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

3. A Complementary Brain and Thought Process: A Family Mind

Grossberg, Stephen. A Half Century of Progress Towards a Unified Neural Theory of Mind and Brain. Kozma, Robert, et al, eds. Artificial Intelligence in the Age of Neural Networks and Brain Computing. Cambridge, MA: Academic Press, 2018. The veteran Boston University neuroscientist and original theorist of this whole BI and AI revolution reviews his 50 year project (search) to theoretically and conceptually explain how our bilaterally complex brains proceed to envision, quantify, consider, think, learn, and effectively act in dynamic social and natural environments. The invited chapter is fully available on the author’s publication page. See herein his major paper Towards Solving the Hard Problem of Consciousness a year earlier in Neural Networks (87/38, 2017), along with Iain McGilchrist 2019. We include 3 quotes to convey its essence and message.

This article surveys some of the main design principles, mechanisms, circuits, and architectures that have been discovered during a half century of systematic research aimed at developing a unified theory that links mind and brain, and shows how psychological functions arise as emergent properties of brain mechanisms. This project advanced in stages by way of revolutionary computational paradigms like Complementary Computing and Laminar Computing that constrain the kind of unified theory that can describe the autonomous adaptive intelligence that emerges from advanced brains. Adaptive Resonance Theory, or ART, is one of the core models that has been discovered in this way. ART is not, however, a “theory of everything” if only because, due to Complementary Computing, different matching and learning laws tend to support perception and cognition on the one hand, and spatial representation and action on the other. (Abstract excerpt)

Complementary Computing clarifies why there are multiple parallel processing streams in the brai to resolve computational uncertainties that cannot be overcome by just one processing stream or stage. Complementary Computing describes how the brain is organized into complementary parallel processing streams whose interactions generate biologically intelligent behaviors. A single cortical processing stream can individually compute some properties well, but cannot, by itself, process other computationally complementary properties. Pairs of complementary cortical processing streams interact to generate emergent properties that overcome their deficiencies to compute complete information with which to represent or control some faculty of intelligent behavior. (35)

The WHAT and WHERE cortical streams are complementary: The category learning, attention, recognition, and prediction circuits of the ventral, or What, cortical processing stream for perception and cognition are computationally complementary to those of the dorsal, or Where and How, cortical processing steam for spatial representation and action. One reason for this What - Where complementarity is that the What stream learns object recognition categories that are substantially invariant under changes in an object's view, size, and position. These invariant object categories enable our brains to recognize valued objects. They cannot, however, locate and act upon a desired object in space. Cortical Where stream spatial and motor representations can locate objects and trigger actions towards them, but cannot recognize them. By interacting together, the What and Where streams can recognize valued objects and direct appropriate goal-oriented actions towards them. (36-37)

Grossberg, Stephen. Conscious Mind, Resonant Brain: How Each Brain Makes a Mind. New York: Oxford University Press, 2022. The octogenarian Boston University poly-neuroscientist was often asked to write a summary work about his luminous studies (search). As a result, this large format, illustrated, 700 page volume proceeds to substantiate and explain his Complementary Computation theory of dynamic cerebral processes and cognitive features. As the quotes describe, into the 21st century and 2020s a vital finding can now be established. Our human neural facility, awareness and responsive behavior is distinguished by a double basis of opposite but reciprocal functions and qualities. One version is the What/Where model of object view and spatial place, which draws on dual cortical streams. Another instance, of course, is our hemispheric halves with their archetypal contrast of dot/connect, node/link, the litany goes all the way to male and female compete/cooperate aspects.

Malleable network topologies, as they serve to inform and communicate are noted to play a significant role. In further regard, as noted in an Introduction (7), Chapter 17 traces our emergent, personal brain/mind epitome deep down to the original complex dynamics of a physical source stage. Sections such as A Universal Developmental Code, Complementarity Biological and Physical Laws, A Universal Measurement Device of and in the World express how active neural cognizance can be found to self-organize in similar accord with physical principles and phenomena.

