#  The Interplay Between Logical Phenomena and the Cognitive System of the
Mind

Kazem Haghnejae Azar  Mathematics Department, Faculty of Science, University
of Mohaghegh Ardabili, Ardabil, Iran<EMAIL_ADDRESS>
###### Abstract.

In this article, we employ mathematical concepts as a tool to examine the
phenomenon of consciousness experience and logical phenomena. Through our
investigation, we aim to demonstrate that our experiences, while not confined
to limitations, cannot be neatly encapsulated within a singular collection.
Our conscious experience emerges as a result of the developmental and
augmentative trajectory of our cognitive system. As our cognitive abilities
undergo refinement and advancement, our capacity for logical thinking likewise
evolves, thereby manifesting a heightened level of conscious experience. The
primary objective of this article is to embark upon a profound exploration of
the concept of logical experience, delving into the intricate process by which
these experiences are derived from our mind.

###### Key words and phrases:

Logical phenomena , Evolution of living organisms, Consciousness experience,
Cognitive science.

section.1 section.2 section.3 section.4 section.5 section.6

##  1\. Preliminaries and Introduction

To gain a comprehensive understanding of the intricate relationship between
the chemical and physical effects of the brain and the experience of
consciousness, it is indeed crucial to delve into the process of transforming
a non-living chemical substance into a living entity and the subsequent
creation of a cognitive system, see Azar (2023)[4]. The transition from non-
living matter to a living organism involves a complex series of events,
including chemical reactions, self-organization, and the emergence of
biological structures. These processes give rise to the fundamental building
blocks of life, such as proteins, nucleic acids, and membranes, which form the
basis for the intricate machinery of a living system. Within this living
entity, the creation of a cognitive system involves the organization and
integration of various components, including neural networks, sensory organs,
and information processing mechanisms. The precise mechanisms through which
consciousness arises from these physical and chemical processes remain a
subject of ongoing scientific inquiry and philosophical contemplation. By
exploring and unraveling the process of converting non-living chemical
substances into living organisms and the subsequent emergence of cognitive
systems, we can gain valuable insights into the nature of consciousness and
the intricate interplay between the physical, chemical, and cognitive aspects
of our existence. This exploration offers a pathway towards a deeper
understanding of the profound phenomena underlying consciousness and the
complex dynamics that give rise to our subjective experiences. As expounded by
Pross (2021)[60], the attainment of a sentient chemical system possessing the
capacity to evolve and adapt in order to optimize its interaction with the
environment assumes paramount importance for the augmentation of persistence.
This protracted process, unfolding over a vast expanse of time, ultimately
engendered the advent of the bacterial cell, signifying a momentous milestone
in the evolutionary trajectory towards more enduring manifestations. According
to Pascal and Pross (2023)[59], even bacteria, which represent the simplest
form of prokaryotic life, possess the ability to sense and respond to a wide
range of environmental signals. These organisms can sense their internal
conditions, coordinate with neighboring organisms, and activate complex
response systems to address ongoing challenges, see Shapiro (2007)[63].

Cognitive systems emerge through the interaction of chemical sensors within
certain compounds with the external environment and internal processes. As
this process continues, it can give rise to unique characteristics in certain
chemical compounds, resulting in the formation of living organisms. The
ongoing development of this process can lead to the emergence of organisms
with more advanced cognitive mechanisms, which we commonly refer to as the
mind. The mind encompasses a range of cognitive abilities such as perception,
memory, learning, and decision-making. These cognitive capabilities are
closely linked to the biological structure of organisms, including the
development of complex nervous systems and brain structures that support
higher-order cognitive functions. It is through the interplay of these
cognitive mechanisms and the biological structures that organisms are capable
of exhibiting more sophisticated behaviors, adapting to their environment, and
engaging in complex cognitive processes.

Indeed, the experience of consciousness can be seen as an evolutionary
development of the cognitive mechanism in living organisms. This process began
with simple living systems and may have even emerged from non-living chemical
systems. Over time, this cognitive mechanism has evolved and become more
complex, culminating in the intricate consciousness experienced by humans and
other advanced organisms. Consciousness is believed to have emerged gradually
in the course of biological evolution. It likely began in simple living
systems with rudimentary forms of perception and awareness. Even single-celled
organisms exhibit basic sensory responses and the ability to navigate their
environment, suggesting the presence of some level of consciousness. As life
forms evolved and became more complex, so did their cognitive abilities. The
development of nervous systems and the emergence of more sophisticated sensory
organs allowed for enhanced information processing and perception. This
evolutionary trajectory led to the gradual refinement and expansion of
conscious experiences.

The human brain comprises approximately one hundred billion neurons, each
establishing connections with tens of thousands of other neurons. These
connections occur through electrochemical junctions known as synapses,
enabling communication between neurons. Through this intricate network,
neurons collaborate and form interactive networks that collectively regulate
various functions of the human body, ranging from fundamental processes like
breathing to complex activities such as composing music. At any given moment,
the brain processes a vast array of sensory information and integrates it with
stored information from memory. This amalgamation of inputs allows the brain
to generate perceptions and thoughts. It is through this dynamic interplay
between sensory input and memory that our conscious experiences and cognitive
processes emerge. The brain’s ability to combine and analyze information in
real-time contributes to our capacity for perception, decision-making, and the
construction of coherent thoughts.

In essence, the brain perpetually processes an immense influx of sensory
information from the external realm. It amalgamates this incoming sensory data
with stored information retrieved from memory, giving rise to perceptions and
thoughts. This integration of sensory input and memory retrieval contributes
to our overarching cognitive experience and the formation of conscious
awareness. As elucidated by Allen (2009)[2], the brain emerges as a product
shaped by a multitude of contextual factors, encompassing the phylogenetic,
somatic, genetic, ecological, demographic, and ultimately, culturo-linguistic
dimensions within which it evolved.

The mathematical concepts employed in this article are elementary and
accessible to individuals with a basic understanding of mathematics.

##  2\. Exploring the Root of Conscious Experience

Pross and Pascal (2017) [58] expound upon a compelling argument, establishing
that chemical systems on the trajectory towards heightened dynamic kinetic
stability and the semblance of life necessitate three fundamental properties
($TFP$). Firstly, these systems must possess the remarkable ability to engage
in self-reproduction, enabling the potential transmission of their intrinsic
characteristics or information to subsequent generations. This property
engenders persistence and the propagation of the system within its
environment. Secondly, the structure of these chemical systems must exhibit
the capacity for variation. This variability allows for the exploration of
diverse possibilities, encompassing mechanisms such as mutation,
recombination, or other forms of structural rearrangements. Through structural
variation, these systems become adept at manifesting new traits or properties,
facilitating their adaptation to the ever-changing circumstances of their
existence. Lastly, the maintenance of a far-from-equilibrium state assumes
paramount importance. A continuous supply of energy is required to sustain the
system’s dynamic behavior. This energy input acts as the driving force,
propelling the system away from thermodynamic equilibrium and unveiling a
tapestry of complex, non-equilibrium behaviors.

According to the statement above, a chemical compound, referred to as
$\gamma$, has the potential to foster the development of a cognitive system
within itself given favorable environmental conditions. When exposed to
suitable energy sources, it is hypothesized that $\gamma$ can undergo a series
of chemical reactions, leading to the formation of complex structures capable
of processing information. Over time, these structures may evolve and become
increasingly sophisticated, ultimately giving rise to a rudimentary cognitive
system as $f(\gamma)$. Thus, the cognitive mechanism, $f(\gamma)$, of this
particular type of chemical component, $\gamma$, is built upon $TFP$ as self-
reproduction, structural variation, and maintenance in a far-from-equilibrium
state. These properties give rise to characteristics reminiscent of cognitive
processes, including information transmission, adaptation, and responsiveness
to environmental stimuli.

Now consider $\gamma$ as a chemical compound with the capacity to influence
cognitive mechanisms, represented by the function $f(\gamma)$. As $\gamma$
undergoes changes and evolves, we can interpret it as a representation of the
brain, while the corresponding function $f(\gamma)$ can be seen as a
representation of the mind, without loss of generality. On the other hand, by
drawing an analogy between the chemical compound $\gamma$ and its cognitive
mechanism ability function $f(\gamma)$, we can establish a parallel to the
relationship between the brain and the mind. In this analogy, the brain
corresponds to the chemical compound $\gamma$, while the mind corresponds to
the cognitive mechanism ability function $f(\gamma)$.

Pascal and Pross (2022)[53] proposes that the ideas presented support a
comprehensive approach to understanding the emergence of life. It suggests
that life originates through contingent events within a specific context,
where kinetic forces drive the development of more efficient self-reproducing
systems. However, this process is constrained by the laws of thermodynamics
and the properties of covalent bonds, particularly those involving carbon. The
paper emphasizes the essential role of organic chemistry, represented by
$\gamma$, in the origin of life process. It highlights the influence of
kinetic barriers associated with covalent bonds. Encouragingly, recent
experiments have demonstrated that simple organic compounds can exhibit
complex kinetic behavior, represented by $f(\gamma)$. According to the paper’s
viewpoint, starting with the hypothesis of an auto-organizational process
based on the kinetic properties of self-reproducing entities allows for a
semi-quantitative assessment of the environmental conditions necessary for
self-organization through organic chemistry. Notably, this assessment is
consistent with visible light as an energy source and moderate temperatures.

In their (2023)[5] paper, Azar introduced a topology for the system of the
human mind, outlining various sets that contribute to its functioning. These
sets are as follows:

$X_{1}$: Sensation set - Represents the reactivity of molecular reactions
associated with sensory input.

$X_{2}$: Primary consciousness set - Involves the initial translation and
processing of input data within the mind.

$X_{3}$: Awareness set - Encompasses knowing, perceiving, and being cognizant
of events or stimuli.

$X_{4}$: Analyzing set - Involves the review and analysis of data within the
mind.

$X_{5}$: Memory set - Represents the storage and retrieval of information and
experiences.

$X_{6}$: Character mentality and mood set - Includes emotions, moods, and
character traits that influence the mind’s state.

$X_{7}$: System components coordinator set - Serves as the central part of the
system, facilitating communication and coordination among various components.

$X_{8}$: Quality of will to accomplish an output set - Refers to the
determination and motivation to achieve desired outcomes.

$X_{9}$: Curiosity along with perception set - Involves a deep sense of
curiosity and exploration of phenomena or concepts without immediate analysis.

