The human cerebral cortex consists of two hemispheres that are not exactly alike and show marked differences in structure and function along a left-to-right axis (Geschwind and Levitsky, 1968; Güntürkün et al., 2020; Karolis et al., 2019; Kong et al., 2018; Kong et al., 2022; Liang et al., 2021; Raemaekers et al., 2018; Sha et al., 2021; Zhong et al., 2021). It has been suggested that the brain favors asymmetry to avoid duplication of neural circuitry having equivalent functions (Karolis et al., 2019; Levy, 1977). For example, bilateral cortical regions showing asymmetry in task-evoked activity have reduced (long-range) connections with the opposite homologous regions, favoring more local connectivity (Karolis et al., 2019).

Asymmetry, that is quantitative hemispheric differences between contralateral homologous regions, supports partly differentiable functional processes (Karolis et al., 2019; Galaburda et al., 1990; Call et al., 2017). Previous work has suggested that functions related to leftward dominance include language processing (Lane et al., 2017; Piervincenzi et al., 2016; Wang et al., 2019), letter search (Pollack and Price, 2019), and analogical reasoning (Urbanski et al., 2016). On the other hand, rightward dominance of functional activation has been related to holistic word processing (Ventura et al., 2019), visuospatial abilities (Chen et al., 2019), emotional processing (Moeck et al., 2020), as well as with psychiatric disorders such as autism spectrum disorder (Floris et al., 2016). In addition to task-related asymmetries, resting state functional connectivity (FC) studies have also reported hemispheric differences. For example, language areas of the middle and superior temporal cortex showed increased connectivity with regions in the left hemisphere relative to their right hemispheric counterparts (Raemaekers et al., 2018), and the right amygdala showed higher connectivity with the entire cortex than the left amygdala (Tetereva et al., 2020). Moreover, previous work has indicated that there are inter- and intra-hemispheric differences in functional connectivity between healthy adults and patients with schizophrenia (Agcaoglu et al., 2018), and between neurotypical individuals and those diagnosed with autism spectrum disorder (Hahamy et al., 2015). It is possible that such functional processing asymmetries may be driven by subtle differences in functional organization between the hemispheres.

One appealing approach to studying functional organization is by evaluating the low-dimensional axes, or gradients, present within the connectome. These approaches embed brain regions on a continuous data-driven space based on their functional connectome (Coifman et al., 2005; Margulies et al., 2016; Vos de Wael et al., 2020). Gradients capture how connectivity profiles from distinct cortical regions are integrated (i.e. similar functional connectivity profiles) and segregated (i.e. dissimilar functional connectivity profiles) across the cortex (Margulies et al., 2016; Bethlehem et al., 2020; Haak and Beckmann, 2020; Paquola et al., 2019). Regions that have similar connectivity profiles are at similar positions along these gradients, whereas regions with dissimilar connectivity profiles are placed further apart. The principal functional gradient, partly reflected in the intrinsic geometry of the cortex, shows that regions of the transmodal systems occupy locations equidistant from unimodal systems (Margulies et al., 2016; Hong et al., 2020; Murphy et al., 2018). Gradients provide a synoptic framework to capture smooth variations of connectivity patterns across the cortical mantle. They describe variations in genetic patterning (Vainik et al., 2020; Valk et al., 2020; Valk et al., 2022, functional processes Margulies et al., 2016; Murphy et al., 2018; Turnbull et al., 2020), and are observed across species (Valk et al., 2020; Coletta et al., 2020; Xu et al., 2020). Gradients have been linked to graph-theoretical markers such as degree centrality (Hong et al., 2019) and microcircuit dynamics (Park et al., 2021) as well as connectivity distance (Hong et al., 2019; Wang et al., 2021). Moreover, the principal gradient describes the geodesic distance between primary and default regions, and relates to cortical microstructure and associated processing hierarchies (Huntenburg et al., 2018). In doing so, and in contrast to clustering or network-based approaches, the gradient framework provides a spatial ordering of functional brain networks, placing them along a gradual axis of connectivity variation reaching from sensory to transmodal areas. In the context of asymmetry of gradient loadings this would mean that a given region with a significant left-ward asymmetry along the first gradient (sensory-to-transmodal) has a connectivity profile more similar to the transmodal anchor in the left hemisphere relative to the right. Consequently, these regions are placed at different positions along the cortical hierarchy, providing novel insights concerning the system-level variations in the asymmetric brain. Indeed, recent research suggests that the principal gradient is asymmetric (Liang et al., 2021; Gonzalez Alam et al., 2022) and that the degree of asymmetry relates to individual differences in semantic performance and visual reasoning (Gonzalez Alam et al., 2022).

