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VII. Our Earthuman Ascent: A Major Evolutionary Transition in Individuality

3. A Complementary Brain and Thought Process

Schore, Allan. The Self-Organization of the Right Brain and the Neurobiology of Emotional Development. Marc Lewis and Isabela Granic, eds. Emotion, Development, and Self-organization. Cambridge: Cambridge University Press, 2000. Dynamic systems theory can bring theoretical rigor to the course of human maturation as an exemplar of a universal evolution. The right hemisphere develops first to engage the mother-infant “reciprocal interactions," which are nonlinear in kind as opposed to the more linear and discrete left brain.

A central principle of this perspective is that a dynamical complex system is assembled as a product of the interactions of the elements of the system in a particular context. The early organization of the human brain is a prototypical example of a hierarchically structured complex system that is dynamically assembled and expresses a capacity to evolve toward a state of higher organization. (155)

Siegel, Daniel. The Mindful Brain. New York: Norton, 2007. The UCLA pediatric psychiatrist and author worries that our alienated, material culture lacks a palliative moral compass and reflective awareness. A major advance would be a “bilateral consciousness” joining the “logical, linguistic, linear, and literal” output of the left hemisphere with the right’s visuospatial, nonverbal, holistic, emotional images. Such an integral balance, as female brains achieve, has a new neurological basis since the cortical columns of the right side are more cross-connected than isolated regions of the left half. An ability to take in the whole, contextual picture would do us well, imbue education, and to help truly achieve, as one might put it, united states.

Singer, Wolf. Recurrent Dynamics in the Cerebral Cortex: Integration of Sensory Evidence with Stored Knowledge. Proceedings of the National Academy of Sciences. 118/33, 2021. Into the 2020s, the senior MPI Brain Research neuroscientist (search) provides a definitive (natural) exegesis of the presence of dual modes of active neural cognition. An on-going informative interplay is described between a person’s represented memory and new experiences so as to reach a viable, beneficial response. In this way, a balance and harmony can occur between one’s past familiarity and a variable external world. An accord then becomes possible of conserved values with novel occasions, rather than current politics where these conserve and create, regress or progress phases are locked in mortal combat. In August of this year, an incarnate complementarity thus achieves a strong scientific affirmation in our desperate midst. Here is the very EarthWise edification that so needs to gain a public veracity and avail in the time left.

Current concepts of sensory processing in the cerebral cortex emphasize serial extraction and recombination of features in hierarchically structured feed-forward networks in order to view the relations among the components of perceptual objects. These concepts are implemented in convolutional deep learning networks and have been validated by the astounding similarities between the functional properties of artificial systems and their natural counterparts. However, cortical architectures also display an abundance of recurrent coupling within and between the layers of the processing hierarchy. This massive recurrence gives rise to highly complex dynamics whose putative function is poorly understood. Here a concept is proposed that assigns specific functions to the dynamics of cortical networks and combines, in a unifying approach, the respective advantages of both recurrent and feed-forward processing. (Abstract excerpt)

Two Complementary Strategies for the Analysis and Encoding of Relations The virtually infinite variety of perceptual objects results from variable combinations of a relatively small set of elementary features, just like the 26 letters of the Latin alphabet suffice to compose western literature. Therefore, cognitive systems need effective strategies to identify these features and to encode the relations among them. (1)

Encoding of Relations in Feed-Forward Networks. One common strategy for the encoding of relations is based on the generation of conjunction-specific neurons in hierarchically structured feedforward networks. Neurons tuned to elementary features distribute their responses through divergent and convergent connections to neurons of the respective next layer. Dynamic Encoding of Relations in Recurrent Networks. A complementary strategy to capture relations among components relies on dynamic combinatorial codes, similar to those used by natural languages. (2)

Last but not least, there is a puzzling analogy with the processes that make quantum computing so fast and efficient. The superposition of wave functions bears similarities to the covert superposition of priors in the correlation structure of spontaneous activity, and the simultaneous and probabilistic evaluation of nested relations resembles the virtually simultaneous and holistic interaction between network nodes that represent, in a probabilistic and graded way, the presence of particular features. It would be truly fascinating if evolution had succeeded to realize, with classical mechanisms, those functions
that quantum computers are particularly good at: the parallel and therefore ultrafast evaluation of the relations between a huge number of probabilistic variables (9)

Smith, Eliot and Jamie DeCoster. Dual-Process Models in Social and Cognitive Psychology. Personality and Social Psychology Review. 4/2, 2000. The growing case for two distinct, alternative modes of thought and memory. Longer term recall is slower and more associative in kind and involves pattern completion while a rapid short term faculty uses a discrete, rule-based procedure.

