Being Biological: Human Meaning in the Age of Neuroscience

Being Biological

Human Meaning

in the Age of Neuroscience

Michael A. Fuller

2022

© 2022 by Michael A. Fuller

Printed in the United States

Fuller, Michael A.

Being Biological:  Human Meaning in the Age of Neuroscience

All rights reserved.  No part of this book may be reproduced, adapted, stored in a retrieval system or transmitted by any means, electronic, mechanical, photocopying or otherwise without the prior written approval of the author.

BISAC:      SCI089000

LIT006000

Includes bibliographical references and index

ISBN      979-8-9873317-0-5 (Hard cover);

979-8-9873317-1-2 (Paperback);

979-8-9873317-2-9 (eBook)

Index by the author

To Kathy

Table of Contents

List of Figures

Introduction

Letting Go of the Self

In the twilight hours of the night that Siddhartha Gautama attained nirvana, he saw all the causes that drove his hopes, desires, and fears, all the external and internal impulses that shaped who he had become. Deeper into the night, he saw the vast net of causes and conditions in which humans had been caught throughout the centuries, the ceaseless churning of the material world that had led to exactly how things were at precisely that moment. He realized then that he had no self, no core of being that stood outside those self-generating cycles of cause and effect. He attained nirvana—the extinction of the self and of those cycles of causation—and became what he now knew he always had been, the Buddha.

This story presents a paradox of identity. In the Buddhist world of inescapable causation, the self dissolves into the universal network of becoming, only to return, exactly the same yet entirely different because the very nature of identity and the system in which it is embedded have shaken off old ontological expectations. First there is a mountain, then there is no mountain, then there is.¹ As the science of the brain steadily encroaches on our sense of freely formed identities, we as a culture will be facing such a night of dissolution of a subjective self still grounded in the remnants of old idealist dreams. I seek, at this juncture, to offer a vision of identity transformed, renewed, and deepened through dispersion into the vast, rich network of biological patterns out of which the self as we know it arises. I make no claims about the status of the soul: I simply do not know; my project is instead to account for what we can know of human experience based on what we can know empirically of the processes of the material world. Central to this empirical knowledge of the relationship of human experience to the phenomenal realm (the manifold of experience) is what neuroscience can tell us about perception, cognition, emotion, and memory.²

I write this book for readers who share a commitment to finding meaning within the nuanced patterns of the world of human experience. I hope to show that neuroscientific accounts are consistent with the complexity of this human world. That mountain, in the end, is still that mountain. The end of King Lear remains a crushing tragedy; Bach’s Mass in B-Minor continues to touch the ineffable: the hopes and sorrows of subjective experience are real.³ What is in our head, being in our head, is real: what else would it be? Our subjective life at times may seem an errant fantasy or will-o-wisp of desire or fear, but it arises from processes of imagination, thought and feeling that unfold in the brain. I suggest that engagement with neuroscientific models offers us a different understanding of our inner life and all that we label the subjective self. The biologically conceived self is the totality of neural structures—the channels and connections constructed over a lifetime of experience—and is as complex, and also as fragile and conflicted, as the self explored in the cultural traditions of the world over the past four thousand years.

Shifting Perspectives

The project of thinking of the self in biological terms is not easy, in part because biology is not just a matter of the test tubes and microscopes that, in the popular imagination, are the mainstay of research. Contemporary biology draws extensively on abstract elements of physics, chemistry, statistics, and—for neural networks in particular—on a branch of mathematics called complex systems theory. There are few simple explanations for biological phenomena in this hybrid discipline because, in fact, Nature is not simple.

The complexity and diversity of biology as a discipline reflect the complexity of its object of study. Its sub-disciplines focus on the myriad different levels of organization out of which organisms arise and within which they live. The diverse components and dynamics of life at the molecular level produce cellular structures with distinctive emergent properties deriving from their molecular organization. Cells form into tissues, and tissues form organs, and on and on until we have individual members of a species. The individuals then participate in larger social organizations and ecosystems with emergent properties deriving from the collective behavior of those individuals.⁴ The success of these emergent group properties in turn biases the genetic survival of those systemic features that, at the lower levels of organization, lead to successful behavior. Biologists study all of this with a corresponding range of research procedures and modes of thought that apply most effectively at the distinctive levels of biological organization. There is no one Biology anymore.