$X_{10}$: Other molecular, physiological, chemical, and physical conditions
set - Represents additional factors related to the molecular, physiological,
chemical, and physical aspects that influence the mind.

According that manuscript, these sets provide a framework for understanding
the different aspects and components involved in the functioning of the human
mind.

In that paper, the aforementioned components have emerged as a result of the
evolution of the $\gamma$ system. The proposed a topology for the mind
endeavors to elucidate a discernible arrangement of system components ($X_{i}$
where $1\leq i\leq 10$) that encapsulates the functioning of a system
resembling that of a human. Nevertheless, it is important to acknowledge that
simpler entities such as artificial intelligence, plants, or insects may not
possess the entirety of the aforementioned components. These aforementioned
components can be aptly described as $\gamma$ arms, which have gradually
manifested over an extensive duration. These formations are the result of
internal chemical and physical metamorphoses transpiring within the $\gamma$,
in addition to the impact of external environmental factors.

Consider the existence of a set of sensitivities within the realm of the
$\gamma$ system, represented by $X_{1}$. As time unfolds, the activities of
$X_{1}$ give rise to the emergence of secondary sensitivities within the
intricate fabric of the $\gamma$ system. These newfound sensitivities,
collectively referred to as $X_{2}$, exhibit a notable responsiveness to the
grouping of elements in $X_{1}$. Each element in $X_{2}$ manifests a distinct
sensitivity to an individual element or a collective composition of elements
from $X_{1}$, thus displaying a spectrum of sensitivities. The genesis of
$X_{2}$ can primarily be attributed to the molecular sensitivities inherent in
the essence of $\gamma$. These sensitivities, both chemical and physical in
nature, react and respond to fluctuations in the states of $X_{1}$. It is
important to note that, beyond its receptiveness to the external environment,
$X_{1}$ also demonstrates a reciprocal responsiveness to internal processes,
including those of $X_{2}$, thereby establishing an ongoing cycle. This cyclic
process paves the way for continual enhancement of the sensitivities exhibited
by both $X_{1}$ and $X_{2}$, ultimately leading to their refinement and
development.

As the process continues, a new generation of sensitizers are generated which
are sensitive to the performance and changes of $X_{2}$. An example of these
sensitizers can be represented by a category denoted as $X_{3}$. It is
important to note that all of these sensitivities are molecular, chemical, and
physical in nature, occurring within $\gamma$. The elements of $X_{3}$ exhibit
functional reactivity that depends on the changes of $X_{2}$ elements. It is
worth noting that in the process of $\gamma$ evolution, other components such
as $X_{3},X_{4},X_{5}$, etc., may arise in parallel as subsequent sensors
within $\gamma$. Consequently, the system components, including the sets
$X_{1},\cdots,X_{10}$, develop a unique sensitivity to their constituent
elements, which is refined over time. As the process continues, a one-to-one
correspondence is established between the system components. For instance, if
we consider $\gamma$ to be the brain, different frequencies of light received
by $X_{1}$ evoke varying and corresponding sensitivities in $X_{2}$, which we
perceive (or experience) as different colors. At this juncture, the chemical
composition $\gamma$ may appear to be a simple system, and we refer to it as
such. The various sensors that give rise to the system’s components ($X_{i}$,
where $1\leq i\leq 10$) are collectively referred to as ”advanced sensors of
all generations” ($ASAG$), or simply ”sensors” according to Azar’s paper
(2023)[5]. It is important to note that these sensitivities develop
incrementally due to a combination of environmental factors external to the
system and chemical and physical reactions within the system.

The root of the experience of consciousness is essentially the result of the
function of $ASAG$ which is described in detail in Azar (2023)[5]. It is
important to note that the interface between a system and its environment is
facilitated by sensors. These sensors enable the system to establish a
correspondence between its experiences and the changes and events that occur
in nature. In this process, the experience of a system is dependent on the
surrounding changes and the behavior of its sensors. It is crucial to evaluate
the reality of a system’s experience within its own context, as the perception
of reality can vary between different systems due to their diverse sensors and
components. For instance, most animals and insects are incapable of perceiving
the roundness of the Earth or its movement around the Sun because their
sensors lack the necessary capabilities. Similarly, humans face similar
limitations in comprehending certain phenomena. Our experience of light
frequencies, for example, manifests as the observation of different colors.
This phenomenon is directly related to the reactions of sensors in components
such as $X_{1}$ and $X_{2}$. If our sensors operated differently, our
experience of perceiving light would be altered accordingly. This principle
holds true for other types of experiences as well. In summary, the interface
between a system and its environment is established through sensory
mechanisms. The system’s experiences are influenced by the surrounding changes
and the behavior of its sensors. The perception of reality must be evaluated
within the context of each system, as different systems possess varying
sensors and components. This leads to different interpretations and
understandings of the surrounding world. Our experience of phenomena,
including light frequencies, is shaped by the reactions of specific sensors.

In the evolution of the cognitive mechanism, there is no clear demarcation
point that separates the transition from non-living to living organisms (Azar
(2023)[4]) or from a state without consciousness to a state with consciousness
(Azar (2023)[5, 6]). Instead, it is generally considered to be a gradual and
continuous process. The evolution of consciousness is believed to have
occurred gradually over an extended period. It is not attributed to a single
defining moment or specific genetic event but rather a cumulative result of
biological and cognitive changes over time. Simple organisms possessed basic
sensory and reactive capacities, which gradually developed into more
sophisticated cognitive abilities in complex organisms.

The fundamental elements of sensory experiences are qualia, which refer to
qualitative sensations or sense data. Qualia are considered the smallest units
of phenomenal experience. The mind utilizes these units to form a detailed
representation of the external world. The accuracy of these representations
determines the extent to which they correspond to the actual external world,
thereby constituting veridical perceptions. These states acquire their
syntactic properties by virtue of their manifestation in the brain. In other
words, qualia, or qualitative sensations, refer to the subjective aspects of
our sensory experiences. They encompass the raw, immediate qualities of
perception, such as the redness of an apple, the sweetness of sugar, or the
warmth of sunlight on our skin. Qualia are highly personal and subjective, as
they are experienced individually and cannot be directly shared or
communicated with others. They are considered the basic building blocks of our
conscious experiences. In every scientific discipline, a consistent set of
subject axioms and methods of reasoning is necessary to address the questions
and challenges within that field. If we consider qualia as the foundational
axioms for the set of conscious experiences, then the definition of these
axioms requires additional fundamental axioms that maintain consistency within
the system. When analyzing qualia, we rely on the conscious experiences of the
system, which are derived from qualia itself. As a result, certain questions
related to the thesis, such as defining the experience of consciousness within
philosophical frameworks, become difficult to answer in isolation. It becomes
necessary to integrate insights from other scientific disciplines such as
biology, mathematics, physics, or chemistry. By combining knowledge from these
diverse fields, we can gain a more comprehensive understanding of the nature
of consciousness and develop a systematic analysis that takes into account
various perspectives and empirical evidence. This interdisciplinary approach
is crucial to tackle the complex questions posed by qualia and to ensure a
more holistic understanding of conscious experiences.

##  3\. Mathematical Approaches in the Study of Consciousness Experience

Integrated Information Theory (IIT) has gained a lot of attention for
potentially explaining, fundamentally, what is the physical substrate of
consciousness. According to the IIT, consciousness is believed to emerge from
the integration of information across a highly interconnected network of
elements. The theory suggests that the extent of consciousness is directly
related to the quantity of information integrated within a given system.
Tononi (2008)[67] has been studied Integrated information and he defined the
function $\phi$ as the amount of information generated by a complex of
elements. The foundational concepts behind IIT were extremely innovative, and
it has been very exciting to see certain predictions being upheld in
experiments. It aims to describe both the quality and quantity of the
conscious experience of a physical system, such as the brain, in a particular
state. An IIT aims to specify for each system in a particular state its
conscious experience. As such, it will require a mathematical model of such
experiences. Kleiner and Tull (2020)[30] aimed to provide a comprehensive
description of both the quality and quantity of conscious experiences within a
physical system, such as the brain, in a specific state. Their contribution
focused on presenting the mathematical framework of the theory, distinguishing
the fundamental elements from auxiliary formal tools. Additionally, they put
forth a definition of a generalized Integrated Information Theory (IIT).
Numerous books and articles, including Chalmers (2003[16], 2009[17])) and
others, have been dedicated to the exploration and examination of
consciousness, as well as the quest for an exact definition of this elusive
phenomenon. These works delve into the intricacies of consciousness, exploring
its nature, properties, and theoretical frameworks in an attempt to shed light
on its fundamental aspects. Chalmers presents the hard problem of
consciousness, which refers to the challenge of explaining how and why
subjective experiences arise from physical processes in the brain. He argues
that purely physical explanations, such as those based on neuroscience, fail
to account for the subjective aspect of conscious experience. Chalmers
distinguishes between the ”easy problems” of consciousness, which involve
explaining cognitive functions like perception and attention, and the hard
problem, which focuses on the subjective experience itself. He suggests that a
satisfactory theory of consciousness must bridge the explanatory gap between
physical processes and subjective experience.

The question of defining consciousness and understanding its nature has been a
subject of deep contemplation and debate among philosophers, neuroscientists,
and cognitive scientists. While there is no universally agreed-upon definition
of consciousness, it generally refers to the subjective experience of being
aware of oneself and the surrounding world. Philosophers often ponder the
question of whether the concept of consciousness can be precisely defined. If
we entertain the idea that a comprehensive definition of consciousness is
attainable, it would inherently be an experience of consciousness in itself.
Furthermore, if such a definition were to be achieved, it would need to be
capable of encompassing and expressing the entirety of our experiences through
its inherent characteristics.

One of the challenges in defining consciousness precisely is that it is an
experiential phenomenon. Any attempt to define consciousness would inherently
involve experiencing it, which creates a circularity in the definition. In
other words, in order to define consciousness comprehensively, one would need
to have a conscious experience of that definition. Moreover, if we assume that
a comprehensive definition of consciousness is achievable, it would need to
encompass and express the entirety of our subjective experiences.
Consciousness is not limited to a single aspect or isolated phenomenon but
encompasses a wide range of mental states, perceptions, thoughts, emotions,
and sensory experiences. Any definition that aims to capture the full scope of
consciousness would need to account for these diverse aspects.

