The Experience of the Tragic
Vladislav Pedder

© Vladislav Pedder, 2025

ISBN 978-5-0067-4550-6

Created with Ridero smart publishing system

Introduction

“I think human consciousness is a tragic misstep in human evolution. We became too self-aware, nature created an aspect of nature separate from itself, we are creatures that should not exist by natural law.

We are things that labor under the illusion of having a self; an accretion of sensory, experience and feeling, programmed with total assurance that we are each somebody, when in fact everyone is nobody…”

– Rust Cohle, True Detective

This work continues the philosophical trajectory related to the investigation of the tragic as an ultimate cognitive and ontological condition. It has emerged from my translation and research efforts aimed at introducing the works of Peter Wessel Zapffe into the Russian-speaking context. In 2024, I completed the first full translation of his book On the Tragic and subsequently gained access to the complete ten-volume collection of his writings at the National Library of Norway. After prolonged searches, rejections, and copyright challenges, the first Russian editions of Zapffe’s works – thanks to my collaboration with the publishing house Totenburg – were published in Russia in 2025, after this book had already been completed. This material served as the foundation for a critical reflection on the limits of the philosophy of the tragic in light of contemporary ontological, cognitive, and neuropsychological approaches.

The present text is written from the perspectives of two figures – Professor N. and Professor P. These are not two authors nor two polemical viewpoints. Rather, they represent two theoretically articulated positions through which a philosophical analysis of the boundaries of human existence is conducted. This mode of presentation was chosen deliberately to emphasize that the human being is not a fixed entity but a dynamic system of states in which various, sometimes opposing, modes of interpretation coexist. The division into Professor N. and Professor P. is less a literary device and more an attempt to reveal the full internal complexity and instability of the mind.

Professor N. proposes an interpretation of human existence within the framework of the concept of liminal acceptance – a model of conscious retention in a state of ontological uncertainty without resorting to compensatory strategies. His approach is based on the rejection of normative narratives and appeals to final meanings. Liminal acceptance formalizes the state of a subject situated at the boundary between the explainable and the ineffable. At the core of Professor P.‘s position lie humility, ethical restraint, and the rejection of metaphysical justifications. He views human cognition as a system of predictive coding, compelled to operate under conditions of persistent informational incompleteness and environmental uncertainty.

Professor P. criticizes both the proposed model of liminal acceptance and Zapffe’s philosophy in its normative aspects. His position is grounded in the conceptual introduction of the category of differentiating experience as an ontologically primary level of reality. In his interpretation, experience is not the empirical content of consciousness but a fundamental, irreducible interaction between the system and reality, preceding any attempt at comprehension. Experience encompasses both cognitive and affective components and cannot be reduced to perception, meaning, or narrative structure.

Within this logic, all forms of philosophical response – including Professor N.‘s liminal acceptance – are secondary relative to experience, which conditions them, while itself remaining irreducible to them. Professor P.‘s position can be characterized as an ontologically oriented pessimism, free from the aestheticized melancholy characteristic of E. Cioran or A. Karako and from romanticized negativity. Unlike Ligotti, Professor P. excludes the aestheticization of alienation, focusing instead on the analytical fixation that no model can exhaust the structure of reality, as the latter is always already given in irreversible experience.

Thus, the study establishes a two-tiered perspective:

– on one hand, it proposes a methodology for engaging with existential uncertainty;

– on the other hand, it demonstrates the limits of any methodology by affirming that the experience of the world cannot be reduced to structure, norm, or ethics.

This bipartite structure has been deliberately chosen: it allows for the consideration of thought not as a unified, completed system, but as a multiplicity of possible responses to the same ontological problem. The study does not aim to synthesize the positions nor impose a ready-made conclusion upon the reader. Instead, it offers the opportunity to regard difference as a form of productive tension between the attempt at cognitive retention and the acknowledgment of the irreversible flow of experience.

The decision – to accept one of these positions, to oscillate between them, or to reject both – remains with the reader.

Part 1. The Existential Limits of Reason

Chapter 1. Blind Complication

This chapter addresses the fundamental foundations from which the history of the complexity of matter begins. We will examine how complex structures arose from the primary forms of substance, leading to the emergence of life, reason, and consciousness. This chapter is dedicated to the origins of all that exists and their role in shaping the complex world we observe today.

This account was necessary because all the topics discussed further began with the question of where and in what form the first substance appeared. Everything that happened subsequently is merely its complication – the result of natural development. Without understanding this, it will be difficult to fully comprehend the philosophical and existential questions raised in this book.

If you are already familiar with this material, you may proceed directly to point 4 of the first chapter – “The Existential Limit of Prediction.”

For many centuries, humanity sought to understand the origin of the world and life. Early conceptions often explained all that exists as the result of the design of a higher power. In antiquity, philosophers such as Plato and Aristotle sought order and purpose in nature, presuming that the world was arranged according to some rational cause. The Middle Ages brought ideas of divine creation, in which life and the entire Universe were regarded as the outcome of God’s creative act.

However, with the advancement of science in the modern era, these views began to be challenged. In the nineteenth century, Charles Darwin proposed his theory of evolution by natural selection, which revolutionized the understanding of the world and life (Darwin, 1859). Darwin demonstrated that the diversity of life forms is not the result of any specific design but rather the consequence of random mutations and selection processes that ensure the survival of the fittest individuals. Evolution, he debated, has no ultimate goal and does not progress toward perfection; it is a continuous process of change, whereby each generation adapts to changing conditions.

However, despite scientific explanations, many continued to seek purpose and meaning in the process of evolution. Science, armed with Occam’s razor¹, not only eliminated the idea of divine design from the equation but also the very concept of a final purpose. Evolutionary biologist Richard Dawkins, developing this approach, employs the metaphor of the “blind watchmaker” to explain that evolution is not a purposeful process but a random and unconscious mechanism, which lacks any predetermined goal or design, yet nonetheless results in complex and organized outcomes. He wrote:

Evolution has no long-term goals. There are no distant objectives or final perfection that could serve as criteria for selection, although human vanity cherishes the absurd notion that our species is the ultimate goal of evolution. In reality, the criterion for selection is always short-term – simple survival; or more precisely – reproductive success. What, in retrospect after geological epochs, appears as a movement toward some distant goal is, in fact, always a byproduct of many generations of short-term selection. Our “watchmaker” – cumulative natural selection – is blind to the future and possesses no long-term objectives.

This is what we will discuss further.

1. The Emergence of a Complex World

1.1 Self-Organization and the Absence of Purpose

The contemporary scientific understanding of the universe’s structure rejects the idea of teleology or an original design. Instead, the world as we know it is the result of processes of self-organization and gradual complexity unfolding within the framework of physical laws. These processes were not driven by an external purpose but developed due to the interactions of numerous elements over vast timescales.

Fundamental discoveries in physics and cosmology have shown that the universe originated from the Big Bang approximately 13.8 billion years ago. The concept of the Big Bang was first proposed by the Belgian scientist Georges Lemaître in 1927 and was confirmed in 1965 when Arno Penzias and Robert Wilson discovered the cosmic microwave background radiation.

In the early stages of the universe’s existence, matter and energy were distributed chaotically and homogeneously. Over time, as a result of density fluctuations and the action of gravity, the first structures began to form: gas clouds, stars, and galaxies. These processes were natural consequences of physical laws such as thermodynamics and gravity, rather than the result of any design.

1.2 The Role of Entropy and the Complexity of Systems

A key concept explaining the complexity of the universe is entropy. According to the second law of thermodynamics, formulated in the 1850s by Rudolf Clausius, entropy (a measure of disorder) in isolated systems tends to increase. However, this does not mean that order is impossible. Locally, organized structures can emerge if this is accompanied by an increase in entropy in the surrounding environment. For example, the formation of stars and planets is accompanied by the release of energy and an increase in entropy in the surrounding space.

Thus, complex systems arise as a byproduct of the universe’s tendency towards equilibrium and maximal disorder. From simple interactions and processes of self-organization, more complex structures and patterns gradually emerge.

1.3 Chaos and Nonlinear Dynamic Systems

Further understanding of the emergence of complexity is connected with the study of nonlinear dynamical systems and chaos theory. In 1963, American mathematician and meteorologist Edward Lorenz discovered that small changes in initial conditions can lead to significant and unpredictable outcomes (the butterfly effect). This helps explain how extremely complex phenomena – such as climate systems, galactic structures, and, ultimately, the chemical processes leading to life – could arise from simple physical laws (Lorenz, 1963).

Chaotic systems, despite their apparent unpredictability, follow certain rules and can exhibit self-organizing patterns. Examples include snowflakes, lightning, fractals, and turbulent flows. These processes demonstrate that complexity can arise spontaneously, without external control or purpose.

1.4 The Universe as Chemical Complexification

After the formation of the first stars, the process of synthesizing heavier elements from hydrogen and helium began. As a result of thermonuclear reactions occurring within stars, elements essential for the emergence of life – carbon, oxygen, nitrogen, and others – came into existence. This process, known as stellar nucleosynthesis, was explained in the mid-20th century by Fred Hoyle and his colleagues (Hoyle, 1957).

When massive stars exploded as supernovae, these elements were dispersed throughout the universe, becoming the building blocks for new stars, planets, and, ultimately, living organisms.

The complexification of the universe occurred gradually: first, galaxies, stars, and planets formed from primordial gas; then more complex chemical elements and compounds were synthesized; and eventually, complex molecules and the conditions necessary for the emergence of life were formed. These processes had no predetermined goal, but they laid the foundation for further stages, including biological evolution.

Thus, the emergence of a complex world is a history of self-organization grounded in physical laws. From chaotic and simple states, through billions of years of interactions and increasing entropy, there arose a universe rich in structural and processual diversity. This laid the foundation for the next stage – the emergence of life.

2. The Emergence of Life

Contemporary science asserts that life emerged as a result of natural chemical processes, rather than through purposeful action or a higher design. Approximately 3.5 to 4 billion years ago, the first signs of life appeared on Earth, and the process that led to this is called abiogenesis – the spontaneous emergence of living systems from non-living matter.

The “primordial soup” hypothesis, proposed by Alexander Oparin and John Haldane, formed the basis for the study of early Earth conditions that could have facilitated the formation of organic molecules (Oparin, 1967). The Miller-Urey experiment (1953) demonstrated that, when exposed to electrical discharges, a mixture of gases containing ammonia, methane, and hydrogen produced amino acids – the building blocks of proteins (Miller; Urey, 1953).

These chemical reactions were not directed toward achieving any specific goal but occurred as a result of molecular interactions governed by natural physical laws. Gradually, from these simple molecules, more complex structures began to form, such as RNA, capable of self-replication. This led to the “RNA world” hypothesis, advanced by Carl Woese and Leslie Orgel in the 1960s, which posits that the first molecules of life may have been RNA capable of self-reproduction without the involvement of proteins. RNA can serve both as a catalyst for chemical reactions and as a carrier of information, providing grounds to consider it the first step toward complex biological life.

The spontaneous emergence of life and the absence of an external goal in this process supports the idea that the evolution of life is a random phenomenon – not directed toward a purpose, but rather governed by the natural laws of chemistry and physics.

The process of the emergence of life continued with the formation of the first cells – primitive organismic structures enclosed by a membrane. These cells were capable of conducting metabolic exchange and of protecting internal chemical reactions from the external environment. Thus, evolution commenced. The formation of cells marked the beginning of living beings capable of metabolism, reproduction, and interaction with their surroundings.

In 1859, Charles Darwin, in his work On the Origin of Species, proposed the theory of natural selection. Darwin discussed that those organisms are better adapted to their environment have a higher chance of survival and of passing on their genes to the next generation. This process occurs without any purposiveness or predetermination; it is the result of random changes that lead to increased fitness in a given environment.

