Chapter 5

The Wonder of Consciousness

Scope. As we stroll through our back yard on a warm summer evening and look up at the stars, we bask in awe of their infinite presence. We watch the moon rise over the hillcrest and cast its silver net throughout the valley. A warm breeze brushes past our face, and our nostrils awaken to the sweet essence of a nearby recently mowed lawn. A distant dog sounds out a warning to an unexpected visitor. As we drink in this experience with all of our senses, we are completely aware – completely conscious – of the immediate world around us. But what does it really mean to be conscious of our environment? What physiological phenomena are occurring within our being that enables us to be aware? In other words, what is consciousness?

There is probably no one quality that identifies us more explicitly as to what we are than does consciousness. Virtually everyone has an intuitive notion of what consciousness is. Is not consciousness after all that part of ourselves that goes away when we fall asleep and reappears when we awaken? Indeed this may be one manifestation of it, but consciousness itself is much more. Consciousness has been the subject of discussion among philosophers from time immemorial, and tomes have been written about it over the past three centuries since the philosophical position established by René Decartes relegated consciousness to a higher-order metaphysical plane. [1] In Decartes perspective, the mind – or consciousness – and the body – or corporeal being – were coexisting but incongruent dual entities that were not in conflict with each other. He had concluded that the realm of the mind was of such a nature that it did not lend itself to the scrutiny of scientific inquiry. Cartesian dualism dominated the worldview of consciousness until around the middle of the Nineteenth Century when the rising sciences of physiology and psychology challenged the separation of Nature and Mind. The works of William James [2] near the end of the 1800s were among the first to insist that consciousness was a process, not an isolated entity – a clear unambiguous departure from that of Decartes.

The scientific study of consciousness has experienced resurgence during the past 15 years. This renewed interest into attempting to address the question of just what is the physics of consciousness seems almost to have been a paradigm shift in the minds of those studying the cognitive sciences. Publications abound on all aspects of consciousness. Not only have several books on this subject suddenly appeared, [3-13] but journals specifically dedicated to the study of consciousness such as the Journal of Consciousness Studies and Consciousness and Cognition have been introduced, as well as have a plethora of papers. In this chapter we will discuss specific fundamental properties of consciousness and relate these properties to recent developments in understanding some of the underlying key brain mechanisms. A basic premise of this thesis – and a position also held by neurobiologic researchers – is that consciousness is real and physical; in other words, subject to the laws of physics. Numerous cognitive studies have been directed at the physics of the brain in an attempt to understand what unites that feature we call “mind” with the outside universe. There is strong evidence, for example, that quantum physics may play a very important role through a mechanism that is not yet well understood. This view is discussed later in the chapter. Much of the recent research in consciousness has been directed away from the traditional theological arguments and has focused on physics and chemistry of the brain activity itself. Hence, any metaphysical arguments will be taken as beyond the scope of what we are trying to show here. This subject is very extensive, so we need to scope it to those aspects that are relevant to this thesis; in other words, an explanation of what consciousness likely is and what brings it on. The objective of this thesis segment is not so much to study the philosophy of consciousness and the history of the evolution of thought on this subject, but instead to present an overview of what it is – or at least what it presently is believed to be from the perspective of neurobiologists who have extensively researched the physiology of the mammalian brain. We will explore its characteristics sufficiently to provide a credible basis for the assertion that the anticipated intellectual behavior expected to evolve from new complex nanoelectronic information systems is indeed emergent sentience. And this argument will build upon the wealth of discoveries recently published as products of on-going research in this area.

We are attempting to understand consciousness by synthesis. Rather than dissecting a brain into its various major components, and then further into ganglia and neurons and finally into individual molecules, we are instead putting the basic pieces of an artificial cognitive system together such that it will evolve a behavior we recognize first as consciousness, and then after a continued development as sentience. This is predicated on the premise that consciousness is a wholistic characteristic that is not a property of matter itself per se, but a manifestation of the organization of that matter. As we will discuss later, the determining principles of consciousness are that its defining physical states must be in a higher state of self-organized criticality that is likely independent of the specific properties of the individual chemistry from which it originally arose.

Characteristics of Consciousness. There are those like Chirk, Koch, and Edelman who claim that consciousness is physical, wrought from the examination of neurons, neuronal clusters, and their various interactions within the brain. By understanding the behavior of these systems, we will understand consciousness. And there are others like Rutgers University philosopher Colin McGinn who contend that because of the cognitive limitations of our brains, consciousness will remain beyond our understanding as a mystery too profound to penetrate. In the same manner that mice could never even conceive of quantum physics, consciousness would remain forever beyond our ken. While the latter argument has most interesting philosophical ramifications, the position of this thesis is the former. Consciousness, after all, exists in the physical world and is subject to the laws of physics.

Nobel Laureate Gerald Edelman, [14] suggests that there are two levels of consciousness: primary consciousness and higher-order consciousness. Primary consciousness is anchored fundamentally in biological processes capable of developing a mental scene or impression that melds together several information sources from different sensory inputs. But this impression exists only in the present temporal state and possesses neither self-awareness nor reference to its past or future, whence the title of his book, “The Remembered Present.” Higher-order consciousness, on the other hand, possesses all of the qualities of primary consciousness and more. This higher form appears to have emerged as language evolved. It can not only conceptualize past and future, but it is self-aware and can understand and reflect upon itself and its own consciousness. However, higher-order consciousness introduces nuances that are likely well beyond the scope of this thesis. Hence, the ensuing discussion will be limited to the former, or primary consciousness. The presentation of the necessary conditions for synthetic sentience need not imply a necessity for higher-order consciousness, although higher-order consciousness would indeed be a tremendous enhancement.

Obviously, consciousness is biologically useful, or it would not have evolved. For example, Crick and Koch suggest that – at least for humans – visual consciousness emerged to produce an optimal real-time single interpretation of the visual scene in light of our past experience, and this interpretation is made available to those parts of the brain responsible for the planning and executing of motor actions. [15] Survival in the environment would deem it more sensible to have a single conscious interpretation, albeit a very complex representation, so as to eliminate hesitation in a crisis. Animals fated with multiple interpretations were eaten.