When considering this all-encompassing definition, it implies that various
phenomena can be categorized as experiences. Let’s denote the set of such
phenomena as $X=\\{A\notin A:A~{}\text{is a set}\\}$. It becomes evident that
$\\{1\\}$ and $\\{1,2\\}$ belong to $X$, suggesting that $X$ is not empty.
Now, viewing $X$ as an experience, we raise the question of whether $X\in X$
or $X\notin X$. Logically, this question should have an answer, yet none can
be found. Through mathematical analysis, I demonstrate that it is not possible
to define all of our experiences with specific characteristics. Consciousness
phenomena are not finite or quantifiable in terms of numbers. Instead, the
transition from one phenomenon to another is a continuous process,
demonstrating a cardinality comparable to that of real numbers.

In the following, we demonstrate that the occurrence of all physical signals
in the brain is unbounded. It is known that for a conscious experience in the
mind, there is at least one physical signal that occurs in the brain. Let
$\mathcal{P}$ represent the set of all physical signals occurring in the
brain, and $\mathcal{E}$ represent the set of conscious experiences in the
mind. Thus, there exists a function $\Gamma$ from $\mathcal{P}$ onto
$\mathcal{E}$ such that for any conscious experience $Y\in\mathcal{E}$, there
exists $X\in\mathcal{P}$ satisfying $\Gamma(X)=Y$. It is evident that the set
of conscious experiences in the mind is unbounded. For instance, for each
natural number $n$, there exists a conscious experience denoted as $f(n)$, and
there exists a relationship $n\longleftrightarrow f(n)$ between them. Since
the set of natural numbers is infinite, the set of conscious experiences
derived from numbers is also infinite. Thus, the occurrence of all physical
signals in the brain is unbounded. This outcome indicates that the information
stored in our memory is not constrained. Consequently, the processing and
analysis of information in our minds will not be limited.

According to the given information, we can establish a relationship between
the set of conscious experiences denoted as $\mathcal{E}$ and the
corresponding physical processes in the brain represented by $\mathcal{P}$. By
categorizing the elements of $\mathcal{P}$ that contribute to specific
experiences, we can define a function $\Gamma^{-1}$ that allows us to trace
back from an experience in $\mathcal{E}$ to the associated elements in
$\mathcal{P},$ enabling a deeper understanding of the underlying processes
involved. The set
$\Gamma^{-1}(\mathcal{E})=\\{\Gamma^{-1}(Y):Y\in\mathcal{E}\\}$ represents the
complete physical domain of the brain in relation to the set of conscious
experiences. However, it is important to acknowledge that not all physical
signals in the brain lead to conscious experiences. Consequently,
$\Gamma^{-1}(\mathcal{E})$ is a subset of $\mathcal{P}$, and it does not
encompass the entire set $\mathcal{P}$. To avoid ambiguity, we restrict the
function $\Gamma$ to its domain, and we assume that the domain of $\Gamma$,
denoted as Domain$\Gamma$, is equal to $\mathcal{P}$. Therefore, we can assume
$\Gamma^{-1}(\mathcal{E})=\mathcal{P}$. This implies that there exists a one-
to-one correspondence between the elements in $\mathcal{P}$ and $\mathcal{E}$.
For instance, if $\alpha$ symbolizes a signal interpreted as a light
frequency, it undergoes successive processing steps $X_{1}$ and $X_{2}$,
leading to the perception of a distinct color. In this context,
$\Gamma^{-1}(X_{2}(X_{1}(\alpha)))$ represents the physical processes
occurring in the brain that are linked to the perception of that specific
color.

The collection of all experiences of a complete system cannot be a set, as it
would lead to a contradiction in set theory. Assuming that $\mathcal{E}$ is
the set of all experiences of a complete system, we would have
$\mathcal{E}\in\mathcal{E}$, which contradicts the axioms of set theory. To
address this issue, we can consider an alternative approach for the collection
of system experiences. If we view all humans as a system, we know that each
individual human has a finite number of experiences within a given time
interval $[t_{1},t_{2}]$. If we define $\mathcal{E}(t)$ as the collection of
all experiences up to time $t$, then $\mathcal{E}(t)$ is finite. It becomes
evident that $\mathcal{E}(t_{1})\subseteq\mathcal{E}(t_{2})$ whenever
$t_{1}\leq t_{2}$. We can then define $\mathcal{E}$ as the union of all
$\mathcal{E}(t)$, denoted as $\mathcal{E}=\bigcup_{t}\mathcal{E}(t)$. This
implies that $\mathcal{E}$ is a countable set representing the possible
experiences of the system. By adopting this approach, we avoid the
contradiction arising from considering the collection of all experiences as a
single set and instead recognize that experiences can be organized and
categorized within a temporal framework, leading to a countable set of
potential experiences for the system.

The approach you’re describing involves defining a hierarchy of sets
$A_{0},A_{1},A_{2},\ldots$ to represent different levels of experiences. The
set $A_{0}$ consists of experiences that do not result from other experiences,
such as seeing colors, feeling pain, or hearing sounds which are called qualia
or subjective experiences. The set $A_{1}$ represents experiences that result
from the experiences in $A_{0}$, and $A_{n}$ result from the experiences in
$A_{0},A_{1},\ldots,A_{n-1}$. However, when we define
$\mathcal{E}=\cup_{i=1}^{+\infty}A_{i}$, we encounter a difficulty in treating
$\mathcal{E}$ as a set. This is because the process of taking the union of
infinitely many sets may not necessarily result in a set according to the
axioms of set theory. This issue is related to the concept of a ”set of all
sets,” which leads to paradoxes in set theory, such as Russell’s paradox. The
paradox arises when considering whether a set can contain itself as an
element. In our case, $\mathcal{E}$ would contain all sets $A_{n}$ as its
elements, including itself, which leads to a contradiction. To avoid this
paradox, one possible approach is to consider the hierarchy of sets
$A_{0},A_{1},A_{2},\ldots$ as a potential progression of experiences rather
than a set-theoretic construction. In this view, $\mathcal{E}$ would represent
the collection of all possible experiences, but it would not be treated as a
set in the traditional sense. Instead, it would be an abstract concept
denoting the entirety of possible experiences within the system. By reframing
$\mathcal{E}$ as a concept rather than a set, we can still discuss the
progression of experiences and their relationships without running into the
paradoxes associated with the set of all sets.

Assume that a function $\Gamma$ processes of our brain’s behavior to a set of
experiences $\mathcal{E}$. On the other hand the function $\Gamma^{-1}$ will
be from $\mathcal{E}$ into all of our brain’s behavior. By restricting
$\Gamma^{-1}$ to $A_{0}$, we obtain $\Gamma^{-1}(A_{0})$, which represents the
set of brain processes caused by external stimuli. Therefore, all activities
and behaviors of the brain that result in an experience can be derived from
the extension of the function $\Gamma^{-1}$ to the complete set of
experiences, denoted as $\mathcal{E}$. Additionally, based on the definition
of component $X_{2}$, it is evident that $X_{2}=A_{0}$. Consequently, if
$\mathcal{E}$ is not a set, then $X_{2}$ is also not a set. The reason for
this issue lies in the existence of different experiences originating from the
same phenomenon. For instance, perceiving the color red with varying
concentrations or imagining it in a dream can lead to distinct experiences. In
other words, the set of all possible experiences for a human system within a
given time period can have an arbitrary size. To illustrate, let’s consider
representing the colors white and black as $w$ and $b$, respectively. We can
define a function $f$ that maps the interval $[w,b]$ to the interval $[0,1]$,
where the elements of $[w,b]$ represent combinations of colors between white
and black. Specifically, $f(x)$ denotes the degree of color indicating the
proximity to white or black when $x\in[w,b]$. Function $f$ is both one-to-one
and surjective. Furthermore, we define $d(x,y)=|f(x)-f(y)|$ for any
$x,y\in[w,b]$, where $d$ represents the distance between $x$ and $y$ in terms
of color perception. It can be concluded that $f$ is an isomorphism. However,
when considering the set of all possible experiences of seeing or imagining
colors between white and black, from a mathematical standpoint, this set has a
cardinality of $c$. It is important to note that while mathematically there
may be an infinite number of possible experiences, not all of them are
attainable or realized in practice. This realization contradicts the notion of
$\mathcal{E}$, which is defined to be countable.

Let us now contemplate a scenario wherein our experiences undergo a continuous
transition from a state of near-absolute brightness to one of absolute
darkness, as exemplified by the observation of a sunset. In this particular
context, it becomes apparent that claiming to have experienced the entirety of
this period as a unified whole would be misleading. The passage of time,
specifically from the stage of complete illumination to that of complete
obscurity, assumes a pivotal role in shaping our experiences. The duration of
this transitional phase can vary significantly, spanning from mere minutes to
prolonged hours, or even extending across multiple days, thereby giving rise
to diverse individual experiences. Put differently, the nature of our
experiences, encompassing the perception of light gradually transforming into
the perception of utter darkness, hinges upon the precise timing of this
process. In essence, the unique character of our subjective encounters is
intimately intertwined with the temporal intricacies governing the transition
from luminosity to shadow.

Hence, as we traverse the realm of our experiences, it becomes increasingly
apparent that drawing a distinct boundary between darkness and light presents
itself as a formidable endeavor. In simple terms, when we witness the gradual
shift from luminosity to obscurity or vice versa, our perceptions do not lend
themselves to establishing a definitive moment of demarcation. We find
ourselves unable to pinpoint an exact point in time where we can confidently
assert that prior to a specific moment ”$t$” there existed light, and
subsequent to that moment, darkness ensued. The fluidity of this transition
defies our attempts to impose rigid divisions within the continuum of our
perceptual journey.

Indeed, as we navigate through the realm of our experiences, it becomes
increasingly apparent that delineating a clear boundary between darkness and
light proves to be a formidable task. In simple terms, when we observe the
gradual shift from luminosity to obscurity or vice versa, our perceptions do
not readily lend themselves to establishing a definitive moment of
demarcation. We find ourselves unable to pinpoint an exact point in time where
we can confidently assert that prior to a specific moment ”$t$” there existed
light, and subsequent to that moment, darkness ensued. The fluidity of this
transition defies our attempts to impose rigid divisions within the continuum
of our perceptual journey.

