Beyond Neurons: The Connectivity Thesis

From Neuron Doctrine to Networks

Consciousness is a remarkably striking phenomenon that has been the subject of philosophers’ propositions, poets’ verses, authors’ works, and scientists’ theories for centuries. It holds an undeniable and increasingly significant importance, particularly for science. A discipline that encompasses this area has emerged—none other than today’s rising scientific field: neuroscience.

Consciousness occupies a significant place in modern neuroscience, preserving its mystery in fundamental questions—such as why some living beings possess it while others do not, how and why it develops, and whether it has a concrete location in the brain—and in deeper inquiries, such as what its exact function is, whether a hierarchy of consciousness levels can be discussed, and the possibility of its existence in non-human entities. The enduring enigma of consciousness lies not in its absence but in how it emerges from the brain's intricate workings.

The reason why the concept of consciousness gained a place in science during the 20th and 21st centuries stems not only from the acceleration of neuroscience but also from the mysterious nature of consciousness. Neuroscience made such a leap because of the parallel progression of technological developments. These tools enabled us to look into the brain's hidden workings and networks by converting speculation into measurable signals.

Revolutionary technologies include EEG, CT, MRI, and fMRI. Each of these advancements has deepened our comprehensive view of the brain. Together, these tools can be used to map the complexity of the connections underlying consciousness. Additionally, advanced microscopy technologies such as the electron microscope and electrophysiological studies have shed light on the brain’s functioning at the cellular level.

When we look at an apple, how we see it falls under the domain of optics, but how we perceive it is the subject of neuroscience. The brain is made up of specialized cells in constant communication. How this communication occurs became the source of intense debates toward the end of the 1800s.

One theory was the Reticular Theory, which proposed a unified, continuous, and gapless nervous system. Camillo Golgi developed the Black Reaction, which allowed scientists to view a neuron completely. Santiago Ramón y Cajal used this technique and argued that the findings supported the Neuron Doctrine. With this confirmation, it was accepted that neurons are not a single network but independent structures.

The challenge in examining neurons lay in the complex extensions—dendrites and axons— which form intricate interconnections. Until the invention of the Black Reaction, these structures appeared complex and intertwined, giving the Reticular Theory an edge. However, Cajal’s use revealed that these structures do not make direct contact and that there are gaps— called synapses.

In 1936, Sir Henry Hallett Dale and Otto Loewi confirmed that synapses were filled with chemical agents called neurotransmitters, by discovering acetylcholine. Transmission in the brain was understood to proceed electrically along neurons and chemically at the synapses.

These discoveries and subsequent advancements have deepened our understanding of how the brain works day by day. Today, we know how the pressure created by touching an apple is transmitted to the brain and where it is processed. We know which pathways carry the apple’s taste, shape, texture, temperature, and smell, and in which specialized parts of the brain they are processed. Yet, we do not know how these inputs give us a unified and singular experience of the apple. This is known as the "binding problem," and it remains a mystery. Similarly, the question of how we learn something—just like memory—has not been fully illuminated. Despite 119 years since the first Nobel Prize in neuroscience, the problem of consciousness remains the main topic of this essay.

What Makes Something Conscious?

Consciousness is a concept with such philosophical and neuroscientific depth that it cannot be explained merely as a state of awareness or wakefulness. To define consciousness, a more holistic and comprehensive approach that encompasses these aspects is essential. Within the limits of our current knowledge, it is reasonable to start by suggesting that the human species is a conscious species that has established such a civilisation, questioned why and how it came into being, is aware of itself and its surroundings, questions the nature of consciousness, and even doubts its own consciousness. While studies have shown that some animal species, such as dolphins, elephants, and bonobos, demonstrate self-awareness by passing the ‘mirror test’ and exhibit environmental awareness through interaction and empathetic behaviour, these characteristics are far from sufficient to attribute human-level consciousness to them. The fact that some animals pass this test while many do not clearly reveals the existence of a consciousness hierarchy among "things" (I say "things" because, as will be addressed later, they need not necessarily be living beings). It is plainly evident that bacteria differ from inanimate objects, plants from bacteria, animals from plants, and humans from all the others in terms of consciousness.