Philosophers have disagreed on the nature of consciousness for centuries. Except for the perspective of Cartesian dualism, which most living philosophers no longer follow, they are still in disagreement. But philosophers are not seeking valid scientific answers. The burden of the scientific explanation has fallen most heavily onto the shoulders of the neuroscientists. And even neuroscientists themselves are not all actively studying consciousness, thinking either that it is indeed the realm of the philosopher or that it is too premature to study now as a scientific problem. Because of attitudes such as these, the study of consciousness as a science is barely over a decade old. But several researchers are nonetheless rallying to the cause and are addressing the mystery of consciousness from the perspective of scientific inquiry. With the recent availability of increasingly more capable tools such as positron emission tomography, magnetic resonance imaging, and microelectrodes, investigators are developing a much greater understanding of the most intimate of brain functions. And a few researchers, glowing from the successes of these endeavors, have been emboldened to study consciousness.

One such investigator is Francis H. C. Crick, who shared the Nobel Prize for the 1953 discovery of the structure of DNA. Crick, who has recently teamed with Christof Koch of the California Institute of Technology, rejects the tenet that consciousness can not be known. He, together with Koch, strongly suggests that only through the study of neurons and their interactions can the scientific community ever accumulate the body of unambiguous empirical knowledge necessary to produce a true scientific understanding of consciousness. Furthermore, they both strongly argue that investigations should focus on visual consciousness. The reason for this, they contend, is that the visual system itself has already been very thoroughly mapped for both humans and animals. Understanding the neurology leading to visual consciousness would lead to the understanding of more subtle phenomena.

Because vision is so dominant a sense with humans, perhaps a short discussion of some of the factors that are essential for visual consciousness would help generate insight into some of the more subtle aspects of consciousness itself. As we look at a scene, we experience a most vibrant image. Yet when we close our eyes and try to recall the same scene, we see a much less detailed image. The former is our normal conscious experience as a real-time response to our environment, although we are also conscious of recalling the memory. The memory itself, however, is much more subdued. Consciousness seems to require the existence of some form of very short-term memory, likely transient and lasting for only a few tens to hundredths of milliseconds. This transient memory, referred to as the “iconic memory,” has been well established experimentally. [16] The transience of the iconic memory is such that if attention is not paid to some element of the scene, the scene will be masked by subsequent visual stimuli. We experience this regularly when we drive the familiar route to work and can recall only fleeting moments of the trip. Yet were we to witness an accident along that same route, our recollection would be more vivid and longer lasting.

How we actually “see” a scene is quite different from what we think we are seeing. While we may think we see the whole scene clearly and in great detail, we do not. But because of our seemingly constant eye movements and the scene itself substituting as a readily available surrogate memory, it only appears that way. [17] And in regard to memory, there is evidence that working memory expands the time span of consciousness but may not be essential for it. Instead, working memory seems to function more or less as a means for delivering elements into vivid consciousness. [18]

Another factor that can enrich consciousness is visual attention, although attention itself is not necessary for visual consciousness. Attention can be derived from the environment through the senses or it can be developed from within the brain itself through thought processes. [19] And we can direct our attention to the total scene or to specific points of interest within the scene. One can see how through such attention shifts consciousness could be at least partially subject to voluntary control in the majority of real-world situations. The neurology for achieving this is not yet agreed upon as it is entwined in the understanding of the neural mechanism of attention and in the debate of how the firings of which coalition of neurons best interprets the visual scene.

But just what is actually going on inside the brain during moments of consciousness, and what is the most generally accepted theory of the mechanisms of consciousness? Although several books and papers have been dedicated to this same question, a short synopsis of the phenomenology would lend insight and perspective into the various points being made in this chapter. The general consensus of neuroscientists is that consciousness emerges through a complex array of interactions between the thalamus and cerebral cortex in what is identified as the thalamocortical system. The thalamocortical system, seen in relationship to other brain components in Figure 5.1, links to the hippocampus, the basal ganglia, and the cerebellum and correlates memory, learning, and perceptual and conceptual categorization. [14] This system is a highly integrated, layered, local synaptic structure that has adapted to rapidly receive densely packed series of multimodal signals. The thalamus itself is known to be a critical “gate” for consciousness, as bilateral damage to it will destroy waking consciousness, whereas lesions to the cortex will damage only certain portions of the conscious experience. The thalamocortical system has emerged as a more recent evolutionary development with the apparent objective of extending the range of adaptive behavior for competition in ever increasingly complex environments.

One phenomenon commonly observed by investigators is a synchronous neuronal activation during sensory input and processing. And this activity is consistent with what would be expected if perception of the external world is to arise through the neuronal actions of spatially and temporally mapping within the brain. Based on this observation, Rodolfo Llinas suggests that the intralaminar nucleus within the thalamic complex generates a temporal adjunct within the thalamocortical process that appears to be necessary for evolving conscious states. [20] His theory is based on several observations of brain physiology, but most significantly on the observation that the neurons of the intralaminar nucleus are found to be projected extensively throughout the cortex, as well as being distributed within the thalamus. Taking the visual system as a typical example, there are numerous examples of temporal “tuning” to attain synchronicity within this system to evoke synchronous responses in the thalamus. [21] Furthermore, widespread synchronicity has also been reported in the cerebral cortex. When visual-stimulus components relate to a singular cognitive object, a temporally coherent oscillation very close to 40 Hz is observed. In addition, neuronal groups that are spatially separated are bound together in time by the 40 Hz rhythm. [20] Because the 40 Hz coherent neuronal activity is generated during cognitive tasks, some researchers suggest that this also represents the resonant properties of the thalamocortical system, since 40 Hz oscillations have also been observed to be intrinsic within this system. [22] Llinas and Pare suggest that because of the high degree of spatial organization displayed by the 40-Hz oscillation, it may be responsible for producing the temporal conjunction of rhythmic activity over large neuronal groups, and this global temporal mapping would generate cognition. [23] They submit that temporally coherent inputs from both specific and nonspecific thalamic neurons at the cortical level serve to implement the binding of sensory information into a single cognitive state. Moreover, the neurons of the intralaminar nucleus mentioned above seem to have a uniquely powerful oscillation mechanism, as they generate bundles of “spikes” at the nominal 40 Hz rate, wherein each bundle comprises eight-to-ten nodes of 1000 Hz each. These “bursts” may act as the temporal binding opportunities for the thalamocortical system because of the extensive connections of the intralaminar nucleus throughout the thalamus and cortex.