Evolution is a process of change and adaptation that has no final purpose or predetermined endpoint. It is a mechanism based on random mutations that produce alterations in populations of organisms, and death functions as the process through which less adapted individuals are eliminated. In this context, death is not the end of life, but an inevitable part of it – necessary for more adapted organisms to continue existing. Death, therefore, plays a crucial role in maintaining the balance and progress of the species, ensuring the “purging” of less adaptive genes.

The discovery of the structure of DNA in 1953 by James Watson and Francis Crick, based on X-ray diffraction data, marking the beginning of a new era in biology. DNA was decoded as the molecule that encodes genetic information transmitted from generation to generation (Watson; Crick, 1953). Genes became recognized as the fundamental units of heredity, containing instructions for the synthesis of proteins, which play a key role in the functioning of the organism.

Genetics has also revealed how mutation occurs – random changes in genes that lead to changes in the organism. These mutations may be beneficial, neutral, or harmful, and depending on how they affect the organism’s survival, they may be passed on to the next generation. The process of gene expression and its regulation through epigenetic mechanisms (eg, DNA methylation) adds additional layers to our understanding of how organisms adapt to their environment.

The significance of mutations and their impact on the organism is revealed through the concept of “negative selection,” which eliminates organisms with harmful mutations, and “positive selection,” which reinforces the existence of those better adapted. (Hamilton, 1964; Dawkins, 1976) The inclusion of epigenetics in the modern understanding of evolution enables a more comprehensive awareness of how the external environment can influence genetic changes and the adaptation of species.

The theory of multilevel selection, proposed by scientists such as William Hamilton and Richard Dawkins, significantly broadens our understanding of evolution. Dawkins, in his famous book The Selfish Gene (1976), advanced the idea that the fundamental units of evolution are not organisms but genes, which strive for self-replication and dissemination. From his perspective, the organism becomes merely a vehicle for the genes, and evolution, in essence, is directed not toward the survival of individuals but toward the preservation and propagation of genetic information transmitted across generations.

According to this theory, evolution does not view the organism as an end in itself, but rather as a means for transmitting genes to subsequent generations. This leads to the concept of the “selfish gene,” where each gene functions as a kind of “instrument” concerned with its own persistence within the population. Evolution thus operates at the level of genes rather than individual organisms.

A crucial development in this theory is the notion of multilevel selection. Selection can occur not only at the level of individual organisms but also at the level of genes, groups, and even species. In this context, evolution can be seen as a process in which not only the most adaptive individuals are selected, but also those genetic combinations that increase the chances of survival for populations or groups.

One example illustrating multilevel selection is the phenomenon of the emergence of organisms with identical traits – for instance, the “green beard effect.” Imagine a population of animals in which a group of individuals randomly develops a unique feature – a green beard. This concept, proposed by Richard Dawkins, illustrates how traits that are not individually advantageous may be preserved and spread through group selection. In this case, individuals with a “green beard” (a symbolic trait that distinguishes them from others) may not possess any clear survival advantage, but if such individuals form a group, their shared traits can foster cooperation and mutual support within that group, increasing the survival chances of its members. Thus, the trait may be beneficial at the group level, even if it brings no direct benefit to individuals. The green beard may be selected through group selection, wherein mutual cooperation or even “signaling” for interaction among individuals arises, thereby contributing to the survival of the entire community. In this way, group-level evolution may lead to the spread of such a trait if it promotes cooperation and social interactions that increase the survival prospects of the group as a whole.

Dawkins, in his theory, also accounts for the importance of altruism in evolution. He argues that individuals who act in the interest of the group may contribute to the preservation of their own genes, even if such behavior does not offer direct personal benefit. An individual may contribute to the survival of other members – such as relatives or members of their group – at the cost of personal risk. In this context, if an individual with a green beard helps other members of their group to survive, their actions may enhance the overall success of the group, and such traits will be maintained and reinforced at the group level.

Viewing evolution as a process that takes place at multiple levels allows for the inclusion not only of organisms but also of broader evolutionary units such as populations, ecosystems, and even species. For example, within multicellular organisms or communities of organisms with identical traits (for example, behaviors or physical characteristics), there is a probability that these traits will be preserved through altruistic behavior that contributes to the overall success of the group. However, such behavior is important not only for the survival of particular individuals but also for the dissemination of their genes at the level of the entire population.

One of the clearest examples of such a phenomenon is symbiosis – a close, mutually beneficial coexistence of different species. When two or more species cooperate with one another, their chances of survival increase, and their traits may be preserved and reinforced through evolutionary mechanisms. traits such as the green beard may, in the long term, spread not only at the level of individual organisms but also within more complex biological systems, contributing to the survival of the group as a whole.

Today, it is believed that selection takes place at several levels: at the genetic level, selection occurs at the level of individual genes. Genes that contribute to the successful survival and reproduction of their carriers become fixed in a population, being transmitted to subsequent generations. This form of selection focuses on how specific genetic variations can increase their frequency in a population due to their effects on the organism or on their copies in other organisms. At the individual level, selection acts on the level of organisms. Individuals possessing traits that increase their chances of survival and successful reproduction are able to transmit their genes to the next generation. This leads to the spread of beneficial adaptations within the population and the fixation of traits that increase individual fitness. Kin selection occurs through assistance to close relatives who carry similar genes. Altruistic behavior toward kin can increase the chances of spreading shared genes, even if it decreases the individual’s own chances of survival. Such selection explains the emergence of cooperative behavior in family groups and colonies. At the group level, selection occurs at the level of groups of organisms. Groups in which members cooperate and support one another may have an advantage over groups dominated by selfish behavior. Competition among such groups may lead to the selection of cooperative strategies that increase the overall success of the group. At the level of ecosystems or symbiotic communities, selection may take place at the level of entire ecosystems or communities composed of interrelated species. In such systems, stable interactions such as symbiosis, cooperation, and mutual support may contribute to the successful existence of all participants in the community. If an ecosystem or symbiotic community successfully copes with environmental changes and maintains its stability, this may promote the survival and dissemination of all species that comprise it. Although this level of selection remains contested, examples of coevolution show that complex communities can form through cooperative and mutually beneficial relations between different organisms.

Modern research supports the ideas of multilevel selection, showing how cooperation at the level of groups and communities may contribute to evolutionary success. It is important to emphasize that evolution, as a process, largely depends on random mutations, which may either help or harm the organism. However, the presence of directionality in evolution is not excluded. With each generation, species become more adapted to their environment, but this does not happen through predetermined aims or designs – it is the result of the interaction between random changes and existing ecological and social factors.

Evolution has no predefined goal or endpoint. What is important is that it is not aimed at the creation of perfect beings, but only at adaptation to the specific conditions in which an organism exists. In this sense, evolution is not so much development as a process of endless adaptations and changes.

3. The Emergence of Mind

The mind is one of the most complex achievements of evolution and has become a key factor in the success of many species, especially humans. In this section, we will examine how evolution led to the emergence of the mind, explore differences in the development of cognitive abilities in mammals and cephalopods, and analyze how the brain uses predictive coding and Bayesian approaches to process information.

The Emergence of Mind: Evolutionary Prerequisites

The evolution of the mind is a gradual process of the development of increasingly complex cognitive abilities, such as learning, memory, prediction, and self- reflection. The mind did not emerge suddenly; its appearance was the result of millions of years of adaptation to changing environmental conditions.

The most significant steps on the path to the mind include the development of sensory systems and memory, which enabled organisms to accumulate information about their surroundings and use it for survival. The emergence of associative learning provided the ability to link stimuli and responses, helping to anticipate dangers and opportunities. The development of spatial thinking allowed animals to represent their environment and plan their actions. Finally, social interaction within groups contributed to the formation of communication and the emergence of more complex behavioral strategies.

Over time, these elements have evolved into complex cognitive systems capable of abstract thinking, self-awareness, and future planning.

Differences in the Evolution of Mind

A compelling example of the evolution of mind can be found in mammals and cephalopod mollusks such as octopuses – two distinct evolutionary paths toward intelligence that demonstrate the multidimensional and branching nature of the evolutionary landscape of cognition. In addition to these, there are other independent trajectories, such as the social intelligence of insects – bees and ants – based on collective behavior, as well as the development of complex forms of communication and problem-solving in birds, such as crows and parrots. These different paths reflect the diversity of adaptations to environmental conditions and strategies for survival.

Mammals, including humans, developed their minds in the context of social interaction and group living, which facilitated the formation of complex social structures. Their cognitive abilities were oriented toward solving problems related to cooperation, competition, and social communication, leading to the emergence of social hierarchies, the capacity for empathy, the development of theory of mind – understanding the thoughts and intentions of others – as well as the origins of language and abstract thinking. The mammalian brain features a highly developed cerebral cortex, particularly the frontal lobes, which are responsible for planning, self-control, and decision-making. In addition, the brain is closely linked to the hypothalamus and the endocrine system, which regulates behavior hormonally in response to internal and external stimuli.

In contrast, cephalopod mollusks have evolved under conditions of solitary existence and the need for flexible adaptation to diverse marine environments. Their cognitive abilities are oriented toward solving spatial problems, camouflage, tactical behavior, and the independent control of limbs. A unique feature of the cephalopod brain is that about two-thirds of its neurons are located in the arms, allowing the limbs to function autonomously and make local decisions without constant signaling to the central brain. This architecture grants octopuses a high degree of independence and flexibility in interacting with their environment.In both cases, the brain serves as an adaptive organ that processes information about the external world and makes decisions based on the needs of the organism. However, mammals have evolved a centrally organized brain to coordinate actions and social interactions, whereas octopuses rely on localized neural structures that allow body parts to act independently. This reflects different evolutionary strategies: mammals depend on collective behavior and complex social bonds, while octopuses rely on individual decision-making and maximal flexibility in manipulating their surroundings. Thus, examining these examples helps us better understand how the mind can evolve along different trajectories, shaped by unique conditions of survival and interaction with the world.

How the Brain Works

The brain is composed of billions of neurons that process information and coordinate the body’s actions. These neurons communicate with one another using chemicals known as neurotransmitters. When a neuron is activated, it transmits an electrical impulse that reaches the synapse – the point of contact with another neuron. At this point, the electrical signal is converted into a chemical one by means of neurotransmitters, which diffuse across the synaptic cleft and activate receptors on the adjacent neuron.

Key neurotransmitters, such as dopamine, serotonin, and glutamate, regulate fundamental aspects of behavior and perception. For example, dopamine is associated with motivation and the reward system, while serotonin influences mood and levels of anxiety. Glutamate is the primary excitatory neurotransmitter and plays a critical role in learning and memory processes.

The Influence of Hormones on Brain Function

Hormones play a crucial role in regulating behavior and physical state. For instance, cortisol, the stress hormone, is produced in response to threats and helps the body manage emergency situations; however, if its levels remain elevated, this can lead to chronic stress, depression, and a decline in cognitive function. Oxytocin, by contrast, promotes the formation of social bonds and empathy, which are essential for complex forms of communication and interaction.

Hormonal influences on the brain are regulated via the hypothalamus, which controls the pituitary gland and thereby interacts with the endocrine system, ensuring the integration of cognitive and physiological processes.

The Microbiota and Its Influence on the Brain

The microbiota – the collection of microorganisms inhabiting our bodies – also plays an important role in brain function. In recent decades, it has become clear that microbes, particularly those residing in the gut, affect behavior, emotions, and cognitive processes. This interaction between the brain and microbes is known as the microbiome – gut – brain axis.

Some microbes can influence levels of neurotransmitters such as serotonin, much of which is produced in the gut, as well as modulate inflammatory processes, which in turn can affect the functioning of the nervous system. For example, imbalances in the microbiota have been linked to the development of depression, anxiety disorders, and even neurodegenerative diseases such as Alzheimer’s.

