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Origin of Consciousness - Integrated Information Theory (IIT)


Contents

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

Consciousness

About 2500 years ago the Chinese sage Lao Tsu (老子) complied the "Tao Te Ching" (the Book of Tao, 道德經), the very first sentence stated :
Tao "The Tao that can be told is not the eternal Tao" (道可道非常道). Since then the "Tao" has been interpreted as a statement, a theory, an extra-sensual experience, ...; while eternal often adopts the meaning of timelessness. Consciousness is neither timeless nor so sacred, but it is a very subjective feeling privileged only to its owner, it can never be described fully to an outsider similarly to the eternal Tao. 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

Figure 01 Tao [view large image]


green, dark green, dark, or anything in between; actually we will never know the "green" color 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".

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)

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 for functional) allows the association of certain brain region (with spatial resolution the size of a pea containing about one million nerve

Figure 02 Active Brain Region [view large image]


Figure 03 Neural Correlates of Consciousness [view large image]


cells) to specific mental task as shown in Figure 02 for seeing. 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 1900'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) 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". 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.

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 include the same occurrence in other big-brained, social animals; its association with the sense of self, and environmental monitoring to adjust behaviour; and the prominent size - up to 200% larger than typical human neurons.

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Integration

Integration Conscious states share a second 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 only the outlines of objects in
The Vision of MM 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

Figure 06 Information Content [view large image]

actual message out of so many possibilities. Therefore, this definition 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