The thalamic input from the cortex is much larger than is the peripheral sensory-system inputs. In the case of the visual cortex, for example, it appears that there are several times more neurons projecting downward into the visual nucleus of the thalamus than are seen going upward to the cortex. This size difference implies that the interactive thalamocortical activity is a dominant brain-function intermediary. Experiments have demonstrated that conscious visual input is highly amplified within the visual cortex, implying that these up and down looping activation cycles are able to amplify a specific sensory input at the expense of others. Also, thalamocortical neurons capable of these intrinsic oscillations enable the brain to generate other rhythmic states that shape the functional events triggered by the sensory system. The global changes in these functional states that result from changes in thalamic neuron firing modes can be fairly dramatic, such as the difference between being asleep or awake. Llinas argues that the thalamocortical system has emerged as the most efficient implementation methodology for temporal coherence across areas of the brain. He suggests that its hublike organization allows radial communication between it and everything within the cerebral cortex. [20] One major benefit of the nearly spherical configuration of the thalamocortical system is that it enables a nearly constant temporal influence to synchronize sensory inputs with internally generated responses and memories. This produces temporally coherent events, and it is this temporal coherence that unites the various fractured external and internal realities into that single entity of what we are. Temporal coherence is an extremely important construct of the brain. It not only generates the composite self as singly perceived, but it also creates the source for the brain’s predictive functions that are critical to survival. Thus one could say that the interchange between the thalamus and the cortex that produces temporally coherent binding events generates that subjectivity we call “self.”

While neuroscientists may generally agree that consciousness is physical, they are widely diverse in regard to how consciousness should be defined or how it should be studied. Crick and Koch, for instance, with their emphasis on visual consciousness – and the methodology they suggest for its study – tend to be reductionists. They suggest, for example, that a visual scene may be made up of numerous sets of small groups of neurons employing “coarse coding,” as named by Ballard et al. [24] In coarse coding a specialized set of neurons represents a specific aspect of the scene being scanned, such as the nose of a face. When the groups are all firing together at face-like objects, the full face appears. There is some evidence for the validity of this model in neural physiology where people with damaged regions of the visual cortex report seeing only partial scenes. One facet of this model that is very favorable to the direction of this thesis is that the likely number of neurons required for any one of these specialty groups, although unknown, would be small. A number on the order of 100 to 1000 would be expected, as opposed to something on the order of one to three orders of magnitude larger.

While these individual specialty groups may ultimately emerge as the correct model of how the information is transferred to the visual system, the total input must nonetheless be correlated together into a coherent scene. And this procedure requires a higher-order integration function, a process Crick and Koch refer to as the neuronal correlate of consciousness. But not everyone accepts this model. One notable dissenting voice is that of Gerald M. Edelman, who shared the 1972 Nobel Prize for antibodies research. Edelman’s approach is less reductionist and more wholistic. He argues that our awareness derives from a process wherein groups of neurons compete with each other to generate an effective interpretation of the environment. He tends to disagree with Crick and Koch’s model of specialized neuronal groups. He suggests that a fundamental property of consciousness is the rapid integration of information. And for this to occur, consciousness must be a global process and not subject to local properties of “specialized” neurons or their location within the brain. Edelman, teaming with Tononi, hypothesized the concept of the “dynamic core,” discussed below. Which model may more closely represent reality is still unknown. Because the research into consciousness is so new, the correct solution is likely to contain elements of both, coupled with characteristics different from either. This thesis tends to favor the wholistic approach suggested by Edelman, as it eliminates the need for a very large number of highly specialized neurons.

Tononi and Edelman refer to the concept of a “dynamic core” of distributed thalamocortical elements, which they define as a group of strongly interacting neurons that make up the predominant cluster of brain regions actively generating the conscious experience at the time scale during which consciousness is taking place. [25] The notion of a dynamic core is an excellent model from which to describe the various neuronal functions that participate in consciousness, and it is clearly a wholistic perspective of this process. This concept eliminates the need to identify location, local properties, anatomic connectivity, or activity level of individual neurons or specific brain regions. Instead, this model enables the brain regions that are interacting among themselves with distinct functional borders within the few hundreds of milliseconds of relevant consciousness to be characterized as a system. A major benefit of this system perspective is that it enables emphasis of both the integration aspects of consciousness and its constantly changing composition. The dynamic-core model highlights the precept that consciousness is a process – not a thing or place. Neural interactions dominate rather than specific neural locations, connectivities, or activities. The dynamic core is not localized, but instead is generally found to be metastable and spatially distributed. This concept eliminates the necessity that local neuron properties or their physical location within the brain would somehow qualify them as uniquely contributing to consciousness. Using the concept of a dynamic core as a model, and following the suggestions of William James and Tononi and Edelman, we note the following specific properties of primary consciousness:

A Process: Consciousness is a process. As William James asserted, [2] consciousness is a continuous, metastable, neural process in the thalamocortical system, although he may not have known of the thalamocortical connection in his time. Consciousness is selective and constantly changing, yet has a center and periphery. It is not a “thing.” Tononi and Edelman [25] refer to the thalamocortical system as a “dynamic core” within which the rapid integration of information occurs. This dynamic core is based less on a structure as it is on the strength of an ensemble of interactions. This strength of interactions also dominates over either local neuron properties or the locations of these neurons. The dynamic core’s temporal maintenance of its unity and metastability while its composition continually changes is indicative of a process as opposed to an entity. At any given time, specific brain areas or neuron groups may be part of the dynamic core, while other equally active areas or neuron groups are not. This phenomenon characterizes the selective nature of consciousness. In addition, neurobiologists are not only able to identify the functional borders of this dynamic core, but they can also determine whether the activity of a given neuron group is inside or outside these borders. Furthermore, these neuron groups can be ranked as to whether they are near the center or near the periphery of the dynamic core by measuring the strength of their interactions with the overall core.

Serial Nature: Consciousness is serial. If one were to consider the dynamic core of the thalamocortical system as a single system comprising a highly integrated process, then one would observe its evolution with time following a single trajectory from one global state to another, while maintaining its integration. [25] Neurobiologic researchers have indeed observed this phenomenon. The single-system characteristic of the dynamic core lends itself to a serial nature of conscious experience wherein events occur only one at a time. Experiments with dual-task tests have verified this to be the case. In a discussion of the psychological “refractory period,” Everitt has demonstrated that conscious discriminations take place one at a time. [26] Furthermore, the time required to complete these discriminations is approximately 150 milliseconds, the time also required for conscious integration. A division of the conscious stream into multiple components to perform simultaneous parallel functions would sacrifice the integration presently experienced between parallel processes, and this approach may be less desirable when considering species adaptation and survival. Clinical observations of such a functional split have been observed in some major physiological trauma such as neurologic disconnections.