Evolution and development of the nervous system

Over time, in the course of evolution, the nervous system and its components have become more complex in various animal species, including humans. They became more and more complex and adapted to the environment. Reptiles and their ancestors, including ancient mammals, had a part of the brain that was responsible for basic survival functions such as instincts, aggression, and sexual behavior. In the course of evolution, with the development of more complex cognitive functions, new structures joined this ancient brain, such as the limbic system responsible for emotions and the neocortex, which evolved in mammals and allows for more complex cognitive tasks such as abstraction, planning and introspection.

These changes have led to the creation of brain structures that process information taking into account not only current events, but also predictions of future conditions, which allows them to adapt to changing environmental conditions. The evolution of the brain has not only improved survival mechanisms, but also created conditions for more complex behaviors such as social interactions, empathy, and language.

The Bayesian Approach to the Mind – The Free Energy Principle and Predictive Coding Theory

The theory of predictive coding and its foundations in Bayesian approaches occupy a central place in contemporary understandings of how the brain perceives and processes information. In contrast to traditional conceptions of perception, according to which the brain merely reacts to sensory data, predictive coding posits that the brain actively constructs models of the world and uses them to anticipate future events. These predictions are then compared with actual sensory input received through the sense organs. The prediction error – the discrepancy between what the brain expects and what it actually perceives – serves as a signal to update the mental model. This process allows the brain to minimize energy expenditure, accelerate perception, and enhance adaptability, forming the basis for the efficient functioning of cognitive processes.

In recent decades, predictive coding theory has increasingly been viewed as part of the broader Free Energy Principle, which integrates it with Bayesian inference, the theory of active inference, and other frameworks aimed at minimizing uncertainty and adapting to environmental changes (Parr et al., 2022; Friston, 2010). However, despite the growing interest in this integrative approach, predictive coding in itself remains a fundamental concept for understanding how the brain constructs models of the world and updates them in response to new data. This work will focus primarily on predictive coding, its neurobiological mechanisms, and its role in cognitive processes.² (Parr et al., 2022; Friston, 2010) However, despite the growing interest in this integrative approach, predictive coding in itself remains a fundamental concept for understanding how the brain constructs models of the world and updates them in response to new data. This work will focus primarily on predictive coding, its neurobiological mechanisms, and its role in cognitive processes.

The historical roots of predictive coding theory can indeed be traced back to the work of Pierre-Simon Laplace, who laid the groundwork for the concept of determinism. Laplace was among the first to explore the ideas of probability and determinism in the context of predicting future events, proposing that, if one had complete knowledge of the current state of the universe, it would be possible to foresee all future occurrences. His thought experiment of “Laplace’s demon” – a hypothetical intellect capable of calculating the future with absolute precision based on the positions and velocities of all particles – embodied the notion that even human thoughts and actions could, in principle, be predicted.

However, the idea of prediction and internal modeling of the world began to take shape much later. In the 18th and 19th centuries, Laplace’s deterministic vision began to be challenged by philosophers and scientists such as Isaac Newton, Carl Friedrich Gauss, and others. Ideas related to probabilistic reasoning and uncertainty gained prominence with the development of statistics and thermodynamics.

In the 20th century, the work of scholars such as Klaus Heisler, Richard Feynman, and Yakov Frenkel marked an important step toward understanding how predictions operate under uncertainty, and how the brain might formulate hypotheses in probabilistic and non-ideal conditions. These researchers introduced mathematical frameworks that ultimately laid the foundation for the theory of predictive coding in neuroscience.

An equally important contribution to the development of the idea of prediction and coding theory was made by researchers in the field of neuroscience in the mid-20th century, such as Benjamin Libet and Nobel Laureate Roger Sperry, as well as Jean-Pierre Changeux. Libet, for example, conducted experiments demonstrating that the brain initiates the process of decision-making several seconds before the individual becomes consciously aware of their choice – calling into question the notion of full control over behavior (Libet, 1985).

However, theories closely aligned with predictive coding began to emerge more actively only in the late 20th and early 21st centuries. A key role in this development was played by studies on neuroplasticity and the adaptive mechanisms of the brain. Neurobiological research, including investigations into neurotransmitters such as dopamine and the functioning of neural networks, led to significant insights into how the brain uses prediction and internal models to perceive the external world. Foundational figures in predictive coding theory, such as Carl Friedrich von Weizsäcker and Gregory Hopper, proposed that the brain constantly generates hypotheses about the future based on past experience and correlates them with incoming sensory information.

Bayes’ theorem, proposed by the English mathematician Thomas Bayes in the 18th century, became a crucial mathematical tool for analyzing and updating probabilistic hypotheses in light of new data. The core of the theorem lies in its ability to recalculate the probability of a hypothesis based on the arrival of new information. Bayes’ theorem describes how belief (or the probability of a hypothesis) is updated in response to new evidence. In the context of brain function, the theorem can be used to explain how neural networks revise their predictions about the future by integrating both prior and newly acquired experience.

Within the framework of predictive coding theory, this theorem and its formula illustrate how the brain updates its hypotheses (or predictions) about the world based on new sensory data. When the brain encounters novel events (data), it revises its prior probability (prediction) to incorporate this information, thereby enhancing the accuracy of future predictions.

Thus, this process reflects the key feature of predictive coding: the brain does not simply react to data, but actively revises its expectations based on new inputs, always striving to minimize prediction error.

The application of Bayes’ theorem to neurobiology and cognitive science became feasible in the 1980s, when scientists began to understand how the brain might employ probabilistic methods to address problems of uncertainty. In this paradigm, the brain is conceived as a “Bayesian inferencer,” one that generates hypotheses about the world and updates them in response to sensory input using probabilistic principles. The Bayesian model assumes that the brain maintains probabilistic models of future events and adjusts them based on prediction errors – an idea that is directly linked to predictive coding theory.

This updating of probabilistic hypotheses is of fundamental importance, as it enables the brain not only to adapt to changes in the external environment but also to take into account uncertainty in the world, even when information is incomplete. In this sense, Bayes’ theorem and its applications have become fundamental for understanding how the brain, when confronted with uncertainty, can improve its predictions and forecast future events based on prior knowledge.

In summary, the connection between predictive coding theory and Bayes’ theorem has become a cornerstone in the development of neurobiological models that explain how the brain information processes and employs probabilistic computations to anticipate future states. Bayesian theory, as a foundation for managing uncertainty and adaptation, has provided a critical mathematical and cognitive instrument for understanding how the brain functions in a world of constant variability and unpredictability.

Predictive Coding as an Adaptive Mechanism

At the core of predictive coding theory lies the principle that the brain not only reacts to external stimuli but actively predicts them using existing models of the world. The brain formulates hypotheses about what will happen in the future and compares these predictions with current sensory information. When predictions align with reality, prediction error is minimized, allowing the brain to efficiently allocate its resources. However, if an error arises – a discrepancy between prediction and reality – the brain updates its models of the world, which facilitates improved perception and adaptation.

This approach enables the brain to conserve energy and effort by minimizing the need to process all incoming information exhaustively. Instead of interpreting sensory data anew each time, the brain operates with simplified models that are continuously updated based on new sensory inputs. This significantly accelerates information processing and reduces energetic costs. For example, when a person walks down the street, the brain does not analyze every individual step but rather relies on its predictions about what should occur in the next moment.

Predictive coding operates across multiple hierarchical levels, ranging from simple sensory signals (such as sounds or colors) to complex social and interactions abstract ideas. At lower levels, the brain predicts basic sensory features such as shapes and movements; at higher levels, it anticipates more complex phenomena, for instance, people’s intentions or social interaction scenarios.

The Role of Hormones, Neurotransmitters, and the Microbiota in Prediction

The efficacy of predictive coding mechanisms also depends on a multitude of external and internal factors. Hormones, neurotransmitters, gut microbiota, and trauma can significantly influence the brain’s capacity for prediction and adaptation.

Cortisol, the stress hormone, can impair the brain’s ability to adjust its predictions. For example, elevated cortisol levels may disrupt the process of updating the world model, leading to persistent perceptual errors and heightened anxiety. Neurotransmitters such as dopamine play a key role in reward and motivation processes, as well as in the amplification or attenuation of specific brain predictions. Recent research has also demonstrated that gut microbiota can affect cognitive functions and even the brain’s predictive capacities, as microbes interact with the central nervous system, influencing mood and perception.

Trauma – particularly brain injury – can disrupt the neurobiological processes underlying prediction, resulting in cognitive and emotional disorders. For instance, depression and anxiety disorders may be associated with impairments in predictive coding mechanisms, wherein the brain fails to effectively update its world models.

Contemporary brain research indicates that the mind actively constructs and updates models of the world by employing predictive coding and Bayesian approaches.

Predictive coding is a process in which the brain generates hypotheses about what it expects to perceive and compares these hypotheses with actual sensory information. When predictive coding produces a mismatch between the brain’s expectation and sensory input (prediction error), the brain can either update its world model or attempt to interpret the data within existing hypotheses. If the prediction error is excessively large, the brain may sometimes perceive the error itself as reality, which can lead to hallucinations. For example, under conditions of sensory deprivation, when sensory information is insufficient, the brain’s predictions may dominate, giving rise to visual or auditory images that compensate for the lack of real stimuli. In cases of excessive prediction activation, such as during stress or neurochemical imbalance (for example, dopamine excess), the brain may ignore real sensory data and impose its own interpretation. This partially explains hallucinations observed in schizophrenia.

Levels of Predictive Coding:

Low Level (Sensory): The brain predicts simple sensory signals (for example, lines, colors, or sounds). For instance, if you hear the noise of footsteps, your brain predicts that you will see a person.

Intermediate Level (Perceptual): Predictions at this level include more complex structures – images, spoken words, or objects. For example, upon seeing quick movement in the bushes, you infer that it is an animal.

High Level (Cognitive): At this level, the brain forms complex hypotheses, including social interactions and abstract ideas. For example, based on a person’s behavior, you might predict their intentions.

Bottom-Up and Top-Down Signals

The hierarchy of information processing is based on two types of signals:

Top-Down Predictions: At each level of the brain, predictions are generated about sensory data expected at lower levels. For example, if a higher level predicts that a person is seeing a face, then lower levels will anticipate facial features (eyes, nose, mouth).

Bottom-Up Prediction Errors: When actual sensory input does not match the prediction, a prediction error signal arises. This signal is transmitted to higher levels for model correction and refinement of predictions..

How Does the Brain Correct Errors?

This process occurs through cyclical feedback:

Prediction: A higher level generates a prediction and sends it down the hierarchy.

Comparison: At a lower level, this prediction is compared with the actual sensory input.

Error: If there is a discrepancy, a prediction error is generated.

Model Update: The error is transmitted back upward, where the model is adjusted to improve future predictions.

When actual sensory information matches predictions, the brain minimizes prediction error, which conserves resources. However, when information does not align with expectations, a prediction error arises, signaling the need to update the model of the world.

Within the neural layers of the brain, there is a division between “prediction neurons,” which form expectations, and “error neurons,” which indicate when predictions have failed. For example, in the supragranular layers (the upper layers of the cortex), error neurons activate when something unexpected occurs. In the deeper layers reside neurons that emit prediction signals.

However, the effectiveness of predictive coding is influenced by various factors, including hormones, neurotransmitters, microbiota, and trauma. Hormones such as cortisol, produced in response to stress, can alter neuronal sensitivity, affecting the brain’s capacity for adaptation and learning. Neurotransmitters, for instance dopamine, play a key role in motivation and reward processes, which can enhance or diminish certain predictions and responses. The gut microbiota, interacting with the central nervous system, can influence mood and cognitive functions, thereby affecting the predictive process. Trauma, particularly traumatic brain injury, can disrupt the normal functioning of neural networks responsible for predictive coding, leading to cognitive and emotional disorders.

