Human Primate Brains
According to Rilling (2014), understanding the evolution of the unique characteristics of the human brain requires studying the brain of other living primate species. In other words, a specific evolutionary change in the human brain cannot be inferred to be unique to the human lineage unless other species sharing a last common ancestor don’t have it. That being said, Rilling emphasizes the role of comparative neuroimaging to investigate the similarities and differences between human and non-human primate brains, and highlights the different imaging techniques that have been used in multiple studies including structural magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI and diffusion-weighted imaging (DWI).
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Structural MRI was among the first imaging techniques used in comparative neuroimaging studies since it provided a promising alternative to sacrificing animals or waiting for their death in order to investigate their brains. One of the first few findings was that humans have larger brains compared to other primates, specifically to chimpanzees. The rates of brain growth seem to be similar in utero for both humans and nonhuman primates, however, a divergence occurs at 22 weeks of gestation where growth rate slows down in nonhuman primates but continues its increase in humans even postnatally (Rilling, 2014, p.48). This postnatal human growth is thought to be focused on white matter development, which suggests that this critical phase of white matter maturation observed only in human infants could be one of the key factors in developing some of the unique characteristics of human cognition. Although a decrease in white matter related to aging is observed in both humans and other primates, it is triggered at an earlier time in the lifespan of humans compared to chimpanzees, which might explain the spread of neurodegenerative diseases in our human populations. In addition to the striking brain size development differences, structural disparities have also been observed. Human brains were found to have more association cortex as opposed to other primate brains. This was represented by a larger expansion in the human prefrontal, parietal and temporal association cortex in a macaque-to-human brain warping compared to primary sensory and motor area expansions. This leads to the idea that a larger area of the human cerebral cortex is allocated to higher-order processing and cognitive skills as opposed to focusing on perceptual processing. Human-macaque comparisons have also shown a human-only expansion of the intraparietal sulcus (IPS) and activation of the anterior supramarginal gyrus, suggesting a consequent difference in 3D perception and tool-use actions respectively. The expansion of the arcuate fasciculus was also found to have a fundamental role in the evolution of human language (Rilling, 2014, p.49-51). Resting-state connectivity PET studies have also shown that in addition to humans, chimpanzees and macaque monkeys possess a default-mode network, emphasizing the argument that these species might also be able to process internal thoughts and have a sense of mental self-projection just like humans do. However, other networks involved in tool use and empathy were found to be absent in macaques including two fronto-parietal networks and another implicating the dorsal anterior cingulate cortex (ACC) and anterior insula. That being said, the dorsal prefrontal cortex had certain connectivity patterns that were absent in macaques including resting-state connections. Despite those differences, DWI studies identified a medial parietal cortical hub that is present in humans, chimpanzees and macaques. However, the general hub distribution in the prefrontal cortex remained different between these species, which emphasizes the importance of evolutionary differences in this specific region as an important moderator and regulator of higher cognitive functions including language, emotions, decision-making and memory among many others. Flinn et al.