Within the realm of philosophical and scientific inquiry, a multitude of
scholars and thinkers embark on the quest to unravel the intricacies of human
experiences through the formulation of rules and methodologies. However, a
fundamental limitation emerges when endeavoring to comprehensively analyze a
system from within itself and establish overarching governing principles. For
the sake of argument, let us assume the existence of a comprehensive framework
designed to analyze and understand all experiences within a specific system.
We denote this framework as $\mathcal{E}$. Moreover, let us consider that
$\mathcal{E}$ represents a subset of the set encompassing all analyzable
experiences, denoted as $\mathcal{E}$.

Let’s consider $\mathcal{E}$ to represent an individual experience. In this
context, we can define the set $\mathcal{H}$ as the collection of times
denoted by $t$ when $\mathcal{E}$ does not occur, which we represent as
$\mathcal{E}(t)$. Mathematically, we can express this as follows:

$\displaystyle\mathcal{H}=\\{t:~{}\mathcal{E}\notin\mathcal{E}(t)\\}.$

It is clear that $\mathcal{H}$ is a non-empty set. Since $\mathcal{H}$ is
bounded above, we can establish its supremum as $t_{0}$. Consequently, for any
$t>t_{0}$, $\mathcal{E}$ belongs to $\mathcal{E}(t)$. Furthermore, the
creation of $\mathcal{E}$ arises from the collection of all our experiences at
time $t_{0}$, denoted as $\mathcal{E}(t_{0})$. Assuming that $\mathcal{E}$ can
analyze $\mathcal{E}$, $\mathcal{E}(t)$ can produce $\mathcal{E}$ for all
$t>t_{0}$. However, $\mathcal{E}(s)$ cannot produce $\mathcal{E}$ for all
$s<t_{0}$.

Now, let’s consider $s<t_{0}<t$. When examining the time interval $[s,t]$, we
notice that our experiences will be severely limited when $t$ and $s$ are
extremely close to each other. This leads to a contradiction in our
assumption.

##  4\. Extracting Logical and Conceptual Phenomena from Experiential Realms

Living organisms are formed through an ongoing process of chemical and
physical interactions involving specific chemical compounds. These compounds
have evolved within cognitive systems, which possess distinct characteristics
within the system of living organisms. This information is supported by the
article ”Azar (2023)[4]” and its associated sources.

Cognitive systems undergo a transformative process, transitioning between
chemical and biological states, encompassing both non-living and living
entities. These systems consist of a fusion of chemical sensors, $ASAG$ (Azar
(2023)[5, 6]), which emerge through the interplay of assessing the chemical
composition of the external environment and internal chemical and physical
processes. As a chemical compound evolves into a living organism, the
cognitive mechanism responsible for this transformation is further amplified
and refined. According to Pamela et al. (2021)[52], basal cognition refers to
the essential processes and mechanisms that enabled organisms to monitor
specific environmental conditions and respond adaptively to ensure their
survival (e.g., finding food, avoiding danger) and reproductive success long
before the emergence of complex nervous systems, let alone central nervous
systems. Basal cognition implies an inherent level of implicit familiarity or
comprehension of the connections between environmental states. In the pursuit
of enhanced thermodynamic stability, which forms the foundation for all
physical and chemical processes, one of the primary avenues is through the
well-established principles of thermodynamics. Azar (2023)[4] posits that
distinguishing between living and non-living organisms based on their
characteristics is not feasible. The transition from a non-living chemical
compound to a living entity is a continuous process without a clear
demarcation point. In their manuscript (Pascal and Pross, 2023)[53], the
authors propose that perception arises from the dynamic interplay between the
replicative system known as the Dynamic Kinetic Stability (DKS) system and its
supportive environment. The DKS system is considered a kinetic phenomenon
associated with the self-organization of life, driven by the power of
replication. Pascal and Pross argue that the DKS system, through kinetic
selection, ”learns” which variations are advantageous and which are not. This
capacity for replication allows the system to both remember and learn,
indicating a mental dimension. Consequently, the concept of DKS provides a
framework for understanding the physico-chemical basis of the mental aspects
of life.

When a system arises due to the interplay of physical and chemical factors in
its environment, the logic and regularity observed within the system are
closely intertwined with the underlying physical and chemical properties of
that environment. In simpler terms, the behavior and functioning of the
system’s components are directly influenced by the mobility and
characteristics of the surrounding environment, as well as the internal
chemical and physical reactions of the system that interact with it. As the
system interacts with its environment, it becomes attuned to the patterns and
cues present within its surroundings, perceiving a certain degree of
regularity. This perception of regularity enables the system to exhibit
intelligent adaptation and responsiveness based on the available environmental
cues. Through the interplay between the system and its environment, the system
can discern meaningful information, recognize recurring patterns, and adjust
its behaviors or internal states accordingly. This adaptation allows the
system to optimize its functioning and enhance its chances of survival or
achieving its objectives within the given environmental context. It is
important to note that the notion of intelligent adaptation and perception of
regularity does not necessarily imply conscious awareness or intentionality.
Instead, it reflects the inherent interconnectedness between the system and
its environment, where the system’s behavior emerges from the dynamic
interactions between its components and the external factors at play. This
perspective acknowledges the profound influence that the physical and chemical
properties of the environment exert on the behavior and functioning of
systems, highlighting the intricate relationship between a system’s internal
processes and its external context.

The regularity manifested within a system can be comprehended as a
correspondence or equivalency between the internal processes intrinsic to the
system and the performance exhibited by its encompassing environment. Given
that the genesis and operation of a system are subject to the influence of the
chemical and physical properties characterizing its environment, a correlation
emerges between the activities and mobility of the system itself and the
activities transpiring within the ambient milieu. Put simply, when an
individual discerns what may appear as intelligent deliberation or purposeful
reasoning in their immediate surroundings, it ensues as a consequence of the
system’s internal adaptation to the physical and chemical functions inherent
to the environment. The correspondence between the system and its chemical and
physical environment consequently engenders the perception of orderly
regularity within our environment, which may inadvertently foster the
supposition of intentional planning. To expound upon this matter with greater
precision, the intelligent mechanisms observed in natural phenomena are indeed
manifestations of the system’s correspondence with its surrounding
environment. They do not serve as indications of deliberate planning or
external intelligence. Rather, they arise from the intricate interplay between
the system and its environment, whereby the system’s behavior and adaptive
qualities emerge from its inherent properties and the influences exerted by
the encompassing physical and chemical factors.

The genesis of a system is intricately tied to the intricate web of chemical
and physical interactions unfolding within its surrounding environment. This
mode of emergence engenders a profound correspondence between the system and
its environment, setting the stage for the system’s perception and
conceptualization of regularity, which may present itself as exhibiting
intelligent reasoning. However, it is essential to recognize that the true
elucidation lies in the inherent correspondence or equivalence characterizing
the system and its environment. To illustrate this idea, let us consider a
hypothetical scenario wherein we construct an intelligent machine endowed with
the capacity to assess human behavior. As this machine observes and analyzes
our actions, it discerns a discernible regularity and logical progression,
seemingly evoking intelligent deliberation. Yet, this apparent intelligence
arises from the approximate correspondence or equivalence established between
our behavior and the internal workings of the machine itself. This
correspondence is established during the construction and design of the
machine, grounding its perception of regularity and intelligent thought.
Consequently, as the system interacts with its environment over time,
undergoing a series of physical and chemical reactions, an equivalence
relationship emerges between the functioning of the system and the intricate
dynamics of its surrounding milieu. It is within this relationship of
correspondence that the system’s perception of regularity is shaped and the
semblance of intelligent thought may manifest. In essence, the interplay of
physical and chemical processes transpiring in the system’s environment
engenders a profound equivalence with the system’s functioning. This resulting
correspondence not only shapes the system’s perception of regularity but also
gives rise to the appearance of intelligent thought, offering insights into
the intricate relationship between a system and its environment.

The order, regularity, and logical patterns that a system perceives in its
surrounding environment are a result of the equivalence relationship between
the system and its environment. This implies that there is no inherent
regularity or logic in nature itself, and the perceived regularity by a system
is a product of this equivalence. The foundation of this equivalence
relationship lies in the way systems are created. As explained earlier, the
sensitivities of a system are based on the physical and chemical behaviors of
its environment. Changes in the environment can trigger responses in the
system, making it sensitive to those changes. Some systems have sensors that
can record these changes in their memory, allowing them to compare and
recognize similar changes when detected by their sensors. In essence, the
system’s sensitivity to its environment and its ability to record and compare
changes contribute to the perception of order, regularity, and logical
conclusions within the system. This perception arises from the equivalence
established between the system and its surrounding environment.

In our daily lives, the logic we use serves as a cognitive tool that
prioritizes coherence and minimizes contradictions. Initially, we learn this
logic by observing nature, and then we refine and develop it through conscious
experiential processes. It is important to note that our focus is not on
delving into the complexities of mathematical or philosophical logic, but
rather on understanding how humans construct logical frameworks for
themselves.

According to the Section 2, we know that the dynamic kinetic stability and the
semblance of life are reliant on three fundamental properties ($TFP$). The
manifestation of characteristic $TFP$ in living organisms, spanning from
single-celled organisms to humans, is attributed to the function of $ASAG$.
The evolutionary progression of sensors has consequently influenced the
development of $TFP$, thereby enhancing the capabilities of sensors within the
systems we encounter. As a logical outcome, the processes occurring within the
system are a consequence of the chemical and physical activities involved in
the creation and evolution of $TFP$.

The presence of system consciousness enriches and reinforces this logical
process, aligning its performance with the enhancement and optimization of
$TFP$. The creation and evolution of conscious experience give rise to another
logical process that emerges from the system’s accumulated experiences.
Consequently, the logical behavior observed in primitive living organisms
lacking animal consciousness experiences can be characterized as pseudo-
logical, as it is limited to the maintenance and promotion of $TFP$ without
the additional depth and complexity brought about by conscious awareness.

The advancement of the system’s logical process occurs concurrently with the
development of the system’s conscious experience. As sensors undergo upgrading
or the system evolves along the path of $TFP$ evolution, other sensors such as
intelligence, talent, emotion, and a sense of responsibility are created. The
existing logic within the system is a consequence of the evolutionary process
of the sensors ($ASAG$) present in the system. This logic functions to uphold
and progress $TFP$. We denote this quasi-logical behavior as $L_{TFP}$.

