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Systematic Review

A Scientometric Approach to Review the Role of the Medial Preoptic Area (MPOA) in Parental Behavior

1
Department of Psychology and Cognitive Science, University of Trento, 38068 Rovereto, Italy
2
Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore 639798, Singapore
3
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
*
Author to whom correspondence should be addressed.
Academic Editor: Alberto Fernandez-Teruel
Brain Sci. 2021, 11(3), 393; https://doi.org/10.3390/brainsci11030393
Received: 25 February 2021 / Revised: 15 March 2021 / Accepted: 16 March 2021 / Published: 20 March 2021
(This article belongs to the Special Issue Hypothalamus, Neuropeptides and Socioemotional Behavior)

Abstract

Research investigating the neural substrates underpinning parental behaviour has recently gained momentum. Particularly, the hypothalamic medial preoptic area (MPOA) has been identified as a crucial region for parenting. The current study conducted a scientometric analysis of publications from 1 January 1972 to 19 January 2021 using CiteSpace software to determine trends in the scientific literature exploring the relationship between MPOA and parental behaviour. In total, 677 scientific papers were analysed, producing a network of 1509 nodes and 5498 links. Four major clusters were identified: “C-Fos Expression”, “Lactating Rat”, “Medial Preoptic Area Interaction” and “Parental Behavior”. Their content suggests an initial trend in which the properties of the MPOA in response to parental behavior were studied, followed by a growing attention towards the presence of a brain network, including the reward circuits, regulating such behavior. Furthermore, while attention was initially directed uniquely to maternal behavior, it has recently been extended to the understanding of paternal behaviors as well. Finally, although the majority of the studies were conducted on rodents, recent publications broaden the implications of previous documents to human parental behavior, giving insight into the mechanisms underlying postpartum depression. Potential directions in future works were also discussed.
Keywords: medial preoptic area; MPOA; parental behavior; scientometry; systematic review; citespace; document co-citation analysis; keyword analysis medial preoptic area; MPOA; parental behavior; scientometry; systematic review; citespace; document co-citation analysis; keyword analysis

1. Introduction

Across many species, social encounters and interactions are ubiquitous and the regulation of social behaviours is essential for health and survival. With the advent of neurobiological methods, researchers are able to investigate the neural basis underlying social behaviour, gaining insight into processes of the brain that govern social behaviour. Among the wide range of social behaviours, this paper will focus on the study of parental behaviour and its neurobiological basis.
As young in mammalian species are usually altricial at birth, parental care is often a critical aspect for the survival and development of offspring. Parental behaviours form a complex category of activities influenced by a range of internal and external factors [1], where laboratory rodents are popular animal models used to study these factors. In rodents, general responses can be categorized into nurturance, indifference/avoidance and infanticide. Specifically, parental behaviours include active behaviours such as nest construction, pup retrieval and licking of pups and quiescent behaviours such as quiescent positioning over pups (see Lonstein and Fleming [2]). Sex differences are observed in parenting behaviours where male and female rodents differ in spontaneity of parental behaviours. While both virgin and postpartum female mice are spontaneously maternal and have an innate motivation to care for pups [2,3], virgin males often engage in infanticide where they attack and kill newborn pups as an adaptive reproductive strategy to increase their mating opportunities [4,5,6,7]. On the other hand, male mice only become parental in the weeks following mating [6]. Similarly, female rats are (i) less likely to be infanticidal [7,8,9], (ii) more spontaneously responsive to pups or likely to become parentally sensitized [10,11,12] and (iii) more consistent in displaying particular parental behaviours [13,14].
In terms of the neurobiology underlying parental behaviours in rodents, the medial preoptic area (MPOA) of the hypothalamus—an area involved in thermoregulation and sexual behaviour—is one of the key areas which has been implicated and is often considered a central node in the control of parenting. Empirical studies found (i) lesions in the MPOA disrupted parental behaviour [15], (ii) high expression of receptors of modulators of parenting such as estrogen, oxytocin, progesterone and prolactin [16], (iii) facilitation of parental behaviour when the MPOA is directly stimulated with estrogen [17,18]. Galanin-expressing neurons has also been found to govern parental behaviour in mice. Loss of galanin neurons in the MPOA was associated with a reduction in parental behaviour in male and female mice while optogenetic activation of galanin neurons reduced pup-directed aggression and induced active pup grooming in male mice [19].

2. The Present Study

Considerable progress in identifying brain areas and neural mechanisms underlying parenting has been made in the last few decades (see [20,21] for reviews). Given the size of the body of this work, the present study used a scientometrics approach to investigate influential and impactful publications in this field through document co-citation analysis (DCA; e.g., [22]), where a co-citation is defined as the citation of two sources together in the same paper. The DCA will show clusters of co-citing publications and papers and temporal and structural metrics of these clusters will be discussed. Specifically, we aim to investigate: (i) common topics of the clusters of publications co-citing each other and (ii) impactful publications. In order to accomplish both aims, a DCA was computed and, especially for investigating the common topics and main trends within the literature, it was supported by an analysis of keywords and indexing terms. The results of the scientometric approach will provide greater insight into research trends and publications in the field of the neurobiology of parenting behaviour.