(2005) provide an overview of the “ecological dominance-social competition” (EDSC) model as an explanation to the unique evolution of human cognitive adaptations and specific traits that make us armed with different sets of skills compared to other species. The article then presents an analysis of some of the major human features and evaluates their compatibility with the EDSC model, relying on the hominin fossil record and human neurobiology and cognition as the main two empirical resources. Flinn et al. begin with presenting different hypotheses that have been explored to explain the evolution of human cognition. According to the authors, many of these hypotheses included ecological problem solving, hunting, a sudden genetic change, sexual selection (female choice hypothesis) and the consideration of the the brain as a “social tool”. All of them encountered limitations in explaining how our hominin ancestors diverged from other species in terms of their cognitive capabilities. For instance, the ecological problem solving and hunting models are not generally accepted since many other species also engage in activities like tool use and scavenging, in addition to the fact they do not account for other aspects that are far from functionality like art and religion. The female choice hypothesis states that females chose to mate only with increasingly intelligent males, which directly acts as a selective pressure within the population towards higher cognitive abilities. However, the lack of sex differences in the overall level of intelligence presents as an unnegligible challenge to this theory (Flinn et al., 2015,
p.11-14). As an alternative to the hypotheses above, the authors introduce the EDSC model being an emergence of selective pressure from within the species as a results of an increase in intrinsic interactions with conspecifics as opposed to extrinsic pressures. This increase in internal interaction and competition for resources and mates results in the evolution of social skills and relationships. As stated by the authors, it “is the extent to which a species has become its own selective pressure, its own principal hostile force of nature”. The key in this model is that humans not only have become ecologically dominant by internalizing their competitions and interactions, but they were also able to become social beings and forge sophisticated sociocognitive and behavioral competencies that shaped the trajectory of their evolution. The fossil record along with neurobiological and cognition studies provide some evidence that support the EDSC model. Some of these include the speciation of humans which reflects a significant pattern of competition within the population. The extension of childhood compared to other species is also another characteristic that suggests the importance of childhood as a critical phase for social development and bonding. Additionally, brain areas responsible for social and cognitive competencies such as language, Theory of Mind and self-awareness were found to be larger in humans and have denser connectivities compared to other primates. Specifically, the prefrontal cortex and the ACC are thought to be involved in processes implying working memory, attention control and the simulation of behavioral strategies (Flinn et al., 2015, p.20-26). The integration of these social conditions, mental simulations and functioning of associated brain regions gives birth to a unique, evolutionary human brain.
Finally, neuroscientific and archeological evidence seems to support most aspects of the EDSC model, which leads us to wonder how the current ecological and social human competencies are going to shape the future of the human brain.
Research Proposal Rilling (2014) provides an overview of structural and developmental differences between human and other primates brains. The author mentions different neuroimaging techniques that were used in various studies, including PET which has been used to measure blood flow and glucose metabolism. Another way PET could be useful is through the determination of the density and distribution of different neurochemical receptors in the brain. Additionally, Flinn et al. emphasize the strength and validity of the EDSC model to explain and analyze the evolution of human cognition and shed light on the importance of social competition and sociocognitive skills. Taking into consideration these two components, I think it would be valuable to make use of PET to investigate the density and distribution of receptors involved in disorders with the most significant social deficits such as autism and thus, make comparisons between autistic children and other primates. Such a comparison would not only provide insights on how different or similar brains from the two species are, but it would also open the door for exploring potential animal (nonhuman primate) models for autism without considering genetic manipulations. Therefore, I hypothesize that autistic children might have a neurotransmitter receptor profile that overlaps with the primates’ with regard to specific brain regions and neurotransmitter pathways responsible for social and behavioral phenotypes that both autistic children and primates lack. The study would require working with three experimental groups: a group of autistic children, a group of healthy undiagnosed children and a group of macaque-monkeys. The second group would serve as a control and baseline for comparison purposes. We also know that autism is related to some sort of dysfunction at different levels in the brain involving neurotransmitter receptors including glutamate and GABA receptors among many others. Therefore, the goal of the experiment would be to see if similar patterns of dysfunction could be observed within monkeys and to determine if those results could be explored to explain the lack of social competency within these animals. Each group would undergo PET neuroimaging to map the density and distribution of these implicated neurotransmitter receptors and proteins and different levels of activity in various brain regions. The results would allow to confirm the extent to which healthy individuals are different from children with autism (by comparing the first two groups) and the neurochemicals that have previously been hypothesized to contribute to the disorder. Additionally, this neuroimaging comparison would also allow the identification of any autism-like patterns in monkeys in terms of the expression and distribution of the proteins and neurochemicals mentioned above. These observations, if found, would lead to the potential generalization of correlations between autism-related social deficits and corresponding brain regions and to project that to the nonhuman brain. To summarize, I think that there might be similarities found in receptor profiles, in both autistic and monkey brains, that are related only to certain social deficits common between the two groups. Implications of this study would not only include determining whether the proposed neuropathology of autism could also be found in other species with certain identical social complications, but it could also serve to create a novel animal model for autism that exploits the patterns of protein expression as opposed to genetic modifications.
