Once again I am subjecting my dear readers to some selections from a biology paper. While this has not yet been labeled as torture by the UN, it might as well be. However as I do not believe in human rights, your only recourse is to run screaming away from your user interface.
This week on things beyond me we will be looking at:
Evolutionary Development of Neural Systems in Vertebrates and Beyond
Lauren A. O ’ Connell
Neurogenetics, Early Online: 1–17
Abstract: The emerging field of “ neuro-evo-devo ” is beginning to reveal how the molecular and neural substrates that underlie brain function are based on variations in evolutionarily ancient and conserved neurochemical and neural circuit themes. Comparative work across bilaterians is reviewed to highlight how early neural patterning specifies modularity of the embryonic brain, which lays a foundation on which manipulation of neurogenesis creates adjustments in brain size. Small variation within these developmental mechanisms contributes to the evolution of brain diversity. Comparing the specification and spatial distribution of neural phenotypes across bilaterians has also suggested some major brain evolution trends, although much more work on profiling neural connections with neurochemical specific city across a wide diversity of organisms is needed. These comparative approaches investigating the evolution of brain form and function hold great promise for facilitating a mechanistic understanding of how variation in brain morphology, neural phenotypes, and neural networks influences brain function and behavioral diversity across organisms.
I can’t wait…
“Although developmental patterning of central nervous systems is remarkably similar across animal phyla, small variations on developmental themes have produced striking variation in brain morphology.”
One of the major themes of this paper is the how conservative the methods of generative neural diversity are.
“Comparative approaches focused on brain development and organization has greatly increased our understanding of brain function and evolution.”
Given the difficulty of comparative approaches, this paper uses a variety of studies to make inferences about existence and nature of neural homologies.
“This work has identified several neural and molecular substrates on which evolutionary forces could shape the proximate mechanisms of generating brain diversity. Variations in patterning of the developing brain can give rise to divergent regional morphology, whereas the manipulation of neurogenesis can promote diversity in brain size. Moreover, alterations in organization and genetic regulation of conserved neurochemicals can result in diverse neural circuits that ultimately influence brain function and behavior.”
So we are looking at mechanisms which influence the shape, size and function of the brain through genetic changes.
“Cellular and morphological diversity of the brain can greatly influence sensory processing and decision making, but a mechanistic understanding of how species or lineage differences in brain organization contribute to behavioral diversity as well as how these processes have diverged (or converged) across evolutionary time remain fundamental questions in neuroscience.”
We are lucky, given the complexity of the brain, that there is any connection between morphology and function. This stoke of luck gives us a window into the function of the brain, and subsequently genetics to see the morphological differences and their effects between species.
“…developmental constraint, based on the observation that changes in regional brain volume scale with total brain size, and mosaic evolution, which is based on the observation that specific brain regions can vary in volume relative to total brain size. Most evidence suggests that developmental constraint and mosaic evolution work simultaneously to sculpt brain diversity, although perhaps on slightly different evolutionary time scales.”
One thing will become clearer through the paper is that, in hindsight, development of neurological diversity seems to stem from changes in the size of various parts which have roughly existed since the beginning of Chordata.
“Perhaps the most obvious feature in comparative neuroanatomy is that of size, where whole brains or specific brain parts differ in volume between species (Finlay & Darlington, 1995). A major example is the enlarged cortex in primates, and especially humans (Barton, 1996; Reader & Laland, 2002). Early in the field of brain evolution, it became apparent that the size of a particular substructure seemed to scale with overall brain size (Finlay & Darlington, 1995). The theory of developmental constraint stems from the observation that total non-olfactory vertebrate brain size accounts for most of the variation in size of particular brain regions (Barton & Harvey, 2000; Finlay & Darlington, 1995; Finlay et al., 2001; Yopak et al., 2010). Thus, brains may respond to selection pressures by growing as a whole, since the brain itself is composed of highly integrated parts with conserved neural networks. Indeed, brain scaling is a conserved pattern found in early vertebrates, suggesting that scaling brain size is favored in response to various ecological demands without compromising basic neural functions (Yopak et al., 2010).”