Rule-based processing also tends to be analytic, rather than based on overall or global similarity. For example, a symbolic rule may single out one or two specific features of an object to be used in categorization, based on conceptual knowledge of the category. In contrast, associative processing categorizes objects nonanalytically, on the basis of their overall similarity to category prototypes or known exemplars. (112)

Spelke, Elizabeth, et al. Beyond Core Knowledge: Natural Geometry. Cognitive Science. 34/5, 2010. In an issue dedicated to the work of Susan Carey, Harvard psychologists (as Carey also) from still another aspect, identify as the Abstract avers two harmonizing phases of a relational pattern, and entrained items. See also in the same issue a companion paper “Bootstrapping the Mind: Analogical Processes and Symbol Systems” by Dedre Gentner.

For many centuries, philosophers and scientists have pondered the origins and nature of human intuitions about the properties of points, lines, and figures on the Euclidean plane, with most hypothesizing that a system of Euclidean concepts either is innate or is assembled by general learning processes. Recent research from cognitive and developmental psychology, cognitive anthropology, animal cognition, and cognitive neuroscience suggests a different view. Knowledge of geometry may be founded on at least two distinct, evolutionarily ancient, core cognitive systems for representing the shapes of large-scale, navigable surface layouts and of small-scale, movable forms and objects. (1)

Stephan, Klaas Enno, et al. Mechanisms of Hemispheric Specialization. Neuropsychologia. 45/2, 2007. Neuroimaging studies of asymmetrical degrees of connectivity amongst bilateral brain areas provide a novel approach to their understanding. In a target test to sort detail and field, the left hemisphere would notice a highlighted letter in a word and phrase, while the right tended to the overall spatial array.

Sun, Weinan, et al.. Organizing Memories for Generalization in Complementary Learning Systems.. Nature Neuroscience. July, 2023. Janelia Research Campus, Virginia and Harvard University brain researchers including James Fitzgerald contribute another view on the effective presence of a dynamic reciprocity between archetypal discrete and integral aspects.

Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. These functions depend on system consolidations by way of neocortical memory traces from hippocampal precursors. Here we introduce a new formalization that reveals a bicameral tension. We resolve it by postulating that memories only consolidate when it aids generalization. This framework accounts for partial hippocampal–cortical memory transfer and a normative principle to understand field observations. Generalization-optimized systems consolidation thus provides new insight into how adaptive behavior benefits from complementary learning systems specialized for memorization and generalization. (Abstract)

Tadic, Bosiljka, et al. Functional Geometry of Human Connectomes. Nature Scientific Reports. 9/12060, 2019. Jozef Stefan Institute, Ljubljana, Slovenia systems physicists (search BT) and a Wilfrid Laurier University, Waterloo, Canada mathematician apply sophisticated network theories to cerebral studies via an expansion to and emphasis upon inherent, generative topologies, aka simplical complexes (Bianconi). In regard, they serve to inclusion of previously unnoticed patterns and processes, which in this neural instance reveals a deeper degree of intra- and inter-hemispheric connectivities. Building on a Hungarian brain atlas (Szalkai), neuroimages of equal male and female subjects finds that women’s brains possess a denser intricacy, as the quotes note. See also Hidden Geometries in Networks Arising from Cooperative Self-Assembly by Mulovan Suvakov, et al in this journal (8/1987, 2018).