3. Materials and Methods

For the present study, the sample of publications was downloaded from the database on Scopus, as done in previous scientometric publications [23,24]. A total of 677 scientific works, published between 01 January 1972 to 19 January 2021, was available on Scopus when using the following research string for the search: “( TITLE-ABS-KEY ( “medial preoptic” ) OR TITLE-ABS-KEY ( “MPOA” ) AND TITLE-ABS-KEY ( parent* ) OR TITLE-ABS-KEY ( matern* ) OR TITLE-ABS-KEY ( patern* ) OR TITLE-ABS-KEY ( mother* ) OR TITLE-ABS-KEY ( attach* ) OR TITLE-ABS-KEY ( nurtur* ) OR TITLE-ABS-KEY ( offspring ) OR TITLE-ABS-KEY ( pup* ) OR TITLE-ABS-KEY ( attack* ) OR TITLE-ABS-KEY ( infanticid* ) OR TITLE-ABS-KEY ( “young” )) AND (LIMIT-TO( LANGUAGE, “English”))”. After downloading the dataset of publications, scientometric analysis was conducted via CiteSpace software (version 5.7.R3). Data was imported in CiteSpace and 43,669 of the 43,728 (99.87%) total references cited in the collected papers were considered valid. A loss of a small percentage of references (~1.0–5.0%), when importing data in the software, is typically due to data irregularities that cannot be processed by CiteSpace. The amount of invalid references can be considered as negligible (Figure 1) [25].
To examine the connections between scientific works investigating the relationship between medial preoptic area and parenting, a DCA was first conducted. DCA is a type of analysis based on the frequency in which two documents have been co-cited (cited together) by subsequent works [26]. On CiteSpace, this type of analysis is conducted not only by considering the documents that are downloaded from scientific databases, but also by analyzing the references that they have cited in their text. Therefore, the DCA generates a network which consists in both citing (the ones downloaded from scientific platforms) and cited documents. In the analysis, the g-index selection criteria was adopted with scale factor k set at 25. The selection criteria and the value for its scale factor were chosen after several trials in which we aimed to optimize the structural metrics of the network. In particular, we attempted the analysis with g-index with k set at 25 and 15, TOP N with N at 50, 15 and 10 and TOP N% with N at 10. These three types of selection criteria rely on different principles to select the nodes that compose the network. The first one, g-index, which is based on the h-index, is the “largest number that equals the average number of citations of the most highly cited g publications” [27]. Conversely, TOP N and TOP N% criteria select the N or N% most cited nodes within a given time slice to form the network. The DCA was subsequently supported by a keyword analysis and the same optimization of node selection criteria was conducted. In this case, the best selection criteria turned out to be TOP N with N fixed at 10.
Structural metrics were used to examine the overall configuration of the network and the details of each node. Structural metrics include modularity Q, silhouette score and betweenness centrality. Modularity Q is an index that ranges from 0 to 1 and indicates the extent to which a network is divisible into single modules or clusters [28]. The homogeneity of these modules is measured using the silhouette score, with values ranging from −1 to 1. The higher the value of silhouette score, the higher the consistency of nodes among the module [29,30]. Betweenness centrality applies to single nodes to describe the degree in which a single node functions as a bridge to connect other nodes which would otherwise be separate. Centrality values range from 0 to 1, where high scores close to 1 indicates likely groundbreaking ideas [24]. For the analysis of single nodes, alongside the already mentioned structural metrics, temporal metrics were examined as well. This group of metrics mainly refers to citation burstness and sigma. Citation burstness is an index that indicates an abrupt change in the frequency in which a node has been cited within a period of time [31]. On CiteSpace, values of citation burstness are computed following Kleinberg’s algorithm [32]. Theoretically, values of citation burstness can range from 0 to infinite. Sigma is a metric obtained by considering betweenness centrality and citation burstness at the same time. Sigma values are computed following the Equation (centrality+1) b u r s t n e s s [29], and they indicate the novelty and the influence of a node among the network of interest.