As inter-hemispheric asymmetry has been observed consistently in human brain structure and function, there may be important (phylo)genetic factors supporting lateralized human cognition (Güntürkün et al., 2020; Corballis, 1989; Corballis, 2009; Güntürkün and Ocklenburg, 2017; Vilain et al., 2011; Vallortigara et al., 1999). Previous work has reported that brain structure asymmetry is heritable (Sha et al., 2021; Zhong et al., 2021), especially in the language areas, and differentiates between humans and non-human primates (Eichert et al., 2020; Eichert et al., 2019; Neubauer et al., 2020; Spocter et al., 2020). At the same time, it has been shown that both humans and apes show asymmetry of brain shape (Neubauer et al., 2020), indicating that asymmetry is not a uniquely human brain feature. However, asymmetry was observed to be more local and variable in humans, potentially suggesting that individual variation in asymmetry in humans varies as a function of localized networks rather than global features. It is of note that the full FC matrix contains both intra-hemispheric and inter-hemispheric connections. Intra-hemispheric connections, compared to the inter-hemispheric connections, have been suggested to reflect inhibition of the corpus callosum and may underlie hemispheric specializations involving language, reasoning, and attention (Gazzaniga, 2000). Conversely, inter-hemispheric connectivity may reflect information transfer between hemispheres, for example, of motoric information, or crude information concerning spatial locations (Gazzaniga, 2000). Previous studies have mainly employed intra-hemispheric FC to study gradient asymmetry (Liang et al., 2021; Gonzalez Alam et al., 2022). However, inter-hemispheric differences in functional connectivity may also have functional relevance. For example, inter-hemispheric connectivity has been reported to be abnormal in patients with schizophrenia (Agcaoglu et al., 2018; Chang et al., 2019) and autism (Hahamy et al., 2015). Indeed differences not only of functional organization within each hemisphere but also between hemispheres, enabled by the corpus callosum, are relevant for integration and segregation of cognitive function and support hemispheric coordination (Gazzaniga, 2000; Toga and Thompson, 2003).

Here, we investigated the genetic basis of asymmetry of functional organization. We first examined whether inter-individual differences in asymmetry of functional organization are under genetic control, that is heritable. Second, we investigated whether asymmetry of functional organization is phylogenetically conserved in macaques. To probe individual variation in asymmetry of functional organization, we utilized a data-driven nonlinear dimension reduction technique, as this approach can provide reliable and robust indices of individual variation of cortical organization (Hong et al., 2020). We first obtained connectomic gradients for each hemisphere separately (left and right intra-hemispheric) as well as those describing functional connectivity from left to right and right to left hemispheres (left and right inter-hemispheric). We then computed the difference between individual gradient scores to study the asymmetry, consistent with prior studies (Liang et al., 2021; Gonzalez Alam et al., 2022). Subsequently, to evaluate the heritability of possible differences between left and right intra- and inter-hemispheric FC gradients, we used the twin pedigree set-up of the Human Connectome Project S1200 release young adults dataset (Van Essen et al., 2013). To assess whether asymmetry is conserved in other primates, we compared the asymmetry of functional gradients of humans with those observed in macaque monkeys using the prime-DE dataset (Xu et al., 2020; Milham et al., 2018). Finally, we conducted a confirmatory meta-analysis to explore the relationship between the patterns of gradient asymmetry and task-based functional MRI activations. Multiple analyses verified the robustness and replicability of our results.