Exploring the mind and self as (ultimately) biological systems requires an awareness of—and respect for—the power of the distinctive paradigms designed to articulate the organizational and behavioral logic of progressively higher levels of structuring. Neuroscience from the beginning has been in active conversation with cognitive science, neurology, and cognitive linguistics. More recently, as neuroscience increasingly explores ever higher levels of brain organization, it has begun to engage with more traditional fields within the broad discipline of psychology and to test its findings and models against those of these long-established fields of study. Still, neuroscience—even in conversation with other fields—is not sufficient in itself. The disciplines needed to articulate adequately the organizational logic of a biologically conceived self extend far beyond biology. Just as chemistry is built upon physics but has its own models, procedures, and objects of inquiry distinct from physics, so, too, exploring large-scale patterns of human experience—even with a commitment to its final biological grounding—must draw upon conceptual tools and models that are different from those of neuroscience.

How, then, do the humanities participate in this cross-disciplinary conversation? Here I think it is crucial for us in the humanities to see our own work, our own domains of inquiry—literature, history, and philosophy, etc.—and our own theoretical models as part of this project of consilience that connects layer upon layer of disciplinary accounts that build upon biological models of brain organization. If we take up the challenge of seeing ourselves as part of a larger intellectual enterprise of explaining what we can of human experience within the dynamics of the material world and think of our own self-understanding in relation to other models of human meaning that arise out of the neuroscientific project, we also challenge those other models to acknowledge and accommodate the complexities of experience explored in the humanities. Artists and scholars in the humanities present a domain of experience that must be part of the human story in its own terms as well as understood as relying on a substructure of biological foundations. In this newly emerging engagement, the accounts that humanists have developed can only be enriched and deepened by their connections to the substratum of biological processes, while at the same time, making distinctive, signal contributions to the larger project.

The Argument of the Book

The argument of the book—to put it in one long sentence—is that the particular developmental logic that gives great weight to affective mechanisms in the shaping of a memory system, in which the objects and events in memory are not discrete but defined through mutual differentiation, produces an inner world of meaning bound to the body and to experience that can serve as the substructure for discourses of meaning and selfhood in the humanities. I begin with the structural logic of representation in the brain, in which contemporary neuroscientific paradigms mirror central theoretical positions in the humanities. That is, the brain models the world and the human body through a hierarchy of neural networks that define increasingly higher dimensional representational spaces. Given the mathematics of neural networks, the brain identifies the objects of experience not individually and atomically but as parts of a system of mutually differentiated activation states.⁵ Thus, the brain uses a structuralist model of meaning by difference. However, the human brain was designed for collective survival, not truth, even if having an accurate model of expectations about the body and the world is very useful for survival. The particular needs and limitations of the body as well as roles of the objects of the environment in contributing to survival crucially shape the structure of the representational systems of the brain. Hence, one key argument of this book at the level of the internal organization of neural networks is that these networks are post-structuralist: they are not arbitrary in the distinctions they make but instead are driven by need and assessments of power and possibility.

A second key argument of the book that derives from the first is that the simple divide between subjective emotion and objective cognition is not just wrong but harmful. The representational structures of the brain are not neutral. Layers of neural networks, beginning with the sensory and somatosensory cortices, extract categories of regularities in the environment and the body that a complex system of neuromodulators produced by subcortical regions define as significant. The organization of the higher order structures is determined by these subcortical systems interacting with early experience of the world and the body. What we call emotions, based on an individual’s experiential articulation of the subcortical systems, are as objective as any higher order biological system. They are real.

The third key argument considers a developmental component of the creation of the self. We are born with a particular body to particular parents in a particular place with its given culture, society, and built environment, all of which impinge as patterns upon the brain as it seeks to extract the internal and external regularities out of which it will build the self. This self is the emergent totality of systems that shape response and action.⁶ However, the brain at birth is not mature. Instead, the cortex develops from the back of the brain (the sensory cortices) forward. At birth, the sensory cortices are experience-ready: they are structured to be ready to rely on information from the already-mature primary process emotions to build neural networks that are experience-dependent. Even the establishment of the long-range connections of the sensory cortices to higher cortical processing areas is experience-dependent. The early self that arises out of this initial affect-laden mapping of the world demonstrates remarkable persistence in shaping the self throughout life.