Unity and Subjectivity: Consciousness is coherent, yet subjective. Because of the strong internal cohesion resulting from the highly integrated dynamic core of the thalamocortical system, any local changes would experience a global impact, hence indicating a system unity. This effect is further reinforced by observing that the various elements within the dynamic core integrate information among themselves more so than they do with their environment. Changes that take place inside the core have an immediate and significant influence on the total core, whereas outside changes have much less effect. The net result is the establishment of a functional border between the core’s informational states and the environment that renders the internal core states as subjective or “private.” This subjective discrimination associated with each of the many different conscious states is but one of the dynamic core’s internal states that affect the temporal evolution of the core itself. In other words, the system itself can discriminate these states internally, or subjectively. Furthermore, as the dynamic core increases in complexity, the number of states having discriminable functional consequences on its temporal evolution increases.

Massive Integration: Consciousness is a product of massive integrations. The concept of neural complexity discussed in Chapter 4 addresses and reinforces the intuitive notion of integration within a neural system. When a neural system is isolated and when the differences that a change in one subset state makes on the remaining system are considered in light of all of the system subsets, the neural complexity model avoids ambiguities inherent with the introduction of codes, symbols, or external observers. Furthermore, the model also avoids any ambiguity with the notion of integration occurring in only one place. In addition, loss of consciousness manifested by neural states demonstrating slow-wave sleep or generalized epilepsy can also be characterized by the concept of neural complexity. In these states functional specialization begins to disappear, resulting in a dramatic loss of integrated information. Although these states are highly integrated, they possess very little information and hence have very low neural complexity.

Coherent: Consciousness is a coherent process. In the earlier chapter on complexity, we discussed information integration and how it can occur among functionally segregated groups of neurons through a process called "reentry." Reentry, as defined by Edelman, [14] is “a process of temporally ongoing parallel signaling between separate maps along ordered anatomical connections.” Through this process, multiple sources of information join to produce a unified behavioral output. For visual consciousness, for example, this process manifests itself as a coherent, unified scene. This coherence, which is a typical characteristic of a conscious impression, is a natural result of global interactions. And the system dynamics favor only those mutually consistent and stable interactions.

Rapid Integration: Consciousness experience is very rapid. The integration of information occurs very quickly for consciousness. This integration time is typically within a few hundreds of milliseconds. Experimental models have confirmed that corticocortical and thalamocortical connection reentry is sufficiently fast to assure that integration of information indeed does occur. Because of the longer observation periods typically required to estimate neural complexity from mutual information,[1] a satisfactory theoretical limit for the measurement of the integration of information is not readily available. The determination of the integration of information over shorter time periods likely will require a different approach, such as one derived from dynamic system theory.

High Complexity: Consciousness is enormously intricate with inherent high complexity, implying an efficient and wide distribution of information among the system elements. A complex neural system is characterized by maximized mutual information between any subset and the remaining system. In other words, activity changes for any subset are maximally distributed to the remaining system. But on the other hand, for a system such as this, the different states of the total system have a very sensitive influence on the activity of each individual subset. Corticocortical and thalamocortical reentry ensures the wide distribution of information, which in turn facilitates distant brain-region interactions.

Global: Consciousness has global access. The information within consciousness is widely distributed. There are two independent correlations to the ability of consciousness information to access different outputs. First, there is access to many states within the same dynamic core, and second, each dynamic core has access to other brain processes. A core possessing high complexity has many functionally discriminable states, each of which influences the core’s function. Accessibility of a specific state depends upon a given state in which the core originally resided and upon the triggering action of the external stimulus. Consciousness can access many different brain functions, and this leads to cooperative interactions among these brain regions. The resulting emergence of a dynamic core greatly increases the ability and effectiveness to access other groups of neurons within the brain. This phenomenon reinforces the observed role that consciousness plays in biofeedback training. [27]

Adaptive: Consciousness is adaptive. As a product of evolution, it is very flexible and is capable of responding to and learning unexpected associations. The dynamic nature of integration and its inherent nonlinearity render consciousness the ability to “relate the unrelated” by associating sensory information from dispersive sources and different temporal references. The maximized interaction among neuronal groups brings about dynamic new associations through the most subtle changes in different brain-region activity. This characteristic is undoubtedly a survival mechanism that has evolved to enable self-preservation for animals facing an open-ended environment.

Quantum Consciousness. While the above properties may relate to what consciousness is, they are frustratingly devoid of explaining how consciousness comes into being. In other words, what precipitates the action that causes consciousness to emerge in the first place? This question is the subject of intense research, and widely disparate hypotheses have been offered. But perhaps one of the most intriguing of these hypotheses is the postulation that consciousness may be the direct result of interacting quantum phenomena - in other words, consciousness may come into being because of quantum physics. This theory is very compelling. Interestingly, the idea of a possible connection between consciousness and quantum physics is not really new. Suggestions of such a possibility can be traced to at least the 1930s from physicist Sir James Jeans [28] and from biologist Alfred Lotka. [29] Yet the idea of such a possibility is most intriguing. If there is indeed a wholistic characteristic to consciousness rendering it unexplainable from a reductionist perspective with traits that are elusive to classical physics, then might some precept derived from quantum physics be offered as an explanation? The emergence of consciousness from within the environment dominated by the complexity of neural interconnections brings with it a veil of mystery bordering on the metaphysical that is not readily explained by classical physics. The underpinnings of quantum physics are also mysterious and counterintuitive. For instance, a single particle such as a photon can generate an interference fringe with itself, implying it exists in two places simultaneously. How is that possible? Yet it is very real. Faced with such dual mysteries, might one (quantum physics) help explain the other (consciousness)? Several researchers have suggested that quantum coherence may be a plausible candidate for providing the global "resonance" required to induce consciousness, and one such theory is discussed below.

Because quantum coherence is critical to the ensuing discussion, it is important to understand what it is. Quantum coherence refers to a property that matter (and energy) exhibit when it remains "unmeasured," thus enabling it to exist simultaneously in more than one state. This existence in multiple states is called superposition. The system is coherent until a measurement is actually made. During coherence, a wave function describes all possibilities of the system - including past and future states, and these possibilities are both true and false. Any interaction with the system constitutes a measurement, and any measurement causes the wave front to collapse and the state to be determined. A manifestation of quantum coherence is the phenomenon wherein multiple particles or components share the same wave function and essentially behave as a single particle or wave.

Critics of these speculations, of course, find numerous equally compelling counter arguments. But the congruence of the quantum-consciousness duality is too compelling to dismiss and warrants further discussion.

