous work on passively-rotated rats has indicated (Shin et al., 2010). Following the Reviewers’ suggestion, we have correlated neuronal activity to angular velocity. We followed the criteria of Kropff et al. (2015) for defining significantly speed-modulated neurons (see details in the revised Methods). We found that only very few identified principal neurons were significantly modulated by angular velocity (4 out of 48), which prevented statistical comparison between L2 and L3 neurons (of note, the proportion of modulated neurons did not significantly differ between L2 and L3: 2/11 and 2/25, respectively; p=0.5, Fisher’s exact test). On the other hand, the majority of FS interneurons was significantly modulated by angular velocity (13 out of 20; p<0.05). We refer to this analysis in the revised manuscript.

We have addressed this comment by providing quantitative details about the passive rotation procedures (Results) “‘Animals were head-fixed on a rotating platform and, and body-centered rotations were manually performed by the experimenter (see video 1). Within the same recording, animals were rotated both clockwise and counterclockwise (average number of inversions, 6.6 ± 4.7; n=310 recordings) and average accelerations (1.3 ± 0.8 rad/s2), decelerations (-1.1 ± 0.7 rad/s2) and angular velocities (1.1 ± 0.4 rad/s) were within the physiological ranges reported by previous studies (…)”; For clarity, we specify that ‘animals were not actively moving during passive rotation’ (Results). We have also added one representative video of a HD cell recording (Video 1). We refer to the speed-modulation of FS INs in the Results ‘The majority of FS interneurons (13 out of 20) were significantly modulated by angular velocity (see Methods) and fired at higher rates during rotation compared to resting periods (Figure 2 —figure supplement 1C’).

3) The higher theta rhythmicity in layer 2 was mostly explained by a few strongly theta modulated cells (Figure 7C). Is there any evidence that these cells were different from the others? Were they all excitatory pyramidal or stellate cells or is there a chance that some were interneurons? By the way, have the authors recorded from any interneurons in the course of this study?

To address this point, we have performed new experiments and added additional recordings from morphologically and cytochemically identified L2 and L3 neurons. The revised Figure 6 contains identified principal neurons (see Figure 6—source data 1, reconstructions in Figure 6A and Author response image 2, and the representative micrographs of spiny dendrites in Figure 6B). The conclusions are in line with the previous manuscript, i.e. theta-rhythmicity is stronger among L2 neurons.

Author response image 2.
Dendritic morphologies of L2 neurons.

We agree with the Reviewers that the difference in theta-rhythmicity can be explained by few cells; in general however, and consistent with previous work (Taube 1990a, Blair and Sharp 1996, Tukker 2015) theta-rhythmic responses were very sparse among PreS neurons – principal cells as well as interneurons (Figure 6D,E and Figure 2—figure supplement 1D-F). To strengthen our theta-rhythmicity finding, we performed a statistical analysis along the lines of Yartsev et al. (2011). Briefly, for each trial of the shuffling procedure, individual spike times were randomly time-shifted. For each permutation, the theta index was calculated and the procedure reiterated 1000 times. The significance value for each cell was assessed based on the resulting null distribution, i.e. a neuron was defined as significantly theta-rhythmic if the theta index was > 95th percentile of its corresponding null distribution. We found that the only significantly theta-rhythmic discharges among principal neurons were indeed contributed by L2 cells (4 out of 4). The results of this analysis are now referred to in the revised manuscript.

To address the Reviewers’ comment, we have reconstructed the morphology of the four neurons with highest theta-rhythmicity (theta-index>5; Author response image 2A) and two neurons with low theta- rhythmicity (theta-index<2; Author response image 2B) [the remaining neurons did not display complete morphology due to incomplete filling, and hence were not included in the morphological analysis].

We can make the following observations: (i) no obvious morphological differences are apparent within these two groups (as assessed by total dendritic length and dendritic complexity index; see Author response image 2C), and (ii) theta-rhythmic responses were observed in both Cb+ and Cb- neurons (we note the striking similarity with MEC, where also both Cb+ and Cb- neurons can express theta-rhythmic firing, albeit with different proportions; Ray et al., 2014). It is important to specify that at present we cannot resolve structure-function relationships within L2, since our dataset of identified L2 neurons is relatively small. We specifically mention this point in the revised manuscript, and state that this remains an open question (see also response to comment 5 below).