While this seems like a trivial question it is an important one for establishing the patterns of evolution in the brain. It may be the case that every part of the brain must be scaled independently, however, given that many species have demonstrated the ability to scale the brain homogenously it is likely the case that there exist mechanisms to scale the whole rather than the parts.
“These findings are often regarded as the brain evolving in response to specific ecological or behavioral selection, although finding causation in these correlations is extremely difficult. Variation in relative brain size has been documented in many vertebrate lineages including mammals (Barton, 1996; Reader & Laland, 2002), birds (Lefebvre et al., 1997; Rehkamper et al., 2008), and teleosts (Gonzalez-Voyer & Kolm, 2010).”
It is fortunate that the growth of the brain as a whole does in some cases provide an ecological benefit, otherwise, we wouldn’t be here.
“In many cases, these variations have been linked to specific behavioral adaptations. Adjustments in brain size correlating with behavioral functions have also been documented in Pheidole ants where relative sizes of mushroom bodies, central ganglion, and optic and antennel lobes vary with caste duties (Muscedere & Traniello, 2012). These differences do not scale with overall brain size and thus also support mosaic brain evolution within invertebrates.”
Again it could have very well been the case that the size of various brain regions didn’t affect behavior and that some other mechanism other than brain region size.
“Variation in brain region size can also vary with an individual ’s experience. In homing pigeons ( Columba livia ), individuals with navigational experience have a larger hippocampus compared with confined birds (Cnotka et al., 2008). Thus, brain size and even regional brain volume is variable across diverse taxa and even within species, representing a substrate on which selection pressures can yield behavioral diversity.”
This is an interesting point which makes understanding the brain all the more complex. Some experience itself can affect the size of various parts of the brain (obvious within the limitation of genetic potential). This should not surprise anyone, but it is important to note.
“Two central mechanisms are early patterning of the embryonic brain and the manipulation of the timing and length of neurogenesis. The role of these mechanisms underlying brain form and function is discussed below with examples in vertebrates and invertebrates.”
This would seem to support the neoteny hypothesis of intelligence. If indeed the size of the brain is roughly correlated to the “timing and length of neurogenesis”. Then it might follow that prolonging brain development, while the animal is a juvenile might also contribute to its size. This paper, though, focuses on the length of neurogenesis in the embryonic brain and its claims should be limited as such.
“The genes that specify brain patterning early in development are highly conserved (Denes et al., 2007; Northcutt, 2001; O’Connell & Hofmann, 2011b; Puelles & Rubenstein, 2003; Rubenstein & Puelles, 1994; Striedter, 2005) and studying developmental trajectories that specify brain patterning within a comparative context can help establish brain region homologies across wide evolutionary distances (Arendt et al., 2008; Medina & Abellan, 2009; Moreno et al., 2009; Puelles et al., 2000; Puelles & Medina, 2002).”
Tell me more!
“Work comparing very early patterning of the neural tube has contributed intriguing insights into the evolutionary origins of the central nervous system. All known bilaterian nervous systems (except nematodes) are established via transforming growth factor β (TGF- β ) family (Bone morphogenic protein (Bmp) and its Drosophila ortholog decapentaplegic (Dpp)) signaling that arranges dorsoventral polarity (Denes et al., 2007; Lowe et al., 2006; Mizutani et al., 2005). The Bmp gradient specifies neural (non-Bmp/Dpp) from non-neural (Bmp/Dpp) tissue and subsequently more complex molecular patterns emerge that specify both anterior-posterior and mediolateral brain patterning, which is also highly conserved among bilaterians.”
Here’s a handy dandy reference diagram, but remember we are talking about brains, not fish.
Basically, within the brain the proteins which control: the up-down orientation of the brain, the front to back and left to right patterns of development are shared between one family of proteins and their orthologs. The neurogenesis phenotypes of bilaterians are highly conserved. Again this means that the proteins involved in controlling development haven’t changed from their common origins, the exception being nematodes. This does not necessarily mean that the genotypes were conserved. In fact, as we will see later they in many cases weren’t. Conservation of phenotype is a surprising thing. Despite the apparent diversity of bilaterian animals, that brain growth is conservative should be surprising. Under selection pressure, this might say mean that a lobster is working with the same protein levers (for neurogenesis) as a mouse despite having little in common with the rest of their morphology. This should be filed under more research needed but these are promising findings.