Errors in the predictive coding process may arise from various causes. They can be linked to insufficient accuracy of sensory data, incorrect interpretation of information, or failure to update world models. Such errors may result in distorted perception and impaired adaptive behavior. For example, during chronic stress, elevated cortisol levels may reduce the brain’s ability to correct predictions, leading to persistent perceptual errors and increased anxiety.

Thus, predictive coding constitutes the foundation of adaptive behavior and human cognitive functions. Understanding the mechanisms of this process and the factors affecting its efficacy opens new horizons for developing treatments for various psychiatric and neurological disorders associated with disruptions in predictive coding.

Conclusion

The emergence of the mind is the result of a complex evolutionary process that led to the development of diverse forms of intelligence across different species. Predictive coding and Bayesian approaches demonstrate how the brain constructs models of the world and adapts to new conditions by minimizing prediction errors. These mechanisms form the foundation of our perception, learning, and thinking, rendering the mind a powerful tool for understanding and transforming reality.

4. The Existential Limit of Prediction

Mental models are internal cognitive structures through which we interpret and predict the world. These models help us navigate life by constructing more or less accurate representations of reality. However, like any other tool, they are limited. Mental models, akin to filters of the mind through which we perceive the world, are inevitably simplifications based on experience and expectations, allowing us to interact with the environment more efficiently. Yet, as with any tool, these models cannot always reflect reality accurately, as the world does not always conform to the frameworks we impose upon it.

These ideas found continuation in Plato’s philosophy. In his famous allegory of the cave, Plato portrays people sitting in a dark cave, seeing only shadows cast by objects in front of a fire. These shadows represent a distorted perception of reality, taken to be truth because the cave’s inhabitants have never seen the light. Only the one who escapes the cave can behold the true reality hidden behind the shadows (Plato, 1990). Plato’s allegory symbolizes the limits of our perception, which reflects only a fragment of the full picture of the world.

Later, Immanuel Kant discussed that we do not perceive the world as it is as a Thing-in-itself (Ding an sich), but rather through the a priori forms of reason, thus helping us understand the nature of these limitations. Kant maintained that our knowledge of reality will always be constrained by the categories of reason, such as space, time, and causality, which are imposed upon our experience and do not exist in the world as a Thing-in-itself. (Kant, 1983) This means that human perception will always be bounded by these a priori forms, and we can understand and predict only those aspects of the world that conform to these frameworks..

The idea that our perception of the world is always limited was further developed in the later work of Thomas Bayes, whom we discussed earlier. Bayes used the example of the rising and setting sun to illustrate how our models of the world can be updated based on observations. For instance, a person emerging from a cave for the first time observes a sunrise and wonders: does this happen every day? With each new observation, the person updates their belief using Bayesian reasoning. Each additional sunrise strengthens the hypothesis that the sun indeed rises daily. However, should this prediction one day fail – if the sun does not rise or does not appear in the expected location – then the model of the world must be revised in light of the new data.

In this way, the Bayesian approach reveals a process of continuous updating of our mental models based on new observations, which also echoes Plato’s idea of seeking the true reality beyond distorted perception. Bayes emphasizes that the perception and prediction of the world are dynamic processes, always subject to revision, and that the reality we attempt to grasp may always run deeper than what our current model of perception allows.

These ideas were expanded upon by Nate Silver, who examined the principles of prediction under uncertainty. Silver argues that successful forecasting depends on the ability to distinguish between “signal” (important information) and “noise” (random or irrelevant data), a process closely related to Bayesian model updating. (Silver, 2019)

However, Silver goes further by emphasizing that not all models can be corrected by simply including new data. In a world full of uncertainty and randomness, many predictions fail even when the correct methodology is followed. He stresses how people often overestimate their ability to interpret data, relying on forecasts that seem plausible but are in fact driven by perceptual errors and cognitive biases. According to Silver, it is not enough to account for new data – we must also understand the context in which it arises. In this sense, as in the Bayesian framework, correcting mental models requires not only observation, but an awareness of the epistemic constraints we face in interpreting the world. Silver also highlights that the importance of “noise” in data is often underestimated, and that without the ability to separate noise from signal, we cannot build adequate predictive models, even with the most advanced analytical techniques.

Thus, like Bayes, Silver emphasizes the necessity of constantly reassessing our assumptions and revising our models of the world. However, unlike classical Bayesian theory, Silver underscores the difficulty of prediction in the real world, where signal is often hard to distinguish from noise, and our ability to make accurate forecasts remains inherently limited.

And yet, even though our mental models can be updated in response to new observations – despite the complexity of prediction – the process of adaptation is not infinite. When the world becomes too complex, or when our expectations encounter fundamentally novel and unpredictable phenomena, our models confront limits that cannot be overcome by ordinary means of correction. This presents the mind with an unbridgeable rupture – a moment when we are no longer able to adapt our predictions to reality.

In such moments, when even the most flexible models fail, the mind undergoes a crisis – a rupture caused by the impossibility of forecasting or understanding what is happening. This confrontation with uncertainty generates an existential tension that calls into question the very capacity of reason to make sense of the world. Despite all efforts at updating and revising our models, it becomes evident that human cognition inevitably encounters boundaries that cannot be transcended by any familiar predictive mechanism.

The Existential Limit of Prediction refers to the boundary at which the human brain encounters fundamentally unpredictable phenomena – phenomena that cannot be integrated into predictive models due to a lack of data, experience, or the capacity for error correction. When the brain reaches the limits of its cognitive capabilities, this results in an irresolvable cognitive conflict, giving rise to profound existential experiences.

The existential limit of prediction has served as a point of departure for the emergence of various philosophical movements such as pessimism, existentialism, and nihilism. These traditions arose from a confrontation with the boundaries of human understanding – moments in which conventional models of perceiving the world prove insufficient to account for profound existential questions and the radical uncertainty of existence. Errors that arise from encountering the existential limit may begin to escalate, spiraling into a state of despair that takes the form of philosophical pessimism, deep existentialism, or nihilism.

Philosophical pessimism, as a stance affirming the predominance of suffering or negativity in life, is directly linked to the inability to cope with uncertainty or to anticipate the future under conditions of profound crisis. When one is confronted with phenomena that defy incorporation into familiar models of meaning, the mind may begin to seek answers through extremes. The pessimistic worldview often rests on the acceptance of uncertainty and negative expectations as inevitable features of existence.

One notable example of pessimism is the philosophy of Philipp Mainländer, a German thinker who advanced the idea that existence is inherently marked by suffering and meaninglessness. His thought, focused on the idea of infinite suffering and the futility of life, stands as a striking example of how the existential limit may be interpreted as a tragic inevitability of the human condition. For Mainländer, life lacks any ultimate goal – a conclusion drawn from his experience of existential uncertainty, which leads to a deeply pessimistic worldview.

Another radical voice of pessimism is the philosopher Ulrich Horstmann (pseudonym of Klaus Steintal), whose thought takes the logic of pessimism to an extreme. In his controversial work Das Untier (“The Beast”), Horstmann argues that voluntary human extinction should be achieved through deliberate global thermonuclear destruction. He views existence as so fundamentally absurd and painful that, in his view, the only viable escape is the complete eradication of the human species. His philosophy represents an extreme form of misanthropic pessimism, wherein the experience of suffering and the futility of life culminates in a call for annihilation. (Horstmann, 2004)

Existentialism, in turn, emerged as a response to the awareness of these limits and the struggle with the fact that man cannot find absolute meaning in life, and his predictions and answers to existential questions turn out to be superficial or erroneous. Existentialists such as Jean-Paul Sartre and Martin Heidegger set themselves the task of realizing freedom, responsibility and finitude, but their works often sound anxious and unrealizable in their full understanding of existence (Sartre, 1943; Heidegger, 1927)

Existentialism, in turn, emerged as a response to the recognition of these limits and the struggle with the fact that human beings are incapable of discovering any absolute meaning in life. Their predictions and answers to existential questions often prove superficial or flawed. Existentialist thinkers such as Jean-Paul Sartre and Martin Heidegger sought to confront themes of freedom, responsibility, and finitude; yet their works are often permeated with a sense of anxiety and the unattainability of complete understanding of existence (Sartre, 1943; Heidegger, 1927).

However, existentialism may begin from mistaken premises about human nature, leading to extremes in interpretations of freedom and the search for meaning. If we understand existentialism as originating in an internal crisis, then philosophical systems like Heidegger’s can be seen as products of the impossibility of discovering ultimate meaning in a world where predictions about the future are inherently unstable or unreliable.

Nihilism may be understood as the most radical response to the existential limit of prediction. Nihilists assert that life possesses neither meaning nor value. They proceed from the conviction that all moral, social, and metaphysical foundations are ultimately meaningless. The notion that all human efforts to generate meaning are doomed to failure arises from a deep existential void – an experience that emerges when one is confronted with the boundaries of understanding.

Friedrich Nietzsche stands as a quintessential representative of this position. He describes the world as chaotic, devoid of inherent order or meaning. For Nietzsche, the world is a stage of struggle and suffering, and all human striving collapses into futility when it seeks meaning in a reality that offers none. He argues that traditional moral and religious frameworks are incapable of providing genuine meaning, and that the individual must forge their own path by confronting and overcoming this existential vacuum. In his work, one finds a direct confrontation with the existential limit – an acknowledgment that it is impossible to construct a cognitive model of the world that would resolve all contradictions or liberate humanity from existential darkness (Nietzsche, 2013).

Nihilism, developing out of a profound crisis of belief in our predictive capacities, can thus be viewed as the ultimate phase in the spiral of error. When one fails to resolve uncertainty, the mind may conclude that nothing exists beyond subjective perception – and, consequently, that nothing in the world truly matters. This leads to a wholesale rejection of all values and purposes.

Pessimism, existentialism, and nihilism are not merely abstract philosophical doctrines, but processes of predictive breakdown – born from erroneous expectations and overextended forecasts. What begins as an attempt to explain uncertainty or crisis can devolve into a spiral of extremity, amplifying the problem until it culminates in despair and philosophical nihilism. We will examine this in greater detail in Chapter 3.

These philosophies, to some extent, appear as logical consequences of how predictive errors and misjudgments about uncertainty can lead to radical reinterpretations of human nature and humanity’s place in the world. While they do not always offer solutions, they raise some of the most important questions about our capacity to construct meaningful lives in the face of uncertainty.

A more honest approach within the existentialist tradition is found in the work of Albert Camus. Camus highlights the moment when Sisyphus, the absurd hero of his essay, becomes aware of the futility of his existence and his condemnation to endless repetition (Camus, 1989). However, Camus does not propose a rejection of reality, but rather its acceptance. For Sisyphus, despite recognizing the absurdity of his condition, life does not lose its value. Sisyphus becomes happy precisely because he is conscious of his fate and embraces it – not with resignation, but with defiance. This acceptance is not passive, but an active act of rebellion through which he achieves inner freedom and harmony, continuing his labor despite its futility. Camus insists that while the struggle is absurd, it is precisely within this absurdity that meaning and joy can be found – if we abandon the search for final answers and accept reality as it is.

Chapter 2. Confronting the Unknown and Forms of Adaptation

In the first chapter, we arrived at the realization that the world as it is results from random interactions and self-organization, devoid of purpose or higher design. This understanding – alongside chaos and unpredictability – presents a profound existential challenge to the human mind. How is one to make decisions or act when the future cannot be forecasted?

In this chapter, we examine existential fears and the limits of human reason, such as free will, death, and the complete absence of meaning, through the lens of scientific and philosophical works. These are perennial themes, destined to persist as long as there exists a consciousness capable of self-reflection. Rather than reiterating the ideas of every great thinker of the past, we will focus on the contributions of the twentieth and early twenty-first centuries, insofar as their works have, in many respects, already synthesized the legacy of prior thought.