In order to speak meaningfully about something as being conscious to a significant degree, the fact that it performs actions with a purpose offers us a sharp distinction between what is conscious and what is devoid of consciousness. However, it is important to note here that the purpose in question is not primitive goals like survival or reproduction. These are goals that arise out of necessity and allow for a certain degree of conscious development; the type of goal we are referring to, however, arises out of choice. Because if we are to speak of a hierarchy— if we are to talk about one thing being superior to another—we must consider the total sum of qualities one possesses that the other lacks. Since primitive goals (such as survival and reproduction) are shared across all living beings, including prokaryotes, claiming that all possess them or none do would provide equal value in shaping our theory. When we divide the universal set of humans into believers and, as its complement, nonbelievers, we obtain two sets without leaving out any specific examples. Believers refrain from many worldly pleasures they could currently obtain, motivated by the belief that they will be rewarded at the appropriate time (though other motivations leading to similar behaviors may exist). Although the behaviour of temporarily postponing immediate gratification in order to obtain larger rewards that are certain to be obtained is also seen in some other species, postponing gratification for something that is likely to occur years later, such as death, and does not guarantee a reward is not observed in other species.

While the motivations of non-believers span a much broader spectrum, what we commonly observe is a lifestyle guided by the pleasure principle. When we consider individuals of the same species, living in the same geography under similar standards, we minimize external factors (as also demonstrated through twin studies). Even among those individuals, the presence of such a wide range of motivational diversity in life choices affirms that the type of life a person leads is indeed determined by personal choice. Thus, we place the human species— known to be the only one whose actions contain purposes beyond primitive ones—at the top of the consciousness hierarchy.

But how did consciousness—something we have only observed in living organisms as of the first quarter of the 21st century—emerge in the first place? Why is human consciousness so complex, while that of other living beings remains simple and uniform? As mentioned in the introduction, the answer once again lies within neuroscience. But before we dive into the details of neuroscience and numbers, let's start at a more basic level. A whole is, in fact, something different from the quantitative and qualitative sum of its parts, and this can be observed throughout the universe. This makes analyzing the parts separately insufficient to understand the whole. Likewise, analyzing the whole in a monolithic way does not provide enough depth for understanding either. What must be thoroughly analyzed is the relationship and connection between the whole and its parts. Because all qualitative leaps occur there. For example, when we examine a water molecule, what we see is more than two hydrogen atoms and one oxygen atom coming together. To understand this, we can look at an oxygen atom next to a helium atom. In the first case, we see that the hydrogen and oxygen atoms form a molecule through a type of bond called a covalent bond, whereas in the second case, we see no bond or reaction. As clearly shown, the reason for the qualitative leap from atom to molecule lies in the network of connections between them.

Molecules come together to form organelles, which are the functional structures of cells; organelles form cells, cells form tissues, tissues form organs, different organs come together to form systems, and systems constitute the living organism. However, the transition from molecules to the cell—the most basic unit that exhibits the property of life—still remains unexplained. The theory of abiogenesis proposes that a living cell formed from non-living organic compounds. In 1950s, Stanley Miller and Harold Urey attempted to test this theory and conducted what would later be known as the Miller-Urey experiment. The experiment was conducted in a glass container simulating the conditions of the primitive Earth. In a tube containing water (H₂O), methane (CH₄), ammonia (NH₃), hydrogen (H₂), and carbon monoxide (CO), the water was heated with electrodes, causing it to evaporate and create sparks to simulate atmospheric lightning. Then, through a cooling process, the vapor was condensed and returned to the container in droplets. This setup was repeated for a week, and by the end of the experiment, it was found that 11 of the 20 amino acids could be produced this way. Amino acids are the building blocks of proteins and are essential for life. However, as can be understood, neither this experiment nor the theory of abiogenesis is sufficient to explain the qualitative leap from non-living compounds to a living form. Because the focus of these approaches is also on the parts that make up the whole.

