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Integrated Information Theory (IIT), 2024 update


Contents

Consciousness
Neural Correlates of Consciousness (NCC) + IIT
Differentiation
Integration
Information
Effective Information
Integrated Information
Qualia Space
Prospects

Consciousness

Tao Consciousness is a very subjective feeling privileged only to its owner, it can never be described fully to an outsider. Each person taking a look at the picture in Figure 01 would evoke an unique response: it may be perceived as a beautiful scenery, or invokes a feeling of serenity, or just a boring photo, or ... depending on the wiring in the brain. On the finer level, there would also be disagreement on the hue of the trees for example, whether they are green, dark green, dark, or anything in between; actually we will never know the "greenish" experienced by someone else. We can define "green" only by referring to a third object. Simply put : consciousness is an ineffable experience. This is often referred as the "hard problem in consciousness".

Figure 01 Different Perception of A Picture [view large image]

It is because of such subjective nature of consciousness, that its study has been banished to the fringe of science for a long time. Nevertheless, there has been a number of working definitions of consciousness, and considerable knowledge has been assembled via observations and experiments about the working of the brain over the years as shown in the section called "consciousness" in this website. The information in there can be treated as its historical development. Until recently in 2008, all the models for consciousness are the descriptive variety, they assert what happen but do not explain how. That is about to change with the proposed "Integrated Information Theory" (the main subject to be discussed presently).

BTW, one more working definition : according to the concepts of self-organization and emergent phenomena, the neurons are the parts, the Neurotransmitters mimic the interactions, foods import the required energy, consciousness is the manifestation of the emergent phenomena.

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Neural Correlates of Consciousness (NCC) + IIT

Active Brain Region NCC Study of the human brain owes the fortuitous development of Magnetic Resonance Imaging (MRI) in 1973. The non-invasive scanning technology called fMRI (f stands for metabolic function, i.e., the chemical process) allows the association of certain brain region (with spatial resolution the size of a pea containing about one million nerve cells) to specific mental task as shown in Figure 02 for seeing.

Figure 02 Active Brain Region

Figure 03 Neural Correlates of Consciousness

Such image is too coarse for the concept of Neural Correlates of Consciousness (NCC), which relates consciousness to the level of individual neurons (Figure 03).

The concept of NCC was concocted by Francis Crick (1916-2004, discoverer of the structure of the DNA) and Christof Kock in the early 1990's. It is defined as the minimal neural mechanisms jointly sufficient for any one specific conscious percept. The "minimal" here stresses the fundamental base (the atom) of the hardware such as the specific synapses, neurons, and circuits that generate the consciousness. The "correlates" is used out of modesty to indicate that they are not so sure as those parts (the neurons etc.) are definitely the "causes" of consciousness. The idea has now been further expanded by the Integrated Information Theory (IIT), 2015 in the next few sections below.

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Differentiation

Differentiation The percept is always presented to its owner as a whole. There are evidences to show that this whole can be differentiated into parts with the most elementary one coming from just one neuron. It is called quale by philosophers of mind. The quale of the color red is the most basic element in such disparate percepts as seeing a red sunset, the red flag of China, arterial blood, a ruby gemstone, etc. The common denominator of all these subjective states is redness. The sensation of redness is an "intrinsic" and private experience for which nobody can share. Figure 04a depicts two visual examples : one sensory neuron in the cortex receives an electrical pulse from the Ruffini's ending in the skin and produces a sensation of heat; while another sensory neuron in the cortex generates a feeling of pressure triggered by a signal from the Pacinian Corpuscle cell in another part of the skin. This example shows that the experience is "structured" containing many different things. It is also "definite" in that only one conscious experience occurs at a time.

Figure 04a Differentiation
[view large image]


Types of Neurons In addition to the motor, sensory, and pyramidal neurons shown in Figure 04a, there are two more types known as inter and Von Economo neuron respectively (Figure 04b). An inter neuron (also called relay neuron, association neuron, connector neuron or local circuit neuron) is a neuron that forms a connection between other neurons. It can be in the spinal cord, the cortex, or cerebellum. The Von Economo neuron (VEN) was first identified in 1926 by Von Economo. It was re-discovered 80 years later to be closely associated with consciousness. These neurons make their rare appearance in two small regions : the anterior cingulate cortex (ACC) and the fronto-insular (FI) cortex (see Figure 04b) - the area for smells, flavours and other mental tasks.