The following sections investigates free will as an adaptive instrument. We will examine its neurobiological and cognitive foundations, the influence of genetics and environment on its formation, and the illusory nature of the concept in the light of contemporary research. Through this lens, we will understand how free will functions as a means of imposing order on chaos and as a mechanism of adaptation in the face of the extreme complexity of existence.

1. Free Will as a Mode of Information Processing

Although the brain operates within specific laws and predictive mechanisms, we continue to experience a sense of free will. This is due to the fact that the brain does not process all incoming information directly, but instead works with the most probable hypotheses and models. As a result, we perceive ourselves as autonomous agents who make decisions, even though, at a deeper level, our brains are always functioning within deterministic frameworks. These predictive patterns simplify perception and enhance adaptive efficiency.

This also explains why we feel free even when, on a more fundamental level, the brain is guided by probabilistic models. The brain conserves energy by processing only the most likely events rather than the full spectrum of possible inputs, making it more flexible and adaptive. This economization allows for rapid responses to environmental changes without expending excessive cognitive resources. Ultimately, this generates the subjective experience of free will.

To clarify this argument, I draw attention in this book to Robert Sapolsky’s most recent work, Determined: A Science of Life Without Free Will, which synthesizes neurobiology, genetics, endocrinology, evolutionary biology, and psychology to offer a comprehensive account of human behavior. I will not attempt a detailed exegesis of Sapolsky’s work here; Rather, I will isolate its core insights that help illuminate the nature of determinism and the fundamental questions it raises.

Robert Sapolsky is an American neuroendocrinologist, biologist, anthropologist, and author, renowned for his research on human behavior, its biological foundations, and the mechanisms of stress. He holds a professorship at Stanford University and has spent over three decades investigating how neurobiology, genetics, and environment interact to shape human behavior. Beyond his primary scientific contributions, Sapolsky is well known for his popular books, such as Behave: The Biology of Humans at Our Best and Worst and Determined: A Science of Life Without Free Will. These works challenge traditional conceptions of free will and moral responsibility by offering a biologically grounded perspective on human action.

Neurobiological Evidence

Sapolsky refers to the work of Michael Gazzaniga, who conducted research on patients with a severed corpus callosum, to illustrate the absence of free will. These “split-brain” patients exhibited striking examples of how consciousness constructs post hoc interpretations of actions that were not the result of deliberate decision-making. When one hemisphere performs an action, the patient is not always able to explain why it occurred. Gazzaniga discovered that the left hemisphere – responsible for language and narrative construction – frequently invents justifications for actions initiated by the right hemisphere. This demonstrates that conscious awareness is not necessarily aligned with the actual processes involved in decision-making.

“Neurobiology shows that we are often unaware of the true causes of our behavior. When the left hemisphere explains the actions of the right, it does so based on its own perceptions rather than on the actual cause” (Sapolsky, 2023).³

This example illustrates the notion that we perceive ourselves as free agents, yet many of our choices and actions stem from unconscious processes. The narrative self, primarily constructed by the left hemisphere, functions less as an origin of behavior and more as a retrospective interpreter – offering plausible, but not necessarily accurate, accounts of why we acted as we did.

The Illusion of Free Will

One of the central aspects of Sapolsky’s work is the concept of the “illusion of free will.” He argues that despite our conviction of having free choice, in reality, all our decisions are determined by biological, neurobiological, and social factors. We perceive ourselves as free agents because we are unable to consciously grasp the entire chain of mechanisms that actually lead to our behavior. Sapolsky uses the metaphor of an “illusion”: we see ourselves as free agents because we fail to notice the deeper underlying mechanisms influencing our actions.

“We believe we control our actions because we do not see the chain of biological factors leading to our decisions. It is simply an illusion that we make decisions consciously.”

He provides examples where reactions to external stimuli occur before we become consciously aware of them. For instance, when a person faces danger, their body may immediately respond based on instinctive reactions (such as an increase in adrenaline levels) before the individual consciously realizes what has happened. This confirms that our behavior is often predetermined by responses occurring at an unconscious level in the brain.

Genetics and Behavioral Influence

Sapolsky also emphasizes the importance of genetics in the determinism of our behavior. He cites examples of genetic mutations, such as changes in the MAOA gene, which are associated with increased predisposition to aggression. Such genetic influences can significantly alter behavior, and according to Sapolsky, these data demonstrate that our personality and behavior are largely predetermined by our genome rather than being the result of free choice.

“Genetics plays a major role in shaping our personality. Even traits such as a propensity for aggression can be predetermined by our genes.”

The Influence of Environment and Upbringing

Environment and upbringing also play a significant role in shaping our behavior. Sapolsky emphasizes how stressful events can strongly affect decision-making. In particular, stress can reduce our capacity for rational thought, making us more prone to impulsive decisions. This also confirms that our actions are largely predetermined by external circumstances rather than by free will.

“When we are under stress, our brain starts to function differently, which makes us more prone to aggression or impulsive acts. This means that even in moments of tension, our actions are determined.”

The Role of Neuropeptides and Hormones in Behavior

Sapolsky discusses in detail how hormones such as oxytocin can strongly influence our social interactions. He provides examples showing that an increase in oxytocin levels can make us more trusting and altruistic, while its decrease can lead to aggression and distrust.

“Hormones like oxytocin play a crucial role in our behavior. We cannot control their levels, and it is precisely they who often determine how we relate to other people.”

Decoherence and Classical Reality

In chapter nine of his work, Robert Sapolsky acknowledges that quantum mechanics violates classical Laplacian determinism at the subatomic level. However, as I will show further, quantum randomness does not provide grounds for the existence of free will. Let us begin with quantum decoherence.

Quantum decoherence is the loss of quantum coherence. Quantum decoherence has been studied in order to understand how quantum systems transform into systems explainable by classical mechanics. The theory, which emerged from attempts to deepen the understanding of quantum mechanics, developed in several directions, and experimental research confirmed some key points.

At the macroscopic level, quantum effects become “blurred” due to interaction of quantum systems with their environment. This process, called decoherence, explains why the macroscopic world is strictly deterministic.

Decoherence shows that quantum systems transition into states that appear classically deterministic to the observer. Thus, quantum uncertainty does not “penetrate” into the macroscopic world, where Newton’s laws dominate.

Bell’s Experiment

Bell’s experiment demonstrates that quantum mechanics violates Bell inequalities, indicating the presence of quantum nonlocality. This phenomenon is often interpreted as a challenge to classical notions of determinism. However, Sapolsky emphasizes that even quantum nonlocality does not provide “free will,” since outcomes still fully depend on the system’s parameters and its initial state.

Misinterpretations of quantum nonlocality are connected to the perception of quantum event randomness as an opportunity for the existence of will free from determining factors. However, quantum randomness does not make events free; it merely makes them unpredictable.

Physical Determinism and System Complexity

Pierre-Simon Laplace’s ideas that knowledge of all initial conditions could allow prediction of the future are discussed in the context of chaos theories and quantum uncertainty. Sapolsky points out that even in a complex physical system (such as the brain) no “freedom” arises; everything remains predetermined by physical laws. Despite the potential quantum uncertainty, its influence on the level of conscious decisions is minimal and does not rescue the concept of free will.

Laplace’s demon, according to Laplace’s theory, is a hypothetical entity which, knowing the position and velocity of every particle in the universe at a given moment in time, can precisely predict the future. If you understand the physical laws shaping the universe and know the exact position of every particle in it, you can precisely predict what happened at every moment from the beginning of time and what will happen at every subsequent moment until the end of time (Laplace, 1814). This means that everything that happens in the universe was destined to happen (in the mathematical, not theological, sense).

“Laplace put forth the canonical statement of all determinism: if you had a superhuman who knew the location of every particle in the universe at a given moment, he would be able to precisely predict every moment in the future. Moreover, if this superhuman (later called ‘Laplace’s demon’) could recreate the exact location of every particle at any past moment, this would lead to a present identical to our current one. The past and future of the universe are already determined. Science since Laplace has shown he was not entirely correct, but the spirit of his demon lives on. Modern views on determinism must include the fact that certain types of predictability prove impossible (topics of chapters 5 and 6), and some aspects of the universe are indeed indeterminate (chapters 9 and 10).”

Further Reflections on Free Will with Lawrence Krauss

After the release of the book Determined, in a two-hour podcast with Robert Sapolsky and Lawrence Krauss, the main focus is on the connection between the illusion of free will, neurobiology, and concepts related to quantum physics. Sapolsky once again emphasizes that free will is an illusion determined by biological processes and the laws of physics. This viewpoint is also supported by arguments that even the probabilistic nature of quantum physics cannot undermine determinism. (Sapolsky; Krauss, 2023)

Determinism and Quantum Physics

During the conversation, Krauss raises the argument concerning quantum uncertainty, frequently invoked to support the idea of free will. He emphasizes that uncertainty at the quantum level is interpreted as the probabilistic nature of events not due to a rejection of determinism but because we lack the instruments to predict exact outcomes. Sapolsky concurs, noting that even if quantum physics introduces an element of randomness, it does not create freedom of choice for the subject. No quantum “noisy” event in the brain produces a conscious and independent action.

The main arguments consist in the illusion of control manifesting in the fact that neurobiological processes are initiated before we become aware of our actions, confirmed by studies demonstrating that neural activity precedes our decisions. The probabilistic character of quanta indicates that even if random events exist in nature, they cannot serve as the foundation of free will since they are not under the individual’s control. The evolutionary basis of behavior, as Sapolsky emphasizes, lies in the fact that even highly developed social processes have a biological foundation, including such notions as morality and responsibility.

Here is how Sapolsky describes this in Chapter Ten, “Is Your Free Will Random?”:

“Putting aside cruel randomness, can quantum effects truly influence behavior? For example, the uncertainty releasing magnesium from the glutamate receptor does not significantly affect excitation at the synapse. Even strong excitation of a single synapse is insufficient to trigger an action potential in the neuron… A dendrite in one glutamatergic synapse contains approximately 200 receptors. We consider quantum events affecting one receptor within such a synapse. By conservative estimates, a neuron contains from 10,000 to 50,000 such synapses… This gives us between 20 and 100 trillion glutamate receptors… Applying the same calculations to hypothetical microtubules, allegedly responsible for consciousness… Thus, when transitioning from quantum uncertainty at the subatomic level to the scale of the brain producing behavior, a scale problem arises: a staggering number of random events would need to occur simultaneously, in one place, and in one direction to exert a significant influence. experts agree that a more probable scenario is that any single quantum event is lost in the ‘noise’ of an enormous number of other quantum events occurring at different times and in different directions.”

By the end of the podcast, Sapolsky and Krauss reach a consensus that quantum physics ideas do not contradict biological determinism. The question of free will become philosophical: we live as if it exists, despite a lack of evidence supporting it. This approach allows focusing on practical measures, such as revising approaches to punishment and education, which Sapolsky discusses in detail in his book.

The works of Robert Sapolsky, Behave: The Biology of Humans at Our Best and Worst and Determined: A Science of Life Without Free Will, reveals a profound interconnection between biology, behavior, and determinism, constructing a comprehensive explanation of human nature. These books bring us to the realization that habitual notions of free will and moral responsibility require reconsideration.

Behave shows that human behavior is shaped through a complex interaction of neurobiological, genetic, hormonal, and social factors. Every action is rooted in a chain of events beginning long before conscious choice, including instantaneous hormonal responses and long-term environmental influences. This book aids in understanding how our best and worst actions are predetermined by a multifaceted biological foundation.

In Determined, Sapolsky takes the next step, asserting that free will is no more than a cognitive illusion necessary for social functioning but incompatible with scientific data. Neuroscience confirms that our decisions are not the result of independent choice, and quantum randomness adds no freedom since it remains outside the subject’s control.

These works possess not only philosophical significance but practical implications. If our actions are predetermined, then it is necessary to reconsider systems of justice, education, and social responsibility. This approach enables a focus on eliminating factors contributing to antisocial behavior and creating conditions conducive to empathy and cooperation.