4. Results

4.1. Document Co-Citation Analysis

The network we obtained for the DCA was composed of 1509 nodes and 5498 links. This means that, on average, each node in the network was connected with 3.64 other references. Furthermore, the network showed a modularity Q index of 0.3841 and a weighted mean silhouette of 0.9257. Thus, the nodes form a network which is modestly divisible into separate modules, each of which is highly homogeneous.
The major clusters identified in the DCA were highly internally homogeneous (see Figure 2 and Table 1). The largest cluster, cluster #0, that was identified consisted of 190 nodes, had a silhouette score of 0.879 and the references composing it were, on average, published in 2010. Cluster #1 was a group of 129 nodes with a high silhouette score of 0.885 and a publication year that, on average, was 2002. The third largest cluster, that is cluster #2, was a group of 115 nodes with a high silhouette score of 0.902 and were on average, published in 1994. The next cluster, cluster #4, consisted of 69 nodes, had silhouette of 0.915 and mean publication year of 1990. Considering the average year of publication of the documents forming a cluster, cluster #6 was the most recent one (mean year of publication = 2014; size = 50; silhouette = 0.968) together with cluster #9 (mean year of publication = 2014; size = 36; silhouette = 0.99).
In the network, 55 nodes showed a citation burst in their history (see Table 2 for the 20 nodes with the highest value of citation burstness). In particular, among the 10 nodes with the highest magnitude of citation burstness, 6 belonged to cluster #0, 3 to cluster #1 and 1 to cluster #2. Specifically, among the three documents with the strongest magnitude of citation burst, 1 belonged to cluster #1 and 2 to cluster #0. In order of burst strength, these three references were authored by Numan and Insel [16], Wu et al. [19] and Numan and Stolzenberg [33]. The document authored by Numan and Insel [16] showed a citation burst of 18.61, which started in 2005, two years after its publication. Wu et al. [19] were the authors of the publication with the second highest citation burst in the network, with a value of 16.05 and a duration of 5 years. Finally, the third document with the strongest citation burst, specifically 14.55, was authored by Numan and Stolzenberg [33]. Among the 20 references reported in Table 2, M. Numan was the first author for 7 of the references. Among these, the node by Numan et al. [34] had the longest citation burst in the network, with a duration of 8 years (from 2005 to 2013). As for the sigma metric, the document with the highest value was again the one published by Numan and Insel [16], with a value of 3.02. Other references with high sigma values were authored by Numan and Stolzenberg [33] and Champagne et al. [35], with sigma values of 2.29 and 1.91, respectively.

4.2. Keywords Analysis

The Keywords Analysis produced a network of 55 nodes and 161 links, meaning that each identified keyword was connected with 2.93 other ones. Furthermore, the resulting network showed a modularity Q index of 0.2488 and a weighted mean silhouette of 0.7898. In the network, 22 nodes showed a citation burst (see Table 3). In particular, by looking at the strength of their citation burst, support, metabolism and physiology had the highest magnitudes of 49.07, 42.12 and 33.13, respectively. Support is a keyword used especially as an indexing term in the Medical Subject Headings (MeSH) database, and it refers to the funding of the research. Therefore, such keyword is not relevant for the understanding of the trends in the research on the role of the MPOA in parenting. As for the duration of the citation burst, two keywords were particularly relevant: rat (strength of burstness = 7.15; burst duration = 22 years) and hypothalamus (strength of burstness = 24.34; burst duration = 21 years). Hypothalamus was also the keyword with the earliest beginning of citation burst, which started in 1972. The other references with the earliest beginning of burstness were theoretical study (beginning of burstness = 1974) and rat (beginning of burstness = 1977). conversely, the keywords with a more recent citation burst were metabolism (beginning of burstness = 2015), physiology (beginning of burstness = 2015), maternal behavior (beginning of burstness = 2016) and male (beginning of burstness = 2018).

5. Discussion

5.1. Document Co-Citation Analysis

The content of the major clusters, whose titles were given using the Log-Likelihood Ratio (LLR) option, identified through the DCA is discussed below. Specifically, clusters are presented following the chronological order in which their documents were, on average, published.

5.1.1. Cluster #4: “C-Fos Expression”

In Table 4, the most active citing documents for cluster #4 are reported. c-Fos is an immediate early response gene encoding a transcription factor that is part of the AP-1 transcription factor complex, which is involved in the regulation of cell proliferation. c-Fos has also been found to be a marker of neuronal activity (see [51]). In particular, as the name of the cluster suggests, some references in the cluster focused on understanding the underlying mechanisms of parental behavior by examining Fos-like immunoreactivity (Fos-lir) in the brain. This approach allowed researchers to find that MPOA is a crucial area for the onset and maintenance of parental behavior. In fact, the MPOA has a greater number of cells showing Fos-lir in maternally active rats [52,53,54]. Within this cluster, the onset of maternal behavior in rats was also examined in relation to lactogen and the central administration of human placental lactogen. Specifically, the work by Bridges and Freemark [55] and Bridges et al. [56] showed that human placental lactogen infusion in the MPOA of steroid-primed nulliparous rats facilitates the onset of maternal behaviors towards a foster young, similar to what was reported for prolactin [57,58,59,60]. For this reason, some references in which authors explored the functional and structural properties of the response to prolactin were included in cluster #4 [61,62,63,64,65,66]. The role of estrogens has also been studied by part of the references of this cluster in regards to maternal behavior in rodents [67,68,69]. For instance, the study by Rosenblatt et al. [70] showed that the MPOA is crucial for maternal behavior even in male rats and that such behavior benefits from a prolonged estradiol and progesterone treatment. This interest found in the citing documents justifies the presence of papers studying the localization and distribution of estrogen receptors in various animals’ brains, such as rodents [71] and quails [72] within the cluster. The study of estrogens and the MPOA, occasionally with a focus on aromatase action, permitted researchers to explore the sexual dimorphism reported for this brain area as well [73,74,75,76,77,78,79].