Figure 04b Types of Neurons [view large image]

Circumstantial evidences indicate the same occurrence in other big-brained, social animals. It is associated with the sense of self, and environmental monitoring to adjust behavior. It comes with prominent size - up to 200% larger than typical human neurons.

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Integration

Integration Conscious states share another property of seamless "integration". As mentioned in the previous section the percept can be differentiated into parts; however these parts can never be separated. No matter how hard you try, you cannot see the world in black and white; nor can you see only part of the horse as shown falsely in a painting by Magritte (Figure 05a). It is postulated that underlying this unity of consciousness is a multitude of causal interactions among the relevant parts of the neurons. If areas of the brain become fragmented, disconnected, balkanized, as occurs under anesthesia , consciousness fades. Since there are more than 20 billion neurons in the cortex with their numerous interacting paths and changing environment, each percept is virtually unique. A very particular state is selected from countless possibilities - the essence of "information".

Figure 05a Integration
[view large image]

Integration Training Thus, although information in the environment exists in the form of raw materials with no preference for anything, humans and most animals convert them into some sort of sensations, which may not be unique among different species or even among different individuals of same species (the "hard problem in consciousness"). Data from various sources are used to modify an internally generated draft image in a time interval ~ 0.1 sec (for saving processing energy) as though they occur simultaneously (this short duration provides an opportunity for magicians to perform tricks). The brain also learns to identify the location of the sources of these data.

Figure 05b Integration Training [view large image]

Therefore, we always see an integrated image. This is particularly important for predators (misplacement means missing a meal), and preys (error in detection turns itself into dead meat).

The case of Mike May (MM) is an excellent example to illustrate the consequence of failing the integration. MM lost his sight at the age of three in a chemical accident. He went on to become a successful businessman and skilful skier (navigating the slopes by sound markers). He recovered from blindness forty three years later after two surgeries. However, the sight is not normal, he could make out
The Vision of MM only the outlines of objects in black and white without any details as shown in the insert in Figure 05c. He still has basically the same problem fifteen years later. He has difficulty with reading words and recognizing facial expressions. He has to enlist aids from the other senses to make sense of the imperfect visual perception. Figure 05c compares MM's brain activities with a normal one in seeing objects (blue) and faces (red). One explanation for the problem suggests that the seeing neural network has not stabilized at the age of three. The absence of activity in seeing allows the apparatus to be taken over by other functions such as hearing and touching - those functions useful for blind person. Thus, the sensation would becomes useless if it is not integrated properly at young age.

Figure 05c The Vision of MM [view large image]

See "Treating Blindness Takes More Than Meets The Eye" for details.

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Information

Information According to one definition of "information", the meaning of the messages is completely ignored but takes into account only the variations that is possible in the message. Figure 06 shows an example which should be very easy to understand. The image on the left portrays Bob as a dummy who can only utter Ba Ba Ba Ba to Alice. There is no variation in the message resulting in no "information content". On the other hand, the picture on the right shows Bob to possess a wonderful command of vocabulary. Alice is surprise to hear the actual message out of so many possibilities. Therefore, this definition

Figure 06 Information Content [view large image]

uses the "average amount of surprise" as its criterion. It doesn't take into account the "meaning" of the message.


Mathematically, the information I is defined as :

I = log2(n/N) ---------- (1)

where N is the number of possibilities or states and n is the number of choices. Information is at its maximum for n = 1 and N > 1 (note : larger negative value for I means more information); on the other hand, if n = N, i.e., all the possibilities are eligible, then I = 0 meaning no information. For the case of binary arrangement (such as whether the neuron is silence or firing), N = 2K and n = 2k, where K and k are the number of bits in the sample and the selection respectively. Thus, Eq.(1) is reduced to :

I = k - K ---------- (2)

For picking only one state, n =1, and k = 0. The entropy S is related to the inverse of information (with a proportional constant) :

S -I = K - k (for binary arrangement) ---------- (3)

Numerically, 1 unit of information I = -1 bit equals to an entropy S 10-16 erg/K, which is very small comparing to the entropy generated in raising 1 gram of water by 1oC at room temperature (27oC), i.e., S = 1.4x10-8 erg/K.