As for interneurons; we performed new experiments, and included recordings from identified (n=3) and putative (n=17) fast-spiking (FS) interneurons in the revised manuscript. Results of the experiments are shown in Figure 2 —figure supplement 1. Briefly, we show that FS interneurons can be reliably classified based on firing rate and spike width criteria, which were confirmed by cell identification (n=3 morphologically identified FS interneurons; see Figure 2—figure supplement 1A and E). In our dataset we made the following observations: first, weakly but significantly modulated HD responses are contribute d by FS interneurons (3 out of 20; along the lines of Tukker et al., 2015), which were significantly stable between the two halves of the recording (stability analysis is referred to in the revised manuscript). Second, theta-rhythmicity was very sparse among FS interneurons. We also show one identified ‘theta cell’, which corresponded to a paravalbumin (PV) -positive interneurons; we thus extend previous observations and show that the sparse ‘theta-cells’ with the PreS (c.f.r. Taube 1990a, Blair and Sharp 1996) and are likely to correspond to a subset of PV-positive interneurons. Third, spiking activity of FS interneurons was strongly modulated by rotational movement. The results of these experiments are shown in Figure 2—figure supplement 1 and referred to in the text.

Our dataset also includes n=3 identified regular-spiking interneurons; however, given the overlap with the regular-spiking principal cell class (which is expected, given their broad AP features; see Figure 2—figure supplement 1A) we do not explicitly refer to this class in the revised manuscript (directional tuning of these neurons is however shown in Figure 2—figure supplement 1B).

We have addressed this comment by adding one supplementary figure (Figure 2—figure supplement 1), revising Figure 6 and performing new analysis. We refer to the theta-analysis and the firing properties of FS INs in the revised manuscript.

4) Following up on the previous point, could the authors report more detailed descriptions of the cells they recorded within the two layers: average firing rate (partially reported in the text), peak firing rates for HD cells, waveform width, etc.

We now provide a table which summarizes the electrophysiological properties of L2 and L3 cells (Figure 6-source data 1), and show the comparisons of spike-waveform properties, head-directionality and theta rhythmicity in the revised Figure 6. The results of this analysis are now referred to in the manuscript. We would like to point out that, following the reviewers’ suggestions, we have indeed found that L2 and L3 identified neurons display very different spike waveforms. Such differences are now shown in the revised Figure 6F,G and we believe they could be instrumental for future classification of tetrode-recorded units. We thank the Reviewers for this comment, as it gave us the opportunity to provide a novel insight into the electrophysiological characteristics of PreS neurons.

We have addressed this comment by performing new experiments and analysis (see revised Figure 6), adding a supplementary data (Figure 6—source data 1) and reporting average and peak firing rates of our HD cells (n=186). These data are referred to in the Results.

5) Is there a relationship between calbindin expression and theta rhythmicity? As the authors reported that these two classes of cells have different output, it will be interesting to show that they are also functionally segregated.

This comment is in line with the previous comment 3 (see corresponding response above). As we stated above, at present we cannot resolve whether theta-rhythmicity in PreS L2 is cell-type specific, as theta-rhythmic responses were observed in both classes (we note the striking similarity with MEC, where also both Cb+ and Cb- can express theta-rhythmic firing, albeit with different proportions; Ray et al., 2014). We quantified and compared theta-rhythmicity among Cb+ and Cb- neurons, and reported the results of this analysis in the revised manuscript (see below). We point out that in the present paper we focus on laminar differences (L2 versus L3) and that the impact of structural heterogeneity of L2 neurons remains an open question.

We have addressed this comment by performing new experiments and analysis (see revised Figure 6D,E), the results of which are referred to in the revised manuscript (Results): ‘Theta-rhythmic spiking patterns were contributed by both calbindin-positive and calbindin-negative neurons (Figure 6E), and average theta-indices did not differ significantly between the two cell classes (calbindin-positive, 2.3 ± 2.3, n=3; calbindin-negative, 3.8 ± 2.5, n=6; p=0.54; we note however that the small dataset of identified calbindin-positive neurons prevents rigorous assessment of structure-function relationships)’.