The establishment of this logic is a common outcome across various living
organisms, arising from the interplay between their internal system and the
behavior of their surrounding environment. In this context, ”correspondence”
refers to the chemical and physical reactions occurring within the system,
which are directly influenced by the behavior of the surrounding environment.
In essence, the system’s activity is a function of the behavior exhibited by
its environment. Put differently, the chemical and physical changes taking
place within the systems have established a correspondence with their
surroundings, serving to maintain and stabilize the state of $TFP$, according
to the paper of Pross (2021)[60]. Consequently, this has contributed to the
emergence of a molecular and chemical-physical logic (or quasi-logic) within
the systems, driven by various natural forces. Indeed, the interaction of
forces and the establishment of a unique state on Earth and in the solar
system have played a role in initiating chemical and physical processes within
the system, ultimately leading to the creation of $L_{TFP}$ within the system.

The development of human conscious experience is facilitated by the emergence
and activation of new sensors within the system, see Azar (2023)[5]. As the
process of complete system consciousness unfolds, it gives rise to pseudo-
logical behavior ($L_{TFP}$), which can lead to illusions, heightened skills,
and other abilities in individuals. For instance, phenomena such as love,
falling in love, or experiencing pleasure from food can be attributed to the
development of the $L_{TFP}$ mechanism. However, the development of new
sensors can also give rise to illusions in humans and certain animals,
sometimes leading to challenges in their relationship with $L_{TFP}$. Examples
of these challenges include instances of humans engaging in harmful actions
like killing children or self-starvation due to delusional beliefs, as well as
cases of animals exhibiting self-destructive behaviors. These actions can be
attributed to the activity of newly developed sensors. Throughout history, the
occurrence of illusions in humans has increased, and this can be directly
linked to the expansion of human consciousness potential specifically, the
birth of new sensors as part of the $ASAG$ system. In this context, an
illusion refers to an emotional response to an event or internal thoughts and
feelings that are largely unrelated to the event itself or our true desires.
For instance, when a person encounters an internal or external event, they may
attribute an emotional cause to it that is not the primary cause of the event.
Furthermore, they may propose a solution to address this emotional cause that
is completely unrelated to the actual event.

The creation of new sensors within the human system leads to the formation of
additional mental images. These new images in the mind are a consequence of
upgrading the system’s sensors ($ASAG$), or more broadly, upgrading the
system’s components. This process has resulted in an improvement in the human
consciousness system. As mentioned earlier, the evolution of conscious
experience in humans has given rise to certain illusions, many of which
contradict $L_{TFP}$. These illusions arise due to the development of our
sensors, or in other words, the development of our conscious experience,
causing us to act beyond the bounds of $L_{TFP}$. The primary cause of these
illusions can be attributed to the tendency of sensors to create illusions
when receiving messages. These messages can take the form of fears related to
events or internal aspects, dreams experienced during sleep or wakefulness, or
specific feelings generated within the system by the sensors. At this stage,
the human consciousness system continually produces illusions, and individuals
live their lives based on these illusions. In some cases, individuals seek to
enhance the status of $TFP$, and this enhancement is often based on skills and
illusions. Unfortunately, as previously mentioned, negative outcomes can arise
from this pursuit. However, it is important to note that during this stage,
not only are illusions created, but human skills and abilities also grow. In
this context, illusions refer to instances where a person attributes a reason
or explanation to an experience that has little or no connection to the actual
cause of that experience. The main cause of these illusions in humans at this
stage is often due to the weaknesses of the system’s components, particularly
the weakness of the $X_{4}$ component. In some cases, illusions are passed
down to new generations by their predecessors, and intriguingly, these
individuals may possess illusions that are not effectively scrutinized by the
$X_{4}$ and other components. It is worth noting that while problems or
deficiencies in system components or illusion training can contribute to the
creation of illusions, our discussion here focuses on the natural and normal
conditions that give rise to illusions.

The development of human consciousness is intricately linked to the expansion
of social life, which, in turn, gives rise to the emergence of skills and the
evolution of components within the human system. These developments contribute
to the advancement of consciousness. Over time, a specific stage of sensor
development occurs that is unique to humans. Consequently, in conjunction with
the development of skills and empirical knowledge, the analysis component
$X_{4}$ undergoes development and begins to analyze illusions. This process of
analysis and skill improvement has led to the establishment of a logical
framework that seeks to identify the exact causes behind various phenomena. At
this stage, the acquisition of logical reasoning by humans hinges on
understanding the behaviors of nature and the relationships between different
forces and laws of nature, both in relation to each other and to humans. The
enhancement of our sensors or system components enables us to identify the
precise cause of most events. By repeatedly experiencing and observing these
events, we come to grasp the true cause-and-effect relationships that govern
them. As an example, at this stage, individuals learn that earthquakes are
caused by the movement of underground rocks along fault lines, rather than
being attributed to the anger of unseen forces or entities. This process leads
to valid arguments such as

  1. (1)

$(p_{0}\wedge\forall n(1\leq n\leq m)(p_{n-1}\Rightarrow p_{n}))\Rightarrow
p_{m}$,

  2. (2)

$(p\wedge\sim p)\Rightarrow q$,

  3. (3)

$p\Rightarrow(q\vee\sim q)$,

  4. (4)

$\forall xP(x)\Rightarrow\exists xP(x)$,

more detail see MacFarlane (2021)[44]. In the first inference of the
propositions mentioned above, $(1)$, our assumption is based on $p_{0}$. It is
important to establish the validity of $p_{0}$ and ensure that it is not
derived from other propositions or dependent on other statements. This raises
the question of how we can be confident that $p_{0}$ is indeed valid.

In the realm of logical reasoning, there are certain propositions that are
considered axioms. These propositions are typically self-evident or
universally accepted and serve as the foundation for further reasoning. They
are not derived from other propositions but are treated as valid starting
points. For instance, propositions that are equivalent to a valid statement
such as $p\vee\sim p$ (the law of excluded middle) are considered axioms.
These propositions are inherently valid based on their logical structure. On
the other hand, we cannot assert with certainty that an event will or will not
occur in a specific moment. Therefore, any proposition that leads to a
contradiction, such as $p\wedge\sim p$, is considered invalid. In summary, in
order to establish the validity of a proposition like $p_{0}$, we need to
examine its logical structure, determine if it is an axiom or derived from
axioms, and ensure that it does not lead to a contradiction. By adhering to
these principles of logical reasoning, we can evaluate the validity of
propositions and construct a reliable framework for knowledge and inference.

Indeed, many people rely on the simple logical structure outlined earlier to
assess the correctness and falsity of propositions and to avoid falling into
illusions. This logical framework, which includes principles such as the law
of excluded middle and the law of non-contradiction, is widely accepted and
serves as a basis for reasoning. However, it is important to note that some
individuals may possess knowledge of logic but still entertain delusional
thoughts. In such cases, factors such as the person’s mental state, incorrect
education, or individual personality traits can contribute to their distorted
thinking. The discussion here primarily focuses on the evolution of human
consciousness and how it relates to understanding the truth or falsity of
propositions. Discerning the truth or falsity of a proposition is indeed a
conscious experience, and our understanding of it is influenced by various
factors. When dealing with the truth or falsity of a proposition, we encounter
several other considerations. Firstly, we strive to ensure the certainty of
logical validity, which involves evaluating the logical soundness of the
proposition and its conformity to established principles. This step helps us
establish a solid foundation for our reasoning. In the second step of this
process, we aim to assess the reliability or quality of our conscious
experience. This involves examining the accuracy and consistency of our
perception, cognition, and interpretation of the proposition and its
associated information. By ensuring that our conscious experience meets
certain standards, we can enhance our ability to discern the truth or falsity
of propositions more effectively. In general, a phenomenon can be classified
as a logical phenomenon when it satisfies the following conditions:

$A_{1}$: The phenomenon is a result of natural forces operating in the world.

$A_{2}$: It is a logical consequence of the underlying natural processes
described by $A_{1}$.

$A_{3}$: The representation of this phenomenon in our conscious experience is
both accurate and comprehensive.

By meeting these criteria, a phenomenon can be considered as a logical
phenomenon, indicating that it adheres to the principles of logic and is
consistent with our understanding of the natural world. Indeed, our ability to
engage in logical reasoning and our conscious experience find their ultimate
foundation in the intricate chemical and physical processes that occur in
nature, including those within our own bodies and brains. These underlying
processes play a pivotal role in shaping various aspects of our cognition,
perception, and the functioning of neural networks. Within our bodies, complex
chemical reactions and interactions take place, enabling the transmission of
signals between neurons and the formation of synaptic connections. These
processes contribute to the establishment and modulation of neural networks
that underlie our cognitive abilities, including logical thinking.
Furthermore, our perception of the world and our conscious experiences are
shaped by the way our sensory organs detect and process various stimuli,
converting them into electrical signals that the brain interprets. The neural
processes involved in perception, attention, memory, and higher-order
cognitive functions are influenced by the underlying chemical and physical
processes occurring within our brains. By understanding the intricate
interplay between these chemical and physical processes and their impact on
our neural networks, we can gain insights into the mechanisms that govern our
logical thinking and conscious experiences. This understanding highlights the
intimate connection between the physical world, our bodies, and the cognitive
processes that give rise to our capacity for logical reasoning and conscious
awareness.

As a result, our logic is often based on natural phenomena that are readily
observable and widely accepted as axioms or foundational principles. These
phenomena serve as the building blocks of our logical frameworks and provide a
basis for making inferences. For example, principles such as cause and effect,
the conservation of energy, and the laws of mathematics are derived from our
observations of the natural world. By grounding our logic in these natural
phenomena, we establish a logical framework that aligns with our understanding
of the world and enables us to make reliable inferences. These foundational
principles, often considered axioms, offer a solid foundation for constructing
logical arguments and reasoning about various aspects of reality. However, it
is important to note that while our logic is influenced by natural phenomena,
it is also subject to refinement, expansion, and revision through ongoing
scientific inquiry and philosophical discourse. As our understanding of the
natural world advances, our logical systems may evolve to accommodate new
insights and discoveries. In summary, our logic is fundamentally connected to
the natural world and is influenced by observable phenomena. By recognizing
and utilizing these natural phenomena as axioms, we can construct logical
frameworks that facilitate accurate reasoning and inference. Nevertheless, it
remains crucial to remain open to further exploration and refinement of our
logical systems as we continue to deepen our understanding of the world.

Indeed, the logic that humans develop for themselves is shaped by a careful
examination of nature’s behavior and their own experiences. The advancement of
sensors and awareness, often referred to as $ASAG$ promotion, plays a crucial
role in facilitating this process. Our logic is primarily influenced by two
main factors:

  1. (1)

Influence of Natural Forces,

  2. (2)

Role of Conscious Experience.