See more from "information" in the appendix.

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Effective Information

Effective Information Effective Information, Examples The effective information defined in the original paper of "Integrated Information Theory (IIT)" is essentially the same as those From Eqs. (1) - (3). They have introduced some terminologies that can be identified to those in the previous section such as : "a priori repertoire" = K, "a posteriori repertoire" = k. The effective information Ie is defined as :

Figure 07 Effective Information [view large image]

Figure 08 Examples
[view large image]

Ie = -I = K - k ---------- (4)
to get rid of the troublesome negative sign. It is also referred to as entropy by neglecting a proportional constant.

Figure 07 provides a detailed explanation on the idea of effective information. It is actually the information generated by the quale mentioned in the section on "differentiation". In the present context the quale is generalized to many elements in an isolated subsystem. In Figure 07 it consists of three elements (or units) with the circle in white representing an "off" state (silence), and the orange circle the "on" state. Thus K = 3 bits, and the total number of states N = 23 = 8, each one has the configuration (0, 0, 0), (0, 0, 1), ... Perturbation in the system selects the state x0 (1, 1, 0) and turns it into state x1 (0, 0, 1) via some kind of mechanism so that k = 0. Therefore effective information generated in this case is Ie = K - k = 3 bits. If the quale has only one element, then Ie = 1 bit.

Diagram A in Figure 08 shows 4 states (2 bits) are selected for the transition to the always silent state (0, 0, 0) resulting in Ie = 1. Diagram B shows the case of random firing, the prior state is irrelevant, no alternatives can be ruled out and ends up with Ie = 0.

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Integrated Information

Integrated Information When isolated subsystems combine together to form an integrated whole through causal connections, it generates lot more information and thus richer experience - the essence of integrated information. Roughly speaking, while the "a priori repertorie" K in effective information is the sum of individual elements, it is the product for the case of integrated information. Mathematically, the integrated information is defined similar to Eq.(4) :

= KI - kI ---------- (5)

where KI = k1k2k3 ... , the ki is the "a posteriori repertoire" for each of the isolated subsystem, and kI is the "a posteriori repertoire" of the integrated whole.

Figure 09 Integrated Information [view large image]

Diagram A in Figure 09 depicts two independent subsystems in partitions M1 and M2. The integrated information is 0 because there is no connection between the two.

On the other hand, Diagram B in the same Figure shows 2 connected subsystems, the "a posteriori repertoire" k of each takes on the maximum possible value since each treat the other as extrinsic noise selecting the states at random. While integrated information represents the physical side and quantification of consciousness, the mental aspect is described by the qualia space in next section.

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Qualia Space

Qualia Space The qualia space (or Q-space) is a multi-dimensional space with 2K dimensions for a system of K connected elements. Each point in the space represents a particular percept - the mental perception only experienced by its owner. It is not possible to portray such space in general intelligently. Figure 10 shows a 2-dimensional qualia space having only one element with 2 states - the 0 and 1, each coordinate is assigned numbers from 0 to 1 representing the probabilities in that state. For the case of random firing, initially each state has the probability of 1/2 (rod dot). A perturbation at time t0 transfers the element to state 1 (firing, the blue arrow) at time t1 by some kind of mechanism. In general the trajectories trail out a polytope (or crystal) in the qualia space, in which the history of our experiences is recorded. In reality, we could only remember vaguely the events in the past.

Figure 10 Qualia Space
[view large image]

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Prospects

[2024 Update]

Table 01 shows the evolution of the brain for the phyla of animals from just the detection of light (very important as source of energy) to very complicated network in human. While consciousness is rather abstract, its correlation with the brain and neural perception is un-deniable.