6) The experiments described were performed in head-fixed rats with passive rotation. Such an experimental design has been used before for thalamic recordings, which showed that head-direction cells can be observed under such conditions, but some differences seem to exist to free movement. Because the entire manuscript is based on this preparation, a control experiment for presubicular recordings in the set-up used here should be performed and some neurons should be recorded consecutively during passive rotation and free movement. Of course, this does not require the difficult juxta recording and labelling of the neurons, but could be done with tetrodes or silicon probes, which give more stable recordings and many cells can be recorded simultaneously. This experiment is well within the expertise of the authors and could be done relatively quickly. Importantly, it would give a quantitative measure how the same neurons fire according to head-direction in passive and free movement. This would answer if the same neurons are head-direction cells and how their head-direction tuning changes under both conditions.

We agree with the Reviewers that, although previous work indicated that HD firing is largely preserved under passive rotation, such control experiments would greatly strengthen our methodological approach and conclusions of the present work. We have thus performed a subset of juxtacellular recordings, where we have sequentially monitored the activity of the same neurons during passive rotation and free behavior [of note: we opted for juxtacellular instead of extracellular recordings because (i) they allow direct comparison with recordings of the present work, which all stem from the juxtacellular configuration and (ii) we are currently not setup for performing tetrode/silicone probe recordings].

We have employed miniaturized equipment for performing juxtacellular recordings in freely-moving animals (Tang et al., 2014), and in a subset of cases (n=4) we were able to (i) obtain a recording from a HD cell, (ii) record it during passive rotation, (iii) release the animal from the head-fixation (without losing the recording) and (iv) monitor the activity of the same HD cell during free behavior. We note this is a particularly challenging procedure, and it is the first time that juxtacellular recordings could be transferred from head-fixation to the freely-moving condition; we think that methodologically this is a potentially interesting extension of our juxtacellular procedures.

The results of these experiments demonstrate that the general tuning properties of HD cells are very similar between passive-rotation and free behavior (mean correlation coefficient of the HD tuning curves, 0.68 ± 0.20, p<0.05; n=4). We show one of these recordings in the revised Figure 2 and report correlations values in the main text. These data thus confirm that bona fide HD cells can be recorded during passive-rotation. We thank the Reviewers for this suggestion, as we think this is an important addition to our work.

To address this comment we have performed new experiments, the results of which are shown in the revised Figure 2D,E and referred to in the revised manuscript (Results): ‘To further confirm that bona fide HD cells can be recorded under passive rotation, in a subset of recordings (n=4) we sequentially monitored the activity of the same HD cells during head-fixation and free-behavior. To achieve this, we used miniaturized recording equipment (Tang et al., 2014), which allowed us to release the rats form head-fixation while maintaining the juxtacellular recording during free movement. As shown in the representative recording in Figure 2D, the general tuning properties of the HD cells were very similar between passive-rotation and free behavior (Figure 2E; mean correlation coefficient of the HD tuning curves, 0.68 ± 0.20, p<0.05; n=4)’.

7) In the Introduction the authors lay out their aim with: "Specifically, it is currently unknown how HDcells are anatomically organized within the PreS, and whether they project to MEC, as long speculated by computational models (see Giocomo et al., 2014 for review)." However, in a previous paper – the corresponding author of present manuscript was a co-auhor in this older paper – they say "..our data do indicate that at least a subset of the MEC-projecting pyramidal cells in layer 3 of the presubiculum is HD" (Tukker et al., J Neurosci 2015). A fair presentation of what has been achieved previously is necessary and should also be reflected in the significance statement.

Along with the Reviewers comment, we have changed the Introduction and Discussion accordingly.

We have addressed this comment by revising the corresponding manuscript text. Specifically, we state that ‘a previous study has indicated that HD inputs reach the MEC (Tukker et al., 2015)’ (Introduction) and that our study ‘complements earlier evidence (Tukker et al. 2015)’ (Discussion).

8) For the presented data, it is key to define the exact border between layer 2 and layer 3, which is not trivial. This should be shown with clear examples and a better description on how exactly it was decided for neurons that were located close to the border.

We agree with the Reviewers that, although in principle we are very confident about theaccuracy of our layer-assignment (which we confirmed by anatomical verification of the recording sites and by cell identification, as stated in the previous version of the manuscript) we acknowledge that there is inevitably a margin of error, especially for neurons located ‘close to the border’.

To address this point rigorously, we have performed a larger number of recording/labeling experiments and we now base all conclusions on morphologically-identified neurons (see revised Figure 6 and Figure 6—source data 1). These conclusions are in line with the previous manuscript. Our previous Figure 5, which was partially based on putatively-assigned recordings, has been removed from the revised manuscript.