“In both vertebrates and invertebrates, anterior-posterior patterning is in part defined by otd/otx (anterior) and unpg/gbx (posterior) expression, with pax2/5/8 expressed at the intersection (Farris, 2008a; Lichtneckert & Reichert, 2005; Schilling & Knight, 2001; Slack, 1993). On the mediolateral axis, patterning is specified by columns of molecular markers, including nk2.2 , gsx , msx , and pax6 , whose expression pattern is conserved in insects, annelids, and vertebrates (Arendt et al., 2008; Arendt & Nubler-Jung, 1999; Cornell & Ohlen, 2000). Together this work suggests a common origin of the centralized nervous system in bilaterians (although the vertebrate nervous system is dorsoventrally inverted compared with invertebrates). This work also highlights some interesting species differences among animals, such as why early patterning in nematodes seems so different compared with other animals. Clearly more comparative work is needed to better understand not only the similarities bilaterian animals share in their nervous systems, but also how and why developmental differences have evolved.”
Moving along to genes, we see that, again, a few genes controlling brain development have been conserved across bilaterians. The exception to this rule is that invertebrates and vertebrates nervous systems are inverted (relative to each other). Also, nematodes are anti-social.
“Comparisons of patterning genes within later developmental stages in the brain (after establishment of the anterior-posterior axis) have been extremely useful in identifying field homologies and evolutionary relationships of these brain regions between very distant taxa (Medina & Abellan, 2009; Moreno et al., 2009).”
What we are looking out for in the bilaterian brains are homologies. These are a bit harder to detect in brains. Homologies in bones are much easier to find.
By manipulating the same genes we can see which part of the brain change in diverse animals to see which parts of their brains are homologous. For example:
“Comparative work has also utilized genetic techniques to spatially manipulate gene expression in an effort to characterize the evolution of regional volume and novel structures. An excellent example is manipulation of the homeobox gene nkx2.1 , where knockdown of nkx2.1 leads to a size reduction of the ventral telencephalon and hypothalamus in both mouse (Mus musculus; Sussel et al., 1999) and the African clawed frog ( Xenopus laevis ; van den Akker et al., 2008).”
i.e. The frog ventral telencephalon and the mouse hypothalamus are most likely homologous. As you can see in the diagram below, you would be hard pressed to find these homologs via visual inspection, though it has been done before.
Figure 1. Evolution of early gene patterning that specifies embryonic brain modularity. Expression of patterning genes pax6 (blue), emx1 (green), dlx (yellow), nkx2.1 (red), and shh (sonic hedgehog; purple) are shown on the lateral-view diagram of developing nervous systems. Orange represents overlap in expression of dlx and nkx2.1. Gene names in parentheses are Drosophila orthologs. Each brain diagram is shown rostral (left) to caudal (right). Dc, deutocerebrum; Hyp, hypothalamus; M, medulla; P, pallium; Pa, pallidum region of the subpallium; Pc, protocerebrum; SP, subpallium; St, striatal region of the subpallium; Tc, tritocerebrum; Th, thalamus. Data gathered from Bachy et al. (2002), Brox et al. (2004), Dominguez et al. (2010), Hauptmann and Gerster (2000), Lowe et al. (2003), Murakami et al. (2002), Murakami and Watanabe (2009), Noveen et al. (2000), Osorio et al. (2005), Puelles et al. (2000), and Urbach and Technau (2003, 2004). [Sonics Mine]
Here you can see why using gene expression makes it easier to track neurological homologies than pure visual inspection. It seems like there was a rotation since the yellow and red (dlx and nkx2.1) seem to have moved from the bottom front to the bottom middle and back. But it is important to notice that these regions go from being small fairly undifferentiated parts of the brain to larger and exaggerated more functional pieces. This is of course how most homologous develop, but I find it amazing that the brain, this apparent bunch of mush seems as conserved as limb bones.