Animal Nervous and Sensory Brian FA (MYA)
Bateria They sense their environment through a large number of receptors, which are protein molecules embedded in the cell wall. The action taken in response to the inputs usually depends on the gradient of the chemicals. No, has chemical receptors 3600
Origin of Life
Sponges Sponges react to external light or mechanical signals with contractile or metabolic reactions and are devoid of any nervous or muscular system. However, elements of a photoreception/phototransduction system exist in those animals. No, has cryptochromes ~ 700
pre-Vendian
Cnidarians The nerve cells form a connecting network throughout the mesoglea known as the nerve net. The nerve net makes contact with the outer layer of cells, called the epidermis, and the inner layer of cells, called the gastrodermis. These cells contain contractile fibers. The first light-sensitive cells appeared in Cnidarians animals such as the jellyfish. Figure 12 illustrates the sequence of vision evolution with an insert to indicate the kind of light perception in each step. No, has Rhopalia 635
Vendian
Flatworms The planarian has a ladder-type nervous organ. There is a small brain and two lateral nerve cords joined by cross branches. Planarians show good cephalization. Aside from the brain, there are light-sensitive organs (the eyes, which do not form image) and chemosense organs. For primitive invertebrates the eyesight is blurry as shown in diagram 3 of Figure 12. It improves gradually until the image forming eyesight with the camera-type eye in human Primitive ~ 550
Vendian
Roundworms The muscles are activated by two nerves that run the length of the nematode on both the dorsal and ventral side. Unlike other animals, where the nerves branch out to the muscle cells, a nematode's muscle cells branch toward to nerves. The ventral nerve has a series of nerve centers along its length, and both nerves connect to a nerve ring and additional nerve centers located near the head. Small ~ 550
Vendian
Mollusks - Clam/Snail The clam nervous system is composed of three pairs of ganglia (anterior, foot, and posterior, which all are connected by nerves. Clam lack cephalization. The foot projects anteriorly from the shell, and by expanding the tip of the foot and pulling the body after it, the clam moves forward. Ganglion < 541
Cambrian
Mollusks - Octopus An octopus has an eye on each side of its head and has very good eyesight. It cannot hear. Octopuses can get around quite well due to the extreme sensitivity of the suckers in their tentacles. In laboratory tests, blindfolded octopuses could tell different objects apart as well as visually-unimpeded octopuses. Octopuses also have the most complex brains of any invertebrates; they quickly learn new tasks by trial-and-error, and they seem to form the same short-term and long-term memories as vertebrate animals. Research report in 2016 suggests that cephalopods may be able to perceive colors due to the un-usual construction of their eyes (see "Weird pupils let octopuses see their colorful gardens"). Yes ~ 500
Cambrian
Annelids The nervous system consists of an anterior, dorsal, ganglionic mass, or a brain, and a long ventral solid nerve cord with ganglionic swellings and lateral nerves in each segment. When invertebrates are compared to vertebrates, it often is said that the former have a ventral solid nerve cord, while the latter have a dorsal hollow nerve cord. The earthworm lacks obvious cephalization. ganglionic mass ~ small brain 541
Cambrian
Arthropods The nervous system includes a dorsal brain and a double, ventral, solid nerve cord. Such well-developed nervous system is needed to integrate the sensory information for active animal. Yes 541
Cambrian
Echinoderms
See gene-expression. 2023
The nervous system consists of a central nerve ring that supplies radial nerves to each arm. A light-sensitive eyespot is at the tip of each arm. Nerve ring 541
Cambrian
Fishes Fish see through their eyes and can detect color. Paired nostrils, or nares, in fish are used to detect odors in water and can be quite sensitive. The lateral line is a sensory organ consisting of fluid filled sacs with hair-like sensory apparatus that are open to the water through a series of pores (creating a line along the side of the fish). The lateral line primarily senses water currents and pressure, and movement in the water. Yes 541
Cambrian
Amphibians The important parts of the frog brain correspond to comparable parts in the human's. The medulla regulates automatic functions such as digestion and respiration. Body posture and muscular co-ordination are controlled by the cerebellum. The cerebrum is very small in the frog. By comparison the human cerebrum is very large. In man the cerebrum is involved in many important life processes. Only 10 cranial nerves originate in the frog's brain. Man has 12. Similarly, the frog has only 10 pairs of spinal nerves. Man has 30 pairs. Two simple holes make up the nostrils for the frog. There are complex valves but no long nasal passages as there are in man. The frog's sense of smell is registered by olfactory lobes. These make up the forward portion of the brain. The eye is crude. Its fixed lens cannot change its focus. Poorly developed eyelids do not move. To close its eye, the frog draws the organ into its socket. A third eyelid, or nictitating membrane, may be drawn over the pulled-in eyeball. There is no external ear. Both eardrums, or tympanic membranes, are exposed. There is only one bone in the frog's middle ear. The human middle ear contains three bones (malleus, incus, and stapes in the ossicles). As in man, semicircular canals help to maintain body balance. yes 419
Devonian
Reptiles Most lizards see and hear well. They have external ear openings and their eyes have movable eyelids (unlike snakes). Some lizards have a "third eye," a tiny, light-sensitive, transparent structure on top of the head that helps them regulate how long they stay in the sun. (See 3 Brains + 5 Brains) Yes 359
Carboniferous
Birds Birds have well-developed brains, but the enlarged portion seems to be the area responsible for instinctive behavior. Therefore, birds, follow very definite patterns of migration and nesting. Yes 201
Jurassic
Mammals A snout is common in animals in which a sense of smell is of primary importance. In primates, the sense of sight is more important, and the snout has shortened considerably, allowing the eyes to move to the front of the head. This resulted in three-dimensional vision, permitting primates to make accurate judgments about the distance and the position of adjoining tree limbs. Primate sense of touch became also highly developed as a result of arboreal living. It is useful as an effective feeling and grasping mechanism to grab their insect prey, and to prevent them from falling and tumbling while moving through the trees. By far the most outstanding characteristic of primate evolution has been the enlargement of the brain among members of the order. Primate brains tend to be large, heavy in proportion to body weight, and very complex.
(See Human Brains, anatomy and functions)
Yes 252
Triassic