In this study, we investigated the extent to which human cortical functional organization is asymmetric using a gradient-based approach. We assessed whether genetic factors shape such asymmetry and evaluated whether patterns of asymmetry are phylogenetically conserved between humans and non-human primates (macaques). We found that the principal gradient revealed hemispheric differences in most cortical regions, excluding the visual cortex. The language network and default-mode network showed the most leftward asymmetry while the frontoparietal network showed the most rightward asymmetry. The observed asymmetry of functional organization along the principal gradient was heritable. At the same time, regions with high asymmetry showed variable heritability. This may suggest that asymmetry in functional organization reflects both heritable and experience-dependent factors. Although the difference in left and right hemispheric functional organization was not significant along the principal functional gradient in a sample of macaques, the inter-hemispheric asymmetric pattern was comparable to the asymmetry pattern observed in humans indicating phylogenetic conservation. Notably, both the language and frontoparietal networks showed a higher leftward asymmetry in humans relative to macaques, indicating cross-species differences in asymmetry of specific transmodal functional networks. Decoding task-based functional activations along the asymmetry axis of the principal gradient, we observed that regions with a leftward preference were associated with language, autobiographical memory, and social cognition domains, whereas those with a rightward preference included cognitive control, working memory, and inhibition. In sum, our study shows the asymmetry of functional organization is, in part, heritable in humans and phylogenetically conserved in humans and macaques. At the same time, we observed that asymmetry of regions linked to higher-order cognitive functions such as language and cognitive control showed marked differences between humans and macaques and variable heritability in humans, possibly reflecting an evolutionary adaptation allowing for experience-dependent specialization.

By studying asymmetry in functional organization using a gradient approach, we have extended previous studies reporting asymmetric functional connectivity. Indeed, although the functional organization of the cerebral cortex has a largely symmetric pattern, it also shows subtle differences between hemispheres (Liang et al., 2021; Gonzalez Alam et al., 2022; Iturria-Medina et al., 2011; Sun et al., 2017). For the intra-hemispheric asymmetry gradients, we found that regions belonging to the language network showed the strongest leftward preference along the principal gradient axis. This indicates that their functional connectivity profiles were more similar to the default mode, relative to their right-hemispheric counterparts. Conversely, ventral multimodal networks were closer to the transmodal apex of the principal gradient in the right hemisphere, relative to their homologues in the left hemisphere. As such, our observations suggest that key transmodal regions, part of the language and control networks, show organizational preference to either the left or right hemisphere. Anterior lateral default mode subnetworks have been shown to uniquely exhibit positive connectivity to the language network (Gordon et al., 2020), possibly leading to increased gradient loadings of the language network in the left hemisphere, placing them closer to the default regions along the principal gradient in the left hemisphere relative to the right. Conversely, the transmodal frontoparietal network was located at the apex of rightward preference, possibly suggesting a rightward lateralization of cortical regions associated with attention and control and ‘default’ internal cognition (Corbetta and Shulman, 2002; Smallwood et al., 2021). The observed dissociation between language and control networks is also in line with previous work suggesting an inverse pattern of language and attention between hemispheres (Karolis et al., 2019; Zago et al., 2016). Such patterns may be linked to inhibition of corpus callosum (Cook, 1984), promoting hemispheric specialization. It has been suggested that such inter-hemispheric connections set the stage for intra-hemispheric patterns related to association fibers (Gazzaniga, 2000). Future research may relate functional asymmetry directly to asymmetry in underlying structure to uncover how different white-matter tracts contribute to asymmetry of functional organization.