5.1.2. Cluster #2: “Lactating Rat”

In Table 5, the most active citing documents for cluster #2 are reported. As the name of the cluster suggests, part of the references in this group studied the relationship between MPOA and parental behavior by focusing on lactating rats. For this reason, some works within the cluster are cited because they explore the brain response to prolactin, the levels of which increase during lactation [82,83,84,85,86,87,88,89]. Other hormones related to this phase have been studied as well [90,91,92]. For instance, the increased binding of oxytocin in MPOA at parturition seems to be important for the molecule to stimulate the postpartum activation of maternal behavior [93]. This onset of maternal behavior after parturition depends on lateral habenula neurons [94,95,96]. As observed in the previous cluster, the MPOA is a brain area that shows an increase in the immediate early gene c-fos or other Fos proteins in maternally active rats [47,53,54,97,98,99,100,101,102]. Such activation of the MPOA appears to have a causal role for the ability to nurture young animals [45,70]. Thus, references composing cluster #2 aimed to better understand some properties of such responses [103,104,105,106,107]. For instance, Lin et al. [108] showed that FosB and Fos in the MPOA (and other areas) are involved in the neural activation during parturition and lactation, not in pregnancy, in rats. Furthermore, a part of that neural activation seems to be independent from olfactory and other sensory inputs, indicating the presence of efferent neurons crucial for the performance of maternal behavior [38,109]. Furthermore, Lonstein and De Vries [110] reported that many of the neurons showing c-fos activity after maternal behavior are GABAergic. For this reason, the authors concluded that some neurons in the MPOA, especially in its dorsal part, and other brain areas (i.e., the ventral bed nucleus of the stria terminalis and the caudal ventrolateral periaqueductal gray) must have either a local or long-range inhibitory effect as a component of maternal behavior. Knowledge of the presence of a circuit of inhibiting maternal behavior within the hypothalamus and in connected brain regions started to emerge from studies of the beginning of 2000s [111,112]. In the same years, Komisaruk et al. [113] reported that in parturient and hysterectomized rats, there is an increase in excitatory interactions in the MPOA. By examining Fos expression during maternal behavior, Stack et al. [43] observed that the MPOA likely modulates the activity of two brain regions: the shell of the nucleus accumbens, and the intermediate part of the Lateral Septum. Another work by Lonstein et al. [114] documented that a number of Fos-immunoreactive (Fos-ir) neurons also express the alpha subtype of the estrogen receptor (ER α ), suggesting that postpartum maternal behavior could be influenced by ER α activity [17]. In fact, [115] noted that MPOA’s susceptibility towards the effects of estrogen increases right after pregnancy termination. To highlight the connection between estrogens and Fos-ir neurons in MPOA, c-fos expression inducted in rodents’ brain by estradiol administration has been reported in the literature [116,117]. In fact, evidence of the central role that such hormones have on maternal behavior comes from studies on the administration of estrogen-progesterone treatment (to simulate a pregnancy-like pattern of hormonal environment) to nonpregnant and ovariectomized rats. These animals were still able to manifest maternal behaviours with treatments simulating the hormonal pattern of pregnancy [118].