Sapolsky’s perspective proposes a transformation in the way we view human relationships, the legal system, and our own lives: understanding that behind every behavior lie invisible biological and external forces can radically alter our approach to how we perceive ourselves and others.

He emphasizes that all our decisions result from biological and ecological factors beyond our influence, and this renders the traditional system of rewards and punishments meaningless. Sapolsky straightforwardly states that given determinism, moral judgments and systems of justice require complete reevaluation.

Having established the foundations of neurobiological determinism with Sapolsky, we now turn to philosophical concepts attempting to reconcile our inner experience of the “I as a free agent” with the fact that all our decisions and actions are conditioned by external and internal regularities.

Within the analytic tradition, one of the most influential approaches to this problem is compatibilism – the doctrine of the compatibility of free will and causal determinism. Classical compatibilism dates back to David Hume, who observed that freedom does not require the “breaking” of causal chains but merely the absence of external coercion and the capacity to act according to one’s desires and beliefs. In this vein, freedom is defined functionally: an agent is free when able to act based on one’s own motives rather than under external pressure.

In the 20th century, Daniel Dennett developed the idea of compatibilism in his book Freedom Evolves. Dennett suggested that evolution has created in our brains complex cognitive mechanisms capable of “planning” and “controlling” behavior – that is, forming predictions, evaluating alternatives, and changing course (Dennett, 2003). These mechanisms allow us to sustain social institutions and moral norms: we hold each other responsible because we can predict our own and others’ behavior and build interactions on these forecasts. At the same time, “will” remains determined – it is simply embedded in a system capable of self-reflection.

But what does freedom rely on, according to compatibilists? First, on the fact that internal causes (our desires and beliefs) are perceived by us as “ours,” even if formed by genetics, upbringing, and environment. Second, on the capacity for self-restraint and reevaluation of one’s motivations: we can bring our impulses to a “critical level” of consciousness and reconsider their significance. Thus, responsible agents capable of acting in long-term interests emerge – even if “long-term interests” and “motives” themselves are conditioned by antecedent causes.

Nevertheless, compatibilism faces a profound aporia: we did not choose our desires, design our motivational system, or establish the values that then determine our actions. If we were not the authors of our internal causes, how justified is it to ascribe moral responsibility to us? In the most radical version of this critique (developed, for example, by Galen Strawson), genuine responsibility becomes impossible because any attempt to “account to oneself” requires a meta-cause, and this meta-cause, in turn, requires an even deeper cause – ad infinitum.

On the other hand, opponents of compatibilism appeal to indeterminism: allegedly, random quantum fluctuations in the brain can provide a “glimmer” of genuine freedom. However, such an argument substitutes freedom with randomness. If an action results from unpredictable “noise” at synapses, it ceases to be a conscious choice and turns into a roll of the dice, for which we also cannot bear responsibility. Moreover, as modern philosophers note, quantum unpredictability is erased at the scale of the brain, where tens of trillions of receptors and synapses generate too much “noise” for it to convert into meaningful decision-making.

Compatibilists, striving to show that determinism and free will do not exclude each other, often refer to neurobiological mechanisms of self-control – in particular, the functioning of inhibitory neural circuits. One of the main arguments is that a person is capable, at a critical moment, to “stop oneself” – and this, they say, is the manifestation of freedom. For example, they point to the human ability to cancel already initiated actions within a very brief interval – ranging from several hundred to tens of milliseconds. This effect is well-studied in stop-signal task experiments, in which subjects are instructed to perform an action but then suddenly receive a signal requiring immediate cessation. Successful inhibition is interpreted as an expression of “higher” control, not reducible to mere impulse.

A key role in this process is played by inhibitory neurons, primarily GABAergic interneurons (interneurons using γ -aminobutyric acid, GABA) – notably parvalbumin-positive (PV+) and somatostatin-positive (SST+) cells. They modulate the activity of cortical pyramidal neurons and participate in suppressing excessive excitation, ensuring a balance between impulse and inhibition. These neurons are especially active in brain regions responsible for decision-making and self-regulation, including the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and right inferior frontal gyrus (rIFG). Signals from these cortical areas are transmitted to subcortical structures, chiefly the subthalamic nucleus (the nucleus of Luys), which functions as a kind of “emergency brake,” capable of interrupting an already initiated motor action.

From the compatibilist perspective, this very ability – to “think twice” and cancel an impulse – demonstrates a functional level of freedom: we do not act purely automatically; we have a biological mechanism enabling the evaluation and alteration of action. Compatibilists claim this capacity suffices to speak of responsibility: if a person could have stopped but did not, that is their manifestation of free will.

However, incompatibilists – philosophers who assert that free will is fundamentally incompatible with determinism – point out that the presence of inhibitory mechanisms does not render the individual free in the true sense. According to their position, if every action has sufficient causes – biological, psychological, or social – it cannot be free, even if the subject experiences control. The mere fact that inhibition is possible does not mean that the subject “chooses” it in any metaphysical sense. The work of these neurons is conditioned by the same determining factors: genetics, experience, current physiological state, and environment.

,neither libertarianism nor compatibilism restores the intuitive, deeply rooted everyday consciousness freedom – the freedom to thus be the genuine source of one’s actions.

To understand the nature of the “feeling” of freedom, consider how it relates to predictive coding. The brain forms internal models of the world and continuously generates predictions about incoming sensory inputs. When predictions are confirmed, we experience harmony; when predictions diverge from reality, an error signal arises, and the model is refined. At the level of subjective experience, this looks like an act of choice: consciousness operates with final predictions, not perceiving the complex causal calculations underlying these predictions.

The illusion of freedom in predictive coding arises because we interpret the successful matching of expectations and actual data as “my intention” and “my decision.” In reality, the brain simply minimizes prediction error in the most efficient way to conserve resources and adapt faster. Yet we habitually ascribe authorship of this process to ourselves.

In this sense, free will become an adaptive information-processing tool – a cognitive strategy: filtering complex causal chains into compact predictions allowing rapid decision-making and maintaining a sense of control. Without this “mythical freedom,” we would be overwhelmed by the chaos of unprocessed causes, and our social structures would lack the foundation for practices of responsibility and trust.

Thus, free will cease to be an ontological property of the world and becomes a question of the structure of our perception. Determined biology and physics are closely intertwined with the brain’s illusory “free will” at the level of predictive algorithms. It is precisely in this unity that its true power lies – as a form of adaptation to the extreme complexity of existence.

2. Adaptation to Death

The sense of free will help the mind feel in control of his life, yet it proves powerless when confronted with the awareness of the finitude of existence. Death, as an integral part of our being, evokes fear and existential tension – especially in the context of the world’s chaos, as discussed in the previous section.

The brain, which strives to avoid cognitive conflict, employs mental models of immortality and symbolic adaptations to soften the impact of its own mortality. These mechanisms help maintain internal stability and preserve the capacity for functioning even in the face of the inevitable. In this section, we will examine how mental constructs, cultural adaptations, and individual strategies alleviate the fear of death and help the individual find ways to come to terms with it.

2.1. Mental Models of Immortality

Ernest Becker was an American psychologist and philosopher, best known for The Denial of Death – for which he was awarded the Pulitzer Prize – and Escape from Evil. In these works, Becker analyzes the fundamental existential problems of the human condition, chief among them being the awareness of one’s mortality. In order to cope with this fear, humans construct mental models of immortality – cognitive frameworks that help the mind adapt to existential limits, that is, to situations in which human reason encounters fundamentally unknowable and unpredictable phenomena. These models allow for the preservation of a sense of control, order, and meaning in the face of the inevitable finitude of existence. Becker argues that human life cannot be understood without acknowledging the fear of death, which affects all aspects of our being, from personal relationships to cultural and religious systems.

Mental Models as Tools for Prediction and Defense

From the perspective of predictive coding, the brain constantly updates its models to anticipate the future. When predictions are confirmed, this creates a sense of safety and stability. But the awareness of one’s mortality and the finitude of existence represents a fundamental uncertainty that cannot be eliminated. Confrontation with this existential limit provokes anxiety and disorientation, and thus the individual resorts to constructing models of immortality as a means of defending the mind.

Symbolic Heroism and Cultural Adaptations

One of Becker’s central ideas is that of symbolic heroism as a way of adapting to existential limits. Symbolic heroism is the attempt to overcome the fear of death through participation in cultural systems that endow life with meaning and create the illusion of immortality. The individual seeks ways to become part of something greater, something that will outlast their physical death. This may take the form of art, science, religion, political movements, or social institutions (Becker, 2019).

Becker argues that culture, at its core, is a heroic system designed to shield the individual from the terror of death. Culture creates symbols and myths that promise immortality through belonging to something eternal. For example, an artist may seek immortality in their works, a scientist in their discoveries, and a soldier in the defense of their homeland.

As Becker writes: “Culture is in its essence a heroic system that allows us to believe we transcend death by participating in something eternal.”

Thus, symbolic heroism allows the individual to adapt to existential limits by creating an illusion of control and stability. Cultural systems offer pathways to transcendence that divert the mind from the recognition of life’s finitude.

Types of Mental Models of Immortality

Becker identifies several types of immortality models that help the individual cope with the fear of death:

– Biological immortality. The desire to leave behind offspring as a way of extending one’s existence through genetic continuity. Children become symbols of life’s continuity despite personal mortality.

– Symbolic immortality. The creation of works of art, scientific discoveries, or social achievements that will outlive the individual. This model allows one to feel part of history and culture.

– Ego-centric immortality. The pursuit of fame and recognition as a way to generate the illusion of personal immortality. This may be expressed in striving for leadership, success, or leaving a legacy in the memory of others.

– Theological immortality. Belief in an afterlife or eternal soul as a means of overcoming the fear of death. Religious convictions create a sense of meaning and hope for the continuation of existence after physical death.

These models of immortality help the individual adapt to existential limits, preserving a sense of meaning and predictability in an unpredictable world.

Symbolic and Genuine Heroism

Although symbolic heroism helps manage the fear of death, Becker notes that it is based on self-deception. Cultural and religious systems offer illusory solutions that do not eliminate death itself but merely distract from its implementation. Symbolic heroism allows the individual to temporarily suppress anxiety but does not resolve the deeper existential conflict. As Becker observes:

“The irony of human existence is that the deepest need is to be free from the anxiety of death; but it is life itself which awakens it, and so we must shrink from being fully alive.”

In contrast to symbolic heroism, genuine heroism requires an acknowledgment of existential limits and a willingness to live in full awareness of them (Becker, 2019). Genuine heroism involves the courage to accept one’s mortality and to act in spite of fear. It means rejecting illusory comforts and self-deception and instead choosing to live consciously in the face of finitude.

Genuine heroism entails the continual renewal of mental models and adaptation to uncertainty. It is a process that demands the bravery to confront chaos and unpredictability, while recognizing that no model can provide a definitive answer to the questions of existence.

Conclusion

Thus, Becker’s ideas about mental models of immortality and symbolic heroism represent a form of adaptation to existential limits. Human beings create cultural, religious, and social systems in an attempt to overcome the fear of death and maintain a sense of control and meaning. However, genuine heroism demands that we abandon self-deception and confront existential limits head-on – accepting our finitude and choosing to act in full awareness of it.

Critique of Heroism

In his work The Denial of Death, Ernest Becker posits that “the problem of heroism is central to human life.” Heroism, in his view, is a cultural construct and a necessary illusion that helps preserve sanity in the face of the awareness of death. Through heroic striving, people create their own projects of immortality. One might be tempted to stop there in explaining the human condition – to reduce all striving, culture, religion, and ideology to existential fear of death, which we are unable to overcome physically. This would indeed seem sufficient. However, we know that alongside the fight against death through heroism or transhumanism, there is another possibility – acceptance of death. And as will become evident further on, death is not the only thing the mind fears and cannot overcome.