Although several people have suggested a correlation between consciousness and quantum physics, [30-34] the foremost champion of this paradigm is Oxford University's Roger Penrose, and his book "Shadows of the Mind," [33] a follow-on to his earlier work "The Emperor's New Mind," [34] has arguably received the most attention recently. His publication of these two books, especially "Shadows of the Mind," has spurred a resurgence of interest in the possible connection between quantum physics and consciousness. Penrose maintains that there is more to intelligence and consciousness than is obtainable by strictly computational means, and representations through digital-computer models scoped solely within the paradigm of classical physics are found wanting. As a long-time critic of the approach and goals of artificial intelligence, he submits that there are qualities of intelligence that will defy interpretation if investigations continue to be sought along the lines being pursued. The goal of understanding these qualities can not be reached with the present mindset. However, he does offer an alternative in the embodiment of a very credible explanation of how consciousness is created.

This explanation comes from his examination of cell cytoskeletons, including neurons, and the microtubules of which they are comprised. A microtubule is a minute hollow cylindrical structure with an outer diameter of approximately 25 nanometers and an inner diameter of around 14 nanometers. The microtubule is further made up of a protein called tubulin, and specifically each microtubule is composed of thirteen columns of tubulin dimers. The dimensions of each tubulin dimer are on the order of eight nanometers by four nanometers by four nanometers, and they can exist in either of two different states (alpha or beta) depending upon the position of a single electron. Figure 5.2 shows a distribution of microtubules within a neuron. A further breakdown of the microtubule showing the tubulins comprising them can be seen in Figure 5.3. The crystal-like lattice structure of the microtubule with its hollow inner core and organized cell function possesses an inherent capacity for information processing that is remarkably suitable for quantum events. And Penrose postulates that there is indeed such an interaction between quantum coherence and the tubulins within the microtubules. He suggests that there is some form of "quantum computing" that occurs within the microtubule tubulins that creates a condition that precipitates consciousness. He argues that quantum coherence grows until a critical threshold related to quantum gravity is reached. At this threshold the coherence abruptly self-collapses. The hypothesis of this postulate is that sequences of these self-collapses create a flow of time and consciousness. An observation of particular relevance to this thesis, and one that may lend further credibility to these arguments, is that the feature sizes of the microtubules and tubulins are all well below the 100 nanometers that identify the regime of nanotechnology. Quantum effects would be expected at these dimensions.

Penrose teamed with University of Arizona's Stuart Hameroff who for some time before Penrose's presentation had also been studying microtubules as potentially having information processing capabilities. [35] Together, they produced a model for consciousness involving an orchestrated objective reduction of quantum coherence in the microtubules of neurons. [36] "Objective reduction" is defined as the physical phenomenon of quantum wave-function self-collapse and was first proposed by Penrose in "Shadows of the Mind." The model of objective reduction as being a self-collapse differs from the random reduction of standard quantum theory caused by the "entanglement" of an observation when an observer interacts with the system and hence "measures" it. The conformational states of the tubulins couple to internal quantum events and cooperatively interact in a self-organizing manner with other tubulins. Coherent quantum superposition of the coupled-tubulin conformational states occurs macroscopically by involving a sufficient population of neurons to provide the global binding required of consciousness. Since objective reduction is a self-collapse, unique patterns of microtubule-tubulin conformational states result that regulate neuronal activities. The emergence of microtubule quantum coherence is equated with pre-conscious processing, which builds until the mass-energy difference among the separated states reaches it critical threshold and self-collapses. If one considers the possibility that attachment of microtubule-associated proteins could act as self-organizing nodes that somehow tune the quantum oscillations of post-reduction tubulin states, then a self-tuning orchestrated reduction would occur. This self-tuning objective reduction process is referred to as the Penrose-Hameroff model of "orchestrated objective reduction."

Let us look at this model in more detail. In this model, quantum superposition and quantum computation are suggested to occur within the microtubules that form the neuronal cytoskeletons. The conformational status of the tubulin subunits comprising each microtubule is sensitive to internal quantum events and act as qubits for quantum computing. The tubulin qubits switch between their two possible states within a nanosecond (10^-9 second) as governed by these quantum forces (specifically the weakest but most numerous and influential Van der Waal forces within a protein structure, the "induced dipole-induced dipole" London forces). The tubulin qubits then interact computationally by nonlocal quantum entanglement in accordance with the Schrodinger equation.[2] This preconscious processing continues until the objective threshold is reached, as determined by the quantum gravity function. Quantum gravity can be thought of as the gravitational self-energy of the superimposed mass separated from itself. It is represented in equation form as Planck's constant divided by the product of 2p and the coherence time. The coherence time is the time from initiation to collapse. The collapse itself, which is the objective reduction, is an actual event in space-time geometry. If this event were to occur at a time sequence coincidental with known neurophysiological processes, then a moment of awareness or consciousness would occur. Required time scales would be on the order of tens to hundreds of milliseconds. Hameroff and Penrose have estimated that 2 x 10¹⁰ tubulins are required to accomplish the 25-millisecond coherence time necessary to produce the 40-Hz thalamo-cortical oscillation "stream of consciousness" described by Llinas. If one considers that all biological cells, including neurons, typically comprise on the order of 10⁷ tubulins, then conceivably a stream of consciousness may be possible with only 2000 neurons! Hameroff and Penrose suggest that a conservative estimate of only 10% of the tubulins actually take part, thus increasing the number of participating neurons to 20,000. Compared with the 100 billion neurons in the brain, this is indeed a very small number.

A variation of the Penrose-Hameroff model has been postulated by physicist Dimitri Nanopoulos who asserts that microtubules participate in cell bioinformation processes through cell structure possessing a code system and that this code system relates to a form of "mental code." [37] As suggested by Penrose and Hameroff, Nanopoulos also speculates that the paracrystalline structure of microtubules enable them to support the superposition of coherent quantum states that would represent a sufficient mental order. He and his colleagues have proposed a mechanism involving string theory for the transfer of the spontaneous collapse of the quantum superposition into this mental order. They suggest that an organized quantum "exocytosis," or release, occurs at the moment of collapse and translates this mental order into a physiological action. His analysis of the spontaneous collapse of a coherent quantum state when tailored for the microtubule system indicates that approximately 10,000 neurons are required to process and imprint this information. The significance of the variation of this version of the Hameroff-Penrose model is the implicit acceptance of the model itself. Nanopoulos and his colleagues are merely exploring characteristics that may more completely explain the mechanism of occurrence.