By engaging with these two fundamental influences, humans develop a logic that
is informed by the forces of nature and the depth of conscious experience.
This intertwined relationship between external observations and internal
reflections allows for the continuous refinement and evolution of human logic.

In the current stage of our development, our conscious experience has the
capacity to enhance itself through the improvement of our sensory
capabilities. This upgraded conscious experience strives to construct a
logical framework that applies to both individuals and society, similar to the
principles of the $L_{TFP}$ that govern human and social systems. We can refer
to this new logic as $L_{\widehat{TFP}}$, which serves as an extension of
$L_{TFP}$.

The emergence of $L_{\widehat{TFP}}$ signifies an evolution in our logical
framework, incorporating enhanced sensory input and an expanded understanding
of the world. It allows for a more comprehensive and nuanced approach to
reasoning, inference, and decision-making. By leveraging the advancements in
our conscious experience and aligning them with the principles of $L_{TFP}$,
$L_{\widehat{TFP}}$ aims to provide a more robust and adaptable logic for
individuals and society as a whole.

The improvement of our sensors indeed plays a crucial role in the development
of this logic. Consequently, $L_{\widehat{TFP}}$ expands and further enhances
the framework provided by the pseudo-logic $L_{TFP}$.

The advancement of human consciousness, coupled with the analysis component
$X_{4}$, contributes to the examination and analysis of delusions. When we
observe or experience a phenomenon, we engage in a more precise investigation
of its underlying causes, guided by the logical process of
$L_{\widehat{TFP}}$.

Throughout this process, we strive to establish consistent axioms that explain
phenomena through logical arguments, with the aim of minimizing contradictions
and paradoxes within this logical framework. The goal is to construct a
coherent and robust system that can effectively account for the complexities
of the world while maintaining internal consistency.

By employing the logical tools provided by $L_{\widehat{TFP}}$ and utilizing
the insights gained through the advancement of our conscious experience and
sensory capabilities, we can refine our understanding of the world and address
delusions or misconceptions that may arise. This ongoing process of
examination and analysis helps to strengthen the logical foundations and
promote a more accurate and comprehensive understanding of the phenomena we
encounter.

Now consider the following three modes for the pseudo logic of living beings:

  1. $L_{1}$:

The process of maintaining and evolving the concept of $TFP$ can be described
as a quasi-logical operation denoted as $L_{TFP}$.

  2. $L_{2}$:

A quasi-logical process utilized for the preservation and development of
$TFP$, incorporating a blend of illusions and skills.

  3. $L_{3}$:

The logical process employed to uphold and enhance $TFP$ (alongside skills and
meticulous event analysis) can be represented as $L_{\widehat{TFP}}$.

In the framework of cognitive systems, the quasi-logical process denoted as
$L_{1}$ serves as a mechanism for preserving the state of $TFP$. However, in
the $L_{2}$ mode, living beings employ a quasi-logical process to maintain and
evolve $TFP$ while incorporating illusions and skills. In this mode, beings
combine logical reasoning with illusions, which can be subjective
interpretations or distortions of reality, along with skills acquired through
experience. Moving beyond $L_{2}$, the $L_{3}$ mode represents a logical
process employed to maintain and improve $TFP$. This mode encompasses both
skills and detailed analysis of events. Referred to as $L_{\widehat{TFP}}$, it
extends the previous modes by incorporating more sophisticated logical
reasoning. In $L_{3}$, systems engage in a comprehensive analysis of events
and phenomena, utilizing their skills alongside logical reasoning to enhance
and refine $TFP$.

The three modes, $L_{1}$, $L_{2}$, and $L_{3}$, represent distinct levels of
logical engagement and sophistication in the context of maintaining and
evolving $TFP$. These modes denote different stages of logical development,
reflecting the progression of human evolution. In the initial stage, $L_{1}$,
there may not have been a pronounced differentiation between the logical
states of $L_{1}$, $L_{2}$, and $L_{3}$. However, as time advanced, humans
transitioned from the $L_{2}$ mode to the $L_{3}$ mode, driven by a desire to
better understand and analyze their experiences. This shift in logic coincided
with the rise of human consciousness. It is important to note that the
progression from $L_{1}$ to $L_{3}$ does not imply a linear or exclusive
process. Instead, it signifies an overall advancement in logical capabilities,
incorporating additional elements such as illusions, skills, and detailed
analysis. These stages represent milestones in the development of human
cognition and the evolution of logical reasoning.

The degree of consciousness experience refers to the level or intensity of
awareness and subjective experience that an individual possesses. It
represents the extent to which a person is conscious of their surroundings,
thoughts, emotions, and sensory perceptions. The degree of consciousness
experience varies among different systems, for more information, please refer
to Tononi (2004)[65], Tononi and Christof (2015)[71] and Lee (2023)[41].

If we classify living organisms into distinct categories, such as humans in
one category and cats or ants in others, and denote the set of these
categories as $\Sigma$, we can establish a function $f$ that maps each living
being in $\Sigma$ to the interval $[0,+\infty)$. In this context, the value of
$f(x)$ represents the level of consciousness exhibited by the living being
$x$. This level of consciousness encompasses the cognitive abilities and
mental experiences of $x$, which contribute to its capacity for perceiving
reality and engaging in logical analysis of phenomena. Consequently, each
living being possesses a unique logic that is contingent upon its specific
degree of consciousness. To illustrate this concept, let us consider the
examples of a human ($x$) and a cat ($y)$. It is widely acknowledged that
humans, in comparison to cats, exhibit a higher level of consciousness when
confronted with various phenomena. For instance, humans possess the cognitive
ability to comprehend the precise causes of an earthquake through a particular
logical framework, whereas a cat lacks this capacity. Therefore, by virtue of
their respective degrees of consciousness, we can infer that $f(y)<f(x)$,
signifying that the degree of consciousness for a cat ($y$) is lower than that
of a human ($x$). This observation highlights the varying levels of
consciousness across different living beings, leading to distinct modes of
logic shaped by their individual cognitive capacities.

If we consider the degree of consciousness for cats and humans within the
intervals $[0,a)$ and $[0,b)$ respectively, it is evident that $a<b$.
Consequently, humans have the ability to analyze the consciousness structure
(or pseudo-logical behaviors) of cats to a significantly greater extent
compared to cats themselves. Furthermore, let’s assume that conditions $L_{2}$
and $L_{3}$ apply to humans with degrees of consciousness within the ranges
$[0,c)$ and $[0,d)$ respectively. In this case, it is clear that $c<d$. The
primary justification for the superiority of situation $L_{3}$ over $L_{2}$
lies in this distinction. Considering the entire set $\Sigma$ as comprising
humans and their ancestors, the precise differences between $L_{1}$, $L_{2}$,
and $L_{3}$ become more apparent based on the aforementioned relationships. It
is important to note that this process of logical change is a result of the
improvement in our sensory capabilities. As mentioned before, the enhancement
of our sensors stems from social life and the development of our skills. It is
worth emphasizing that our conscious experience does not undergo instantaneous
changes. Therefore, the transition from $L_{1}$ to $L_{2}$ and from $L_{2}$ to
$L_{3}$ occurs gradually over time. It is important to acknowledge that
certain factors, such as incorrect education, illness, or other issues, can
impact individuals’ mental states and potentially alter some of the
aforementioned conclusions.

When a person in the pseudo-logic state $L_{2}$ interacts or collaborates with
a person in the state $L_{3}$, establishing a common logical language becomes
essential for effective analysis of events. The process of reaching a shared
logical framework involves aligning and harmonizing their respective
perspectives, assumptions, and reasoning methods. To bridge the gap between
$L_{2}$ and $L_{3}$, the individuals involved must engage in open and
meaningful communication. They need to communicate their thoughts, ideas, and
interpretations of events to foster mutual understanding. This communication
allows them to identify areas of agreement, as well as areas of divergence, in
their logical approaches. In this process, it is crucial to recognize that the
person in state $L_{2}$ may bring unique insights and perspectives influenced
by their inclusion of illusions and acquired skills. Meanwhile, the person in
state $L_{3}$ can contribute their detailed analysis and refined logical
process. By actively listening to each other, acknowledging their differing
perspectives, and striving to find common ground, individuals in $L_{2}$ and
$L_{3}$ can work towards establishing a shared logical language. This language
acts as a foundation for evaluating and analyzing events collaboratively,
despite their initial differences in logical states. Ultimately, the goal is
to reach a comprehensive understanding that incorporates the strengths and
insights of both $L_{2}$ and $L_{3}$, leading to more nuanced and well-rounded
conclusions.

##  5\. Corollary

The structure of human thought and perception is intricately linked to its
constituent components, which collectively contribute to a diverse range of
perceptions. Our behaviors and our understanding of the environment are
significantly influenced by the functioning of these system components.
Consciousness, in my viewpoint, can be seen as the initial term that either
enters the system through sensory input or is generated by the system’s
internal components. This initial translation forms the bedrock of our
comprehension of the environment, and the efficacy of the system’s components
relies on the quality of this initial translation. The performance of
consciousness is contingent upon the capabilities of the system’s sensors to
receive and transmit information to conscious awareness. By closely examining
simpler systems such as plants, insects, or even artificial intelligence, we
can glean insights into the workings of more complex systems like the human
system. Through a thorough examination of how systems function, we can
approach philosophical inquiries concerning the human mind and our
understanding of the world with greater precision. It is essential to
acknowledge that notions of absolute reality and absolute truth lack intrinsic
meaning. The truth or falsehood of a phenomenon is intricately intertwined
with the system that processes it. In the absence of systems, concepts like
correct or incorrect propositions and real or unreal phenomena lose their
significance. It is through the existence of systems that these concepts are
created and endowed with meaning. Systems provide the framework within which
these concepts can be contemplated and understood. In summary, the structure
of human thought and perception relies on its constituent components, which
shape a range of perceptions. Consciousness serves as an initial translation
that influences our comprehension, and its performance hinges on the
capabilities of the system’s sensors. By examining simpler systems, we can
gain insights into more complex ones. Understanding systems allows us to
address philosophical questions with greater precision, recognizing that
notions of absolute reality and truth are contingent on the system processing
them. Concepts like correctness and reality derive their significance from the
existence of systems.