5.1.3. Cluster #1: “Medial Preoptic Area Interaction”

In Table 6, the most active citing documents for cluster #1 are reported. As suggested by the name of the cluster, and anticipated by the previous one, the interest of researchers in those years was oriented towards expanding the focus of attention towards a circuit, and not only a single area, controlling parental behavior. For these reasons, researchers started to look at the interactions between the MPOA and other brain regions in order to better understand the regulation of parental behavior [120]. To do so, Numan et al. [34] hypothesized that the way in which the MPOA facilitates maternal behavior in rats involves circuits of inhibition [121]. In fact, the MPOA forms connections with the nucleus accumbens, which exerts inhibitory GABAergic control over the ventral pallidum, a central region involved in eliciting maternal responses in response to pup stimuli. For the authors, the MPOA facilitates maternal behavior by inhibiting the nucleus accumbens and, therefore, indirectly activating the ventral pallidum. In support of the role of the nucleus accumbens in maternal behavior, the study by Olazabal and Young [122] showed that oxytocin receptors in this brain region, whose expression increases in the MPOA and other areas after parturition [123,124,125,126], is related to the expression of spontaneous maternal behavior in prairie voles. In the same way, dopamine D1 receptors antagonists disrupt retrieval and licking of pups in rats when injected in the nucleus accumbens [46,127,128], and also in the MPOA [129]. The region of the nucleus accumbens critical for pup-retrieval behavior seems to be the shell [130], which seems to be involved in the consolidation of maternal memory [131,132]. Even with some subtle differences, dopamine receptor antagonists modify parental behavior even in prairie voles [133]. Dopamine in the nucleus accumbens was also linked to rats’ maternal behavior [134], specifically, pup licking/grooming [35]. Based on this evidence, some authors suggested that the neural system controlling maternal behavior in rats could overlap with the dopamine circuit of rewards in the brain [135,136,137,138]. The neural model designed to explain the mechanisms with which the MPOA controls maternal behavior included two paths of actions [37]. In the first one, the activated MPOA would inhibit a central aversion system responsible for defensive and avoiding behaviors towards pups. In the second, the MPOA would act by exciting the mesolimbic dopamine system in order to promote voluntary maternal responses [139,140,141]. Therefore, some references within the cluster were cited because they explored the properties of the dopamine mesolimbic circuit [142,143,144,145,146,147,148]. The neural model of maternal behavior was refined in the review written by Numan and Stolzenberg [33]. Here, the authors discussed the interaction between the dopamine system and the MPOA [149]. In particular, they reported findings suggesting that the MPOA activates the shell region of the nucleus accumbens through mesolimbic dopaminergic inputs in order to control aspects of maternal appetitive behavior [43]. To facilitate the effect of the MPOA on the nucleus accumbens, dopamine from the incerto-hypothalamic system interacts with steroid and peptide hormones to finally act on the MPOA [150,151]. For this reason, part of the references in the cluster were cited because they studied the effects of steroid or peptide hormones on parental behavior [115,119,152,153,154,155,156,157,158,159]. As a matter of fact, some of these molecules seem to be crucial for maternal aggression aimed at protecting offspring [160,161,162,163,164,165]. If dopamine levels in MPOA seem to increase during lactation [166], the neural origin of such molecular inputs was debated. For instance, Miller and Lonstein [167] did not find a significant number of dopaminergic terminals arriving at the MPOA from the zona incerta of the brain, but found them in other brain regions, such as the ventrocaudal posterior hypothalamus, the medial supramammillary nucleus and part of the ventral tegmental area. In fact, the causal role of the ventral tegmental area, a crucial area in the mesolimbic circuit whose activity is regulated by GABAergic and glutamatergic connections from the bed nucleus of the stria terminalis [168,169,170], in maternal behavior is documented by Numan et al. [171]. In this regard, a temporary inactivation of the ventral tegmental area in postpartum female rats interferes with the preference for pup-paired context in a conditioned place preference paradigm and reduced pup licking and pup retrieval behaviors [172]. In the same way, the inhibition of the medial prefrontal cortex negatively affected the pup retrieval behavior in maternal rats [173]. The motivational perspective on the female’s response to her offspring started to grow following the trend of research in the 2010s. It became clear that in that period, immediately after parturition, several brain structures (including the MPOA) contribute towards inducing a pup-specific bias to the motivational circuitry [15,41,174,175].