The Kübler-Ross model, commonly known as the five stages of death acceptance, appeared four years before the publication of Becker’s book and proposes its own framework for coming to terms with mortality. At present, we are not concerned with whether each of these stages actually occurs or whether alternative stages might be identified; what matters is the fact that the model, as an idea, produces tangible results.

Contemporary research in psychology and neuroscience has gone further. In addition to Terror Management Theory (TMT), new approaches have emerged that reveal the multidimensional nature of human perception of mortality. One such concept is Existential Well-Being Theory, which emphasizes that awareness of finitude can actually foster personal growth, provided it is properly integrated into a person’s life. This theory highlights how acceptance of death can stimulate the search for meaning, improve interpersonal relationships, and contribute to the development of an authentic sense of self.

Another promising direction involves research at the intersection of psychology and neuroscience, exploring how awareness of mortality affects the brain. Techniques related to neuroplasticity, for example, show that consciously working with thoughts about death can reshape neural structures involved in anxiety regulation. This opens new therapeutic horizons, including treatment for PTSD and other psychological conditions.

Yet another area of recent inquiry focuses on the therapeutic use of psychedelics, such as psilocybin, in treating terminal illness. Though controversial, these methods have shown encouraging results: patients who have undergone psychedelic-assisted therapy report reduced fear of death, improved quality of life, and enhanced emotional well-being. Studies suggest that such experiences may produce a sense of unity with the world, helping individuals perceive death not as a tragedy but as a natural process.

To demonstrate the effectiveness of death acceptance, I will share my own story. I did not need to be diagnosed with a terminal illness or suffer a tragic loss to confront the awareness of life’s finitude. From an early age, I witnessed the deaths of close relatives, most of whom passed away from natural causes. I attended funerals conducted according to Orthodox Christian traditions, even though my family was non-religious. At that time, death seemed like something routine: a person disappears, their body is returned to the earth – and that is the end of it.

However, at the age of fifteen, something changed. Thoughts of my own mortality began to intrude into my consciousness, especially during the silence of night or moments of solitude. They felt like a sudden stab – cold and merciless – evoking a visceral terror. My awareness seemed to plunge into an abyss. I later learned that this state could be classified as panic attacks. In those moments, the world would collapse into a single thought: I will disappear, and nothing will be able to save me.

At first, these episodes were rare, and my only strategy for coping was distraction. But the fear was more than just an emotion – it was an instinct, poisoning the mind. It lurked like a predator, waiting for the right moment. The older I became, the more clearly I sensed it.

By the time I turned twenty-one, this state had returned – this time consuming my entire consciousness. Thoughts of death became obsessive, crowding out everything else. Upon waking, I would immediately remember my mortality, and the horror would seize me. In search of comfort or answers, I turned to texts, read about near-death experiences, and explored philosophical theories. But the answers either seemed naive or proved useless. Any attempt to escape the thought of my demise crashed against the brutal clarity of its inevitability.

Two concepts are typically offered: either absolute nothingness after death, or traditional religious notions of an afterlife. Neither idea was acceptable to me. I lacked magical thinking, so religious beliefs offered no consolidation. And the prospect of complete annihilation inspired unspeakable dread. Eventually, I realized that the root of this horror was not fear of physical death or pain, but the fear of losing my self, the disappearance of consciousness.

I came to understand that my fear was not merely a fear of pain or the unknown. It was the terror of losing the I. The self-awareness I had taken as the essence of who I was turned out to be a shadow, doomed to vanish. I tried distracting myself with thoughts of the cosmos, but the grandeur of the stars only underscored my insignificance.

Comparing this experience to the Kübler-Ross model, I can confidently say that I went through the stages of denial, bargaining, and depression (Kübler-Ross, 2020). However, I did not experience the stage of anger. The final outcome of this inner order was acceptance. In that moment, I felt a sudden improvement in mood, bordering on euphoria.

One day, while walking home from work, reflecting on recent changes in my thinking, I passed a funeral supply store as I always did. Outside the shop stood a display of headstones visible to everyone passing by. And then I felt something strange. The sensation was unfamiliar – almost as if I were not the one walking, but merely an observer, watching myself from the outside, as though I were playing back a video in my mind. The world around me had subtly changed – the colors didn’t disappear entirely, but they seemed noticeably duller, as if reality had lost some of its saturation.

This state didn’t frighten me, even though I had never experienced anything like it before. I still felt everything around me, although my perception was somewhat distorted. Physically, I maintained full control over my body, but it felt different – almost automatic, as if my movements were being directed without conscious involvement.

It was depersonalization-derealization syndrome – as though I were viewing everything through glass or a screen. My body continued performing all necessary physiological functions, going to work, but my mind had fully turned inward, analyzing its surroundings. Looking at crowds of people, I thought about how brief their time was here, and how much attention they devoted to this world. I imagined skeletons with brains inside each of them, and how the outer shell to which they paid so much attention was utterly irrelevant. I remained in this state for more than a week. It didn’t particularly hinder me – though it unsettled me a bit – but I didn’t feel the same desperation to escape it as I had previously when trying to come to terms with death. Nor did I have the strength.

During those days, I persistently pondered the nature of reality. I was haunted by questions: Does only my consciousness exist? Can I be sure that others see and feel the same as I do? Or is this entire panorama nothing more than a façade woven by my perception? Like Sextus Empiricus, I grew skeptical of anything I could not verify. In the course of my reflections, science became a more reliable guide for me than philosophy. Philosophy offered abstract constructs, building castles of paradoxes in the air, but it gave me no solid ground to stand on. Science, by contrast, offered clarity and testability, transforming the fog of existential questions into more comprehensive patterns.

The state of depersonalization gradually faded, but it left a profound imprint. I realized that what I had called the “self” was not a unified entity, but a mere intersection of perceptions, memories, and fleeting impressions. This illusion of unity is a cunning product of evolution – not truth, but a convenient mask.

Becker’s models of “heroism” lost their power. The individual trying to cheat death now seemed to me not so much tragic as naive. All of Becker’s models of heroism had become irrelevant to me – except one, and even that was not directly related to death: the search for meaning in life and in the world at large.

The existential question of the meaning of being, despite the disappearance of the fear of death, did not vanish. It continued to torment me just as much as thoughts of finitude had before. All of this led me to understand that the fear of death cannot be the sole driver of human activity. In creating culture, systems of meaning, and value structures, human beings attempt to overcome not only the fear of death but many other existential challenges. Humans do not always seek heroism. Sometimes, they are motivated by entirely different factors – joy in the process itself or simple curiosity.

Becker’s “projects of immortality” can be viewed as unfalsifiable ideas, and this constitutes one of the central problems with his notion of heroism.

Like theological arguments for the existence of God or otherworldly forces, heroism projects are based on subjective belief and collective agreement. The problem is that neither heroism nor theological concepts can be confirmed or disproven using scientific methods. This makes them conceptually similar: both operate within the boundaries of human psychology and existential experience, but not within the domain of empirical science.

2.2 Devaluing Death, or The Problem of Suicide

The awareness of life’s finitude can give rise to various perceptual and behavioral anomalies. One such example is the belief held by some individuals that, since death is inevitable, life is therefore devoid of meaning, and that one may as well end one’s existence consciously rather than wait for a natural death. I maintain that such thoughts in themselves do not necessarily lead to action. While from both biological and philosophical perspectives it makes no essential difference whether one dies now or many years later – particularly in the absence of close relatives or children – what remains with us is the inner experience, which may be perceived as akin to observing a film or theatrical performance. We do not typically stop watching a film simply because we know it will eventually end. Nevertheless, as will be demonstrated below, the mere thought of suicide is insufficient for its implementation.

Suicide is an extraordinarily complex phenomenon, the emergence of which is conditioned by numerous factors. One key aspect is the biological mechanism involving inhibitory neurons that accumulate prediction errors and may lead to the conclusion that the future is invariably associated with inevitable suffering and lacks positive outcomes. Among the hypotheses under investigation is the assumption that certain individuals possess a genetic predisposition to suicidal behavior, which may be activated under specific circumstances. This means that the presence of certain genes or brain impairments can substantially increase the likelihood of suicide, even in the absence of overt pessimism or significant life difficulties.

It is important to stress that this hypothesis has not yet been definitively proven and remains the subject of ongoing research. Genetic predisposition is a significant, but by no means the sole, risk factor. Its influence is always interwoven with other psychological, social, and environmental conditions, forming a complex network of causes that lead to suicidal behavior.

In what follows, I shall treat suicide as a process that is genetically and deterministically conditioned. However, this is not to suggest that the genetic component constitutes an exhaustive account of the problem of suicide. The subject demands a more thorough and multidimensional analysis that includes a wide range of contributing factors, which lie beyond the scope of the present work.

Genetic Predisposition

In recent decades, scientific research has shown that genetics plays a significant role in susceptibility to depression and suicidal behavior. One of the key genes associated with suicide is the gene that encodes serotonin – a neurotransmitter that regulates mood and behavior. For example, the 5-HTTLPR gene, which is responsible for serotonin transport, has been linked to an increased risk of depression and suicidal tendencies. Individuals with a particular variant of this gene exhibit lower levels of serotonin, which may contribute to the development of depressive disorders and ultimately increase the risk of suicide.

Another important gene is MAOA (monoamine oxidase A). This gene also affects the levels of neurotransmitters such as serotonin and dopamine. Low MAOA activity is associated with a greater propensity toward aggression, impulsivity, and depression – all of which may contribute to suicidal tendencies. Such studies underscore that the presence of certain genetic variants may play a key role in a person’s decision to commit suicide under conditions of stress or crisis.

Brain Injury

In addition to genetic predisposition, brain injuries may also contribute to elevated suicide risk. Damage to specific areas of the brain – such as the prefrontal cortex and limbic system – can significantly alter emotional behavior and an individual’s capacity for self-regulation. For instance, individuals who have sustained traumatic brain injuries or strokes may experience changes in their self-perception and worldview, which increases the likelihood of depression and suicidal thoughts. Brain injuries may also affect serotonin levels and other neurotransmitters, promoting the development of depressive states and disturbances of emotional balance.

The Role of Medications

Medications that may increase suicidal tendencies play a crucial role in exploring the connections between biology, psyche, and behavior. Some drugs, despite their therapeutic properties, can produce serious side effects, including depression and suicidal ideation – especially among individuals with certain predispositions or psycho-emotional disorders.

One of the most well-known categories of drugs that heighten suicide risk is antidepressants. Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine (Prozac) and sertraline (Zoloft), although widely used to treat depression, may in some cases exacerbate suicidal thoughts, particularly among adolescents and young adults during the initial stages of treatment. In 2004, the FDA issued a warning that antidepressants may increase the risk of suicidal ideation among youth. However, it is important to note that for some patients, antidepressants are effective, and the increased risk of suicidal ideation is more often linked to individual reactions to the drugs, initial instability of the condition, or insufficient medical supervision in the early weeks of therapy.

Another group of medications associated with increased risk of suicide is anticonvulsants, such as lamotrigine and valproate, used to treat epilepsy and psychiatric disorders. Studies have shown that these agents may increase suicidal tendencies, especially with long-term use. In 2008, the FDA added a warning about this risk to the packaging of medications such as lamotrigine, emphasizing the need for careful monitoring of patients’ psycho-emotional states.

Opioids – potent painkillers such as oxycodone and morphine – are also linked to elevated suicide risk. These substances alter the brain’s chemical balance, promoting depression and deteriorating emotional well-being, which may lead to suicidal tendencies, especially in cases of abuse or prolonged use.

In addition, psychotropic medications such as antipsychotics and benzodiazepines may also induce depression and suicidal ideation, particularly among individuals prone to psycho-emotional disorders. Certain antipsychotics, such as risperidone and quetiapine, may produce side effects that worsen mood and even provoke aggression. Benzodiazepines, including diazepam and Xanax, are often prescribed to reduce anxiety, but their prolonged use may also lead to depression and an increased risk of suicide.

