The cortex is divided into two hemispheres that do not function independently. Rather, they are connected by commissural fibers, most notably the corpus callosum which is thought to coordinate function across the brain (Gazzaniga, 2000; Innocenti et al., 2022; Ocklenburg and Guo, 2024; Zhou et al., 2013). Within these circuits feedforward and feedback pathways represent two fundamental types of information flow (Berezovskii et al., 2011; Markov and Kennedy, 2013b). In the case of sensory processing, feedforward connections typically carry sensory input toward areas higher in cortical hierarchy where more complex processing occurs (Felleman and Van Essen, 1991; Mumford, 1992; Rockland and Pandya, 1979; Siegle et al., 2021). Conversely, cortical feedback typically originates in higher-order areas and projects back to brain areas of lower hierarchical rank (Felleman and Van Essen, 1991; Markov et al., 2014; Rockland and Pandya, 1979). These pathways are believed to be crucial for modulating sensory processing (Weiler et al., 2024), enhancing signal fidelity (Xu et al., 2012), integrating contextual information (Zhang et al., 2014), and forming predictions (Keller and Mrsic-Flogel, 2018; Leinweber et al., 2017; Rao and Ballard, 1999).

Based on its cytoarchitecture the mammalian neocortex contains up to six layers that are believed to play distinct roles in feedforward and feedback processing (Harris et al., 2019; Markov et al., 2013a; Markov et al., 2014). For instance, retrograde tracing (Markov et al., 2014) and physiological analysis (Bastos et al., 2015; Buffalo et al., 2011) in the visual cortical system of primates indicate that supragranular layers are the main source of feedforward projections while infragranular layers are the main source of feedback input. Moreover, the ratio of supra- to infragranular layer projections has been used to reveal the anatomical basis of visual cortical hierarchy in primates and mice (Barone et al., 2000; D’Souza et al., 2022; Markov et al., 2014; Yao et al., 2023). While it is established that functional cortical hierarchy (at least in the visual system) reflects the laminar organization of cortical input within the ipsilateral hemisphere, it remains unknown how this is combined or even reflects the organization of input from the contralateral hemisphere. More specifically, to date there remains no cortex-wide anatomical analysis that investigates the nature of circuit hierarchy onto a given area that arises from both hemispheres. Also, which cortical layers are responsible for the establishment of the intra- versus the interhemispheric cortical hierarchy is not understood.

In this study, we utilized state of the art retro-AAV-based neuronal tracing in adult mice to determine the anatomical location of input neurons and map the cortex-wide projectome onto the primary visual (VISp), the primary somatosensory barrel field (SSp-bfd), and the primary motor (MOp) cortices. We employ an anatomically based hierarchy metric that not only enables us to define the contribution of Layer 2/3 (L2/3) and the infragranular layers but also enables us to disassociate the roles of Layer 5 (L5) and L6 in the organization of cortical feedback circuits. Our results indicate extensive and symmetric projection patterns across the two hemispheres and reveal a key role for L6 in routing cortical feedback information.

To systematically map the cortical projections onto primary sensory and motor cortical areas in adult mice, we utilized retrograde tracing with a recombinant AAV-variant, AAV-EF1a-H2B-EGFP (nuclear retro-AAV), which is taken up by axon terminals (Tervo et al., 2016) and results in EGFP expression in the nuclei of projection neurons (Figure 1A, Figure 1—figure supplement 1A). This tracer was injected in either VISp (n = 6), SSp-bfd (n = 6), or MOp (n = 6), spanning across all cortical layers of each target area (Figure 1A, Figure 1—figure supplement 2, Figure 1—figure supplement 3). Importantly, only brains that had viral transduction levels of the white matter below 0.1% of the total bolus volume were included (Figure 1—figure supplement 2B). Following ex vivo two-photon tomography (Ragan et al., 2012) and 3D brain registration (Niedworok et al., 2016) detected cell nuclei (Tyson et al., 2021) were assigned according to the cortical areas of the Allen Mouse Brain Common Coordinate Framework (Claudi et al., 2020; Wang et al., 2020, CCFv3, Figure 1B, excluding the targeted injection area). We found that the vast majority of neurons (>99%) projecting to all target areas were non-overlapping with GAD-expressing cells (Figure 1—figure supplement 4A). Regarding L6 projection neurons, they were also found to be non-overlapping with NTSR1-expressing L6 corticothalamic cells and therefore indicative of Layer 6 corticocortical cells (L6 CCs) (Figure 1—figure supplement 4B, C).