5.1.4. Cluster #0: “Parental Behavior”

In Table 7, the most active citing documents for cluster #0 are reported.
In particular, Rutherford et al. [178] followed the approach of research suggesting the involvement of the reward system on parental behavior [48,134,179,180]. By using a place preference method, Mattson and Morrell et al. [181] found that the MPOA was the only area showing a larger activation when dams preferred pup-associated versus cocaine cues, a preference that has been replicated in the literature [182,183]. In this rewarding process, oxytocin is a molecule that, for its role in social cognition and social rewards [184], plays a role in the stimulation of dopamine in the mesolimbic system, making child stimuli more rewarding [40,185]. During the 2010s, it became evident that maternal experience also has a role in regulating behaviors targeted at caring for offspring [186]. For instance, the dopaminergic response to pup-exposure in the shell of the nucleus accumbens depends on the female’s experience with pups, with higher experience associated with higher levels of dopamine [187]. In fact, the mesolimbic pathways sustain the changes due to maternal experience, with both dopamine receptor subtypes in the nucleus accumbens allowing the consolidation of this experience-dependent memory [188]. Olazabal et al. [189], by proposing new models to explain maternal behavior in different species and contexts, highlighted the flexible role of the MPOA in such neural circuits, an area that seems to facilitate maternal behavior during the early postpartum period and inhibit it in the later postpartum [190]. This transient role within the motivational system that the MPOA plays in the regulation of parental behavior is also detected in the available literature on the topic [41]. A final aim of the work by olazabal et al. [189] was to extend the knowledge obtained from other species to human mothering. This intent, as in other works in the literature [191], was pursued also by Lonstein et al. [192], who compared the evidence on the biopsychological influences that regulate maternal behaviors obtained from studies on animal models (mainly rats and sheep) to extend the understanding of human maternal behavior. The authors of this review reported many similarities and differences in factors influencing mothering among species. The differences would be linked to species-specific features, such as the role of hormones, of each sensory system, the flexibility in behavior, whether there is a language or not, and the role of cortical functions. These evidence led many researchers to explore the mechanisms underlying postpartum neuropsychiatric disorders, which are reported by many women. In particular, the review written by Mchenry et al. [193] studied the changes in reproductive steroids in order to activate maternal behavior and their association with postpartum neuropsychiatric disorders in many women, especially affective disorders [194,195]. The authors suggest that many brain regions, including the MPOA and the ventral bed nucleus of the stria terminalis, could mediate these effects for their influences on motivation and anxiety during the postpartum period [193,196]. This influence of the MPOA and the bed nucleus of the stria terminalis appears to depend on maternal experience [177]. In fact, maternal memory, which in part depends on amygdaloid V1a receptors [197] and the nucleus accumbens shell [198], is known for influencing the female’s behaviors towards pups in rats [199]. Furthermore, following the trends of research investigating neural plasticity mainly in the MPOA and the hippocampus [200,201,202,203,204], Pawluski and Galea [205] and Pawluski et al. [206] showed that the properties of the hippocampus vary during pregnancy and mothering. An insight on postpartum mood disorders following alterations of the maternal neural systems was also given by other references in the cluster [42,207,208].
Another trend of research within the cluster looked at the fact that lactating dams are less fearful than non-maternal animals and they exhibit lower hypothalamic-pituitary-adrenal (HPA) activation in response to potential environmental threats [209]. The diminished responsiveness of the HPA axis, which leads to a general sense of calmness in mothers, are due to the modified activity within two systems: a circuit that inhibits the HPA axis (e.g., oxytocin and prolactin systems) and another one with excitatory effects on the HPA axis. The first one would see an increased activation during lactation, whereas the second one would see a reduction in its activity [210]. The review by Bosch [211] was focused on the role that the reduction of anxiety in lactation plays in maternal behavior. In fact, high innate anxiety in dams tends to lead to intense and protective maternal behavior alongside an increased aggression towards a virgin intruder. Such behavior is considered functional to protect the pup against infanticide. Oxytocin and vasopressin are involved in this process reported in the review [44,212,213,214]. As a matter of fact, the release of these molecules in areas such as the hypothalamus and the limbic system contributes to the regulation of maternal behavior, including maternal anxiety and aggression [150,165,215,216,217,218,219,220,221,222,223,224,225,226]. For this interest, some references within the cluster were cited because they studied the mechanisms of action of those molecules [49,227,228,229,230,231,232]. Specifically, the mother’s brain sees an increased release of oxytocin during breastfeeding. When functional magnetic resonance imaging is used on dams, the brain’s pattern of activation following administration of oxytocin overlaps with the pattern of activation during pup suckling. This pattern included brain regions known for their role in regulating olfactory discrimination, emotions and reward [233]. Moreover, pup suckling activates multisensory processes in the brain of lactating dams [234,235]. In the review by Dobolyi et al. [236], authors focused on the role of the input from pups that activate the MPOA and, therefore, maternal behavior. The authors discussed that, in rodents, neurons containing the tuberoinfundibular peptide of 39 residues in the posterior thalamus appear to be good candidates to convey the suckling information to the MPOA, supporting maternal responsiveness. The way in which these inputs influence the neurons in the MPOA seems to depend on modifications of the gene expression, which seem to support maternal behavior [237,238,239]. In particular, chromatin remodelling mediates these alterations in the long-term [240,241].
Within this cluster, Tsuneoka et al. [36] studied the subregions in the MPOA that are necessary for maternal behavior in mice. Their results showed that the central part of the MPOA is crucial for maternal behavior, for its lesions lead to infanticide. Moreover, this subregion of the MPOA shows a c-fos activation during maternal behavior mostly in regards to GABAergic and peptidergic (galanin, neurotensin, and/or tachykinin2 mRNAs) neurons, as in other studies [19]. Alongside this interest on deepening the understanding of the role of the MPOA in female parental behaviors, some authors within the cluster tried to examine whether such knowledge could be applied to males’ parental behavior [242,243]. As a matter of fact, males do not undergo the hormonal cascade at a female’s parturition, postpartum ovulation and lactation. Nevertheless, in new fathers, the MPOA, the bed nucleus of the stria terminalis and the caudal dorsal raphe nucleus are activated in response to pups [244,245]. As in females, paternal experience in rodents is associated with a diminished activation in fear/anxiety brain regions and an increased activity in the network responsible for affiliative responses, which included the MPOA [246]. Upon becoming parents, male rodents have to inhibit the mechanisms responsible for infanticide and activate direct parental behavior towards the offspring. Evidence showed that the downregulation of the activity of neurons along the vomeronasal system, mainly sensitive to non-volatile chemosensory stimuli, is responsible for the shift from aggression towards pups in sexually naive male mice to the display of paternal behavior in fathers [247]. Nevertheless, virgin males’ aggressive behavior guided by the activity of the vomeronasal system seems to rely on the morphological features of the pup and salivary chemosignals [248]. Similar to female rodents, the central part of the MPOA plays a crucial role in parental behavior in male rodents, alongside the bed nucleus of stria terminalis. In fact, Tsuneoka et al. [50] showed that the activity in these two brain regions was able to classify paternal and infanticidal motivation with high accuracy (95%). Furthermore, lesions of the central MPOA induced infanticide, whereas lesions of the rhomboid nucleus of the bed nucleus of stria terminalis showed the opposite pattern, inhibiting infanticidal behaviors in virgin males. Moreover, the expression of androgen receptor and estrogen receptor (ER) α and their interaction with testosterone is fundamental for males’ sexual, aggressive and parental behaviors. This expression depends on the neuronal subtypes and the subregions examined in the MPOA [249].