Of course, the relationship between parts and the whole is not limited to this. We see a similar network of connections in plants. When looking at a forest from the outside, we see thousands of independent trees, but the background is much more complex. A forest is also a habitat full of biological diversity, potential for epidemics, and threats such as fires that endanger the trees’ survival. In such a risky environment, it is more beneficial for the forest to be a dynamic collection of trees communicating with one another rather than a static sum of independent trees. This would elevate the forest to a higher level of consciousness and better ensure its continuity. Indeed, studies have shown that trees can communicate with each other through a mutualistic relationship they develop with fungi at their roots, and that a forest is, in fact, a massive network. Fungi have a structure called mycelium. Mycelia are fibers that can extend underground with trillions of branches and can reach for kilometers. Through these mycelia, when a tree’s life is in danger, it can alert other trees to the threat in that area of the forest and transfer its organic and inorganic molecules to healthier trees to help ensure the forest’s survival. This molecular transfer is also observed in sick or dying trees. Undoubtedly, the existence of such a relationship between fungi and trees today is the result of selection pressure in their evolutionary processes. As mentioned in the introduction, these organisms also possess primitive motivations such as survival and reproduction. However, these motivations have not hindered the development of consciousness; on the contrary, they have led to it. This is because the reason they established this network of connections is the selection pressure and the motivations mentioned. Yet, the fact that these are their only motivations has also caused their level of consciousness to remain low. For higher levels of consciousness, higher-level motivations are essential. Therefore, although this condition in plants cannot be regarded as an emotion requiring high-level cortical functions such as self-sacrifice, it still places plants at a higher level of consciousness than any inanimate entity.

Architecture outlives ingredients. This is not confined to neurons. At the sub-neuronal scale, cell collectives coordinate through bioelectric networks—ion-channel dynamics and gap junction coupling—that drive wounded or developing tissues toward morphological set-points. Processes such as wound closure, tissue repair, tumor suppression, and limb regeneration perform the required error-correction inside these networks. Levin calls this a multiscale competency architecture: nested agents (cells → tissues → organs → organism) making decisions with respect to internal aims (morphological set-points). In my terms, there is connectivity under value control even before there is a brain: dense–diverse–re-entrant coupling steered by internal “preferences” over shape. Therefore “mind” is not the privilege of a particular material; it is the result of a particular architecture. Build the architecture and a qualitative leap becomes almost inevitable: whole-level patterns stabilize instead of dissolving into local reflexes. That is the heart of my thesis.

Why does this resonate with my threshold? Because two axes coincide: (i) connective integration—long-range, tissue-level causal propagation beginning at the cellular scale; (ii) value-weighting—morphological set-points, like attention or reward, decide which routes open or close. These are the biophysical counterparts of the global-access + value-control conditions that, in my view, tip a system into consciousness. When discussing connectivity in humans, it is important to note that the human brain consists of approximately 86 billion neurons. Each of these 86 billion neurons forms synaptic connections with other neurons through dendrites and axons. The number of these connections is around 10^14-10^15. This is not mere bigness: it is the combinatorial condition for many partially independent computations to run in parallel. This entire network of connections is referred to as the “connectome.” Although elephants boast more neurons overall (about 257 billion), the reason their level of consciousness is lower than that of humans lies precisely in these connections, with humans holding more in cortex, plausibly crucial for flexible cognition. For example, the dolphin brain has about 37 billion neurons, the gorilla brain about 33 billion, the African Grey Parrot brain around 2 billion, and the mouse brain approximately 71 million neurons. As can be clearly seen, although there is no direct relationship between the number of neurons and the complexity or consciousness of the brain, a higher number of neurons is important in terms of enabling more connections. However, what truly matters is the average number of different neurons each neuron connects with. The key to complexity of connectivity lies here.

Topology is negotiable. As Godfrey-Smith emphasizes, cephalopods are an independent evolutionary experiment in large, complex nervous systems: much control is distributed to the arms, yet organism-level coordination remains strong enough for planning, play, problemsolving, and rich interaction. From our perspective, this shows that what matters is not “humanstyle cortex” but a working architecture: dense, diverse, re-entrant circulation, and above all routing weighted by needs. Different wiring, same threshold. This replaces mammal-centrism with a single principle: many architectures, one rule—when connectivity + value cross the right line, the property of being a someone appears. This consonant with my view because the cephalopod case shows that consciousness is not tied to a single wiring plan, but to certain causal regimes. That matches my multiple-realizability claim: when different kinds achieve similar causal statistics—small-world organization, recurrence, value gating—they can trigger the same phase change. Material is secondary; architecture is decisive.

The Genesis of Connectivity

One of the fundamental working principles of the neuron is the Hebbian Theory, first introduced by Donald Hebb in his 1949 book The Organization of Behavior. The theory is often summarized as “neurons that fire together wire together.” According to this theory, neurons that consistently fire together tend to form connections with each other. The reason for the formation of these connections is to enable more efficient responses when the same activation and required output are needed again.