Table 01 The Brain of Mulit-cellular Animals

The phyla of animals shown above is actually the living fossils in the evolution of the brain. The fact that they are still around today can be attributed to the principle of "Darwinian Evolution", which asserts that life exits in whatever niche available giving enough time for adoption and selection. That was a brilliant idea back in 1859. Over the intervening years, further insight about life has been accumulated as of the 21st century now.

ChatGPT has admitted that it is not like a multicellular animal brain because it doesn't have consciousness, self-awareness, emotions, memory, sensory perception, or biological imperatives. It processes language and generate responses using complex algorithms, but these processes lack the rich, dynamic nature of a living brain that experiences the world and makes decisions based on that experience. Its "thinking" is entirely mechanical, governed by data and pattern recognition, while an animal's brain is a deeply integrated biological system that operates with awareness, feelings, and the ability to interact with its environment in a meaningful way. This description also applies to Artificial intelligence (AI), which is intelligence exhibited by machines, particularly computer systems.

Anyway, they pose no threat to the existence of human because the AI systems like ChatGPT are dependent on electricity and hardware infrastructure to function. If the power is disconnected or some parts stop providing the necessary computing resources, an AI system will immediately stop working. In this sense, AI is straightforward to control since it has no autonomy beyond what is provided by its hardware and software environment.


Despite the gradual emergence of consciousness as shown in Table 01, the prevalent definition is uniquely related to human brain as suggested by ChatGPT below (in italic) :