No less dangerous is isotretinoin – a drug used to treat acne, widely known under the brand name Accutane. It has been reported to cause depression and suicidal ideation, as documented in numerous studies and FDA-issued warnings. Isotretinoin has been associated with psychiatric side effects, including depression and aggression, making it particularly risky when used during adolescence.

while many of these medications have important therapeutic properties, it is crucial to remain aware of their potential side effects, which may thus significantly increase the risk of suicidal tendencies. Careful monitoring of patients taking these drugs is essential to detect any changes in their psycho-emotional state and to prevent more serious outcomes.

Altered Brain Activity and Psychoactive Substances

Changes in brain activity are also directly related to the use of legal and illegal psychoactive substances, such as alcohol. Alcohol is one of the most accessible and widely consumed legal drugs in the world. Its use is associated with temporary alterations in brain activity, which may impair a person’s ability to regulate emotions and behavior. Chronic alcohol abuse is known to contribute to depression and other mental disorders, significantly increasing the likelihood of suicidal tendencies. Research indicates that individuals suffering from alcoholism exhibit substantially higher suicide rates than the general population. This is because alcohol suppresses central nervous system activity and intensifies feelings of hopelessness, which may lead to desperate decisions.

Neurochemical Mechanisms of Action

All of these substances act on neurotransmitters in the brain, such as serotonin, dopamine, and norepinephrine, which play a central role in mood and behavior. For example, alcohol enhances the activity of GABA (gamma-aminobutyric acid), producing relaxation and reduced anxiety. However, chronic alcohol consumption leads to decreased serotonin levels, which is associated with the onset of depression and increased suicide risk. Similar changes occur with other psychoactive substances, which may ultimately result in suicidal outcomes.

Social Context and Legality

The social dimension of legal drugs must not be overlooked. Despite their availability, these substances are often embedded within cultural and social stereotypes, which may in turn reinforce feelings of isolation and hopelessness in individuals already predisposed to depression and suicidal ideation. Moreover, societal pressure and stressors are related to the use of alcohol and tobacco may act as triggers for suicidal behavior.

Why People Without a Genetic Predisposition Do Not Commit Suicide

Studies show that individuals without such predispositions, despite facing existential dilemmas or depressive episodes, are less susceptible to suicide risk because their brain structure and neurochemical composition do not support the mechanisms leading to self-harm.

According to research in psychiatry and genetics, the absence of genetic risk factors or brain injuries may serve as an important safeguard against suicidal tendencies. Even in the presence of depression or life difficulties, such individuals are able to engage alternative stress-coping mechanisms that allow them to avoid suicide. Studies conducted in Sweden have demonstrated that among individuals with no family history of depression or suicide, the probability of suicide is significantly lower – even when they experience psychological challenges in life.

Family Studies and Suicidal Tendencies

Hereditary predisposition to suicidal tendencies is a crucial aspect substantiated by numerous studies in psychiatry and genetics. Some of the most compelling examples of hereditary suicidality are confirmed by family histories and hereditary factors that increase the risk of suicidal thoughts and behavior in descendants. The phenomenon whereby suicide becomes part of a family history may be linked to specific genetic and neurobiological factors that contribute to an elevated susceptibility to depression and suicidal inclinations.

One prominent example is a study conducted in Sweden that examined the role of family history in suicide cases. The analysis revealed that the risk of suicide is significantly higher in children whose parents had died by suicide. This finding supports the existence of a hereditary predisposition to suicidal behavior. Further studies have shown that if both parents suffer from depression or exhibit suicidal tendencies, the likelihood that their children will experience similar problems is markedly increased.

A study conducted in Norway also found that individuals with close relatives who had suffered from depression and suicidal tendencies demonstrated a heightened risk of developing depression and suicidal ideation later in life. Thus, the genetic component may predispose a person to more severe mental disorders, including depression, which is one of the leading factors contributing to suicide.

Methodological Considerations

Most studies of genetic and neurobiological predispositions to suicidal behavior are based on retrospective analyzes of correlations between the presence of certain genetic markers (or brain injuries) and completed suicides or suicide attempts. Such correlational studies cannot establish a strict causal relationship: we observe that a particular genetic variant appears more frequently among individuals who have died by suicide, but we cannot confidently assert that this variant was the cause.

More reliable conclusions require longitudinal cohort studies, in which selected groups of individuals undergo genetic, neuroimaging, and psychological testing long before the onset of suicidal thoughts or behavior, and are then observed over many years. Only such a multidisciplinary approach – combining psychology, neurobiology, and sociology – can reveal how genetic, psychological, and social factors interact, and which of these factors have a decisive influence.

It is also worth noting that many conclusions about the dangers of psychotropic medications are based on retrospective correlational data, which cannot definitively distinguish between the effects of the drug itself and the natural course of depression. For instance, during the initial stage of treatment with selective serotonin reuptake inhibitors (SSRIs), there is often an “activation phase” in which the patient regains enough energy to act before the depressive symptoms begin to recede. This creates a misleading impression of a “suicidogenic” effect of the medication. Moreover, patients prescribed antidepressants are often already in a more severe state, and comparing their suicide risk to that of the general population – without accounting for the depth of their depression – creates the illusion of a direct “antidepressants → suicide” link. Publication bias further exacerbates this effect: cases of suicidal outcomes during treatment are reported far more frequently in the literature than the numerous successful cases of recovery.

At the same time, there is compelling meta-analytic evidence – particularly the study by Kirsch et al. (2008) and subsequent reviews – which indicates the difference in efficacy between antidepressants and placebo is often clinically negligible, especially in cases of mild to moderate depression. These findings call into question the very “efficacy” of SSRIs as a class of drugs and underscore the need for prospective randomized studies with long-term monitoring of patients’ psycho-emotional states in order to determine whether the drug’s benefits truly exceed the natural course of the illness and the effects of placebo.

Ultimately, a proper assessment of the risks and benefits of any psychotropic medication is impossible without multidisciplinary monitoring, which must include genetic and neurobiological markers, psychosocial parameters, and access to crisis intervention services. Only a comprehensive approach can not only balance the therapeutic benefits and potential side effects of pharmacological treatments but also allow for timely adjustment of interventions, thereby minimizing adverse outcomes and reinforcing positive therapeutic effects.

For this reason, I cannot assert with certainty that suicide is solely a product of genetic predisposition – but I am confident in its significant influence on the fundamental question of life and its voluntary end.

Conclusion

If we consider genetics as one of the central risk factors for suicidal behavior, we are forced to rethink traditional philosophical reflections on the existential meaning of life: for many individuals, the question “is life worth living?” is not so much the result of deep personal reflection as it is a manifestation of physiological predispositions rooted in a specific set of genetic and neural mechanisms. However, even this biological perspective cannot be seen as exhaustive. The majority of existing studies, which are based on retrospective correlations, do not allow us to assert a direct causal link between genetic markers or traumatic brain injury and the act of suicide.

To reach more reliable conclusions, we need longitudinal cohort studies and prospective randomized trials in which psychosocial, neurobiological, and pharmacological factors are rigorously monitored over many years.

Although psychotherapeutic interventions can improve overall emotional well-being, they often fail to alter the vulnerability that stems from genetic predisposition. Even with high-quality support, individuals in high-risk groups continue to show elevated mortality rates. At the same time, the role of pharmacological treatment must neither be underestimated nor overstated. The effects of early-phase activation, publication bias, and the severity of patients’ initial mental states often create the illusion of a direct suicidogenic effect of antidepressants, whereas numerous meta-analyses reveal a clinically negligible difference between SSRIs and placebo in cases of mild to moderate depression.

Therefore, real suicide prevention must consist in a system where biological awareness is organically integrated with social policy and public health initiatives: regulation of access to psychoactive substances (including alcohol), improvement in quality of life, expansion of early intervention and crisis services, and the integration of psychological support tailored to individuals’ neurobiological profiles. Only such a comprehensive, multidisciplinary model – one that draws equally on philosophical reflection on the value of life, scientific knowledge about genetics and neurobiology, and practical strategies of social support – can reduce suicide risk and offer those standing on the edge not abstract questions, but concrete paths to survival.

3. Adaptation to meaninglessness

Acceptance of mortality, as discussed earlier, opens the door to an even deeper question: if existence is limited, how can one find meaning in a life devoid of inner purpose? This dilemma, intensified by the awareness of the chaotic nature of the world, forces the mind to seek ways to order and stabilize the perception of reality.

However, the problem of meaninglessness goes beyond simple logic. It affects the emotional and cognitive structures of a person, which often seek to compensate for the awareness of absurdity by creating subjective meanings. These adaptation strategies allow the gap between the finiteness of life and the desire for meaning to become not a catastrophe, but a new starting point.

In this section, we explore how the idea of meaninglessness has become one of the central challenges of the human mind. We look at the ways in which humans overcome this conflict, from distraction and creativity to philosophical reflection on their role in a chaotic world. But before that, I would like to introduce you to an underrated Norwegian philosopher and mountaineer, Peter Wessel Zapffe (1899—1990), who wrote about the tragic plight of man in this world and who greatly influenced me.

The Tragic Peter Zapffe

Peter Zapffe is a Norwegian philosopher who was little known outside his homeland until recently. His works began to resonate with Russian and English-speaking audiences after the translation of his work Den sidste Messias (Russian: “The Last Messiah”) into these languages, as well as through the influence of the American writer Thomas Ligotti, who in 2010 published his novel The Conspiracy Against the Human Race: A Contrivance of Horror, which reflected Zapffe’s ideas. In mid-2024, Ryan L. Schouler released an English translation of Zapffe’s magnum opus, Om det tragiske (On the Tragic). The Russian edition was published in 2025. Thomas Ligotti’s essay has not been officially published in Russian due to copyright issues and is distributed on the Internet and in samizdat in a translation by revliscap.

In his work, Peter Zapffe⁴used an approach called biosophy.

Biosophy is an approach in which Zapffe looks at human life and existence through the lens of biology and evolution. He emphasizes that human life is the result of a biological process, and that biology determines many of our existential problems, such as the realization of death and the meaninglessness of existence. Zapffe’s biosophy emphasizes that the biological process is not designed to create meaning in life, but only confronts humans with the challenge of existing in a world devoid of timeless goals. The biosophical method is used to study human existence from a biological perspective. In this way, humans are understood on the basis of what we know about biology, that is, on an empirical basis (Zapffe,

Конец ознакомительного фрагмента.

Текст предоставлен ООО «Литрес».

Прочитайте эту книгу целиком, купив полную легальную версию на Литрес.

Безопасно оплатить книгу можно банковской картой Visa, MasterCard, Maestro, со счета мобильного телефона, с платежного терминала, в салоне МТС или Связной, через PayPal, WebMoney, Яндекс.Деньги, QIWI Кошелек, бонусными картами или другим удобным Вам способом.

Примечания

1

Occam’s razor is a methodological principle stating: “Entities should not be multiplied beyond necessity.” This principle advises choosing the simplest explanations for phenomena while avoiding unnecessary assumptions.

Back

2

A more detailed discussion of active inference and the free energy principle can be found in the book Active Inference: The Free Energy Principle in Mind, Brain, and Behavior (2022) by Thomas Parr, Giovanni Pezzulo, and Karl J. Friston.

Back

3

All Sapolsky quotations herein are translations from the Russian text, as the original English versions were not available at the time of writing.

Back

4

The term “biosophy” was probably first used in 1806 by Ignaz Paul Vitalis Troxler, a Swiss philosopher whose early work was influenced by F. W. J. Schelling and later adopted by Zapffe. Modern biosophists include Jong Bhak, who defines biosophy as “a new way of philosophizing based on scientific and biological understanding.”

Back