VI. Life’s Cerebral Faculties Become More Complex, Smarter, Informed, Proactive, Self-Aware
2. The Evolution of Cerebral Form and Cognizance
Gabora, Liane and Kirsty Kitto. Concept Combination and the Origins of Complex Cognition. Swan, Liz, ed. Origins of Mind. Berlin: Springer, 2012. University of British Columbia and Queensland University of Technology psychologists propose, and carefully defend, that an evolutionary advance to modern humans was aided by novel abilities to place isolated objects and episodes into a contextual ground. The cultural stages of Merlin Donald are surely drawn upon, similar to Chris Collins’ Paleopoetics, which this theory well aligns with. As a result, life’s penchant for enhanced creativity is explained through better ways to join artifacts and experiences into new combinations and perspectives. (One is reminded of Arthur Koestler’s 1970s bi-association model.) View each author’s publications for more creative insights about emergent human imaginations, often rising from quantum realms. And may we altogether lately glimpse a self-creating natural genesis that is trying to discover and choose itself?
At the core of our uniquely human cognitive abilities is the capacity to see things from different perspectives, or to place them in new context. We propose that this was made possible by two cognitive transitions. First, the large brain of Homo erectus facilitated the onset of recursive recall: the ability to string thoughts together into a stream of potentially abstractor imaginative thought. Computational modeling of recursive recall in an agent-based artificial society resulted in the agents generating more diverse and valuable cultural outputs. We propose that the capacity to see things in context was enhanced much later, following the appearance of anatomically modern humans. This second transition was brought on by the onset of contextual focus: the capacity to shift between a minimally contextual analytic mode of thought, and a highly contextual associative mode of thought, conducive to combining concepts in new ways and ‘breaking out of a rut’. We summarize how both transitions can be modeled using a theory of concepts, and how they interact and shift in meaning when they appear in different contexts. (Abstract)
Geary, David, et al, eds. Evolutionary Origins and Early Development of Number Processing. Amsterdam: Elsevier, 2015. With roots in the work of Rochel Gelman and Claude Gallistel, who write a Foreword, this retrospective study illumes across the creaturely procession from invertebrates to primates and homo sapiens a consistent ability to estimate and count, lately as arithmetic and algebra. With chapters by Giorgio Vallortigara, Irene Pepperberg, Tasha Posid and Sara Cordes, Joseph Cantlon, and other authorities, whether fish or fowl a trend evolved from an initial analog mode that could assess quantities into a later symbolic number phase. A parallel theme then notes how infants and children proceed to learn in the same way. To reflect, the whole temporal cosmos appears as a long education to learn numerical categories and alphabet letters so as to write, read, and discover.
Ginsburg, Simona and Eva Jablonka. The Evolution of Associative Learning. Journal of Theoretical Biology. Online in Press, 2010. See also by the authors: Epigenetic Learning in Non-Neural Organisms in Journal of Biosciences (34/4, 2009) and Experiencing: A Jamesian Approach in Journal of Consciousness Studies (17/5-6, 2010). These papers by the Open University of Israel, and Tel Aviv University, philosophers of science contend that life’s developmental procession is to be seen as most characterized and guided by a ramifying central nervous system with attendant sentient capabilities. As a surmise, might one then imagine, by this novel distinction, a grand evolutionary education of a self-edifying cosmos in emergent quest of its own self-witness and conception?
We have argued that the emergence of associative learning altered the life and adaptive possibilities of animals. It marked the beginning of a new stage in the history of life, with brains and learning becoming the main engines of animal evolution. The effects of associative learning are compatible with the large changes in morphology and behavior seen in Cambrian metazoans. (17)
Gollo, Leanardo, et al. Single-Neuron Criticality Optimizes Analog Dendritic Computation. Nature Scientific Reviews. 3/3222, 2013. We cite this posting as a good example of neural researchers validating how much of an exemplary nonlinear portal are human brains, in both byte digital and integral holistic aspects. The multiple affiliations of the authors listed below offers proof nowadays of science’s worldwide venue.
Leanardo Gollo: IFISC, Instituto de Fısica Interdisciplinar y Sistemas Complejos (CSIC - UIB), Campus Universitat de les Illes Balears, Spain; Systems Neuroscience Group, Queensland Institute of Medical Research, Australia; Oscar Kinouchi: Faculdade de Filosofia, Ciencias e Letras de Ribeirao Preto, Universidade de Sao Paulo, Brazil; Center for Natural and Artificial Information Processing Systems – USP; Mauro Copelli: Departamento de Fısica, Universidade Federal de Pernambuco, Brazil.
Gurturkun, Onur and Thomas Bugnyar. Cognition without Cortex. Trends in Cognitive Science. Online March, 2016. In an article that represents another mid 2010s synthesis, Ruhr-University Bochum, Germany and University of Vienna neuroscientists explain how mammalian and avian faculties develop in parallel, convergent ways. While mammals, primates, and we humans have a prefrontal cortex to think by, bird brains achieve this by adapting other cerebral areas for this purpose. The result, known as homoplasy, is an independent evolution of similar characters and abilities due to common selection pressures. It is then concluded that the most cerebral prominent feature is the relative connectome quality between neural nets, in whatever domain.