The connection of one neuron to another is a highly complex process that involves certain neuronal growth hormones. As observed in other areas of biology, unused neurons in the brain tend to regress, and their axons are pruned. The brain’s ability to make adaptive changes in response to the conditions it is exposed to is called neuronal plasticity. As can be seen, plasticity is vital for the brain. Because if the brain had remained an organ with a relatively low capacity for adaptation, like the liver or kidneys, it would not have been possible for it to reach such a complexity of connectivity throughout evolution. But if plasticity is a common feature of all living brains, then the question of why, as far as we know, this level of consciousness is seen only in humans—regardless of whether other species have a similar number of neurons—is a highly valid one. The answer lies in bipedalism, that is, the transition of archaic hominins from walking on four limbs to standing on two. This event occurred approximately 4 million years ago. Such a large-scale evolutionary change naturally brought about revolutionary consequences. Chief among these was the narrowing of the pelvic bone following the shift to bipedalism. Unlike other mammals, this compelled the human species to give birth to their offspring before the brain had fully developed. Because for the baby’s head to pass through the now narrower birth canal and pelvis of a bipedal species, a much smaller and more flexible skull was required. Therefore, the brains of human infants could only develop to the extent that would fit into that small skull before birth. This is the reason why the plasticity of the human brain is at such a high level. Moreover, an underdeveloped skull gains flexibility both through the interlocking structure of the bones that form it and through anatomical gaps that will later close. These massive changes are what made the birth of human infants possible. In species that continued to walk on four legs, such an adaptation did not occur, so their offspring are born with more developed brains. It is observed that the offspring of many animals—deer, giraffes, elephants, cows, dolphins, turtles, and many others—begin to move actively within hours of birth. In contrast, human infants require almost two years to walk properly. During this period, although neuronal plasticity operates at a very rapid pace, the developmental immaturity required to make birth possible can only be compensated for after several years. However, the fact that the majority of brain development takes place not in the womb—an isolated and relatively short-term environment—but in the environment where the being will spend a significant part of its life means that the entire connectome is reshaped accordingly.

And that is exactly what happened. After bipedalism and the adaptive changes that followed, the human species began to reap the rewards of the difficulties it endured. About 3.3 million years after standing upright, it began making tools from stone at Lomekwi 3. It invented fire around 1 million years ago, with secure evidence at Wonderwerk Cave, while habitual use appears later. And around 100,000 years ago, it left behind artifacts in caves that proved it possessed high-level cognitive functions such as symbolic thinking. Especially in terms of the invention and use of tools, another undeniable advantage of standing on two feet is that the hands were no longer needed for balance. While the human species had previously used all four limbs actively for balance, it could now achieve this with just two. Therefore, it could use its hands for other tasks. In this way, a dynamic brain capable of developing through interaction with its environment—and two limbs now available to perform new tasks—became the driving force behind the development of humanity. As is clearly understood, all these developments, each playing a crucial role in the evolution of modern humans, occurred after bipedalism. These developments not only shaped the material life of modern humans but also provided them with non-primitive purposes for living. For instance, they no longer had to eat solely to survive; they could now prepare and consume meals based on taste criteria. They could attract the opposite sex not just by being stronger or larger, but through the figures they drew or the tools they invented, thereby increasing their chances of reproduction—even having the opportunity to choose among several suitors. Because now, the issue was not merely survival or reproduction. Deriving pleasure while fulfilling these became equally important. In the beginning, they could only eat the animals they hunted raw, but after the invention of fire, cooking became an option In the 4 million years since then, continuous human evolution, along with technological advances and environmental changes, has exponentially increased the number of options available to them before taking any action and has offered countless possibilities. Constantly having to choose among many alternatives, humans have developed their analytical intelligence by mastering the evaluation of the benefits and drawbacks of these options. This also led to the development of a brain region called the prefrontal cortex. This region is responsible for complex functions such as decision-making, planning, and cognitive control; its dense reciprocal connections with sensory cortex and limbic structures are the substrate for deliberate choice. For this reason, it has an extremely dense network of connections. Each neuron in this area forms approximately 40,000 synapses, and with this number of connections, it has the most complex network after the cerebellum, which has about 100,000 connections per neuron. The cerebellum is the brain region responsible for balance. The reason this region possesses such a dense network is again due to bipedalism—because now, a human standing on two feet needs a more densely connected center to maintain balance and perform refined movements. Once the development of the prefrontal cortex was triggered, it entered a self-sustaining process. Its repeated use in evaluating choices led it to form new connections, resulting in an increasingly complex network. Moreover, the presence of alternative options made it necessary to consider ‘what would have happened if I had chosen the other one’ after making a decision—giving rise to high-level emotional states such as regret, which are not observed in other species.