We furthermore investigated whether such individual variations in asymmetry of functional organization could be attributed to genetic factors. To do so, we performed heritability analysis enabled by the twin design of the Human Connectome Project (Van Essen et al., 2013). Previous work indicated that brain structure including cortical thickness, surface area, and white matter connection (Kong et al., 2018; Sha et al., 2021; Zhong et al., 2021), as well as functional connectome organization (Colclough et al., 2017; Ge et al., 2017) are heritable. Our twin-based heritability analyses revealed heritable asymmetry of the principal functional gradient in the entire cortex, excluding visual cortex. At the same time, studying the association between heritability and asymmetry patterns we observed mixed results. Although we observed that the language-related area PSL showed the highest heritability, the highly asymmetric area 44 (Broca’s area) showed the lowest heritability. This may reflect a differential (dorsal and ventral) pathway of language development in the frontal and temporal lobe, where the dorsal pathway to the inferior frontal gyrus matures at later stages in development (Brauer et al., 2013). For example, previous work found that temporal language areas showed high heritability of cortical thickness asymmetry (Sha et al., 2021) and white matter connection asymmetry (Zhong et al., 2021) but frontal language areas did not. Such posterior-anterior differences may be due to developmental factors or axes of stability versus plasticity in the cortex (García-Cabezas et al., 2017). A case study of an individual born without a left temporal lobe found that frontal language areas in the left hemisphere did not emerge in the absence of temporal language areas in the left hemisphere, and that language functions instead relied on the right hemispheric functional network (Tuckute et al., 2022). It is thus possible that Broca’s area may mature after more posterior language regions in hierarchical fashion, which may be related to decreasing heritability in frontal language areas (i.e. more influenced by developmental and/or environmental factors). Recent work suggests that asymmetric patterning of brain structure and function are largely determined prenatally and unaffected by preterm birth (Williams et al., 2021). In neonates, asymmetric patterns were largely observed in primary and unimodal areas, whereas association regions were largely symmetric. Thus, asymmetry in association regions may be more experience-dependent. One focus of future work could thus be to evaluate the development of asymmetry in functional organization. Moreover, by means of GWAS approaches, it may also be possible to get more insight in specific genes and associated processes involved in functional asymmetry.

Evaluating the correspondence of asymmetry of functional organization between humans and macaques, by aligning the human gradients to the macaque gradient space (Xu et al., 2020), we observed a similarity between asymmetry of the principal gradient in both species in case of intra-hemispheric connectivity. This indicates functional asymmetry of within-hemispheric connectivity may be conserved across primates. At the same time, we found that language, default mode, and frontoparietal networks showed qualitatively more asymmetry in humans (human >macaque). These findings may support the notion that though asymmetry is a phenomenon existent across different primates, regions involved in higher order cognitive functions in humans are particularly asymmetric. Previous work studying asymmetry in white matter structure in primates found that humans showed more leftward arcuate fasciculus volume and surface relative to macaques (Eichert et al., 2019). The arcuate fasciculus is a white matter tract implicated in language functions by connecting Broca’s and Wernicke’s areas (Geschwind, 1970). Moreover, by comparing humans, macaques, and chimpanzees (Eichert et al., 2020), evolutionary modifications to this tract in humans relative to other primates have been reported, possibly derived from auditory pathways (Balezeau et al., 2020). At the same time, other structural studies have also observed leftward asymmetry of language areas in chimpanzees, indicating that asymmetry of language-regions per se may not be a human-specific feature (Spocter et al., 2020; Xiang et al., 2020). Fittingly, there are no significant differences of thickness and area asymmetry between humans and chimpanzees in superior temporal lobe (Xiang et al., 2020). Studying the endocranial shape of humans and non-human primates, temporal and occipital cortices showed local differences in asymmetry across species, and much more variability in humans relative to non-human primates (Neubauer et al., 2020). This suggests that whereas brain asymmetry is a phenomenon observed throughout mammals (Assaf et al., 2020), specific nuances may relate to species-specific behavioral and cognitive differences. Future research could assess asymmetry of brain organization in other primates, and relate observed differences in functional organization to those in white matter structure.