There is a fascinating ramification to the orchestrated-objective-reduction model of consciousness, and that is the speculation as to when in the evolution of organisms may consciousness have emerged. Hameroff and Penrose both have also offered thoughts on this subject. If one accepts the premise that a fairly small number of neurons (or other cells, as it is yet to be proven that the active cell must be a neuron) are actually required to produce a stream of consciousness, then in how primitive a life form does that spark of consciousness first occur? Our androcentric mindset proclaims that only humans are conscious. But with probable certainty that paradigm is most unlikely. While it is equally unlikely that all living things are conscious, many people may be greatly surprised to learn how ubiquitous consciousness may actually be. If one considers quantum-coherence time and the number of tubulins (specifically neural tubulins) as the distinguishing parameters, one could derive some insight as to where within species development consciousness may begin to emerge.

A single-cell organism such as a paramecium has no neurons. Yet it is able to swim, react to stimuli, and find food. But is it conscious? The coherence time of its nominal 10⁷ tubulins is on the order of 50,000 milliseconds, a period just short of a minute. It is highly unlikely that coherence times could dwell that long, so single-celled organisms are probably not conscious. But what if we were to consider larger primitive organisms? The C. elegans nematode has 302 neurons, giving it 3 x 10⁹ tubulins. Its coherence time would require it to maintain quantum isolation for only 133 milliseconds, which may be possible! Because organisms such as these were prevalent 540 million years ago, Hameroff and Penrose speculate that a form of primitive consciousness may have caused the burst of evolution known as the "Cambrian explosion." Consciousness would have a distinctive advantage for survival. Possession of a primitive consciousness would greatly augment finding food and avoiding predators, thus increasing the odds of continuing the species. Given this, then higher-order species possessing distinct brains are without doubt conscious, or at least they possess some form of consciousness. If one accepts this premise, then one would very likely be inclined to see fish, birds, and our fellow mammals in a whole new light. Consciousness, then, could very well be a parallel but more primitive characteristic of the brain that superimposes and augments brain functions. The function of complexity of the massively large number of neuronal interconnections, on the other hand, is likely the primarily condition or cause of sentience and intelligence, with the neurons themselves functioning more as switches.

The thirst to understand consciousness will no doubt continue to be approached through computational systems and processes, but the orchestrated-objective-reduction model is very compelling and deserves the international attention it is receiving from the science community. As suggested by Penrose and Hameroff, something greater than mere computational processes is required to ignite the spark that ultimately precipitates consciousness. Maybe quantum physics offers the solution, and perhaps some variation of "quantum computing" with microtubule tubulins is indeed the ignition source. Clearly more work needs to be done. However, we are inclined to accept this hypothesis as the likely scenario for the explanation of consciousness, as this has been the most consistently plausible explanation of any we have found. It is simple and profound. It dramatically changes any preconceived prevailing perceptions of what consciousness may be or at what stage of evolution it would be expected to materialize. It is a condition of being for all higher-order species and likely exists in at least certain fragmentary forms in simpler but multi-celled species (e.g., possibly in as simple a form as C. elegans). It is pervasive and ubiquitous, and we submit that consciousness is a prerequisite for sentience. Before any entity - whether it be biological or man-made - can be sentient, it must first be conscious.

Onset of Sentience: To say that an entity is sentient is to say that it is capable of feeling and perception. But what exactly does one mean by “feeling” and “perception?” A feeling can be said to be the sensation that results from the processing of sensory data for which an immediate active response may or may not be required. A perception can be thought of as an intellectual awareness of an environmental condition for which some response may be necessary. If having sensations and perceptions are criteria for sentience, then where in biological systems might the transition occur where pure sensing ends and sensations begin to evolve as a result of processing the sensory input? Certain forms of pure sensing occur in all species under certain conditions. Numerous biological processes ranging from the control of heart rate, the response of the iris to light, and maintenance of correct blood chemistry involve autonomous sensing that do not result in sensations. But where in the evolution of intelligence does the transition occur between mere “hard-wired” response to stimuli resulting in a predictable reaction and the ability to process those stimuli and modify behavior accordingly?

In order to show the relevance of these aspects to man-made systems, we will explore the biological parallels and attempt to estimate where the onset of sentience may occur in the animal kingdom. From this information, we will present an analogy as to where such a transition might be expected for a synthetic system.

First, let us explore sensing itself. There is obvious difference between mere sensing and perceiving what is sensed. Sensing involves responses on the part of the system that typically, although not always, manifest in some form of behavior. For both plants and animals in all of biology, information is derived from the environment and is used to enhance the chances of survival for any given species. Plants have evolved a rudimentary hard-wired sensing system to help them survive and adapt. For example, they react photochemically to better orient themselves to the direction of sunlight, and insect infestations cause many plant species to release natural insecticides. Simple organisms in the animal kingdom are repelled by a caustic environment but are attracted by what is recognized as food. All of these are predicable responses to what are in many cases fairly sophisticated biological sensors. But none of these entities themselves is sentient, or even close to it. Although environmental sensing is necessary, sensing alone is not a sufficient condition for sentience. In fact, a much more intelligent-seeming response than that observed by simple organisms is witnessed from a pollution-control monitor that processes inputs from its temperature, pressure, and chemical sensors to minimize pollutants in a dynamic flow environment. In essence, this pollution-control system is processing sensory input information from the environment and is using this information to modify its response to certain environmental characteristics. Yet this system is not sentient. As is the case for lower biological forms, artificial systems sense and make sensory discriminations while neither experiencing sensations nor being sentient.

Just as consciousness is a prerequisite for sentience, sentience is a precondition for intelligence. But what characterizes intelligence? An example of one form of intelligence might be the demonstration of elementary problem solving in a circumstance where an unexpected event requiring a fairly complex response is encountered from the external environment, and the responding entity has no preconceived or preprogrammed experience of such an event. Yet the responding entity executes a logical, patterned response to that event that leads to a successful conclusion - and can repeat that same response. For instance, a glass container of corn affixed with a small red plate may be placed into a pigeon's cage. The pigeon had never experienced this before, but it sees the corn and pecks on the glass; however, nothing happens. It pecks once on the red plate and again nothing happens. But when it pecks twice on the red plate, a kernel of corn is released. When it associates two pecks to the red plate and consistently continues with that pattern, it has solved the problem and demonstrated intelligence as it relates to this class of problem. The degree of evolving sentience necessary to produce intelligence depends upon at least two characteristics: The first is the “quality” of information processing performed by a nervous system on the sensory input from the environment. The second aspect is the sophistication to which that processed information is used to modify the behavior of the system both when responding to the environment and when anticipating environmental changes. Sensory information must be processed by the system, and that processed information must then be used to control the system’s behavior. In biology, what a system senses is often determined by what it is capable of discriminating. A more complex system has a more refined discrimination capability and is hence capable of a richer sensory system. For instance, the mobility of higher-order animals imposes more demanding sensory requirements, resulting in a more highly developed sensory system. And this processed sensory information is manifested both as sensations or feelings and as perceptions of phenomena being presented by the environment.