The work embodies a revolutionary Principia of Mind that clarifies how autonomous adaptive intelligence is achieved. Because brains embody a universal developmental code, further insights emerge about shared law in living cells from primitive to complex and onto how networks of interacting cells support developmental and learning processes in all species. These novel brain design principles of complementarity, uncertainty, and resonance are then traced to the physical world with which our brains ceaselessly interact, and which enable our brains to incrementally learn to understand those laws, thereby enabling humans to understand the world scientifically. (Publisher)

A question concerns how the complementarity organization of our brains may be related to the complementary properties of the physical world. Here I will note that this occurrence was first proposed in the 1920s by the physicist Niels Bohr from quantum mechanics. The phenomena involves different aspects such as position and momentum for waves and particles. If the brain is a kind of universal measurement system of physical environs such as light, heat and pressure. This fact raises the question of whether brains may have assimilated basic physical principles throughout evolution. (7)

What and Where Cortical Processing Streams These two types of learning, perceptual/cognitive vs. spatial motor, to on in different brain systems. The ventral>/i> stream processes information that enables us to recognize objects. It is thus called the What version. Thedorsal phase provides information about where objects are in space and how to act upon them. It is accordingly called the Where and How mode. (28) I will suggest in Figure 1.19 how they obey “computationally complementary” laws. Complementarity implies the need to balance the capabilities of each version against those of the other. (aka herein as a Golden Mean). (28)

Complementary Processing Streams for Perception/cognition and Space/action. I have called this paradigm Complementary Computing because it describes how the brain is organized into complementary parallel processing streams whose interactions generate biologically intelligent behaviors. A singly cortical stream can compute some properties well, but cannot, by itself, process orther computationally complementary properties. Pairs of cortical streams interact, using multiple stages, to generat emergent features that overcome their complementary deficiencies to compute complete information with which to represent or control some intelligent faculty. (29)

Universal Design for Self=Organizing Measurements and Prediction Systems. Implicit in these conclusions is the fact that principles, mechanisms and architectures in this book are about fundament problems of measurement and how a self-organizing system and represent and predict outcomes in a changing world. Mind and brain are explained by these theories because they are natural computational embodiments of these occasions. (34)

Grossberg, Stephen. The Complementary Brain: Unifying Brain Dynamics and Modularity. Trends in Cognitive Sciences. 4/6, 2000. A pervasive reciprocity amongst neural activities such as gestalt ‘boundary completion’ and detailed ‘surface filling-in,’ which then mirrors the extant physical realm, is described.

This article reviews evidence that the brain’s processing streams compute complementary properties. Each stream’s properties are related to those of a complementary stream in the way that two pieces of a puzzle fit together. It is also suggested how the mechanisms that enable each stream to compute one set of properties prevent it from computing a complementary set of properties….I suggest that the concept of pairs of complementary processes brings new precision to the idea that both functional specialization and functional integration occur in the brain. (234) According to this view, the organization of the brain obeys principles of uncertainty and complementarity, as does the physical world with which brains interact (and of which they form a part). I suggest that these principles reflect each brain’s role as a self-organizing measuring device in and of the world. (235)

Grossberg, Stephen. Towards Solving the Hard Problem of Consciousness. Neural Networks. 87/38, 2017. The Boston University pioneer systems neuroscientist (search) continues his half century of innovative theoretical contributions. Visit SGs website for more publications, along with many credits such as founding editor of this journal. The 50 page essay further finesses how dynamic brain resonances achieve an informed awareness by way of two reciprocal cognitive modes. This generative essence dubbed Complementary Computing proceeds by an integral interplay of ventral fast object What and slower dorsal holistic Where (Why) streams. Three quotes follow to properly report this advance, bold added. And we record that these insights add more scientific evidence for a natural, universally manifest, bigender trinity. But a deep disconnect remains between such findings and political, militarist societies and nations locked in mortal conflict between these very archetypes. .

The hard problem of consciousness is the problem of explaining how we experience qualia or phenomenal experiences, such as seeing, hearing, and feeling, and knowing what they are. To solve this problem, a theory of consciousness needs to link brain to mind by modeling how emergent properties of several brain mechanisms interacting together embody detailed properties of individual conscious psychological experiences. This article summarizes evidence that Adaptive Resonance Theory, or ART, accomplishes this goal. ART is a cognitive and neural theory of how advanced brains autonomously learn to attend, recognize, and predict objects and events in a changing world. ART has reached sufficient maturity to begin classifying the brain resonances that support conscious experiences of seeing, hearing, feeling, and knowing. This analysis also explains why not all resonances become conscious, and why not all brain dynamics are resonant. The global organization of the brain into computationally complementary cortical processing streams (complementary computing), and the organization of the cerebral cortex into characteristic layers of cells (laminar computing), figure prominently in these explanations of conscious and unconscious processes. (Abstract excerpts)