According to the exposition presented in this discourse, two universals emerge
as objects of intelligibility for human beings. The first universal pertains
to the world that encompasses the breadth of our experiential encounters. It
is within this realm that the fabric of our experiences is woven, and it is
our sensory apparatus that assumes the role of the creators, serving as the
vital interface between this experiential world and the second universal. The
second universal, distinct from the world of direct experience, constitutes
the domain in which our experiences reside. It is a realm that transcends the
immediate grasp of our senses, yet is accessible through the intricate
interplay of cognition. In this interplay, the potential and functionality of
our sensory apparatus assume paramount significance, as they serve as the
lynchpin connecting these two universals. Crucially, the potentiality and
functionality of our sensory system play a pivotal role in bridging the
connection between these two realms. The abilities and limitations of our
sensory apparatus determine the information we can receive and transmit,
thereby facilitating subsequent cognitive processes. It is through this
intricate interplay, facilitated by our sensory system, that we gain an
understanding of the universal and its operational mechanisms. In essence, our
comprehension of the universal and its workings hinges upon the potentiality
of our cognitive system and the flow of information mediated by our sensory
apparatus. These aspects shape our perception and enable us to navigate the
interplay between the experiential world and the realm of our experiences,
ultimately contributing to our understanding of the intricacies that underlie
our existence.

Indeed, the representation of the information received by the system as a set
$A$ and the potential of the system as $w$ allows us to conceptualize the
system’s capacity to perceive and interpret the world as a function of these
variables, denoted as $\varphi(A,w)$. This function, $\varphi(A,w)$,
encapsulates the interplay between the information encoded in the set $A$ and
the potentiality of the system represented by $w$. It determines the system’s
range of awareness and understanding of the world, delineating the boundaries
within which observations are made and conclusions are drawn. Anything beyond
this range remains inaccessible to us, as it falls outside the purview of our
perception and cognitive faculties. It is crucial to recognize that our
perception of the world, influenced by the operation of our sensory apparatus,
can undergo transformations. These transformations may manifest as the
creation or disappearance of perceptual phenomena, such as birth or death,
rain or earthquake, and so forth. However, it is important to note that these
transformations do not imply a literal creation or disappearance of the
underlying experiential universe represented by $\varphi(A,w)$. Rather, they
signify alterations or changes in our perception and experience of the world,
within the defined range determined by the function $\varphi(A,w)$. In
summary, the function $\varphi(A,w)$ captures the system’s capacity to
perceive and interpret the world, constrained by the information encoded in
$A$ and the potentiality represented by $w$. Transformations in our perception
do not imply the literal creation or disappearance of the experiential
universe, but rather reflect changes in our subjective experience within the
boundaries defined by $\varphi(A,w)$.

Throughout the evolutionary trajectory of human consciousness, distinct stages
have emerged, each characterized by its own set of transformative dynamics. In
the initial stage, as consciousness began to take shape, humans embarked upon
a journey of skill development intertwined with the presence of illusions.
Within this phase, individuals often ascribed various phenomena to their own
illusions, simultaneously honing their skills and abilities. However, as
consciousness continued to evolve, a subsequent stage unfolded—one marked by
the emergence of logical frameworks and systems. These logical systems
represented a novel facet of human experience, transcending the limitations
posed by illusions. The development of these logical systems was a direct
consequence of the expanding repertoire of skills and abilities possessed by
humans, enabling them to approach and resolve challenges in a more logical and
rational manner. Crucially, these logical systems, in a remarkable interplay,
further augmented the skills and abilities of consciousness. The symbiotic
relationship between logical systems and skill development played a pivotal
role in propelling human consciousness forward. It is within this intricate
dance of logical frameworks and skill enhancement that humans distinguish
themselves from other creatures, showcasing a unique cognitive prowess. In
essence, the progression of human consciousness entails an initial stage
characterized by the coexistence of illusions and skill development, followed
by the subsequent emergence of logical systems. These logical systems, firmly
rooted in the continued refinement of skills and abilities, then propel human
consciousness to new heights, forging a distinctive demarcation between humans
and other beings in the natural world.

In summary, cognition encompasses a complex interplay between material and
non-material aspects, influenced by a myriad of material causes. This
cognitive process also yields material consequences, both within the system
itself and in its surrounding environment. Our perception of the world is
constructed through the intricate capture and processing of images by our
sensory organs. These images, once analyzed, can give rise to the creation of
new images, forming a continuous chain of interconnected visual
representations. Emotions, reasoning, inferences, doubts, and perceptions all
manifest as diverse forms of these images, each contributing to the
multifaceted tapestry of our cognitive experience. Internal and external
projection of these images constitutes the essence of the image creation
process. The significance, rationality, or illusory nature of a phenomenon can
be understood as the manifestation of various images that emerge as a result
of preceding images. Likewise, the presence or absence of a phenomenon can be
comprehended through this same principle of image generation. The process of
image creation is intricately entwined with the influence of external and
internal physical and chemical processes within our cognitive system. These
processes play a pivotal role in shaping our cognitive experiences and the
images we perceive, forming a profound interplay between the material dynamics
of our existence and the non-material aspects of cognition.

Data availability. No data were used to support this study.

Conflicts of Interest. The authors declare that they have no conflicts of
interest.