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The areal and modular organization of cortical input onto VISp, SSp-bfd, and MOp

The resultant projection maps revealed labeling of several hundred thousand neurons located throughout both cortical hemispheres (Figure 1—figure supplement 1B), with approximately 80% located ipsilaterally and 20% contralaterally (Figure 1B, C, p < 0.05, two-sided Wilcoxon signed-rank test), irrespective of identity of the target injection site. While all three target areas received ipsilateral input from almost all cortical areas (VISp, range: 41–44, n = 6; SSp-bfd, range: 43–44, n = 6, MOp, range: 33–39, n = 6, Figure 1D) the two sensory cortical targets received input on average from more areas than the primary motor cortex (Figure 1D, sensory = 43.58 ± 0.26, n = 12 vs. motor 36.67 ± 0.99, n = 6; p < 0.001, two-sided Wilcoxon rank-sum test). Comparing the inputs from both hemispheres showed that VISp and MOp injections revealed partial asymmetry in the number of areas labeled per hemisphere (Figure 1D, VISp ipsilateral = 43.33 ± 0.49 vs. VISp contralateral 38.33 ± 0.72, MOp ipsilateral = 36.67 ± 0.99 vs. MOp contralateral 30.67 ± 0.67, p < 0.05, signed-rank test), whereas the source of input to SSp-bfd appeared to be mirrored across the two hemispheres (Figure 1D, SSp-bfd ipsilateral = 43.83 ± 0.17 vs. SSp-bfd contralateral 42 ± 1.61, p = 0.5, two-sided Wilcoxon signed-rank test).

Importantly, we found there to be no instance where a projection area in the contralateral hemisphere did not have an ipsilateral counterpart. These data show that both primary sensory and motor cortices receive an abundance of functionally diverse input from cortical areas outside their primary contralateral (homotopic) area indicating significant cross-modal integration within and between the two hemispheres (Figure 1E).

To understand the relative contribution of a given area to the projectome for each hemisphere we performed a correlation analysis on the relative fraction of labeled cells per area normalized to the total hemispheric count. Excluding the homotopic target area, that always contained the highest number of cells per area, but including all the cases where the number of cells in an area exceed ten in at least three mice (see Methods), we found a strong correlation between the fractional count of neurons in a given ipsilateral brain area with its contralateral counterpart (VISp R² = 0.74 ± 0.02, p < 0.05; SSp-bfd R² = 0.64 ± 0.1, p < 0.05; MOp R² = 0.83 ± 0.03, p < 0.05, linear regression fit, Figure 1E, F). This relationship was observed independent of the target identity (Figure 1F, G). When directly comparing the within hemisphere relative projection weights of the individual cortical areas across the two hemispheres, we found that 33/40 (VISp), 44/44 (SSp-bfd), and 29/33 (MOp) were not significantly different from one another which indicates significant bilateral symmetry in the relative contribution of a given area to its hemispheric projectome (Figure 1G, individual one-sample t-tests on contra–ipsi difference, Bonferroni multiple comparison correction).