Structural MRI was among the first imaging techniques used in comparative neuroimaging studies since it provided a promising alternative to sacrificing animals or waiting for their death in order to investigate their brains. One of the first few findings was that humans have larger brains compared to other primates, specifically to chimpanzees. The rates of brain growth seem to be similar in utero for both humans and nonhuman primates, however, a divergence occurs at 22 weeks of gestation where growth rate slows down in nonhuman primates but continues its increase in humans even postnatally (Rilling, 2014, p.48). This postnatal human growth is thought to be focused on white matter development, which suggests that this critical phase of white matter maturation observed only in human infants could be one of the key factors in developing some of the unique characteristics of human cognition. Although a decrease in white matter related to aging is observed in both humans and other primates, it is triggered at an earlier time in the lifespan of humans compared to chimpanzees, which might explain the spread of neurodegenerative diseases in our human populations. In addition to the striking brain size development differences, structural disparities have also been observed. Human brains were found to have more association cortex as opposed to other primate brains. This was represented by a larger expansion in the human prefrontal, parietal and temporal association cortex in a macaque-to-human brain warping compared to primary sensory and motor area expansions. This leads to the idea that a larger area of the human cerebral cortex is allocated to higher-order processing and cognitive skills as opposed to focusing on perceptual processing. Human-macaque comparisons have also shown a human-only expansion of the intraparietal sulcus (IPS) and activation of the anterior supramarginal gyrus, suggesting a consequent difference in 3D perception and tool-use actions respectively. The expansion of the arcuate fasciculus was also found to have a fundamental role in the evolution of human language (Rilling, 2014, p.49-51). Resting-state connectivity PET studies have also shown that in addition to humans, chimpanzees and macaque monkeys possess a default-mode network, emphasizing the argument that these species might also be able to process internal thoughts and have a sense of mental self-projection just like humans do. However, other networks involved in tool use and empathy were found to be absent in macaques including two fronto-parietal networks and another implicating the dorsal anterior cingulate cortex (ACC) and anterior insula. That being said, the dorsal prefrontal cortex had certain connectivity patterns that were absent in macaques including resting-state connections. Despite those differences, DWI studies identified a medial parietal cortical hub that is present in humans, chimpanzees and macaques. However, the general hub distribution in the prefrontal cortex remained different between these species, which emphasizes the importance of evolutionary differences in this specific region as an important moderator and regulator of higher cognitive functions including language, emotions, decision-making and memory among many others. Flinn et al.
(2005) provide an overview of the “ecological dominance-social competition” (EDSC) model as an explanation to the unique evolution of human cognitive adaptations and specific traits that make us armed with different sets of skills compared to other species. The article then presents an analysis of some of the major human features and evaluates their compatibility with the EDSC model, relying on the hominin fossil record and human neurobiology and cognition as the main two empirical resources. Flinn et al. begin with presenting different hypotheses that have been explored to explain the evolution of human cognition. According to the authors, many of these hypotheses included ecological problem solving, hunting, a sudden genetic change, sexual selection (female choice hypothesis) and the consideration of the the brain as a “social tool”. All of them encountered limitations in explaining how our hominin ancestors diverged from other species in terms of their cognitive capabilities. For instance, the ecological problem solving and hunting models are not generally accepted since many other species also engage in activities like tool use and scavenging, in addition to the fact they do not account for other aspects that are far from functionality like art and religion. The female choice hypothesis states that females chose to mate only with increasingly intelligent males, which directly acts as a selective pressure within the population towards higher cognitive abilities. However, the lack of sex differences in the overall level of intelligence presents as an unnegligible challenge to this theory (Flinn et al., 2015,