A fourth key argument of the book derives directly from the first three: memory and language (as one component of memory) are not subject to the infinite regress of the referent but deeply embodied. Beginning in early infancy, rapidly developing cortical and subcortical networks extract meaningful patterns re-presenting emergent objects and events encountered in experience. Additional networks bind these patterns to sounds, which eventually become words, and other networks construct the syntactic features of the infant’s language. Neuroscientific research into the development of memory and language has made significant progress in outlining the ontogeny of meaning in general and of language in particular and of their connections to other aspects of infant development. The adult versions, needless to say, grow out of the initial infant structures and processes and provide us with a supple theory of reference for language that remains entirely within the material realm (and thus makes no claims beyond its limited empirical applicability). There is little cost to humanists in accepting such a neuroscientific theory of reference. Quite to the contrary, there is much to be gained. Returning language to the body and to history (and bracketing metaphysical concerns for the Absolute) turns the focus of meaning to the particularities of experience.

Taken together, the points I underscore present a model of substantial, this-worldly meaning in which the self—through its biology and its history—participates in a larger world of the patterns that permeate phenomenal experience. I argue moreover that this model of meaning as a complex web of relationships is implicit in a synthesis of the current state of the fields of computational, affective, and developmental neuroscience along with the neuroscience of memory. The humanities can—and should—draw on this emerging synthesis to participate in exploring the nature of the construction of meaning in conversation with neuroscience.

The Structure of the Book

This book presents in stages a model of meaning based on my selective synthesis of neuroscientific perspectives. The first step is large because it requires an imaginative reenvisioning of our encounter with the world in all its aspects: it asks us to turn away from our sense of the givenness of experience. We need to take seriously the specifically biological reconstruction of the encountered world and not just as a metaphor. In this account, nothing that we know, hope, feel, or remember is what it seems, as it fragments into activations of networks of neurons spread across the brain. The first chapter begins this shift in the conceptual framework by introducing the basic elements of the biological substructure of experience. The chapter first introduces neurons themselves, moves to simple mathematical models of neurons and then explores the modeling of ever more complex networks of neurons. These models for the behavior of neural networks are central to contemporary neuroscientific theorizing and provide the foundation on which the rest of the book is built. However, recent theorizing about the computational logic of the brain has come to stress that brains are built not simply to react to input but to predict what is most likely the cause of the present input and to then plan responses to that cause in a timely and accurate manner. Therefore, I next introduce the increasingly important perspective of predictive processing in which the goal of the neural organization of the neocortex is to build a model of the patterns of the world so that, once the model is developed, most of our understanding of the world in our seemingly immediate encounter with it is in fact a form of recalling past patterns, developing expectations and plans based on predicting the present, and checking for errors in those predictions.

The second chapter shifts from the tightly structured world of neural networks to an overview of the organization of the brain and its component systems within which neuronal networks take shape and connect with one another. The first goal of this chapter is simply to introduce the names of the regions of the brain that appear throughout the rest of the book so that the reader can know where the regions are, what systems they are a part of, and what their usually-described functions are. The second goal is to stress that most brain functions—from emotion to vision to planning—are an ensemble performance in which areas and nuclei from all over the brain participate. Toward this end, the last part of the chapter introduces models of connectivity in the brain that have been developing in research on network neuroscience, the study of the ways in which the discrete local neural networks interconnect to form large-scale, long-distance networks whose formal structures are studied in graph theory.⁷

The third chapter draws on the modeling from chapter one to present an overview of the visual system, the best-studied of all the sensory systems in the brain. The chapter takes another step in the fragmentation of experience. The details of the processing of visual information starting in the retina dispel the illusion of the immediacy and simple coherence of what one sees when one opens one’s eyes. Starting with the types of cells in the retina itself, the chapter makes clear that the evolved specificity of biological systems matters, but also that human systems, while distinct in many ways, are part of an evolutionary continuum. The chapter traces the ways in which visual data, already transformed in the retina, undergo layer upon layer of extractions of ever higher order patterns to identify significant objects and events. However, the end of the chapter returns to the theme of predictive processing and presents a detailed view of vision as half-seen, half predicted: the predictive model is both computationally efficient and—crucially—accounts for the massive feedback connections at every level within hierarchies of neural networks. Higher levels of the visual system develop expectations about the world (or at least about the patterns of activations they have received) and draw on these expectations to interpret and—through feedback loops—to shape the data that comes to them. The chapter presents a concrete example of how we see and live in the remembered present.