The first paradigm is called Complementary Computing. Complementary Computing describes how the brain is organized into complementary parallel processing streams whose interactions generate biologically intelligent behaviors. A single cortical processing stream can individually compute some properties well, but cannot, by itself, process other computationally complementary properties. Pairs of complementary cortical processing streams interact, using multiple processing stages, to generate emergent properties that overcome their complementary deficiencies to compute complete information with which to represent or control some faculty of intelligent behavior. (44-45)

For example, the category learning, attention, recognition, and prediction circuits of ART are part of the ventral, or What, cortical processing stream for perception and cognition. The ventral stream exhibits properties that are often computationally complementary to those of the dorsal, or Where and How, cortical processing stream for spatial representation and action. One reason for this What–Where complementarity is that the What stream learns object recognition categories that are substantially invariant under changes in an object’s view, size, and position. These invariant object categories enable our brains to recognize valued objects without experiencing a combinatorial explosion. They cannot, however, locate and act upon a desired object in space. Where stream spatial and motor representations can locate objects and trigger actions towards them, but cannot recognize
them. By interacting together, the What and Where streams can recognize valued objects
and direct appropriate goal-oriented actions towards them. (45)

Habib, Reza, et al. Hemispheric Asymmetries of Memory. Trends in Cognitive Sciences. 7/6, 2003. The left prefrontal cortex is involved with episodic memory encoding while right PFC processes memory retrieval and remembering.

Halford, Graeme, et al. Relational Knowledge: The Foundation of Higher Cognition. Trends in Cognitive Science. 14/11, 2010. Neuroscientists from Australia and Japan claim, which much technical theory, that an integrative, semantic analogy is of premier importance in the evolution and conduct of operational thought. With a nod to the “dual process” school, this phase is seen as complementary to analytic particulars.

Han, Dongqi, et al. Synergizing habits and goals with variational Bayes. Nature Communications. 15/4461, 2024. Microsoft Research Asia, Shanghai, & Okinawa Institute of Science and Technology neuroscholars propose still another edition of nature’s common propensity to seek and adopt dual modes of an ingrained familiarity which can also be open to and assimilate new experiences. Many other versions spread across the website such as bifocal tradition and innovation (C. Keyes) and Iain McGilchrist’s left thing – right image brain/world. We then wonder in the third decade of our global 21st century as their polar opposition becomes violent however can all these substantial findings be seen as a natural optimum propensity. See also Linking fast and slow: The case for generative models by Johan Medrano, et al in Network Neuroscience. (8/1, 2024).

Both reliable and flexible behaviors are vital for biological and artificial embodied agents. Such responses are often set into two types: habitual (fast but rigid), and goal-directed (open but slow). Their occasions have been attributed to dual systems in the brain, but recent studies have revealed a sophisticated interplay between them. Our theoretical approach uses variational Bayesian theory, see note below. Habitual behavior depends on the prior experience, without a specific reason, while goal-direction relies on intention herein by minimum free energy. Our work suggests a fresh perspective on the neural mechanisms of complementary habits and goals, so to shed light on future research in decision making. (Excerpt)

In cognitive neuroscience, intelligent agents such as people and other mammals are thought to engage in two types of habitual and goal-directed behaviors. Habitual refers to the actions that are performed automatically, without thought or intent, so as to maximize benefits such as seeking food and avoiding danger. Goal-orientation has the aim of achieving something such as going to a certain place. This mode is based on knowledge about the world and responsive to an environment since it involves conscious decision-making and planning. (1)

Both efficient and flexible activities are crucial for biological agents. In regard, we proposed a novel model to provide better cognitive explanations by way of a deep learning variational Bayes which enables simulations using vision-based tasks with motor action. Our framework sheds new light on how to best achieve and balance both reciprocal states. (9)

Bayesian statistics compute and update probabilities after obtaining new data. Bayes' theorem then implies the conditional probability of an event as well as prior information or beliefs about the event or conditions. Variational Bayesian methods are a family of techniques typically used in complex statistical models consisting of observed variables (data) as well as unknown parameters, latent variables, and relative randomness.