Based on their degree of inter-areal cortical connectivity it has been suggested that the mouse neocortex consists of six anatomical modules referred to as prefrontal, lateral, somatomotor, visual, medial, and auditory (Figure 2A, Harris et al., 2019). To determine whether the areal projections reflect any underlying modular organization we next analyzed the distribution of projection neurons according to their respective module. First, while the VISp projection was heavily dominated by input from the visual module (Figure 2B, ipsilateral visual module fractional count 0.42 ± 0.02 vs. lateral module 0.19 ± 0.02; contralateral visual module 0.42 ± 0.03 vs. lateral module 0.22 ± 0.02, p < 0.001, two-sided unpaired t-test), both the SSp-bfd and MOp targets received input predominantly from the somatomotor module (Figure 2B, SSp-bfd: ipsilateral somatomotor module fractional count 0.62 ± 0.05 vs. visual module 0.16 ± 0.03, contralateral somatomotor module 0.53 ± 0.02 vs. lateral module 0.24 ± 0.02, p < 0.001; MOp: ipsilateral somatomotor module 0.83 ± 0.02 vs. lateral module 0.08 ± 0.01, contralateral somatomotor module 0.71 ± 0.03 vs. lateral module 0.14 ± 0.01, p < 0.001, two-sided unpaired t-test). For both the visual module projection onto VISp and the somatomotor module projections to SSp-bfd and MOp there were similar contributions from the majority of the underlying areas (Figure 2C). Second, although both VISp and SSp-bfd received significant input from all modules in both hemispheres, we find there to be almost no input onto MOp from the visual, auditory, and medial modules in either hemisphere (Figure 2B, less than 0.01 fractional count for each of these three modules). Finally, there also appears to be biases in the relative density of projections. For example, we find that the lateral module in the contralateral hemisphere projecting to VISp is more strongly weighted than its ipsilateral counterpart and that this is driven primarily by the connection from the temporal association area (TEa) and ectorhinal cortex (ECT) (Figure 2B, C, lateral module ipsilateral 0.19 ± 0.02 vs. contralateral 0.22 ± 0.02, p = 0.05, one-tailed paired t-test). While this contralateral dominance of the lateral module also emerges from the projection profiles to SSp-bfd and MOp it is rather mediated by many, albeit less dominant, lateral module areas (Figure 2C, SSp-bfd: lateral module fractional count ipsilateral 0.1 ± 0.01 vs. contralateral 0.24 ± 0.02, p < 0.001, one-tailed paired t-test, MOp: lateral module ipsilateral 0.08 ± 0.01 vs. contralateral 0.14 ± 0.01, p < 0.01, one-tailed paired t-test).

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The laminar organization of cortical input to VISp, SSp-bfd, and MOp

Next, we asked whether there were specific subsets of projection neurons that might differentially contribute to the local and global projection by quantifying the distribution of neurons across all cortical layers in both hemispheres (Figure 3A1–A4). First, for each injection target we find that the majority of detected neurons were located in L2/3, L5, and L6a (Figure 3B) with a very low fraction of labeled neurons in L4 and L6b. To begin to explore the laminar structure in the input to the three target areas we next compared the relative dominance of these three main layers. Regardless of hemisphere, L2/3 was found not to be the dominant layer of inter-areal input (Figure 3C1, C2, D1, D2). For VISp and MOp L6 dominated both the intra- and interhemispheric projection (Figure 3C1, C2, D1, D2, p < 0.01, one-way ANOVA, Tukey–Kramer multiple comparison correction). In the case of SSp-bfd, L5 and L6 dominated the contralateral input (Figure 3C2, D2, L5 vs. L2/3 and L6 vs. L2/3, p < 0.01, one-way ANOVA, Tukey–Kramer multiple comparison correction) and shared dominance with L2/3 only for the ipsilateral projection (Figure 3C1, D1, L5 vs. L2/3, p = 0.06; L6 vs. L2/3, p = 0.64, one-way ANOVA, Tukey–Kramer multiple comparison correction). When pooled across target areas, we find that the majority of projection source areas display L6 dominance, followed by L5 with only a small fraction of areas exhibiting L2/3 dominance (Figure 3E, p < 0.05, one-way ANOVA, Tukey–Kramer multiple comparison correction). These data show that L6 CCs are a key player mediating intra- and interhemispheric connectivity onto primary sensory and motor areas.

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Cortical input projections onto VISp, SSp-bfd, and MOp reflect a hierarchical organization

In primates, the laminar distribution of projection neurons has been used to interpret the degree to which corticocortical networks might be feedforward or feedback (Barone et al., 2000; Markov et al., 2014; Vezoli et al., 2021). A predominance of incoming projection neurons from supragranular layers (L2/3) signifies a feedforward connection, whereas a higher proportion in infragranular layers (Layers 5 and 6) is considered to reflect a feedback projection (Figure 4A). Additionally, cortical areas with a higher proportion of projection neurons in infragranular, compared to supragranular layers, are suggested to have a higher hierarchical rank (Figure 4A). Thus, the hierarchical rank of a specific projection area can be estimated by calculating the fraction of infragranular labeled neurons (fILN) (Figure 4A, B). Previously in the mouse visual cortex, similar anatomical measures of hierarchy have been performed using anterograde tracers (D’Souza et al., 2022) and modified retrograde rabies virus (Yao et al., 2023) to identify either target lamina or presynaptic cell populations. Using retrograde AAV-EF1a-H2B-EGFP and by detecting EGFP expression in the nuclei of projection neurons we find a very similar hierarchical ranking of the higher cortical visual areas as previously shown (Figure 4—figure supplement 1, D’Souza et al., 2022; Siegle et al., 2021; Yao et al., 2023).