We thus believe that there are no issues of layer assignment in the revised manuscript. Having the neurons identified, and a marker (calbindin) which labels PreS L2, makes it is trivial to assign neurons to the layer of origin (we note the analogy with MEC, where layer 2/3 boundary is also clearly demarcated by the calbindin staining; see previous own work e.g. Ray et al., 2014; Tang et al., 2014; Tang et al., 2015).

To address this comment, we have performed new experiments, the results of which are presented in revised Figure 6, Figure 6—source data 1 and referred in the corresponding sections of the results.

9) How was the rotation speed compared between different experiments?

Animals were manually rotated by the experimenters (see Video 1); hence rotation was not systematically controlled across experiments. Nevertheless, we show that rotation speed, accelerations and number of inversions did not differ between L2 and L3 recordings, and hence cannot account for the (strong) electrophysiological differences between L2 and L3 neurons.

To address this comment we have performed new analysis, the results of which are referred to in the revised manuscript (Results): ‘The electrophysiological differences between L2 and L3 neurons were not accounted for by biases in rotational parameters, since average angular velocities (L2, 0.96 ± 0.31 rad/s; L3, 0.96 ± 0.33 rad/s; p=0.8), accelerations (L2, 1.41 ± 0.82 rad/s2; L3, 1.24 ± 0.89 rad/s2; p=0.4) and decelerations (L2, -1.27 ± 0.74 rad/s2; L3, 1.12 ± 0.81 rad/s2; p=0.3) were not significantly different between L2 (n=11) and L3 (n=25) recordings’.

10) For the physiological identification of layer, a histological example of a lesion should be shown. Is it really possible to make such a small lesion to determine the border?

This comment is in line with the comment 8 (see corresponding response above). We would like to specify that electrolytic lesions were performed in a preliminary set of experiments, were we explored the electrophysiological signatures of L2. It was sufficient for us to see that lesions were centered in (but not necessarily restricted to) L2 (as shown in Author response image 3A), or located at the expected distance from it (as shown in Author response image 3B; we also show an example of a ‘recording site’, i.e. where cell identification failed but the laminar location of the recording site could be assigned to L2). Lesions and ‘recording sites’ were thus not used for routine assignment of recordings to layers, but they were instrumental for our initial assessment of the L2 location and for subsequent targeting juxtacellular recording to this layer. The corresponding section of the Results has been clarified accordingly.

Author response image 3.
Representative electrolytic lesions and ‘recording site’, which aided identification of PreS L2 in a subset of preliminary experiments.

In response to this (and the above) comments, we undertook a rigorous approach: we identified a larger number of neurons and now base our conclusions on morphologically identified cells (see revised Figure 6 and Figure 6—source data 1). We have thus removed our previous Figure 5, and we do not include putatively- assigned recordings in the revised manuscript. We thus believe that there are no issues of layer assignment in the revised manuscript (see also response to comment 8 above). We thank the Reviewers for this comment, as we believe it gave us the opportunity to greatly strengthen the conclusions of our work.

We have addressed this comment by performing new experiments, the results of which are presented in the revised Figure 6. We have also removed the previous Figure 5, and L2/L3 comparisons are now based on identified neurons (see revised Figure 6). We have also clarified this issue in the revised results, where we state that electrolytic lesions were performed for assessing the location of L2 in a preliminary set of experiments (see also Methods).

11) It would be useful to get a slightly better picture of where exactly in presubiculum the study was done, perhaps with a zoomed-out anatomical illustration, and location on an atlas, so that the exact region is more obvious for anyone who might want to pursue this further.

We provide a better overview and low-magnification pictures of the dorsal PreS (where thisstudy was performed; Figure 1—figure supplement 1) along with a number of molecular and histochemical markers which outline the PreS borders (Figure 1—figure supplement 2).

We have addressed this comment by including 2 supplementary figures (Figure 1—figure supplement 1 and Figure 1—figure supplement 2). The results of these experiments are referred to in the revised text (Results).

The analysis is focused on MEC but the interconnections with RSC are also very important to understand, as the authors note in the discussion, and the impact statement could be adapted to include this. We would like to know more about which part of RSC (e.g. AP location, layer etc) was targeted and exactly what the labelling patterns were.