p.11-14). As an alternative to the hypotheses above, the authors introduce the EDSC model being an emergence of selective pressure from within the species as a results of an increase in intrinsic interactions with conspecifics as opposed to extrinsic pressures. This increase in internal interaction and competition for resources and mates results in the evolution of social skills and relationships. As stated by the authors, it “is the extent to which a species has become its own selective pressure, its own principal hostile force of nature”. The key in this model is that humans not only have become ecologically dominant by internalizing their competitions and interactions, but they were also able to become social beings and forge sophisticated sociocognitive and behavioral competencies that shaped the trajectory of their evolution. The fossil record along with neurobiological and cognition studies provide some evidence that support the EDSC model. Some of these include the speciation of humans which reflects a significant pattern of competition within the population. The extension of childhood compared to other species is also another characteristic that suggests the importance of childhood as a critical phase for social development and bonding. Additionally, brain areas responsible for social and cognitive competencies such as language, Theory of Mind and self-awareness were found to be larger in humans and have denser connectivities compared to other primates. Specifically, the prefrontal cortex and the ACC are thought to be involved in processes implying working memory, attention control and the simulation of behavioral strategies (Flinn et al., 2015, p.20-26). The integration of these social conditions, mental simulations and functioning of associated brain regions gives birth to a unique, evolutionary human brain.
Finally, neuroscientific and archeological evidence seems to support most aspects of the EDSC model, which leads us to wonder how the current ecological and social human competencies are going to shape the future of the human brain.
Research Proposal Rilling (2014) provides an overview of structural and developmental differences between human and other primates brains. The author mentions different neuroimaging techniques that were used in various studies, including PET which has been used to measure blood flow and glucose metabolism. Another way PET could be useful is through the determination of the density and distribution of different neurochemical receptors in the brain. Additionally, Flinn et al. emphasize the strength and validity of the EDSC model to explain and analyze the evolution of human cognition and shed light on the importance of social competition and sociocognitive skills. Taking into consideration these two components, I think it would be valuable to make use of PET to investigate the density and distribution of receptors involved in disorders with the most significant social deficits such as autism and thus, make comparisons between autistic children and other primates. Such a comparison would not only provide insights on how different or similar brains from the two species are, but it would also open the door for exploring potential animal (nonhuman primate) models for autism without considering genetic manipulations. Therefore, I hypothesize that autistic children might have a neurotransmitter receptor profile that overlaps with the primates’ with regard to specific brain regions and neurotransmitter pathways responsible for social and behavioral phenotypes that both autistic children and primates lack. The study would require working with three experimental groups: a group of autistic children, a group of healthy undiagnosed children and a group of macaque-monkeys. The second group would serve as a control and baseline for comparison purposes. We also know that autism is related to some sort of dysfunction at different levels in the brain involving neurotransmitter receptors including glutamate and GABA receptors among many others. Therefore, the goal of the experiment would be to see if similar patterns of dysfunction could be observed within monkeys and to determine if those results could be explored to explain the lack of social competency within these animals. Each group would undergo PET neuroimaging to map the density and distribution of these implicated neurotransmitter receptors and proteins and different levels of activity in various brain regions. The results would allow to confirm the extent to which healthy individuals are different from children with autism (by comparing the first two groups) and the neurochemicals that have previously been hypothesized to contribute to the disorder. Additionally, this neuroimaging comparison would also allow the identification of any autism-like patterns in monkeys in terms of the expression and distribution of the proteins and neurochemicals mentioned above. These observations, if found, would lead to the potential generalization of correlations between autism-related social deficits and corresponding brain regions and to project that to the nonhuman brain. To summarize, I think that there might be similarities found in receptor profiles, in both autistic and monkey brains, that are related only to certain social deficits common between the two groups. Implications of this study would not only include determining whether the proposed neuropathology of autism could also be found in other species with certain identical social complications, but it could also serve to create a novel animal model for autism that exploits the patterns of protein expression as opposed to genetic modifications.