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Independent of the target area, the average fILN for both hemispheres indicates that cortical input onto VISp, SSp-bfd, and MOp reflects predominantly a feedback organization (Figure 4C). However, on average, and compared to the ipsilateral projection, the average fILN of the contralateral hemisphere is larger across all injection targets (Figure 4C, p < 0.05, one-sided paired t-test, respectively). Moreover, the overall contralateral input appears more narrowly distributed in its degree of anatomical hierarchy, maintaining relatively high fILN values across all brain areas (Figure 4C, D; fILN range ipsilateral: 0.42 ± 0.1 to 1.0 ± 0.0 vs. contralateral: 0.66 ± 0.07 to 1 ± 0). As a consequence, regardless of the target area, we found a significant negative correlation between the areal fILN values on the ipsilateral side and the magnitude of the difference in the fILN of their contralateral counterpart (Figure 4E, VISp: r = –0.71 ± 0.07, SSp-bfd: r = –0.7 ± 0.04, MOp: r = –0.77 ± 0.04, p < 0.05, Spearman correlation) although the ranking of contralateral hierarchy remained similar to that of the ipsilateral hierarchy (Figure 4F, ipsi- vs. contralateral fILN: VISp: r = 0.74 ± 0.03, SSp-bfd: r = 0.63 ± 0.08, MOp: r = 0.63 ± 0.03, p < 0.05, Spearman correlation). In line with the classical view of reciprocal feedforward/feedback connectivity (Angelucci and Petreanu, 2023; Markov et al., 2014; Young et al., 2021) and in the case where we can directly compare the interconnectivity of two target sources within the ipsilateral hemisphere (VISp and SSp-bfd), we see feedforward input from VISp to SSp-bfd and feedback input from SSp-bfd to VISp (Figure 4E, Figure 4—figure supplement 2A, B, magenta and green arrows). However, all contralateral areas were found to provide predominantly feedback input (Figure 4D–G, Figure 4—figure supplement 1A–C). These data also reveal unique instances, for example in SSp-bfd, where the ipsi- and contralateral input from a subset of visual areas showed opposing signatures in their anatomical organization. Ipsilateral mediating feedforward while contralateral providing feedback input (highlighted in red in Figure 4E, Figure 4—figure supplement 1A–C). Together, this hierarchical analysis shows that input onto these primary sensory and motor areas is mediated largely by a high proportion of L5 and L6 neurons and that both ipsi- and contralateral input is predominantly feedback (Figure 4G). However, in some instances ipsilateral input can appear strongly feedforward and in stark contrast to the feedback organization of projections from the same area in the contralateral hemisphere.

Increased contralateral hierarchy is due to input from sensory and motor areas

Within the ipsilateral hemisphere, anterogradely labeled sensory–motor module projections have been shown to exhibit low hierarchy compared to lateral, medial and prefrontal modules (Harris et al., 2019). Using retrograde tracing and our fILN measure we find this to be the case not only for the ipsilateral hemisphere but also for the contralateral hemisphere (Figure 5A). Strikingly, ranking cortical modules according to their fILN values revealed extremely similarly high levels of feedback from prefrontal, medial, and lateral modules (pf-m-l) from both hemispheres. In contrast, the fILN values for visual, auditory, and somatomotor (v-a-sm) modules were different across the two hemispheres (Figure 5A, B) with the contralateral hemisphere providing much stronger feedback (Figure 5A, B, ipsilateral fILN 0.65 ± 0.02 vs. contralateral fILN 0.79 ± 0.01, p < 0.001, two-sided paired t-test). The difference between the ipsi- and contralateral fILN was also significantly larger for the v-a-sm compared to the pf-m-l modules when the data were partitioned according to the target areas (Figure 5C, p < 0.001, one-sided paired t-test). This therefore appears to be another generalizable principle concerning the organizational hierarchy onto the primary sensory and motor cortices. Moreover, these results suggest that the global differences in the fILN between the two hemispheres observed above are mainly due to hemispheric differences in the fILN between the v-a-sm modules.