Mapping brain imaging data to networks, where nodes represent anatomical regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity. (Abstract)

To summarise, our study reveals how the functional geometry of human connectome can be expressed by higher-order connectivity, simplicial complexes and induced cycles. This kind of structure is built into the anatomical communities of the brain at the mesoscopic scale in both hemispheres. In this context, new topological measures of the consensus networks quantifies the perceptive differences between connectomes. Specifically, in the studied female and male consensus connectomes, a part of connections is more natural to invoke in the female than in the male brain, where much more fibres need to be launched to identify them. Whereas the other fraction of such connections consists of edges that appear exclusively in the consensus female connectome, they have not been identified in the consensus male connectome. (9)

TenHouten, Warren. Time and Society. Albany: State University of New York Press, 2005. From studies of Australian Aborigines and European-Australians, the UCLA biosociologist proposes a complementarity based on bicameral brain hemispheres. As noted in the quotes, this neural basis can define two modes of time perception and subsequent social culture. A recapitulation between individual brain maturation and the course of history is tacitly evident, for both proceed from an initial holistic milieu to a later, longer particulate stage. (Now poised at the verge of a worldwide humankind, an emergent reciprocity of both phases would seem a salutary resolve.)

It is proposed that the ordinary-linear mode of time consciousness is an aspect of the logical-analytic, serial mode of information processing of the left side of the brain, and patterned-cyclical time consciousness of the gestalt-synthetic, global, and simultaneous information processing of the right side of the brain. (7) The RH maintains in the present a spatial-cognitive model of our surroundings, a global awareness of the web of life, of the patterns, processes, and oscillations of nature and culture; it is a worldview, a dynamically interrelated basic cognitive structure that is collectively held and constantly updated. (75)

Insofar as the left and right sides of the brain are involved in spatial and linear-temporal information processing, respectively, we see a process of development first of RH-dependent spatial reasoning and second of LH-dependent temporal reasoning. (79) In the development of the human, the right hemisphere develops earlier than does the left hemisphere, which is not a new phenomenon with humans but rather has a long evolutionary history and exists in other species as well. (116)

Thatcher, Robert. Cyclic Cortical Reorganization: Origins of Human Cognitive Development. Geraldine Dawson and Kurt Fischer, eds. Human Behavior and the Developing Brain. New York: Guilford Press, 1994. A discussion of the prime properties and formative sequence of the bicameral brain.

It is argued that the left-hemisphere expanding sequence reflects a process of functional integration of differentiated subsystems, whereas the right-hemisphere contracting sequence is a process of functional differentiation of previously integrated subsystems. These left- and right-hemisphere cycles are repeated throughout the life span and are postulated to represent a process that iteratively narrows the gap between structure and function by slowly sculpting and refining the microanatomy of the brain. (232-33)

Thompson, Valerie. Towards a Metacognitive Dual Process Theory of Conditional Reasoning. Oaksford, Mike and Nick Chater, eds. Cognition and Conditionals: Probability and Logic in Human Thinking. Oxford: Oxford University Press, 2010. In this chapter, the University of Saskatchewan psychologist succinctly contributes to growing realizations of these archetypal complements. But once again, and in the next chapter “A Multi-layered Dual-Process Approach to Conditional Reasoning” by Niki Verschueren and Walter Schaeken, in this approach they are yet to be connected with their obvious brain hemispheres.

Dual-Process Theories have emerged as the dominant theoretical framework for human reasoning and decision making. These theories commonly assume that reasoning and decision making are accomplished by the joint action of two types of processes: Automatic system 1 processes give rise to a highly contextualized representation of the problem and produce rapid, heuristic (experienced-based, common sense) answers. System 2 implements more deliberate, decontextualized analytic processes.

Trimble, Michael. The Soul in the Brain: The Cerebral Basis of Language, Art, and Belief. Baltimore: Johns Hopkins University Press, 2007. An esteemed professor of behavioral neurology at the University of London affirms complementary hemispheres with the neglected right side as the seat of our integral affinity.

The left and right hemispheres of the brain manipulate information differently, but it is only recently that the important contributions of the right hemisphere to our cultural achievements have become clearer. The right hemisphere more than the left is involved with the creation of the sense of self, is dominant for control of emotion and for retrieval of autobiographical memories, and is intimately involved with processing personally bonded features of an individual’s world – essentially, that which is familiar and is necessary for the creation and appreciation of poetry and music… (231-232)

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