But what can we say about perception? The perception aspects of sentience imply an emerging awareness of the environment in at least some conscience form. The processed sensory information has enabled the system to somehow develop an “intellectual” grasp of certain conditions about the external environment. For this discussion, we would like to explore the feasibility of a transition from the first level of consciousness to the onset of sentience as it might apply to a system synthesized from nanotechnology. For this exploration we will speculate on certain aspects of implied degrees of animal intelligence that are likely to be somewhat approximate, as we will need to scale known information regarding higher-order brains to conditions that apply to lower-animal forms. But it is from these degrees of implied animal intelligence that we can draw a parallel from which to anticipate the probable complexity admissible for the emergence of synthetic sentience.

What characterizes a perceptive response to sensory input? One might argue that even an "intelligent" response to sensory stimuli may not by itself be a sufficient indication of sentience, but it is likely an important step. Sentience is distinguished by the character and complexity of an entity's information processing that leads to a resulting directed behavior. One measure of this directed behavior might be based on how much response to stimuli experienced by any given species is learned as opposed to being innate. The photochemical response of a plant to a changing light source is clearly innate, as is that of an octopus threatened with danger by emitting a cloud of ink. But the responses of higher animals, especially mammals, are more complex.

As a point of departure – and controversy – for this argument, we will suggest that all species capable of modifying their behavior in a manner such that their responses to new stimuli would be different from an expected “hard-wired” response can be said to possess some degree of sufficient intelligence to demonstrate perception. For instance, the act of finding food might be a good example to use for this demonstration of intelligent behavior. A myriad of experiments have been conducted with numerous species where food is presented behind an enclosure visible to the animal, but requiring some complex act on the animal’s part to reach it. In our andocentric world, we tend to forget that deriving food from a resource-constrained environment is one of the catalysts that produced intelligence in the first place. A measure of a given animal's intelligence is reflected on how cleverly it works through complex solutions to receive the reward, and whether it can repeat the solution. Then when the sequence of the required solution is changed, the animal should modify its behavior and derive another solution. For example, birds have demonstrated an ability to peck out a proper sequence of a moderately complex apparatus to retrieve a seed of grain and to relearn a new sequence when the apparatus was modified. [38] One behavioral characteristic widely considered an indication of a higher-level intelligence - long thought to be solely the realm of humans, but recently expanded to include primates in general - is the ability to manufacture and use tools. But now birds have also joined this elite group. New Caledonian crows have consistently demonstrated the capability of manufacturing and using two different types of hook tools as an aid when foraging for prey in dead wood. They use hooked-twig and stepped-cut barbed leaves, which they cut themselves. Furthermore, they have a fairly high degree of standardization! [39] And of course there is the famous example of the gorilla Koko who was taught to communicate via sign language and not only could ask for food, but could also carry on simple conversations. She has command of over 1000 signs in American Sign language and is also responsive to the spoken word. [40] If these studies were expanded and the data somehow standardized, then somewhere between a simple organism and a human a gradient would appear that would signify the onset of sentience. The neural complexity and “wiring” connectivity possessed by a species falling within this region would represent the minimum expectation for the emergence of sentience within a man-made system.

While such an “ordering of relative intelligence” would be difficult to quantify, perhaps anecdotal experimental results could be correlated with neocortical research conducted on different species. The neocortex is generally considered to be the root for the evolution of intelligence. Its structure appears in the more recently evolved species – mammals – and differentiates mammals from other species. [41] Furthermore, brain size and both neocortical volume and surface correlate very well within the different mammalian orders. If one accepts the premise that sentience is a precondition for intelligence, then we should explore some of the aspects of the relative intelligence among animal species so that we may infer where in the chain of evolution we might expect the onset of sentience.

Starting with the largest brains where we have the most experience, one would assume to a first order that a big brain would imply greater intelligence. But when comparing among species, one must be careful lest one obtain skewed results. For example, very early research in this area compared the ratio of brain weight to body weight as a possible way of deriving relative intelligence among species. But this simplistic approach revealed that both mice and humans have a body weight that is 40 times the brain weight – and small birds have a body weight of only 12 times the brain weight. These results would seem to imply that mice and men are of equal intelligence (many women would agree) and that birds were considerably smarter. But brain weight does not increase linearly with body weight. Instead, the increase in brain size with body size follows a specific exponential rule. In the late Nineteenth Century, Snell derived the following equation relating brain and body weight:

E = C S ^r (1)

where E and S are body and brain weights, respectively, and C is a constant referred to as a “cephalization factor.” The r is an empirically determined generally accepted exponent that was derived initially by Bonin [42] and is approximately two-thirds for most mammals. The rationale for the two-thirds exponent is based on the premise that the major determinant for required brain size is the body surface. Given a characteristic length of an animal, its surface increases with the square of that length, while its volume increases with the length cubed. If brain size growth were then taken as the animal's surface per volume, then the two-thirds exponent would result. [43] Figure 5.4 shows the brain and body weights for various species with Snell’s equation overlaid representing a best fit of the data. One might note that the polygon connecting the outer limits of the data points shows the elephant and blue whale at the extreme points. Although elephants are generally considered to be fairly intelligent, there is no evidence that they are more intelligent than humans. Therefore, interpretation of this figure requires a methodology for establishing the relative brain capacities of the different species independently of body size. One method commonly used for factoring out body size is to calculate the displacement of each data point from the best-fit line in the polygon and use these residuals to estimate an index of brain size relative to that which would be predicted for a particular animal. Relative brain capacities for different species could then be compared. By entering the brain and body weights for different species into Snell’s equation and solving for C, one can then determine the ratio of the calculated C with that of the average mammalian value. The result is the index referred to as the “encephalization quotient” or EQ. The EQ index enables one to compare the brain capacity of a given species with what would be expected of an animal of comparable weight with average encephalization. The following table (Table 5-1) shows the encephalization quotients for a select set of mammals. [44]

While this table presents a wide variation between mice and men and also aligns with what we may intuitively feel is the approximate correct order of evolving intelligence, is this method truly a good index for comparing relative intelligence among mammals? Could such a table be expanded to lower-intelligence species with the expectation of identifying a transition to sentience? While this table provides a ranking of species as contenders for relative intelligence, this ranking needs to be validated from behavioral data before any rigorous conclusion can be formed relating brain size to intelligence. Obviously this table would need to be expanded dramatically, for it is very likely that all species identified in this limited sample are sentient.