Although overall intra- and inter-hemispheric connectivity showed a strong spatial overlap in humans, we also observed various differences between the metrics across our analysis. For example, although we found both intra- and inter-hemispheric differences in gradient organization to be heritable, only for the former was a correspondence between the degree of asymmetry and heritability found. Similarly, comparing human and macaques, we only observed conservation of spatial patterning of asymmetry was conserved for intra-hemispheric connections. Whereas intra-hemispheric asymmetry relates to association fibers, commissural fibers underlie inter-hemispheric connections (Tzourio-Mazoyer, 2016). It has been suggested that there is a trade-off within and across mammals of inter- and intra-hemispheric connectivity patterns to conserve the balance between gray and white-matter (Assaf et al., 2020). Consequently, differences in asymmetry of both ipsi- and contralateral functional connections may be reflective of adjustments in this balance within and across species. Secondly, previous research studying intra- and inter-hemispheric connectivity and associated asymmetry, has indicated a developmental trajectory from inter- to intra-hemispheric organization of functional brain connectivity, varying from unimodal to transmodal areas (Friederici et al., 2011; Szaflarski et al., 2006). It is thus possible that a reduced correspondence of asymmetry and heritability in humans, as well as lack of spatial similarities between humans and macaques for inter-hemispheric connectivity may be due to the age of both samples (young adults in humans, adolescents in macaques). Further research could study inter- and intra-hemispheric asymmetry in functional organization as a function of development in both species, to further disentangle heritability and cross-species conservation and adaptation.

The functional relevance of asymmetry along the sensory-transmodal axis was evaluated in the human brain by projecting meta-analytical task-based coactivations along asymmetric effects of the functional principal gradient. In line with our expectations based on the distribution of asymmetry within functional networks, we found that task-based activations associated with language processing leaned leftward while task-based activations associated with executive functions leaned rightward, specifically in the intra-hemispheric pattern. This suggests that lateralized functions supported by the brain’s asymmetry have functional relevance (especially higher order cognitive functions such as language and executive control). Indeed, related work has shown a direct link between asymmetry and semantic and visual recognition skills (Gonzalez Alam et al., 2022), suggesting that asymmetry of individuals relates to variation in behavioral performance in these domains (Gonzalez Alam et al., 2022; Gonzalez Alam et al., 2019). Our observation of asymmetry of language versus executive functions may also be in line with notions of differential axes of asymmetry, dissociating symbolic/language, emotion, perception/action, and decision functional axes (Karolis et al., 2019). The asymmetry of principal functional gradient in humans and macaques showed a divergence along these axes, possibly indicating cross-species variability within the lateralization archetypes in primates. Notably, left hemispheric language lateralization is enabled throughout language development while right hemispheric language activation declines systematically with age (Olulade et al., 2020). Therefore, future research may focus on studying how the lateralization of human behavior is shaped by development and aging and how this may impact function and behavior.

Although we showed asymmetry in functional organization, there are various technical and methodological aspects to be considered. In the current work, we used the MMP (Glasser et al., 2016) for surface-based human fMRI data. A previous study used the atlas of intrinsic connectivity of homotopic areas (Xiang et al., 2020) (AICHA, https://www.gin.cnrs.fr/en/tools/aicha) for voxel-based fMRI data (Liang et al., 2021). In line with the results of that study, we found similar intra-hemispheric differences in functional gradients. Extending that work we additionally used the DK atlas (Desikan et al., 2006), which is often used in structural asymmetry studies (Sha et al., 2021; Postema et al., 2019). We again found asymmetric patterns, with a rightward dorsal frontal lobe and leftward posterior superior temporal lobe. The other temporal regions, having leftward or rightward asymmetry using MMP, showed no or less asymmetry using the DK atlas. Possibly, such subtle differences are not captured by the DK atlas, with only 34 cortical parcels per hemisphere. Evaluating the consistency of functional asymmetry across different datasets, we found that HCP (n=1014) and UKB (n=34,604) showed consistent leftward asymmetric functional organization in the language and default mode networks but no consistent rightward asymmetry of the frontoparietal network. Such differences may be due to technical differences between the datasets (Xifra-Porxas et al., 2021). However, it may also reflect sample specific differences in asymmetry. Indeed, whereas the HCP sample consists of young-adults with an age-range of 22–37 years, the UKB has a comparatively older and wider age range (from 40 to more than 70 years). Thus, it is possible the observed differences in the frontoparietal network are directly related to age-related asymmetry effects (Olulade et al., 2020). Due to the small sample size of macaques, it is important to be careful when interpreting our observations regarding the associated asymmetry, and its relation to patterns observed in humans. Therefore, further study is needed to evaluate the asymmetry patterns in macaques using large datasets (Milham et al., 2018; Messinger et al., 2021).