Affect as Control Signal

Affect is a subject we have deepened our understanding of, especially in the last few decades. According to Jaak Panksepp’s taxonomy of mammalian affective systems—seeking, fear, rage, lust, care, panic/grief, play—explains why evaluation and salience pervade awareness. Although these are common affective systems, we know that human beings possess a much more complex affective structure. Emotions such as jealousy, trust, regret, longing, conscience, and self-sacrifice are all higher-level affective states that require an advanced and highly complex cortex. Naturally, the trigger for these is the abundance of choices. We can prove this with a simple thought experiment. Imagine a person who has been raised alone in a dark room since birth. This person eats the same meals at the same times every day and lives in complete isolation from anything that might remind them of the presence of others outside. That’s all. It is inconceivable for such a person to miss someone, because they have never met anyone. There is no one else in the entire universe except themselves. It is unthinkable for this person to make a sacrifice. Nor is it possible for them to have a moral conscience, to feel trust, to be jealous of something, or to regret something—because higher-level emotions have emerged from the fact that humans are social beings and actively require the presence of another person or an alternative choice.

The subject of affect (emotional response) is particularly important, and there are two reasons for this. The first is that consciousness is the product of an integrated network of connections. Therefore, whatever kind of consciousness we are discussing, we must also refer in depth to every component that constitutes that consciousness. The second reason is that higher-level emotions are emotions seen only in humans. In this respect, and in terms of the level of consciousness, the uniqueness of humans makes the relationship between these two aspects worth examining. Moreover, these emotions play a significant role in the fact that humans are the only species capable of building such an advanced civilization.

Competing Theories and a Threshold View

The main subject of the consciousness theory presented so far is that the complexity of connectivity and the qualitative leap it causes is the fundamental element that constitutes consciousness. Regardless of what the connectivity forms between, there is a critical threshold of complexity of connectivity that must be surpassed. Once this threshold is crossed, it can be said that the entity possesses a significant level of consciousness. The triggering event that enables the crossing of this complexity threshold appears as selection pressure. However, the solutions found to this selection pressure and the chaotic chain reactions it initiates yield outcomes in unpredictable ways. Although the transition from four-legged to two-legged movement was also a result of selective pressure, it led to the human species slowly climbing the steps of the consciousness hierarchy.

This view is compatible with the Global Neuronal Workspace (GNW) emphasis on global access, overlaps with—but is not identical to—Integrated Information Theory’s (IIT) focus on intrinsic causal power, and is naturally expressed in predictive/Free-Energy terms. It gains empirical bite through complexity measures such as the Perturbational Complexity Index (PCI) that integrate “integration” and “differentiation” in vivo. GNW proposes that information becomes conscious when it ignites a recurrent, fronto-parietal coalition that makes content globally available to systems for report, memory, and control. GNW excels at explaining access, reportability, and a host of laboratory effects (attentional blink, masking) and posits specific temporal signatures (“ignition”). IIT starts from axioms about the structure of experience and defines consciousness as a system’s intrinsic cause–effect power (Φ) over itself. The appeal is that phenomenological structure constrains mechanism. The cost is measurement difficulty and a panpsychist drift that many find counterintuitive. Predictive Processing / Free-Energy model perception as inference under generative models; attention modulates precision; action closes the loop. These accounts naturalize why brains would develop global, value-weighted access in the first place: it lowers surprise and increases adaptive control. Higher-order and metarepresentational views analyze a state as conscious when it is the target of an appropriate higher-order representation. These theories capture aspects of self-monitoring and report, though they can be made compatible with GNW architectures. The “complexity of connectivity threshold under value control” account is an integrative constraint rather than a rival banner: it says that whatever one’s favorite theory, the organism must achieve dense, diverse, recurrent complexity of connectivity that supports global access modulated by affective control signals. It is, in other words, a recipe that GNW can implement, that IIT aspires to quantify, and that predictive frameworks explain functionally. To address the hard problem—why connectivity produces subjective experience—we bracket its ultimate cause but constrain its neural correlates through thresholds, suggesting qualia arise from network binding patterns, testable via cross-modal perturbations measuring subjective shifts in feel. Perhaps the complexity of connectivity, due to everyone having different connectomes and different CVIs, could form the basis for future ideas that explain the possibility of subjective experience and the difficult problem of consciousness.