“Comparative work analyzing expression of patterning genes among closely related species suggests that these early signals establish divergent brain patterns that are elaborated on later in development. The best example to date comes from African cichlids, where behavioral and ecological variation has contributed to a rapid parallel radiation (Kocher, 2004) and a corresponding explosion in brain diversity (Gonzalez-Voyer et al., 2009a, 2009b).”
The lakes of the East African Rift provide the fragmented landscapes that encouraged the rapid speciation of African cichlids.
“These comparative studies have shown that patterning genes can clearly be manipulated to produce a neural phenotypes similar to other closely relates species. However, it is unclear how this variation is specified in the genome or how these modifications affect behavior.”
Essentially scientists can modify genes of African cichlids to reverse engineer brains of other cichlids. This demonstrates the properties of these genes that allowed experimentation (diversification) in brain diversity in the first place. Species don’t lose the phenotypes which allow for manipulation of brain components. If they did then one could not utilize one cichlid sub-species to reverse engineer the brain of another.
“Primary sensory areas can vary greatly in size between and within species (Airey et al., 2005; Krubitzer & Seelke, 2012) and such size variation has dramatic behavioral consequences. For example, genetically manipulating patterning genes emx2 , lhx2 , or pax6 in mouse development can alter the size of somatosensory and motor areas (Bishop et al., 2000; Monuki et al., 2001; Monuki & Walsh, 2001). These genetic manipulations ultimately lead to behavioral deficiencies, suggesting that cortical areas have reached an optimal size over evolutionary time (Leingartner et al., 2007). Moreover, sensory dependent plasticity from the thalamocortical axon tract can drastically affect cortical field size in a modality dependent manner (Sur & Rubenstein, 2005).” [Emphasis Mine]
This is an interesting tangential discovery. At face value it is merely yet another confirmation that genes can change the size of parts of the brain. The more interesting part is that the change led to behavioral deficiencies. This is a demonstration of the need for conservation of phenotype. If a phenotype is optimized any change to it could be deleterious. Where-as adaptability is important, there is likely a trough between fitness maxima for various phenotypes.
“Initiating and maintaining neurogenesis can have drastic effects on founder cell populations that birth neurons and on the number of neurons that progenitor cells can produce. These mechanisms are altered in the evolution of the expanded cortex in mammals and other brain structures across animal phyla.”
Again we are returning to the neoteny hypothesis. The prolonging of neurogenesis is a conserved method of increasing the number of neurons in the brain. Not only that, but check out this next section.
“In early mammalian brain development, the neural tube closes to form lateral ventricles and two layers of proliferative neuroepithelial cells are formed in a radial fashion along the ventricles (Kriegstein et al., 2006). As cortical neurogenesis proceeds, they migrate radially out of the proliferative zones into what will ultimately form a layered cortex. Delaying neurogenesis leads to an increase in the founder cell population, which can ultimately produce more neurons. Work in rodents has shown that a delay in cell cycle progression results in increased cortical tissue into a more primate-like cortical phenotype (Chenn & Walsh, 2002; Pilaz et al., 2009; Vaccarino et al., 1999).”
This implies that there is a loose hierarchy nascent in brain development. The longer neurogenesis takes the more “primate-like” the brain (in that they saw multiple rounds of cell division with the progenitor cells). This does not suggest that only one gene is necessary to make a mouse a primate, but simply that the some of the mechanisms which make the brain more primate-like work in simpler mammalian brains.
“The longer period of neurogenesis in P. japonica [https://en.wikipedia.org/wiki/Japanese_beetle ] presumably leads to a larger mushroom body volume. These differences are correlated to foraging tactics where larger mushroom bodies are present in diet generalist beetles compared with diet-specialist beetles and thus larger mushroom bodies may allow for more broad foraging behavior. Combining evidence from these comparative studies, it appears that either manipulating the timing or length of the period of neurogenesis influences divergence in brain substructure size and can contribute the evolution of different behavioral strategies.”
