Владислав Педдер – The Experience of the Tragic (страница 4)

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).