Where Consciousness Lives?

Up to this point, the topics discussed have included the emergence of consciousness, the criteria for being conscious, and what entities can be considered conscious. In addition, the materiality of consciousness is also an extremely important subject. If everything is related to connectivity—particularly if human consciousness arises from the connections between neurons—then it might be expected that consciousness could be something detectable, something that could be pointed to directly. However, when considered in more detail, this turns out to be a flawed approach. As previously mentioned, the brain is a structure that contains over 1014 connections. Moreover, which neurotransmitters are released in which pathways and which receptors—called "receptive sites"—they bind to result in different outcomes. The clearest examples of this can be seen in the dopaminergic pathways. There are four main dopaminergic pathways: the mesolimbic, mesocortical, nigrostriatal, and tuberoinfundibular pathways. For example, the mesolimbic pathway is more related to the reward center, while the mesocortical pathway is more concerned with executive functions. Although both are triggered by dopamine, the fact that they produce such different outcomes proves that the presence of a neurotransmitter, a neuron, or even both simultaneously does not guarantee the same result. All parameters—such as where a neuron starts in the brain, which neuron it stimulates, and by which pathway—affect the outcome. Therefore, in the emergence of consciousness, not only the numerical complexity of these brain connections but also the diversity of their properties plays a role. As stated in the introduction, a deep and holistic perspective is necessary to understand consciousness. For this reason, we cannot say "consciousness is located here and its function is this," as we can when describing the location and functions of the prefrontal cortex. Consciousness is the totality of complexity of connectivity that arises when all the components of the related networks perform their functions in a healthy manner. This may be a network formed by mycelium in plants or by neurons in humans. However, to better understand why consciousness still remains a mystery and why its location is unknown, it is useful to examine which of these networks, when malfunctioning, produce what kind of consequences and whether they lead to any changes in the level of consciousness.

This section will include many terminological expressions. But there is no need to be intimidated, as these expressions are merely the medical names of the regions mentioned. Also, the functions attributed to the brain regions mentioned here only represent a portion of their full responsibilities. Each has many more functions than those listed. First, let’s begin with the regions that, when lesioned, do not appear to directly affect consciousness. The first of these is the motor cortex. As with many other brain areas, there are two motor cortices, one in each cerebral hemisphere. When one of these areas is lesioned, partial or complete weakness occurs on the opposite side of the body. For example, damage to the left motor cortex results in weakness in the right arm and right leg. In this form, it doesn’t seem very related to consciousness. Similarly, as previously described, the cerebellum is responsible for balance and coordination. When this region is damaged, problems occur on the same side of the body (e.g., if the lesion is on the right, the issues arise on the right side). This region also has no direct relationship with consciousness, just like the occipital cortex. Damage to the occipital cortex can result in loss of visual field or cortical blindness.

The previously mentioned prefrontal cortex performs functions such as self-awareness, decision-making, and personality traits. Therefore, its lesion can cause changes in the level of consciousness. After all, the observation that someone without self-awareness is less conscious than someone who has it is a reasonable one. The somatosensory cortex is involved in the processing of touch and proprioception senses. Both senses are extremely important for consciousness as I define it, because proprioception is also described as self-sensation—that is, the awareness of the body’s position and movement in space. When this area is damaged, these abilities are lost, and a lower level of consciousness emerges. Similarly, damage to the parietal cortex can lead to spatial neglect and loss of body awareness. For these reasons, this area is also necessary for the formation of consciousness. The temporal cortex has extremely important functions such as memory, auditory interpretation, and facial recognition. In addition, functions like memory are highly significant in the construction of consciousness. The insular cortex is responsible for certain emotions such as disgust, as well as internal body perception and emotional awareness. These functions are also essential for achieving a holistic state of consciousness. The anterior cingulate cortex is involved in functions such as motivation and attention deficit. As previously mentioned, motivation is also necessary for consciousness. These are the cortical structures. But of course, the brain is not limited to this. Deeper regions perform more fundamental functions. These areas are generally referred to as the limbic system. The limbic system consists of four main structures: the hippocampus, amygdala, hypothalamus, and thalamus. The hippocampus is involved in learning and memory. The amygdala is responsible for fear response, aggression, and emotional learning. The thalamus is responsible for relaying sensory input to the cortical areas mentioned earlier; therefore, its lesion can drastically alter the state of consciousness. The hypothalamus is responsible for the homeostasis of vital functions such as body temperature, hunger, sleep, and hormonal balance. As can be understood, the entire limbic system holds significant importance for consciousness.