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L6 dominates the projection from many of the intra- and interhemispheric cortical areas

We next sought to determine which cortical layers within the v-a-sm modules might account for the comparatively high contralateral fILN values. There are at least three possible scenarios that could give rise to high fILN values. Theoretically, increased fILN can stem from a reduction in the proportion of projection neurons located within L2/3, an increase in the proportion of projection neurons within L5/6, or a synergistic effect involving opposing changes in supra- and infragranular layers (Figure 6A). By pooling all areas (n = 24) within the three key sensory and motor modules for the contralateral side we observe a significant reduction in L2/3 neurons for all target areas (Figure 6B, ipsi- vs. contralateral L2/3 fractional counts: VISp 0.25 ± 0.02 vs. 0.15 ± 0.02, SSp-bfd 0.36 ± 0.02 vs. 0.22 ± 0.03, MOp 0.23 ± 0.01 vs. 0.1±0.01, p < 0.001, one-sided paired t-test) and a concomitant increase in L6 cells in VISp and SSp-bfd (Figure 6B, ipsilateral vs. contralateral L6 fractional counts: VISp 0.38 ± 0.02 vs. 0.42 ± 0.01, SSp-bfd 0.24 ± 0.04 vs. 0.4 ± 0.01, p < 0.05, one-sided paired t-test). We found there to be no change in the fraction of L5 neurons between the ipsi- and contralateral hemispheres (Figure 6B, ipsi- vs. contralateral L5 fractional counts: VISp 0.19 ± 0.02 vs. 0.21 ± 0.01, p = 0.38; SSp-bfd 0.27 ± 0.04 vs. 0.28 ± 0.01, p = 0.86; MOp 0.13 ± 0.02 vs. 0.12 ± 0.2, p = 0.24, two-sided paired t-test).

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We next compared the fraction of projection neurons in a given layer to its counterpart area and layer to identify which areal subpopulations of cells might be responsible for the observed global differences in the fILN (Figure 6C). We find there to be many areas where the fraction of L2/3 cells is significantly decreased compared to L5 and L6. L5 was more heterogeneous containing instances of both decreases and increases in the average fraction of labeled cells between the two hemispheres (Figure 6C). In the vast majority of cases L6 showed a relative increase in its proportion of labelled cells compared to both L2/3 and L5. Taking only those areas where we observed a significant change in the fraction of L2/3, L5, or L6 cells we found that, depending on the target area, 30–60% of sensory-motor areas showed a dramatic reduction in the fraction of contralaterally labeled L2/3 neurons compared to their ipsilateral areal counterparts. In contrast, between 30% and 50% of areas showed increases in contralateral L6 cells. On the other hand, L5 showed on average little change since its fractional contribution both increased and decreased depending on the target area (Figure 6D). These data show that increased fILN in the contralateral hemisphere is due to an increase in relative abundance of L6 CCs and indicates their key role in routing interhemispheric feedback.

Finally, to determine the importance of L6 in the establishment of both the ipsi- and contralateral hierarchies and the difference between the two (Figure 4D), we excluded L6 from the fILN calculation (Figure 4A). First, by comparing the default ipsilateral fILN values for all cortical areas located within the v-a-sm modules to those when L5 or L6 was excluded, we observe significant changes in fILN (Figure 6E, p < 0.001, two-sided paired t-test, Bonferroni multiple comparison correction). Importantly, the reduction in ipsi fILN was greatest when L6 was excluded compared to L5 (Figure 6E, p < 0.05, one-sided paired t-test, Bonferroni multiple comparison correction). This was also observed when performing the same comparisons on the default contralateral fILN (Figure 6F). Excluding L6 from the contralateral default network actually had such a significant impact that the resultant fILN was substantially lower than the default ipsilateral side (Figure 6F, default fILN ipsilateral 0.65 ± 0.03 vs. fILN contra excluding L6 0.52 ± 0.05, p < 0.05, one-sided paired t-test, Bonferroni multiple comparison correction). These data show that L6 exerts a major influence on the anatomical organization of cortical input onto VISp, SSp-bfd, and MOp and accounts for the differences in the feedback hierarchy observed within and between the two hemispheres.

By performing comprehensive bilateral cortical circuit mapping onto VISp, SSp-bfd, and MOp we find that both primary sensory and motor areas receive extensive input from the majority of areas not only located in the ipsilateral (Ährlund-Richter et al., 2019; Brown et al., 2021; Hafner et al., 2019; Muñoz-Castañeda et al., 2021; Sun et al., 2019; Yao et al., 2023) but also contralateral cortical hemisphere (Goulas et al., 2017; Yao et al., 2023). This indicates significant cross-modal interactions not only within but also between the two cortical hemispheres. With only a few exceptions, we find that the identity, hierarchical rank and relative projection weights of input areas is highly conserved across the two hemispheres. One such exception relates to the contralateral lateral module whose composite cortical areas, compared to the ipsilateral module, display a stronger connection onto VISp (Yao et al., 2023), SSp-bfd and MOp indicating it may be a unique but generalizable feature of interhemispheric connectivity.