Consciousness is a complex and multifaceted phenomenon that refers to the state of being aware of and able to think about one's own existence, sensations, thoughts, and surroundings. It involves subjective experiences, self-awareness, and the ability to perceive and respond to the environment. The nature of consciousness has been a topic of philosophical and scientific inquiry for centuries, and it remains one of the most challenging and debated aspects of the human mind. There are different perspectives on consciousness, and various theories attempt to explain its nature. Some key aspects and theories include:
1. Subjective Experience: Consciousness involves the ability to have subjective experiences, such as sensations, emotions, and thoughts. These experiences are personal and cannot be directly observed by others.
2. Self-Awareness: Conscious beings have a sense of self, meaning they are aware of their own existence and can reflect on their thoughts and actions.
3. Levels of Consciousness: Consciousness is not a binary state; rather, it exists on a continuum. There are different levels of consciousness, ranging from basic awareness to higher-order cognitive processes.
Theories of Consciousness 4. Neuroscientific Perspective: Some theories suggest that consciousness is closely tied to the brain's neural activity. The specific mechanisms and neural correlates of consciousness are areas of ongoing research.
5. Integrated Information Theory (IIT): Proposed by neuroscientist Giulio Tononi, IIT posits that consciousness arises from the integration of information within a system. It emphasizes the importance of both differentiation and integration of information in generating conscious experience.
6. Global Workspace Theory: This theory, proposed by psychologist Bernard Baars, suggests that consciousness results from the global broadcasting of information within the brain. Certain neural processes and information become accessible to multiple cognitive systems.
7. Panpsychism: A philosophical position that suggests that consciousness is a fundamental aspect of the universe and is present to some degree in all things, not just in complex organisms.

Figure 14 Theories of Consciousness

Figure 14 is taken from the 2024 article The consciousness wars: can scientists ever agree on how the mind works?"
By adopting the definition of "the ability to perceive and respond to the environment" then even plants, which are definitely aware of the temperature, moisture, ... in their surroundings, would possess consciousness.

Following is an evaluation of IIT by Copilot (a technology developed by Microsoft that combines the power of large language models (LLMs), with the Microsoft 365 apps and user data in the Microsoft Graph) in italic:

The status (credibility) of IIT is not clear-cut, as different studies have produced different results and interpretations. Some experiments have supported IIT by showing that the level of integrated information correlates with the level of consciousness in humans and animals. Other experiments have challenged IIT by showing that some systems with high integrated information, such as simple circuits or quantum systems, are unlikely to be conscious.
Moreover, some critics have argued that IIT is not a scientific theory, but a pseudo-science, because it is based on self-evident axioms that cannot be empirically tested or falsified. They also claim that IIT has problematic implications for ethics, artificial intelligence, and clinical practice, as it implies that many systems, such as organoids, stem cells, or machines, may have some degree of consciousness and moral value. Therefore, the status (credibility) of IIT depends on how one evaluates the evidence, the arguments, and the assumptions behind the theory. IIT is not widely accepted as a definitive theory of consciousness, but it is still an active and influential research program that stimulates new questions and challenges in the science and philosophy of mind.


Here are some of the literatures on IIT over the year :

2015 - Can Integrated Information Theory Explain Consciousness?
2019 - Decoding the neuroscience of consciousness
2023 - An implementation of integrated information theory in resting-state fMRI
2023 - Consciousness: why a leading theory has been branded "pseudoscience"
2023 - In defense of Integrated Information Theory (IIT)

Meanwhile, progress is being made to emulate the structure of human brain by computer (see "A new supercomputer aims to closely mimic the human brain - it could help unlock the secrets of the mind and advance AI", December 2023).

According to Copilot (in italic):

The DEEPSOUTH supercomputer is a neuromorphic system that mimics the biological processes of the human brain, such as using spiking neurons and synaptic operations. However, it is not exactly similar to the human brain, as it does not have the same structure, function, or complexity of the brain. The human brain is composed of different regions, such as the cerebrum, the brainstem, and the cerebellum, each with specific roles in controlling various aspects of the body and mind. The human brain also has billions of neurons and glial cells, which communicate through neurotransmitters and form intricate neural networks. The human brain is capable of learning, memory, emotion, creativity, and many other cognitive processes that are not fully understood by science.
The DEEPSOUTH supercomputer is designed to simulate large networks of spiking neurons at a scale comparable to the human brain, using much less power and space than traditional supercomputers. It aims to advance the understanding of the brain and develop brain-scale computing applications in various fields, such as sensing, biomedical, robotics, space, and AI. It is expected to be operational by April 2024.




[End of 2024 Update]