We provide now a better overview of which portion of RS cortex was targeted for retrograde tracer injections. First, we show how this region and the corresponding border with PreS can be reliably outlined by a number of markers and histochemical stainings. Second, we show representative injection sites. Third, we show the corresponding labeling pattern within the contralateral PreS and a quantification of retrogradely-labelled neurons across PreS layers. These results are shown in Figure 1—figure supplement 2 and figure supplement 3 and referred to in the text.

We have addressed this comment by including 2 supplementary figures (Figure 1—figure supplement 2 and Figure 1—figure supplement 3). The results of these experiments are referred to in the revised text (Results) and the revised Methods.

We also need a lot more details about the behavioural manipulation – how was the animal rotated, with what angular acceleration and velocity, how many reversals, what visual cues were available, etc.

We provide these details in the revised manuscript (Results and Methods, see below). For clarity, we also show a video of a representative HD cell (Video 1). We have also performed additional analysis, and provide average values of angular acceleration and deceleration, angular velocity and number of reversals (see below). As for the available visual cues, we specify that bot habituation to head fixation/rotation and experiments were performed in the ‘cue-rich’ environment of the laboratory setting. Under dim illumination, rats had thus visual access to both proximal cues (e.g. computer screens, cold-light source, stereomicroscope) and distal cues (e.g. Faraday cage, ceiling, curtains), including the experimenter, which was always located in the same relative position during the passive rotation experiment. These details are now referred to in the text.

We have addressed this comment by performing new analysis, the results of which are referred to in the revised manuscript (Results): ‘Animals were head-fixed on a rotating platform and, and body-centered rotations were manually performed by the experimenter (see Video 1). Within the same recording, animals were rotated both clockwise and counterclockwise (average number of inversions, 6.6 ± 4.7; n=310 recordings) and average accelerations (1.3 ± 0.8 rad/s2), decelerations (-1.1 ± 0.7 rad/s2) and angular velocities (1.1 ± 0.4 rad/s) were within the physiological ranges reported by previous studies’. We also provide a video of a representative HD cell (Video 1) and more details about the available cues in the revised Methods: ‘Habituation and recordings were performed under slightly-dimmed ambient illumination in the ‘cue-rich’ environment of the laboratory setting. Thus both during habituation and recordings, rats had visual access to both proximal cues available in the immediate vicinity (e.g. computer screens, cold-light source, stereomicroscope, etc…) and distal cues (i.e. Faraday cage, ceiling, curtains, etc…), including the experimenter, which was always located in the same relative position during the passive rotation experiment. These cues were thus the most likely source of ‘anchoring’ stability to HD firing (see e.g. Knierim et al., 1995 for review)’.

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

Essential revisions:

1) The additional data and figures are particularly useful. Please include one of the sub-parts of Figure 1—figure supplement 1 (micrograph plus line drawing) in the main paper, to help the reader visualize the anatomy.

In line with the Reviewers’ comment, we have added one panel to our revised Figure 1 (new Figure 1A).

2) Please complete the presentation with a wiring diagram including the cell types, their properties, distribution and connections, summarizing the take-home message visually (akin to a graphical abstract).

We have made such diagram. This diagram could be included as Figure 6 —figure supplement 1 (we explored alternative options –e.g. adding it to our current Figure 6- but we find it difficult to include it as part of existing figures without significantly compromising their size/resolution).

However, we feel that this schematic representation is rather redundant and adds too little information for justifying its inclusion as a stand-alone figure. Moreover, it will increase our already-large number of supplementary items. We would therefore prefer not to include the diagram in the revised manuscript. However, if the Reviewers/Editor feel it is necessary, we will include it and upload it as Figure 6 —figure supplement 1.

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

The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

The reviewers found the article adequately revised but one reviewer had the following recommendations. The reviewer found the additional data and figures particularly useful and recommended that one of the sub-parts of Figure 1—figure supplement 1 (micrograph plus line drawing) be moved to the main paper to help the readers visualize the anatomy. Also this reviewer suggested that the authors add a wiring diagram including the cell types, their properties, distribution and connections, summarizing the take-home message visually (akin to a graphical abstract).

In line with the Reviewers’ comment, we have added one panel to our revised Figure 1 (new Figure 1A).

We have uploaded the diagram as Figure 6 —figure supplement 1


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