Assumptions on the neural basis of cognition usually focus on cortical mechanisms. Birds have no cortex, but recent studies in parrots and corvids show that their cognitive skills are on par with primates. These cognitive findings are accompanied by neurobiological discoveries that reveal avian and mammalian forebrains are homologous, and show similarities in connectivity and function down to the cellular level. But because birds have a large pallium, but no cortex, a specific cortical architecture cannot be a requirement for advanced cognitive skills. During the long parallel evolution of mammals and birds, several neural mechanisms for cognition and complex behaviors may have converged despite an overall forebrain organization that is otherwise vastly different. (Abstract)
Hartenstein, Volker and Angelika Stollewerk. The Evolution of Early Neurogenesis. Developmental Cell. 32/4, 2016. As our nascent cerebral humankinder reconstructs how we came to be ourselves, UCLA and Queen Mary University of London evo/devo neuroscientists provide a comparative overview of neural progenitors across the animal kingdom, along with neurogenetic mechanisms which form embryonic brains.
The foundation of the diverse metazoan nervous systems is laid by embryonic patterning mechanisms, involving the generation and movement of neural progenitors and their progeny. Here we divide early neurogenesis into discrete elements, including origin, pattern, proliferation, and movement of neuronal progenitors, which are controlled by conserved gene cassettes. We review these neurogenetic mechanisms in representatives of the different metazoan clades, with the goal to build a conceptual framework in which one can ask specific questions, such as which of these mechanisms potentially formed part of the developmental “toolkit” of the bilaterian ancestor and which evolved later. (Abstract)
Hartenstein, Volker, et al. Modeling the Developing Drosophila Brain. BioScience. 58/9, 2008. By creative employ of digital three-dimensional models, UCLA developmental biologists provide a graphic display of the compartmental and hierarchic maturation of the fly brain from neurons and axons to a macrocircuit anatomy.
Harzsch, Steffan, ed. Development of the Arthropod Nervous System: A Comparative and Evolutionary Approach. Arthropod Structure & Development. 32/3-4, 2003. An update to the volume by Breidbach and Kutsch above, with contributions on invertebrate neurogenesis in chelicerates, crustaceans and hexapods.
Haun, Daniel, et al. Origins of Spatial, Temporal and Numerical Cognition. Trends in Cognitive Sciences. 14/12, 2010. In a special issue on the subject, psychologists and anthropologists from Germany, England, Italy, and the Netherlands, including Nicola Clayton and Giorgio Vallortigara, attest to a progression of complex brains and their acuities which is now realized to grace and orient the span of life’s emergent evolution.
Herculano-Houzel, Suzana. Coordinated Scaling of Cortical and Cerebellar Numbers. Frontiers in Neuroanatomy. 4/Article 12, March, 2010. A further exposition by the Brazilian researcher in favor of brain evolution “in concert” via a “universal numerical relationship” that spans the sequence of mammalian species. We people possess a highest, optimum neuron population and complex net arrangement, but what makes us extra special is our membership in the major evolutionary transition to a social worldwide collective intelligence.
Here I show for the first time that the numbers of neurons in the cerebral cortex and cerebellum are directly correlated across 19 mammalian species of four different orders, including humans, and increase concertedly in a similar fashion both within and across the orders Eulipotyphla (Insectivora), Rodentia, Scandentia and Primata, such that on average a ratio of 3.6 neurons in the cerebellum to every neuron in the cerebral cortex is maintained across species. This coordinated scaling of cortical and cerebellar numbers of neurons provides direct evidence in favor of concerted function, scaling and evolution of these brain structures, and suggests that the common notion that equates cognitive advancement with neocortical expansion should be revisited to consider in its stead the coordinated scaling of neocortex and cerebellum as a functional ensemble. (Abstract, 1)
Herculano-Houzel, Suzana. The Human Brain in Numbers: A Linearly Scaled-up Primate Brain. Frontiers in Human Neuroscience. 3/Art. 31, November, 2009. From our late vantage, humankind’s collaborative facility is progressively reconstructing the Metazoan neural architectures it arose from. By way of novel instrumentation, an Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, neuroscientist here argues for an evolutionary continuum best tracked by the number and density of neurons and networks. As a result, prior views of encephalization by brain size or mosaic areas are set aside for a concerted, integrative cerebral coordination. While human brains possess a premier neuronal quantity, this can be set in a constant train with life’s long cognitive ramification.
To conclude that the human brain is a linearly scaled-up primate brain, with just the expected number of neurons for a primate brain of its size, is not to state that it is unremarkable in its capabilities. However, as studies on the cognitive abilities of non-human primates and other large-brained animals progress, it becomes increasingly likely that humans do not have truly unique cognitive abilities, and hence must differ from these animals not qualitatively, but rather in the combination and extent of abilities such as theory of mind, imitation and social cognition. (8)
Hofman, Michel. Evolution and Complexity of the Human Brain. Gerhard Roth and Mario Wullimann, eds. Brain Evolution and Cognition. Heidelberg: Spektrum, 2001. Common organizing principles are seen to persist throughout their evolutionary ramification which then suggests an archetypal Bauplan. Since we posted this in March 2004, the Netherlands Institute for Neuroscience researcher has stayed on message. See for example a 2014 paper Evolution of the Human Brain in Frontiers in Neuroanatomy (Vol. 8/Art. 15).
It is evident that the potential for brain evolution results not from the unorganized aggregations of neurons but from cooperative associations by the self-similar compartmentalization and hierarchical organization of neural circuits and the invention of fractal folding, which reduces the interconnective axonal distances. (518)