Table 5-1. Encephalization Quotient for Various Mammal Species.

SPECIES	EQ
Human	7.44
Dolphin	5.31
Chimpanzee	2.49
Rhesus Monkey	2.09
Elephant	1.87
Whale	1.76
Fox	1.59
Dog	1.17
Cat	1.00
Horse	0.86
Sheep	0.81
Ox	0.54
Mouse	0.50
Rat	0.40

Another index that relates the size of the neocortex to other brain structures as a means of determining more highly evolved brains – and hence intelligence – was developed by Heinz et al. [45] Since we know that consciousness is experienced through the thalamocortical region of the brain, it is reasonable to assume that such a neocortical-based ratio might be a good indicator of the probable onset of sentience. The Heinz et al. team compared brain structures for sample species within the animal-kingdom orders insectivora and scandentia along with various primate suborders including humans.[3] The team learned that the neocortex was the most progressive of the brain structures. When they compared the neocortex of various species with that of tenrecinae across various orders and families of species, they learned that the cortex of insectivora was an average of 2.7 times larger than found in species tenrecinae, and the scandentia order was greater by a factor of 10.5. A comparison with the prosimian primates showed that the primates were 21 times larger. The non-human simians were 51 times larger, and the human neocortex is 200 times larger. As brain size progresses from that of the insectivores to the higher primates, the neocortex increases rather dramatically in size. However, during this expansion process, the ratio of the neocortex volume to that of the total brain remains fairly constant, indicating that other forebrain structures become a smaller percentage of the total brain volume as the brain size increases. This increasing ratio of cortex-to-“other” structure could be taken as an indicator of evolving intelligence. And somewhere in a progression of this nature we should find evidence of emerging sentience. However, the data collected by Heinz et al. referenced only mammals, and our survey requires the inclusion of characteristics for lower-form species as well.

Another factor we should consider in this comparative-intelligence argument is the number of neurons found in the central nervous system of various species. Higher intelligence obviously necessitates a larger number of neurons. However, higher intelligence also requires a more complex neural connectivity. But these two systems do not grow in size proportionally as the brain volume increases. Macphail observed that the actual number of neurons per unit volume declines as the brain volume increases, but neural connectivity actually increases. This implies that brain volume is likely driven more strongly from connectivity than from the number of neurons. Given this observation, one might suggest that as a point of departure for quantifying the transition region for the onset of sentience, one could develop two graphs: First, one could consider generating a graph of the number of neurons or of neural connectivity as a function of the ratio of the cortex to some other brain structure, such as the cortex-to-thalamus ratio. The thalamus might be selected as the normalization parameter because the thalamus functions as a relay of sensory information to the cortex. And onto that graph one could superimpose the cortical ratios of different species within the animal kingdom. Although the connectivity-to-neuron ratio increases with increasing brain size, one could assume it remains constant for the purpose of obtaining a rough order of magnitude quantization for the likely onset of sentience. For mammals at least, the thickness of the cortex is nominally two millimeters [46] and varies minimally across species, so a minimal error would likely be introduced if one worked solely with the cortical area. Then the number of cortical neurons per species could be scaled roughly with the cortex area. And from this quantization one could then at least develop an impression for the required complexity necessary for the emergence of sentience within the animal kingdom and apply this estimate to a synthetic system.

Figure 5.5 is an attempt to display such a graph with the human neural connectivity at the upper end of the scale. The human brain has on the order of 100 billion neurons, each with 1000 to 10,000 connections. For this graph we can assume an upper limit of 10¹⁵ for human neural connectivity. If the human parameter is taken as the high end of this graph and scaled accordingly with those of other species, then a graphical representation like Figure 5.5 would result. From a figure such as this, one could speculate as to where one might begin to look for a transition region depicting the likely onset of sentience. Albeit subjective, one could at least initially be guided by empirical observations of the characteristics of known species as discussed above. A major limitation of this approach, however, is that lower-order species do not possess a thalamus, or other major brain components for that matter. Yet these lower-order species may have evolved sufficient neural complexity to experience an emerging sentience.

A second graph that one could generate, and one that likely would be more directly applicable to the design of a man-made sentient system, is a graph of the number of neurons possessed by a given species shown as a function of the different species themselves. Figure 5.6 is a depiction of such a result. With this approach one could estimate the probable range of neurons and neural connectivity required for threshold sentience by determining where in the evolution of species would sentience likely emerge. From these species one could establish an order of magnitude estimate of the number of neurons and synaptic connections required to comprise the transition region for the onset of sentience. Therefore, when following this biological parallel for a man-made sentient system derived from nanotechnology, one would expect a requirement for a similar number of neuronal “nodes” as well as a similar connectivity complexity in order to achieve a threshold of synthetic sentience. As a point of departure for this thesis, we will assume that species with rudimentary intelligence possess a sufficient number of neurons for emergent sentience. Although it is highly unlikely that a housefly would qualify, there is considerable evidence of intelligent behavior in reptiles and fish. [47, 48] One must of course recognize that in Nature there are always exceptions. One will find examples of more intelligent simpler creatures and duller complex ones. But if we assume the region around reptiles and fish as qualifying for our purpose, then from Figure 5.6 we would expect to need on the order of 10⁷ neurons as a minimum necessary for the onset of sentience. If we further assume that each neuron has at least 1000 dendrites, then we would expect to require a minimum of 10¹⁰ connections within a computer system before such a system could approach experiencing sentience.

While 10¹⁰ connections may seem like a staggering number, we can gain a better perspective from the following. First, today's Pentium 4 chip is made up of nominal 100-nanometer transistors, resulting in a population on the order of 10¹⁰ transistors per square centimeter. If we were to approximate each transistor as a single bit with two connections, then we could say that the technology is already available to produce a system with 10¹⁰ connections. Now assume that each connection represents a synapse and consider that a synapse is essentially the biological equivalent of a computer’s “bit.” If we were to further assume continuation of the current progression of Moore’s Law – especially in light of the recent progress in nanoelectronics discussed earlier, then we would expect that the bit densities of integrated circuits will approach 10¹