5.2. Keywords Analysis

The analysis of the keywords with a citation burst supports the trends of research that emerged from the analysis of publications composing the network’s clusters. In particular, besides the keywords indicating the brain region of interest for the specific studies (central nervous system, hypothalamus, medial preoptic area, preoptic area and brain), the other indexing terms mostly referred to the methodology used to investigate the relationship between the MPOA and parenting. As observed from the results, the vast majority of studies in the field was conducted on rats using methods to analyze protein expression within the brain. Furthermore, as emerged from the discussion on clusters, most of the studies focused on the period of time around pregnancy (pre- and postpartum). Furthermore, although the majority of the studies exploring the role of the MPOA in parenting were conducted on females, research interest has recently involved males and paternal behavior as well.

6. Conclusions

In this paper, we used a scientometric analysis to identify research trends in past publications investigating the association between the MPOA and parental behaviour. We found four major clusters that characterised significant time periods in this dynamic area of research in order of chronology: “C-Fos Expression", “Lactating Rat", “Medial Preoptic Area Interaction" and “Parental Behavior". Initial research interest focused on examining an established physiological response in the brain associated with the maternal response (first cluster) and then, mainly by the study of lactating rats (second cluster), new models to explain maternal behavior were conceptualised. Subsequently, equipped with insight gathered from these new models, researchers turned their focus towards investigating brain circuitry beyond just the MPOA in controlling parental behaviour (third cluster). Finally, the most recent predominance in research looks at disentangling the many aspects of parental behaviour, including paternal behavior and infanticide (fourth cluster). The keyword analysis also identified terms, especially those associated with brain regions and methodology, that extend beyond the clusters, revealing possible foundations for subsequent research contributing to this line of work.
This study has some limitations which we outline here. Firstly, The publication sampling method employed specifies a constraint of identified keywords to be present in the titles, which, though it has the obvious advantage of streamlining the selection process, excludes relevant publications which may not have been captured [252]. Consequently, underlying themes in the research not reflected in the publication titles, abstract or keywords may have been overlooked. Next, only a few keywords were used to extract source articles from a single database, Scopus. Extensions of this work may consider using alternative keywords and including other databases (e.g., Web of Science) to determine whether the pattern of results hold. This specific scientometric approach may also be unable to fully encapsulate the extent of the trends in this research, particularly in view of unpublished works [253].
Another limitation of the scientometric approach is that it strongly relies on citations among documents. This method gives insight into the trends of research, but it does not capture the specific nature of the relations among co-cited papers. Analysing citations among documents leads to a bias towards past publications. In fact, documents published in the past tend to have higher number of citations as compared to more recent ones. This difference in the number of citations between past and recent publications would not reflect a difference in importance and scientific impact, but a difference in the “years of life" of a publication. A final and more technical limitation is that the references within the file downloaded from Scopus were not always consistent in the way they are cited by other publications. Sometimes this leads CiteSpace to consider two formats of citation of the same reference as two different publications. For this reason, some documents appear more than once within a cluster or even within the network. As regards to the four main clusters that were discussed, only a small number (3.4%) of references within the four main clusters that were discussed in the present article were repeated. Being this rate negligible, we have preferred not deleting them from the original file to not lose useful information.
The role the MPOA plays in parental behaviour continues to be a dynamic area of research. Historically, there has been a large focus on parental behaviour in mothers, particularly in the pregnancy or lactating stages of motherhood, for the role of the hormones associated with those phases. As seen in the fourth cluster, there is a growing trend in research investigating infanticide and paternal behaviour. Future work may build on this relatively recent development and use the findings in this paper as a guide in the literature exploring the role of the MPOA on parental behaviour. This line of research in paternal behaviour could lead to the elucidation of the underlying basis of sex differences in nurturing behaviors among parents, particularly sexual dimorphisms in the brain. Nonetheless, continual work in examining the neural correlates of maternal behaviour has relevant practical implications in understanding the driving factors predisposing many women to experience neuropsychiatric conditions in the postpartum period, namely depression [254].

Author Contributions

Conceptualization, G.E. and A.C.; methodology, A.C.; formal analysis, A.C.; investigation, A.C.; data curation, A.C.; writing—original draft preparation, A.C., J.P.M.B. and M.J.-Y.N.; writing—review and editing, A.C., J.P.M.B., M.J.-Y.N. and G.E.; visualization, A.C.; supervision, G.E.; funding acquisition, G.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by grants from the NAP SUG to GE (M4081597, 2015-2021).