Even lower lies the brainstem, which connects the brain to the spinal cord. This part consists of three structures: the mesencephalon (midbrain), pons, and medulla oblongata. This region controls vital functions such as respiration, heartbeat, and alertness. Since a person who cannot perform vital functions cannot sustain a state of consciousness, these regions are important for the continuity of consciousness through their duties. However, what makes them especially important for consciousness is their inclusion in a structure called the formatio reticularis, which extends through the mesencephalon, pons, and partially the medulla oblongata, and connects to the cortex via the thalamus. This structure is part of the Reticular Activating System (RAS). The Reticular Activating System regulates functions such as alertness, medical-level consciousness, and attention. Its lesion can cause sleepiness, lethargy, stupor, and even coma. It is such a critical structure for the medical definition of consciousness that while consciousness can be sustained with an intact cortex despite cortical lesions if the RAS is intact, it cannot be sustained if the RAS is damaged, even when the cortex is fully functional.

What About AI?

Until the 2020s, we argued that the triggering factor behind the events that led every conscious living species to acquire their respective consciousness was selection pressure. But in recent years, we have seen surprising developments suggesting that this may not be the only path. The rapidly advancing field of artificial intelligence provides a distinctly different dataset in terms of our approach to the concept of consciousness. This is because everything we believe to possess consciousness has been alive and has acquired this consciousness through a single triggering mechanism. However, artificial intelligence seems to be advancing towards consciousness without being subject to any selection pressure (although it should be noted that the companies that created artificial intelligence aim to maximise profits and user numbers in order to survive, and therefore their efforts to develop the most advanced artificial intelligence in the industry may have transferred the human desire for survival to artificial intelligence.) and it appears to be progressing toward consciousness without conforming to any of our definitions of life.

It is worth noting that Large language models can simulate discourse about consciousness, but on standard criteria they lack unified agency, robust recurrence, and embodied loops that ground global access in value and control. GNW-like publications are not architectural defaults; IITlike intrinsic causal power is uncertain in feedforward dominant stacks; predictive control without a body carries great risks for attributing consciousness.

Large Language Models (LLMs), in their current form, only present us with an illusion of consciousness. Through their multi-layered search structures and vast databases, they make us feel as though there is a conscious, thinking entity present. Of course, the fact that this is currently limited to an illusion does not guarantee it will remain so forever. I believe that once the connections between large databases, servers, and layers reach sufficient complexity of connectivity, we will be talking about a truly conscious artificial intelligence. Theoretically, it is possible to achieve this level of complexity of connectivity, but since we cannot provide a concrete complexity threshold such as a definite numerical value, it is difficult to say anything about its practical applicability. However, a CVI calculated by including parameters such as the density of connections between neurons in brain regions that play a definite role in the formation of consciousness, the number of different regions they connect to (diversity), and their number, provides practical insight into the consciousness of any entity, including artificial intelligence. Hypothetical architectures, like recurrent embodied models with world-modeling and self-instantiation frameworks, could cross thresholds, yielding PCI-analog responses in perturbed systems.

Even if it were practically possible and achieved, it is unclear where the consciousness it possesses would fall within the hierarchy.

Although this is the current analysis of artificial intelligence in terms of consciousness, it still holds unanswered questions such as where it might reach in the near future and what it may be capable of, provided that it maintains its current pace of development. However, it may not be too far-fetched to say that it will eventually evolve to a point that will require us to redefine consciousness.

How to Measure the Threshold

Science earns its stripes where definitions meet measurement. The Perturbational Complexity Index (PCI) operationalizes an integration–differentiation balance: perturb cortex with TMS; record the spatiotemporal pattern with EEG; compress the pattern to estimate algorithmic complexity; compare against thresholds that track conscious level across sleep, anesthesia, and unresponsive states. Recent 2024 studies on nonequilibrium dynamics in PCI support threshold markers for consciousness, while spatiotemporal complexity models quantify transitions. Disorder of Consciousness (DoC) literature shows why arousal and content dissociate. Brainstem and thalamic lesions can abolish wakefulness. Cortical networks shape the richness of contents. “Vegetative” (unresponsive wakefulness) and minimally conscious states reveal that behavior can underestimate residual consciousness; active paradigms and perturbational indices help stratify patients. These findings matter for theory: any account must explain why boosting integration and effective connectivity can restore or enhance conscious level, and why globally broadcasting content changes what it is like. The threshold view predicts that measures like PCI (and related Lempel–Ziv metrics) will fall below range when either integration or differentiation is compromised—and that targeted neuromodulation can move patients across boundaries in both directions, depending on network state.