To conclude, we investigated the genetic and phylogenetic basis of asymmetry of large-scale functional organization. We observed that the principal (unimodal-transmodal) gradient (Margulies et al., 2016) is asymmetric, with regions involved in language showing leftward organization and regions associated with executive function showing rightward organization. This asymmetry was heritable and, in the case of organization of intra-hemispheric connectivity, showed spatial correspondence between humans and macaques. At the same time, functional asymmetry was more pronounced in language networks in humans relative to macaques, suggesting adaptation. The current framework may be expanded by future research investigating the development and phylogeny of functional asymmetry as well as its neuroanatomical basis in healthy and clinical samples. This may provide important insights in individual-level brain asymmetry and its relation to human cognition.

The current research complies with all relevant ethical regulations as set by The Independent Research Ethics Committee at the Medical Faculty of the Heinrich-Heine-University of Duesseldorf (study number 2018–317).

All human data analyzed in this manuscript were obtained from the open-access HCP young adult sample (https://www.humanconnectome.org/), UK Biobank (https://www.ukbiobank.ac.uk/). Macaque data came from PRIME-DE (http://fcon_1000.projects.nitrc.org/indi/indiPRIME.html). Gradient analyses and visualization were performed using the Python package Brainspace (Vos de Wael et al., 2020) (https://brainspace.readthedocs.io/en/latest/index.html). Heritability analyses were performed using Solar Eclipse 8.5.1b (https://www.solar-eclipse-genetics.org). Task-based function association analyses were based on NeuroSynth (Yarkoni et al., 2011) (https://neurosynth.org/). Full statistical scripts can be found at https://github.com/CNG-LAB/cngopen/tree/main/asymmetry_functional_gradients (copy archived at swh:1:rev:07d4a1a03267dac12ac8bfbccc8e09049cac9f31;path=/asymmetry_functional_gradients).

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Author details

1. Bin Wan

   1. Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
   2. International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity (IMPRS NeuroCom), Leipzig, Germany
   3. Department of Cognitive Neurology, University Hospital Leipzig and Faculty of Medicine, University of Leipzig, Leipzig, Germany
   4. Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany

   Contribution

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

   For correspondence

   wanb.psych@outlook.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9077-3354

2. Şeyma Bayrak

   1. Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
   2. Department of Cognitive Neurology, University Hospital Leipzig and Faculty of Medicine, University of Leipzig, Leipzig, Germany
   3. Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany

   Contribution

   Validation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Ting Xu

   Center for the Developing Brain, Child Mind Institute, New York, United States

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

4. H Lina Schaare

   1. Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
   2. Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany

   Contribution

   Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4259-0793

5. Richard AI Bethlehem

   Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0714-0685

6. Boris C Bernhardt

   McConnell Brain Imaging Centre, Montréal Neurological Institute and Hospital, McGill University, Montréal, Canada

   Contribution

   Funding acquisition, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9256-6041

7. Sofie L Valk

   1. Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
   2. Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
   3. Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

   Contribution

   Conceptualization, Data curation, Supervision, Funding acquisition, Validation, Methodology, Project administration, Writing – review and editing

   For correspondence

   valk@cbs.mpg.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2998-6849

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