Institutional Review Board Statement

Due to the nature of this study as a bibliographic review, ethical review and approval of this study were waived.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data will be available upon request.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
DCADocument co-citation analysis
Fos-irFos-immunoreactive
Fos-lirFos-like immunoreactivity
HPAhypothalamic–pituitary–adrenal
MPOAMedial preoptic area

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Figure 1. Study flow diagram.
Figure 1. Study flow diagram.
Brainsci 11 00393 g001
Figure 2. Network of publications generated through the Document Co-Citation Analysis (DCA). The 17 major clusters are highlighted and divided by colour.
Figure 2. Network of publications generated through the Document Co-Citation Analysis (DCA). The 17 major clusters are highlighted and divided by colour.
Brainsci 11 00393 g002
Table 1. Metrics of the 10 largest clusters identified by computing the Document Co-Citation Analysis (DCA).
Table 1. Metrics of the 10 largest clusters identified by computing the Document Co-Citation Analysis (DCA).
Cluster IDSizeSilhouetteMean Year
01900.8792010
11290.8852002
21150.9021994
4690.9151990
6500.9682014
7410.9662001
8390.9832004
9360.992014
10290.9891987
11270.9831987
Table 2. Description of the identifying characteristics of the 20 publications with high citation burstness metrics generated in the DCA.
Table 2. Description of the identifying characteristics of the 20 publications with high citation burstness metrics generated in the DCA.
ReferenceStrenght of BurstnessYearBeginning of BurstnessEnd of BurstnessBurst DurationSigmaCentrality
Numan and Insel [16]18.6120032005201163.020.06
Wu et al. [19]16.0520142015202051.840.04
Numan and Stolzenberg [33]14.5520092010201772.290.06
Tsuneoka et al. [36]13.6720132014202061.490.03
Numan [37]10.9520062007201361.710.05
Numan and Numan [38]10.2419951997200251.160.01
Dulac et al. [39]9.5820142015202051.190.02
Shahrokh et al. [40]8.9420102011201761.480.04
Pereira and Morrell [41]8.9020112013202071.290.03
Numan et al. [34]8.2620052005201381.580.06
Bridges [42]7.3920152016202041.000.00
Stack et al. [43]7.2020022005201051.280.04
Bosch and Neumann [44]7.1920122013202071.110.01
Champagne et al. [35]7.0920042005201271.910.10
Brown et al. [45]6.9919961997200251.410.05
Keer and Stern [46]6.5919992004200731.180.03
Numan and Numan [47]6.3019941998200241.210.03
Numan [48]5.9220072008201571.050.01
Meddle et al. [49]5.8320072010201441.010.00
Tsuneoks et al. [50]5.8220152017202031.010.00
Table 3. Main characteristics of the twenty-two keywords with the generated citation burstness metrics in the Keywords Analysis.
Table 3. Main characteristics of the twenty-two keywords with the generated citation burstness metrics in the Keywords Analysis.
ReferenceStrength of BurstnessBeginning of BurstnessEnd of BurstnessBurst Duration
support49.071979199516
metabolism42.12201520205
physiology33.13201520205
central nervous system28.94197819879
hypothalamus24.341972199321
medial preoptic area14.022010202010
maternal behavior11.07201620182
pregnancy10.05197819857
male8.59201820202
protein expression7.90200220108
preoptic area7.82200420084
rat7.151977199922
estradiol6.55198719892
radioisotope6.54198419906
animal tissue5.57200920112
endocrine system5.37198219842
ovariectomy5.24198719892
theoretical study4.82197419773
histology4.67198019822
aging4.551978198912
brain4.24198719881
animal cell3.92198719892
Table 4. All the 9 citing documents in cluster #4 identified using the DCA.
Table 4. All the 9 citing documents in cluster #4 identified using the DCA.
ClusterCiting DocumentGCSCoverage
4Nagano and Shinoda [80]209
4Bridges et al. [56]789
4Fleming and Walsh [53]799
4Fleming and Korsmit [54]1088
4Dellovade et al. [79]327
4Rizvi et al. [81]1357
4Rosenblatt et al. [70]756
4Bridges and Freemark [55]346
4Ehret and Buckenmaier [69]365
Table 5. Major 10 citing documents in cluster #2 identified using the DCA.
Table 5. Major 10 citing documents in cluster #2 identified using the DCA.
ClusterCiting DocumentGCSCoverage
2Kalinichev et al. [102]5421
2Stack et al. [43]10315
2Lonstein et al. [114]7214
2Komisaruk et al. [113]3113
2Sheehan and Numan [115]4813
2Stack and Numan [107]5613
2Grattan [119]11412
2Lin et al. [108]2912
2Li et al. [101]8812
2Lonstein and De Vries [110]6411
Table 6. Major 10 citing documents in cluster #1 identified using the DCA.
Table 6. Major 10 citing documents in cluster #1 identified using the DCA.
ClusterCiting DocumentGCSCoverage
1Gammie [120]6925
1Curtis et al. [176]5719
1Numan [37]15917
1Numan and Stolzenberg [33]22417
1Numan et al. [128]11915
1Numan and Woodside [174]8915
1Pereira and Morrell [41]8414
1Perrin et al. [177]3714
1Numan et al. [34]9114
1Olazabal and Young [122]17612
Table 7. Major 10 citing documents in cluster #0 identified using the DCA.
Table 7. Major 10 citing documents in cluster #0 identified using the DCA.
ClusterCiting DocumentGCSCoverage
0Lonstein et al. [192]6231
0Numan and Young [250]13123
0Mchenry et al. [193]2020
0Olazabal et al. [189]5518
0Dobolyi et al. [236]4018
0Yoshihara et al. [226]1518
0Rutherford et al. [178]8117
0Bosch [211]10016
0Bridges [42]14616
0Numan [251]016
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