Chapter Four, on emotion, continues the exploration of the ways in which the brain shapes the neocortical modeling of the world it encounters. The brain at birth knows almost nothing about the body or the world. Yet the processes of response developed through the hierarchies of neural networks in the neocortex require specifically neocortical models of the body and the world in order to anticipate, assess, and respond. The affective system, built upon bodily connections to the structures in the brain stem, is responsible for providing information on bodily needs to the experience-dependent cortical networks both for immediate action and as a crucial way to determine what is important in the patterns of encounter. A central question for affective neuroscience is how the cortical mappings of the midbrain systems produce the emergent properties we observe in what we know as emotions. That is, humans are social creatures, yet sociality is not directly in the genes but is the tertiary-level emergent result of early system dynamics. How do the cortical responses to the midbrain systems lead to this result? The chapter sets out the three levels of the affective system and traces their interaction as well as their impact on other cortical networks for perception, cognition, planning, and memory.

While the chapters on vision and affect both stress the particular features of the biological systems that implement them, the fifth chapter, on developmental neuroscience, goes deeper into the impact of the processes by which these systems emerge in humans. Some animals are precocial—relatively mobile and mature at birth—but humans are altricial, needing to be nurtured. As noted above, the human cortex is experience ready, with some neuronal systems already adequate to begin the bootstrapping process of learning. Although the general pathways and broad functional organization of the cortex is genetically determined, much of the synaptic organization and the timing of its development are experience-dependent. Chapter Five gives an overview of the development processes, looks at the complex implications of the experience-dependent design, and concludes with an exploration of the dynamics of the emergence of the neuronal self.

The emergent neuronal self develops not just expectations but dispositions toward objects and events and towards its own body. The processes for memory—its encoding, maintenance, and appropriate recall—are crucial in the development of the neuronal networks of the brain and are the topic of Chapter Six. In modeling the important perceived regularities in the world, any change in synaptic weights in the construction of neural networks is a form of memory. However, most discussions of memory in the brain focus on higher order processes that mature as the brain develops in childhood. Traditionally, memory has been divided into a set of distinct functional types: two types of memory used in immediate processing—short-term and working memory—and two types of long-term memory: procedural and declarative memory (which then is divided into episodic and semantic memory). The chapter will focus on the development of episodic and semantic memory. It begins with the neuronal networks for initially encoding experience into episodic memory and then shifts to sleep and the process of memory consolidation which creates the links between episodic and semantic memory. The chapter concludes by briefly looking at the neuroscience of a particularly complex, flexible and distinctly human form of high-order combinatorial semantic memory structures—language—and what linguistic objects (texts) contribute to the shaping of the self as it is articulated within semantic memory.

The first six chapters examine key neuronal systems that provide the substructure for experience, selfhood and meaning. The final chapter uses two examples to explore the implications of the microstructural dynamics for the highly mediated patterns of lived experience. Since the neuroscientific models in this book analyze how we attend to the world, they serve as a form of phenomenology, which studies the logic of how we apprehend the objects and events that appear before us. In the first part of the chapter, I therefore consider analogies between the neuroscientific account and the formal phenomenology of Jean-Luc Marion as presented by Cassandra Falke’s application of Marion’s phenomenology to the experience of reading. I end with a comparison of the embodied, phenomenological model of meaning implicit in the neuroscientific framework with the classical Chinese poetic tradition, which is built on assumptions that mirror the neuroscientific model in significant ways. I offer these frameworks from very different traditions as two examples—among many possibilities within our broader humanistic endeavor—of ways in which we can contribute distinctive articulations of human experience both to our conversations with neuroscience and to our own explorations of how we, as biological creatures, participate in a world deeply resonant with meaning.

Chapter One

Reframing

Meaning lies in patterns of connection and their implications. Humans have evolved as creatures powerfully built for the extraction of—and response to—patterns in the world, in the body, and in the body’s interaction with the world. This chapter introduces the microstructure of the human capacity to discover and create meaning and lays the foundation for all that follows in my account. The chapter introduces the basic models for neural network processing through which the brain organizes patterns, from basic perception to memory, emotion, and the