Again even in beetles we see that prolonged periods of neurogenesis lead to increases in the size of the brain (in this case only one part). In turn changes to the size and shape of the brain result in behavioral changes. Conservation of similar methodology to alter brain size makes sense. It removes the need for costly “experimentation” to find alternative methods for generating brain diversity. Given that minor changes to the brain have drastic effects, the conservative approach to change would be more efficient at generating diversity (vs. looking for novel methods). For example if a beetle population faced a shortage in the sources of their specialist diet, ask yourself would it be more likely that a completely novel method of behavioral adaption emerge or that existing pathways to alter neurogenesis (probably extant in the genome) would be selected for? This also suggests that there may be some rough relationship between specialist and generalist behavior (see Koalas) though again more research needed.
“Many neurochemical systems, such as catecholamines and neurosecretory cells, are ancient and date back to at least the evolution of the bilaterian nervous system, although whether these cell types serve the same role in modulating brain function is unknown. Cell specification and migration patterns specify neurochemical phenotypes throughout the brain that play important roles in behavior.”
“Catecholamines are produced mainly by the chromaffin cells of the adrenal medulla and the postganglionic fibers of the sympathetic nervous system. Dopamine, which acts as a neurotransmitter in the central nervous system, is largely produced in neuronal cell bodies in two areas of the brainstem: the substantia nigra and the ventral tegmental area. The similarly melanin-pigmented cell bodies of the locus ceruleus produce norepinephrine.”-La Wik [Not in paper]
That these phenotypes (though not necessarily their function) have been conserved since bilateral first emerged, again points to the conservative nature of brain development.
“All animals have evolved flexible strategies allowing them to respond to a social stimulus in an adaptive manner (Krebs & Davies, 1997). Context-appropriate behavioral decisions are critical for an individual’s fitness and are carried out by evaluating the salience of external stimuli and integrating this information with internal physiological cues. Remarkably, many of the neurochemicals that facilitate these decision-making processes are conserved across vertebrates and in some cases across bilaterians (O’Connell & Hofmann, 2011a).”
While there is always room for improvement, this makes it clear why phenotypic stability is important. Decision making is essential to fitness. It is especially essential, if you have sacrificed nutrients to develop a bunch of neurons only to have them inert when a decision is direly needed.
“Context-appropriate behavioral decisions are critical for an individual’s fitness and are carried out by evaluating the salience of external stimuli and integrating this information with internal physiological cues. Remarkably, many of the neurochemicals that facilitate these decision-making processes are conserved across vertebrates and in some cases across bilaterians (O’Connell& Hofmann, 2011a). At least in vertebrates, there are two well-studied neural circuits involved in information processing leading to these adaptive behavioral decisions. The mesolimbic dopamine system [https://en.wikipedia.org/wiki/Mesolimbic_pathway] is characterized by dopaminergic projections from the ventral tegmental area to the forebrain basal ganglia and is largely studied in mammals due to its biomedical relevance in deleterious behavioral disorders (Hyman et al., 2006; Joshua et al., 2009b; Schultz, 1997; Schultz et al., 1997; Wise, 2004b). Although drugs of abuse hijack the dopamine reward system, its natural function appears to be the evaluation of stimulus valence (Aragona & Wang, 2009; O’Connell & Hofmann, 2011a, 2011b; Reiner et al., 1998; Wise, 2004b). The other neural system involved in social decision-making is the so-called “social behavior network,” composed of steroid-sensitive brain regions, mostly located in the hypothalamus. The social behavior network was originally proposed in mammals (Newman, 1999), but has since been expanded to other vertebrate lineages (Crews, 2005; Goodson, 2005; O’Connell & Hofmann, 2011a, 2011b).” [Bold Mine]
“Currently, popular theories implicate the basal ganglia primarily in action selection; that is, it helps determine the decision of which of several possible behaviors to execute at any given time. In more specific terms, the basal ganglia’s primary function is likely to control and regulate activities of the motor and premotor cortical areas so that voluntary movements can be performed smoothly. Experimental studies show that the basal ganglia exert an inhibitory influence on a number of motor systems, and that a release of this inhibition permits a motor system to become active. The “behavior switching” that takes place within the basal ganglia is influenced by signals from many parts of the brain, including the prefrontal cortex, which plays a key role in executive functions.” –La Wik
Evaluation of stimulus valence reminds me of the humble starfish. Without some sort of rudimentary centralization of neurons a creature cannot evaluate the valence of any stimulus, but must instead fight itself over what to do. It is interesting that in order to establish valence the basal ganglia inhibits motor systems until they are activated due to, assumedly, a signal with import. This is exactly what a Starfish doesn’t do. Let’s say we were to model each system as a star with a hub at the center.