Han, Shihui and Ernst Poppel, eds. Culture and Neural Frames of Cognition and Communication. Berlin: Springer, 2011. An edition in Springer’s On Thinking series based on a Sino-German workshop on cognitive neurosciences held in Beijing, October, 2008. A project of Peking University and Munich University, it was sponsored by the Parimenides Center in Munich. Parimenides, a 5th century Greek scholar, embodies the view of a deeper, primary dimension beyond appearances, from which our world emanates and gains significance. This volume discusses bicameral Asian and European societies with regard to relative cerebral substrates and integral and analytical complements. Initial chapters by neuroscientists such as Bruce Wexler, Joan Chiao, Genna Berko, Georg Northoff and Yinn Ma draw on neuroimaging techniques to nuance neural anatomies between the reciprocal cultures. Papers by Nalini Ambady, Dida Fleisig, Yoshihiro Miyake, Elenora Rossi, and colleagues go on to insights about life’s self-making development upon a sequentially bilateral planet. For example, westerners seem to abstract figures from ground, while eastern attention is more upon the field context in which articles abide. Contributions by Albrecht von Muller and Britt Glatzeder are noted herein.

Hartwigsen, Gesa, et al. How does Hemispheric Specialization Contribute to Human-defining Cognition? Neuron. 109/13, 2021. MPI Human Cognition and Brain Sciences, University of Montreal (Yoshua Bengio) and McGill University neuropsychologists advance our growing understandings of how totally important the asymmetric, complementary halves of our cerebral endowment are to every aspect of cognitive activity. The paper then achieves a rarest comparison with the dual process model to faster, serial detail and slower, holistic context systems. Into the 2020s, a vital realization these bigender archetypes signify nature’s universal parents to children bicameral code-script.

Many human cognitive faculties arise from flexible interplay between specific neural modules, within hemispheric asymmetries. Here, we discuss how these computational design principles can enable advanced cognitive operations such as semantic understandings of world structure, logical reasoning, and communication via language. We draw parallels to dual-processing theories of cognition akin to (Daniel) Kahneman’s System 1 and System 2. We integrate these aspects with the global workspace theory to explain the dynamic relay of information between both modes. (Abstract excerpt)

Hellige, Joseph. Laterality. Ramachandran, V. S., editor-in-chief. Encyclopedia of the Human Brain. Amsterdam: Academic Press, 2002. A summary article that affirms a basic complementarity of higher and lower frequency, categorical and spatial, processing capabilities between left and right hemispheres. Also surveyed is their evolutionary path through the animal kingdom and the right to left developmental sequence in humans.

Herve, Pierre-Yves, et al. Revisiting Human Hemispheric Specialization with Neuroimaging. Trends in Cognitive Sciences. 17/2, 2013. Groupe d’Imagerie Neurofonctionnelle, Université Bordeaux Ségalen, neuroscientists report novel instrumental insights and verifications of the functional lateralization of our asymmetrical brains. These new capabilities can better assess the relative engagement of each side from early childhood to adult maturation. In general, a consistent leftward shift develops with age from an early “inter-hemispheric” balance to a dominant LH “intra-hemispheric connectivity.” Again the RH is found to specialize for visuospatial attention and the LH for language.

Hickok, Gregory and Steven Small, eds. Neurobiology of Language. Cambridge, MA: Academic Press, 2015. A UC Irvine cognitive scientist and a neurologist assemble an 89 chapter treatise with main sections about Neurobiological Foundations, Behavioral Foundations, Large-Scale Models, Development, Learning, and Plasticity, Perceptual Analysis of the Speech Signal, Word and Sentence Processing, Discourse Processing and Pragmatics, Speaking, Conceptual Semantic Knowledge, Written Language, Animal Models, Memory for Language, Breakdown and Treatment, and Prosody, Tone, and Music. We enter here because in many places the volume endorses a dual process theory (search e.g. Nina Kraus, Maryanne Wolf, Laura Otis) which involves a whole brain interplay of left side letter detail and right half prosody relations. In regard see 24. Are Pathways and Streams in the Auditory Cortex by Josef Rauschecker and Sophie Scott, and 27. The Dual Loop Model in Language by Cornelius Weiller, et al. As a surmise, it seems that cerebral form and activity always reverts to these complementary archetypes.

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