## References

  * [1] Agozzino L, Balázsi G, Wang J, Dill KA (2020) How do cells adapt? Stories Told in Landscapes. Annu Rev Chem Biomol Eng 11:155-182. https://doi: 10.1146/annurev-chembioeng-011720-103410
  * [2] Allen JS (2009) The lives of the brain human evolution and the organ of mind, Harvard University Press.
  * [3] Ameta S, Arsène S, Foulon S, et al. (2021) Darwinian properties and their trade-offs in autocatalytic RNA reaction networks. Nat Commun 12, 842.  https://doi.org/10.1038/s41467-021-21000-1
  * [4] Azar, K.H. (2023) The quest for the definition of life. arXiv:2210.12072 [q-bio.NC], https://doi.org/10.48550/arXiv.2210.12072
  * [5] Azar, K.H. (2023) A model for conscious experience of mind. Submitted.
  * [6] Azar, K.H. (2023) The Dynamic Evolution of Cognitive Mechanisms: Unraveling the Origins of Consciousness. Submitted.
  * [7] Bartlett S, Wong ML. (2020) Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars. Life (Basel) 16;10(4):42.  https://doi: 10.3390/life10040042. PMID: 32316364
  * [8] Baum DA (2018) The origin and early evolution of life in chemical composition space. J Theor Biol. 456:295-304. https://doi: 10.1016/j.jtbi.2018.08.016
  * [9] Belthle KS, Tüysüz H (2023) Linking Catalysis in Biochemical and Geochemical CO2 Fixation at the Emergence of Life, ChemCatChem, 15(4):1-6. https://doi: 10.1002/cctc.202201462
  * [10] Birch J, Schnell AK, Clayton NS (2020) Dimensions of animal consciousness, Trends in Cognitive Sciences 24(10):789-801. https://doi.org/10.1016/j.tics.2020.07.007
  * [11] Boly M, Seth AK, Wilke M, Ingmundson P, Baars B, Laureys S, Edelman DB, Tsuchiya N (2013) Consciousness in humans and nonhuman animals: recent advances and future directions. Front. Psychol 4:1-20. https://doi.org/10.3389/fpsyg.2013.00625
  * [12] Calvo P (2017) what is it like to be a plant? J Consciousness Studies 24(9-10):205-227.
  * [13] Carruthers P, Laurence S, Stich S (2007) The innate mind: Structure and Contents (New York, 2005; online edn, Oxford Academic). https://doi.org/10.1093/acprof:oso/9780195179675.001.0001
  * [14] Carruthers P (2017) In defence of first-order representationalism. J Conscious Stud 24(5–6):74–87. http://www.jstor.org/ stable/41237 346
  * [15] Carruthers P (2019) Human and animal minds: the consciousness questions laid to rest. Oxford University Press, Oxford.
  * [16] Chalmers, DJ (2003) The content and epistemology of phenomenal belief. Consciousness: New Philosophical Perspectives. Oxford University Press.
  * [17] Chalmers, DJ (2009) The character of consciousness. Oxford University Press.
  * [18] Charlat S, Ariew A, Bourrat P, Ferreira Ruiz M, Heams T, Huneman P, Krishna S, Lachmann M, Lartillot N, Le Sergeant d’Hendecourt L, Malaterre C, Nghe P, Rajon E, Rivoire O, Smerlak M, Zeravcic Z. (2021) Natural Selection beyond Life? A Workshop Report. Life. 11(10):1051. https://doi.org/10.3390/life11101051
  * [19] Clark RE, Manns JR, Squire LR (2002) Classical conditioning, awareness, and brain systems. Trends Cogn Sci 6:524–531. https://doi.org/10.1016/ s1364- 6613(02) 02041-7
  * [20] Cleland CE , Chyba CF (2007) Does ’life’ have a definition? in Planets and Life: The Emerging Science of Astrobiology. Cambridge University Press, 119-131.
  * [21] Cleland CE (2012) Life without definitions. Synthese 185(1):125-144. https://doi.org/10.1007/s11229-011-9879-7
  * [22] Cleland CE (2019) The quest for a universal theory of life, University Printing House. Cambridge CB2 8BS, United Kingdom.
  * [23] Crick F, Koch C (1990) Towards a neurobiological theory of consciousness. Semin, Neurosci 2:263–275. http://resource.nlm.nih.gov/101584582X469
  * [24] Cooper GM (2019) The Cell: A molecular approach. Oxford University Press.
  * [25] Cornell CE, Black RA, Xue M, Litz HE, Ramsay A, Gordon M, Mileant A, Cohen ZR, Williams JA, Lee KK, Drobny GP, Keller SL. (2019) Prebiotic amino acids bind to and stabilize prebiotic fatty acid membranes (2019) Proc Natl Acad Sci 116(35):17239-17244. http://doi: 10.1073/pnas.1900275116
  * [26] Frenkel-Pintera M, Haynesa JW, Martin C, Anton S, Petrova BT, Burcara, Ramanarayanan Krishnamurthya, Nicholas V, Huda Luke J, Lemana, Williams LD (2019) Selective incorporation of proteinaceous over non- proteinaceous cationic amino acids in model prebiotic oligomerization reactions. Proc Natl Acad Sci 116(33):16338–16346. https://doi.org/10.1073/pnas.1904849116
  * [27] Greer PL, Bear DM, Lassance JM, Bloom ML, Tsukahara T, Pashkovski SL, Masuda FK, Nowlan AC, Kirchner R, Hoekstra HE, Datta SR. (2016) A family of non-GPCR chemosensors defines an alternative logic for mammalian olfaction. Cell. 165(7):1734-1748. https:// doi: 10.1016/j.cell.2016.05.001
  * [28] Jeziorski J, Brandt R, Evans JH, Campana W, Kalichman M, Thompson E, Goldstein L, Koch C, Muotri AR (2022) Brain organoids, consciousness, ethics and moral status. Semin Cell Dev Biol.144:97-102. https://doi: 10.1016/j.semcdb.2022.03.020
  * [29] Jianhui L (2019) On the definition of life. Philosophy Study 9(9):497-511. https://doi.org/10.17265/2159-5313/2019.09.001
  * [30] Kleiner J, Tull S (2020), The Mathematical Structure of Integrated Information Theory, Frontiers in Applied Mathematics Computer Science, 1-14.
  * [31] Kaklauskas A, Abraham A, Ubarte I, Kliukas R, Luksaite V, Binkyte-Veliene A, Vetloviene I, Kaklauskiene L A (2022) Review of AI cloud and edge sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States. Sensors 22:1-80.  https://doi.org/10.3390/s22207824
  * [32] Kepa R-M, Carlos B Andrés E (2017) Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems. Open Biol. Published by:Royal Society 7(4):1-10. https://doi.org/10.1098/rsob.170050
  * [33] Knuuttila T, Loettgers A (2017) What are definitions of life good for? Transdisciplinary and other definitions in astrobiology, Biology and Philosophy 32(6):1185–1203. https://doi.org/10.1007/s10539-017-9600-4
  * [34] Koch C, Tsuchiya N (2012) Attention and consciousness: related yet different. Trends Cogn. Sci 16:103–105. https://doi.org/10.1016/j.tics.2006.10.012
  * [35] Koch, C., Massimini, M., Boly, M. et al. (2016) Neural correlates of consciousness: progress and problems. Nat Rev Neurosci 17, 307–321. https://doi.org/10.1038/nrn.2016.22
  * [36] Kolb, V.M. (2016) Origins of Life: Chemical and Philosophical Approaches. Evol Biol 43, 506–515. https://doi.org/10.1007/s11692-015-9361-4
  * [37] Krämer, J. et al., (2022) Molecular probes, chemosensors, and nanosensors for optical detection of biorelevant molecules and ions in aqueous media and biofluids. Chem. Rev. 22(3): 3459–3636. https://doi.org/10.1021/acs.chemrev.1c00746
  * [38] Kristin H. Gilchrist, Laurent Giovangrandi, R.Hollis Whittington, Gregory T.A. Kovacs (2005) Sensitivity of cell-based biosensors to environmental variables, Biosensors and Bioelectronics, 20(7):1397-1406. https://doi.org/10.1016/j.bios.2004.06.007
  * [39] Lamers J, Meer TVD, Testerink C (2020) How plants sense and respond to stressful environments. Plant Physiology 182:1624–1635. https://doi: 10.1104/pp.19.01464
  * [40] Laureys S, Tononi G (2009) The neurology of consciousness cognitive neuroscience and neuropathology. Elsevier Ltd.
  * [41] Lee, A-Y (2023) Degrees of consciousness. NOÛS. 57, 553-575.  https://doi.org/10.1111/nous.12421
  * [42] Lehn J-M (2007) From supramolecular chemistry towards constitutional dynamic chemistry and adaptive chemistry Chem. Soc. Rev. 36:151-160. https://doi.org/10.1039/B616752G
  * [43] Liang W, Cheng L, Tang M (2016) Identity recognition using biological electroencephalogram sensors, Journal of Sensors, 1-10. https://doi.org/10.1155/2016/1831742
  * [44] MacFarlane J (2021) A contemporary introduction in the philosophical logic. New York, NY 10017.
  * [45] Malaterre C, Chartier JF, Beyond categorical definitions of life: a data-driven approach to assessing lifeness. Synthese 198, 4543–4572 (2021). https://doi.org/10.1007/s11229-019-02356-w
  * [46] Mallatt J, Blatt MR, Draguhn A, Robinson DG, Taiz L (2021) Debunking a myth: plant consciousness. Protoplasma 258:459–476. https://doi: 10.1007/s00709-020-01579-w
  * [47] Malaterre C, Jeancolas C, Nghe P (2022) The origin of life: what is the question? Astrobiology. 22:(7)851-862. http://doi.org/10.1089/ast.2021.0162
  * [48] Merindol R, Walther A (2017) Materials learning from life: Concepts for active, adaptive, and autonomous molecular systems. Chem. Soc. Rev. 46:55-88. https://doi.org/10.1039/C6CS00738D
  * [49] Muchowska KB, Varma SJ, Moran J, Nonenzymatic Metabolic Reactions and Life’s Origins Chemical Reviews 2020 120 (15), 7708-7744 DOI: 10.1021/acs.chemrev.0c00191
  * [50] Nani A, Manuello J, Mancuso L, Liloia D, Costa T and Cauda F (2019) The neural correlates of consciousness and attention: Two Sister Processes of the Brain. Front. Neurosci. 13:11-69. https://doi: 10.3389/fnins.2019.01169
  * [51] Nir Y, Tononi G (2010) Dreaming and the brain: from phenomenology to neurophysiology. Trend Cogn Sci 14(2):88-100. https://doi:10.1016/j.tics.2009.12.001
  * [52] Pamela, L. et al. (2021) Reframing cognition: getting down to biological basics Phil. Trans. R. Soc. B3762019075020190750 http://doi.org/10.1098/rstb.2019.0750
  * [53] Pascal R, Pross A (2022) On the Chemical Origin of Biological Cognition. Life. 12(12):1-12. https://doi.org/10.3390/life12122016
  * [54] Pascal R, Pross A, Sutherland JD (2013) Towards an evolutionary theory of the origin of life based on kinetics and thermodynamics. Open Biol. 3:130-156. https://doi.org/10.1098/rsob.130156
  * [55] Pascal R, Pross, A (2016) The logic of life. Origins of life and evolution of biospheres 46:507 -513. https://doi.org/10.1007/s11084-016-9494-1
  * [56] Pascal R, Pross A (2019) Chemistry’s kinetic dimension and the physical basis for life. Journal of Systems Chemistry 7(1):1-8.
  * [57] Polina Pavlinova, Camille N Lambert, Christophe Malaterre, Philippe Nghe (2022) Abiogenesis through gradual evolution of autocatalysis into template-based replication, FEBS letters 597(3):344-379. https://doi.org/10.1002/1873-3468.14507
  * [58] Pross A and Pascal R (2017) How and why kinetics, thermodynamics, and chemistry induce the logic of biological evolution. Beilstein J Org Chem. 13:665-674. https:/doi: 10.3762/bjoc.13.66. PMID: 28487761
  * [59] Pascal, R. and Pross, A. (2023) Mind from Matter: The Chemical Connection. Isr. J. Chem. 63(7-8), 1-7.  https://doi.org/10.1002/ijch.202300038
  * [60] Pross A. How was nature able to discover its own laws-twice? (2021) Life (Basel). 12;11(7):1-8. https://doi: 10.3390/life11070679
  * [61] Segundo-Ortin M, Calvo P (2022) Consciousness and cognition in plants. Wiley Interdiscip Rev Cogn Sci 13(2):15-78. https://doi: 10.1002/wcs.1578
  * [62] Stewart JE (2019) The origins of life: The Managed-Metabolism Hypothesis. Found Sci 24:171–195. https://doi.org/10.1007/s10699-018-9563-1
  * [63] Shapiro, J.A. (2007) Bacteria are small but not stupid: cognition, natural genetic engineering and socio-bacteriology. Stud Hist Philos Biol Biomed Sci. 38(4), 807-819. https://doi: 10.1016/j.shpsc.2007.09.010
  * [64] Slootbeek AD., van Haren MHI., Smokers IBA, Spruijt E (2022) Growth, replication and division enable evolution of coacervate protocells. Chem. Commun. 58:11183–11200. https://doi.org/10.1002/adbi.202200180
  * [65] Tononi G (2004) An information integration theory of consciousness. BMC Neurosci 42(5):1-22. https://doi.org/10.1186/1471-2202-5-42
  * [66] Tononi G (2005) Consciousness, Information integration, and the brain. Prog Brain Res 150:109–26. https://doi: 10.1016/S0079-6123(05)50009-8
  * [67] Tononi G (2008) Consciousness as integrated information: a Provisional Manifesto. Biol Bull 215(3):216–242. http://dx.doi.org/10.2307/25470707
  * [68] Tononi G (2012) The integrated information theory of consciousness: an updated account. Arch. Ital. Biol 150:56–90. http://dx.doi.org/110.4449/aib.v149i5.1388
  * [69] Tononi G (2015) Integrated information theory. Scholarpedia 10(1):41-64. http://dx.doi:10.4249/scholarpedia.4164
  * [70] Tononi G, Boly M, Massimini M, Koch C (2016) Integrated information theory: from consciousness to its physical substrate. Nat Rev Neurosci 17:450–461. https://doi.org/10.1038/nrn.2016.44
  * [71] Tononi, G. and Christof, K. (2015) Consciousness: here, there and everywhere? Phil. Trans. R. Soc. 1-18. http://doi.org/10.1098/rstb.2014.0167
  * [72] Trefil J, Morwitz HJ, Smith E (2009) The origin of life. American Scientist 97(3): 206-214. https://doi:10.1511/2009.78.206
  * [73] Trewavas A, Baluška. F, Mancuso S, Calvo. P (2020) Consciousness facilitates plant behavior. Trends Plant Sci 25:216-217. https://doi.org/10.1016/j.tplants.2019.12.015
  * [74] Trujillo CA, Muotri AR (2018) Brain organoids and the study of neurodevelopment, Trends Mol. Med. 24:982–990. https://doi.org/10.1016/j.molmed.2018.09.005
  * [75] Whitesides, G. M.; Grzybowski, B. Science 2002, 295, 2418–2421. https://doi:10.1126/science.1070821
  * [76] Ziemann AE, Allen JE, Dahdaleh NS, Drebot II, Coryell MW, Wunsch AM, Lynch CM, Faraci FM, Howard MA 3rd, Welsh MJ, Wemmie JA. (2009) The amygdala is a chemosensor that detects carbon dioxide and acidosis to elicit fear behavior, Cell 25;139(5):1012-1021. https://doi: 10.1016/j.cell.2009.10.029