The starfish would not evaluate the valence the nerve signals nor would it inhibit its limbs. In fact star fish will on occasion tear themselves apart not-deciding where to go. In the mammalian brain the basal ganglia would receive signals from all the motor systems (then inhibit them) then perhaps consult with the prefrontal cortex and then release the motor systems according to some criteria. This is to prevent under normal conditions deciding to go right and left at the same time (just the sort of counter-productive thing a star-fish would do). These two neural circuits don’t quite go back to bilateral but conservation through vertebrates is significant. That they are conserved is as important as what is conserved. That the: evaluation of stimulus and “social behavior network pathways” are the ones that remain homologous throughout vertebrate point to their importance to vertebrate evolutionary strategy.
“As animals must evaluate stimulus valence in addition to physiological cues (such as hormone or reproductive state) to produce an adaptive behavioral response that is context appropriate, the mesolimbic reward system and social behavior network together form a larger social decision-making network (O’Connell & Hofmann, 2011a, 2011b, 2012). The fusion of the mesolimbic dopamine system and social behavior network comprises 13 brain regions that are interconnected and are present in all vertebrates (O’Connell & Hofmann, 2011b). The bases for these neural homologies include similarities in developmental origins during brain patterning (Figure 1), neurochemical profiles, and similarity in hodology (O’Connell & Hofmann, 2011b), although it should be noted that these homologies are tentative and not necessarily one-to-one. Identifying the neural homologies of brain regions involved in adaptive decision-making across vertebrates set a foundation to extend the analysis into evolutionary changes on the neurochemical level.” [Bold Mine]
These pathways are neither always going to look the same nor function the same. It interesting that social decision making pathways preceded the development of the more social vertebrates (like mice). Of course the existence of social behavioral pathways does not necessarily imply social intra-species behavior. I’m sure anti-social species still need to make social decisions regarding how to handle others of their same species. I could be missing something about vertebrate evolution, though.
“To uncover major evolutionary themes across animals within the social decision-making network, information was gathered from decades of neuroanatomical studies to catalog the presence or absence of specific neurochemicals important to social behavior and the main results are summarized here from O’Connell and Hofmann (2012). A focus was placed on nonapeptide systems (oxytocin, vasopressin, and their receptors), steroid hormone systems (aromatase, and the classical androgen, estrogen, and progesterone receptors), and the dopamine system (dopaminergic cell populations and dopamine receptors), as all these systems play established and conserved roles in behavior. When comparing the qualitative differences (total presence or absence of a gene product) in neurochemical profiles across vertebrates, several trends became apparent. First, the neurochemical profiles across vertebrates within the social decision-making network are remarkably conserved over 450 million years of evolution (O’Connell & Hofmann, 2012). Secondly, where there was variation across vertebrates, the location of neurochemical ligand – producing cells (dopaminergic and nonapeptide-producing) was more variable across vertebrates than the receptors (dopamine D1A receptor, steroid hormone receptors, and nonapeptide receptors) (O’Connell & Hofmann, 2012). Finally, there seemed to be different selection pressures on different brain regions. For instance, the preoptic area, which serves many behavioral and physiological functions (Dominguez & Hull, 2005; Gvilia et al., 2006; Ishiwata et al., 2002; Numan, 1974; Wood, 1998), was neurochemically very conserved across vertebrates. However, the striatum, a multimodal receptive structure involved in reward processing and motor control (Wickens et al., 2007), was the most neurochemically variable across vertebrates.” [Bold Mine]
Why neurochemical producers’ locations (output) are less conserved than receptor locations (input) is discussed below.