Earlier studies indicate that input from the other hemisphere onto a given area arises primarily and almost exclusively from the same contralateral area (Fenlon and Richards, 2015; Yorke and Caviness, 1975; Zhou et al., 2013). While we find many labeled cells in the contralateral target area, our data indicate that heterotopic connections are a prominent anatomical feature of the interhemispheric network (Goulas et al., 2017; Swanson et al., 2017; Szczupak et al., 2023; Yao et al., 2023). For both primary sensory areas the majority of the contralateral input comes from heterotopic areas located within target areas’ home module followed by areas located within most of the remaining modules. In contrast, MOp appears to receive very little input from areas relating to medial, visual, and auditory modules.

Neurons projecting from the contralateral hemisphere are believed to primarily reside within L2/3 and to a lesser extent in L5 (Fame et al., 2011; Pal et al., 2024; Ramos et al., 2008; Yorke and Caviness, 1975). From an anatomical organization perspective, this would be designated as predominantly feedforward (Markov et al., 2014; Markov et al., 2013a; Markov and Kennedy, 2013b). We however find that L2/3 dominates the projection from the least number of cortical areas. Rather for the majority of areas, L6 emerges as a major source of both the intra- and especially the interhemispheric projection (Liang et al., 2021; Olavarria and Van Sluyters, 1983; Yao et al., 2023), especially for VISp and MOp. The combined dominance of L5 and L6 projecting neurons shown here indicates that the vast majority of cortical projections to primary sensory and motor regions are feedback in nature.

One explanation regarding the apparent discrepancy in these two sets of observations may be due to technical differences and limitations of different tracing approaches. Chemical or protein-based anterograde and retrograde tracers such as Cholera toxin subunit B (CTB) have been widely used but have low transduction efficiency (Saleeba et al., 2019; Weiler et al., 2024) compared to recently developed retrograde viruses (Tervo et al., 2016). Second, mouse cre lines are a common tool for targeting specific cells in specific layers (Bortone et al., 2014; Harris et al., 2019; Yao et al., 2023). However, as is the case for L6 CCs (Vélez-Fort et al., 2014), not all cell types are accessible using cre-driver lines. In our study, we targeted all cell types located throughout all laminae within the target area that is in contrast to previous tracing studies that appear biased toward upper layers of the injection area (Adaikkan et al., 2022; Chovsepian et al., 2017; Massé et al., 2017). It also seems unlikely that the observed predominance of L6 labeling revealed here can be attributed to labeling bias since our viral injections effectively covered all cortical layers and excluded the white matter. Moreover, multiple contra- and ipsilateral areas exhibit significant labeling in L2/3 and/or 5 and prior studies using non-viral tracers such as CTB or Fluorogold have similarly reported a dominance of L6 projection neurons in the same specific pathways (e.g. SSp-bfd → VISp, Bieler et al., 2017; Weiler et al., 2024) as those revealed here using a retro-AAV-based approach.

The idea that cortical feedforward and feedback circuits may have an anatomical signature has been extensively interrogated in the mammalian visual cortical system (D’Souza et al., 2022; Felleman and Van Essen, 1991; Harris et al., 2019; Markov et al., 2014; Yao et al., 2023) where there exists a plethora of physiological data indicating functional hierarchy. In primates, feedforward and feedback neurons tend to reside in different cortical layers (Markov et al., 2014) and the ratio of supra- to infragranular neurons has been employed to anatomically define visual cortical hierarchy (Barone et al., 2000; Markov et al., 2014).

Here, we demonstrate in mice that the fILN metric effectively ranks higher visual areas that is consistent with the anatomical organization derived from axon termination patterns, as well as retrograde rabies tracing (D’Souza et al., 2022; Harris et al., 2019; Yao et al., 2023) and physiological experiments that describe functional hierarchy in mice (D’Souza et al., 2022; Jia et al., 2022; Siegle et al., 2021). By applying fILN-based area ranking cortex-wide, we uncover a global organization that is largely consistent with the hierarchical ranking of cortical areas based on anterograde labeling (Harris et al., 2019), placing sensory–motor modules at the bottom and lateral, medial, and prefrontal modules at the top of cortical hierarchy. Our data therefore demonstrate that the fILN metric can serve as a continuous parameter whose ranking may be used as an estimate of feedforward and feedback hierarchy for understanding cortical connectivity.