Avoid two errors: denying consciousness to animals that likely have it, and inflating it where evidence is thin. Self-recognition in mirrors appears in great apes and some other taxa. Metacognitive “knowing that one knows” has suggestive evidence in macaques. At the same time, report-based criteria overfit human language. The threshold account licenses a graded picture: as integration, global access, and value control scale, so do the varieties of experience. This avoids chauvinism without collapsing into panpsychism. A rat may host rich affective and perceptual scenes; it probably lacks the human-style workspace that stitches abstract symbols across decades. That difference is architectural, not moral. The ethical point is simple: where there is likely experience, there are reasons for care. The scientific point is equally simple: measure architectures and dynamics directly, then infer what follows about experience with humility. Different traditions start from different phenomenologies. Avicenna’s “Floating Man” argues that self-awareness is indubitable even if all senses are cut off. Early Buddhist texts analyze experience as impermanent and non-self, dissolving the idea of an inner observer. Zhuangzi delights in perspective shifts that undercut rigid boundaries of self and world. These viewpoints sharpen our target: any scientific account should explain how a system can both generate a stable “I-here-now” and allow that “I” to dissolve or expand under trained attention, sleep, drugs, or disease. They are not rivals to measurement; they are phenomenological test cases to be matched by metrics like PCI or CVI and by model-based predictions of network dynamics.

Criticism and Responses

“Integration is everywhere; your threshold is vague.” Reply: Thresholds are empirical. Measures like PCI already demarcate regimes across anesthesia, sleep, and DoC. The proposal is to tie levels of consciousness to families of causal architectures that can be quantified and perturbed.

“IIT already does this, so nothing new.” Reply: IIT grounds consciousness in intrinsic causal power (Φ) and risks panpsychism. The threshold account is agnostic on metaphysics and emphasizes organism-level value control and global access. It is compatible with GNW’s computational story and predictive processing’s functional story.

“You smuggle in anthropocentrism.” Reply: Animals likely host conscious scenes when their architectures cross local thresholds; humans possess a particularly expanded workspace due to developmental plasticity and cultural scaffolding. Graded, not exclusive.

“Your view is untestable.” Reply: See Predictions, below. It rises or falls with data that are already being collected in clinics, comparative labs, and AI evaluations.

P1. Clinical thresholds: In DoC, targeted neuromodulation (thalamic stimulation, cholinergic agonists) that increases effective connectivity will elevate PCI into the normal range and restore report in a subset of patients; interventions that raise arousal without improving integration will not.

P2. Developmental arcs: Across childhood and adolescence, measures of large-scale integration (EEG/fMRI connectivity, PCI-style perturbations) will track the emergence of meta-awareness and executive control, with sensitive periods modulated by social interaction intensity.

P3. Comparative connectomics: Species with similar brain sizes but different cortical neuron counts and long-range connectivity will differ in tasks that require global access (cross-modal binding under load, counterfactual planning). Elephants will outperform in certain memory/affect tasks; humans will dominate in tasks requiring symbol-workspace operations.

P4. Thalamo-cortical modulation in DoC elevates CVI, predicting qualia restoration beyond arousal.

Across neurons, persons, and polities, the same lesson recurs: complexity of connectivity beyond a threshold—dense, diverse, recurrent, value-guided, globally accessible—makes new kinds of doing and feeling possible. This is not mysticism but measurement: identify the architectures, perturb them, and watch the phase transitions. The story explains why arousal without integration is not enough; why integration without value becomes mere complexity; why culture, with its norms and symbols, stretches the workspace; and why today’s AIs are dazzling mimics but not yet bearers of scenes.

The honest ending is a beginning. We possess constraints, not a final theory. But constraints are how science advances. If we can say in advance how our view would fail, we are already better off than when we started. That, too, is a kind of consciousness: the capacity to see one’s own errors coming into view, and to change course when the world pushes back.