“From analyzing neurochemical patterns in brains of over 80 species across vertebrates, it is my impression that receptors are basally expressed throughout the brain so that when shifts in ligand input occurs, whether through the emergence of a new ligand producing cell group or through seasonal or sex-specific projections, the shift in ligand production would be immediately biologically meaningful. Thus, one of the major trends across vertebrate brains is that there is variation in input, via changes in the spatial distribution of ligand production or neurochemically variable basal ganglia regions that integrate external information, whereas the spatial distribution of neurochemical receptors and the brain regions involved in behavioral output are more conserved across vertebrates (Figure 3). The current hypothesis is that such variation in the spatial distribution of dopaminergic and neurosecretory cells in neurochemically variable brain regions is where species or lineage differences in sensory processing takes place, corresponding to how some animals are evaluating environmental stimuli differently, whereas the conservation of neurochemical receptor locations may be where conserved behavioral output is executed, such as aggression and sexual behavior. ” [Bold Mine]
This is a fascinating asymmetry. That one function would be more conserved is a tantalizing example of evolution selecting for higher adaptability and robustness of systems at the same time. Evolution is here playing with the way animal process stimuli while conserving responses i.e. the pathways to the canned (conserved responses) are more variable than the responses themselves. This asymmetry points towards the shared nature of baser response functions, while allowing for diversity of interpretation of environmental signals.
Figure 4. Evolution of neuroethological systems. ( A ) Deep homology refers to conserved phenotypes that are governed by conserved mechanisms across wide evolutionary distances. Ball and stick figure in each circle represents a gene network. ( B ) The convergence of behavioral phenotypes that have independently arisen in various taxa may rely on a convergence of underlying mechanisms. ( C ) A convergence of phenotype that has arisen independently in different animal taxa may have very different underlying mechanisms. ( D ) Phenologs refer to phenotypes that may appear very different, but share similar underlying protein interaction networks.
This could be a topic in and of itself.
“In the case of deep homology, behaviors that are shared across animals, such as aggression, reproductive behavior, or vocal communication, rely on ancient gene modules that are highly conserved and promote similar behaviors…Although this concept accounts for conserved gene modules facilitating conserved behaviors across animals, it does not account for the repeated and independent evolution of behavioral phenotypes.”
We need a new word for carcinisation of phenotype. Though I suppose carcinisation fits convergent phenotypes as well as anything else. If anyone has a better fun word or thinks it fits just fine let me know.
“Other complex traits have also evolved independently and repeatedly in many taxa, such as monogamy or paternal care, which are present in some species of mammals (Brotherton & Komers, 2003), birds (Reynolds & Székely, 1997), reptiles (Gardner et al., 2002), frogs (Brown et al., 2010; Weygoldt, 2009), fish (Kuwamura et al., 1993; Whiteman & C ô t é , 2007), and arthropods (Fetherston et al., 2010; Nalepa, 1991).”
Monogamy is a seemingly stable evolutionary strategy. It independently evolved in mammals, birds, frogs, fish and arthropods. This is a very strong attractor indeed. Now it could be equally said that given how common R-selected breeding strategies are that they are also evolutionary successful, but it would be interesting to see if R-selection is tied to one or a few genes or if it is more of a default state.
“Comparative approaches have shown that variations on brain developmental processes, such as early brain patterning or the timing of neurogenesis, can give rise to divergent neural and behavioral phenotypes. Although we know a great deal about where different neurochemical cell groups are located in animals brains, we still understand little about the specific conditions these cells respond to or how they are connected within a larger neural circuit. Determining how the brain evolves to promote divergent or convergent behaviors will require more comparative work, especially in non-mammalian vertebrates and invertebrates. However, with the advent of new high throughput technologies, this goal is now closer to our grasp than ever before. As information on the molecular and neural substrates of behavior from a diversity of animals becomes available, we will finally be able to mechanistically determine the patterns of brain evolution that underlie behavioral diversity.”
There is a saying that evolution is a series of quick fixes. This paper has been an interesting journey on just what is conserved through neural homologies. The specific mechanisms involved are much deserving of further investigation.