Typically, feedforward projections are characterized as ‘drivers’ while feedback projections are seen as ‘modulators’ of neuronal activity (Markov et al., 2013a). Our anatomical data reveal that VISp, SSp-bfd, and MOp mostly receive feedback from the ipsilateral cortex. This is generally expected as these targets are the first cortical areas to receive sensory input or to initiate motor functions. The predominance of feedback projections suggests a modulatory role rather than driving input onto these primary cortical areas. From our data, the pairwise intra-hemispheric connectivity between VISp and SSp-bfd aligns well with historical theories of cortical hierarchy, which suggest that feedforward connections are typically complemented by reciprocal feedback connections, at least within the ipsilateral hemisphere (Angelucci and Petreanu, 2023; Felleman and Van Essen, 1991; Markov et al., 2013a; Young et al., 2021). Our data also reveal a notable exception that appears to involve ipsilateral primary and higher visual cortical areas providing cross-modal feedforward input onto SSp-bfd. On the other hand, input from the same areas on the contralateral side are feedback in their organization as one might expect to observe for higher-order areas. The fact that, regardless of the target area, contralateral projections are predominantly feedback suggests that the conventional rule of reciprocally feedforward and feedback projections does not apply for interhemispheric input at least to primary areas VISp, SSp-bfd, or MOp. It will nevertheless be interesting and important to further investigate the hierarchical organization of cortical input onto higher cortical areas such anterior cingulate and retrosplenial cortex or within subregions of a given sensory area (e.g. higher compared to lower visual cortical areas).

Due to their dominant feedback bias, contralateral inputs may act as modulators of cortical activity within their ipsilateral target regions (Innocenti et al., 2022; Markov et al., 2014). For instance, inactivation of contralateral somatosensory areas in monkeys increases the receptive field size in the ipsilateral somatosensory area, suggesting a loss of modulatory contralateral input (Clarey et al., 1996). Moreover, contralateral auditory projections act to sharpen frequency tuning in its ipsilateral counterpart (Slater and Isaacson, 2020) and activation of contralateral visual projections strongly modulates visual cortical responses in the binocular zone of VISp (Zhao et al., 2013). However, these studies focused purely on homotopic areas while the functions of heterotopic areas largely remain elusive. Given the observed extent of heterotopic input, future studies should address their functional roles in hemispheric communication and ultimately in behavior.

By showing that hierarchical disparities between the two hemispheres are largely accounted for by differences in the input from the sensory–motor modules, we offer a more nuanced understanding of interhemispheric communication and a prominent role for L6 that is strategically positioned within the cortex. Additionally, we show that increased fILN is predominantly due to the target areas receiving input from L6 CCs rather than L6 corticothalamic cells. L6 CCs not only integrate input from and output to its local cortical column (Vélez-Fort et al., 2014) but also receive substantial thalamic input, at least in sensory areas (Crandall et al., 2017). Moreover, responses of L6 CCs to external stimuli temporally precedes those in other cortical layers (Egger et al., 2020). Thus, L6 CCs are ideal candidates to rapidly relay information to other cortical areas thereby providing feedback modulation (Weiler et al., 2024), suggestive of predictive coding (Rao and Ballard, 1999), or the transmission of efference copy (Latash, 2021; Vallortigara, 2021; von Holst and Mittelstaedt, 1950).

Processed data and source data for individual figures are available at https://doi.org/10.5061/dryad.8kprr4xzd. Code to replicate the analysis and figures is available at https://github.com/simonweiler/layer6_anatomy (copy archived at Weiler, 2025). For access to the raw image stacks, please directly contact t.margrie@ucl.ac.uk.

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Author details

1. Simon Weiler

   Sainsbury Wellcome Centre for Neuronal Circuits and Behavior, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4731-8369

2. Manuel Teichert

   Jena University Hospital, Department of Neurology, Jena, Germany

   Contribution

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

   Contributed equally with

   Troy W Margrie

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0009-0008-8129-6849

3. Troy W Margrie

   Sainsbury Wellcome Centre for Neuronal Circuits and Behavior, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Writing – original draft, Project administration, Writing – review and editing

   Contributed equally with

   Manuel Teichert

   For correspondence

   t.margrie@ucl.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5526-4578

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