The second type of connection required for consciousness is between those items in working memory in order to spot patterns or chunks, or simply to maintain a sequence of items. A fast rhythm between neurons throughout the cortex can maintain the links between distinct objects and allows us to analyze and manipulate them in working memory.
EEG, with its millisecond accuracy, is also excellent at providing a time frame for consciousness. These widespread high gamma rhythms don’t immediately follow the presentation of a stimulus. Instead, they are relatively protracted, as you might expect when much of the brain has to coordinate its activity, and they take at least 300 milliseconds to form. This is a very similar value to the time it takes attention to filter sensory input according to our current goals.
CONSCIOUSNESS, IN THEORY
I can now paint an overall empirical picture of consciousness. If a vivid red rose comes into view, my experience of it is built up over a third of a second, as an initially brutal neuronal competition leads to the shaping of brain activity around my attention toward the rose. An ultrafast, harmonious neuronal rhythm spreads outward from the thalamus and merges my collective neural information of the rose, which is stored in specialist areas throughout my cortex. This high-frequency, long-range, unified mental chunk will also broadcast itself into the prefrontal parietal network, where the experience will come to life.
But if I were faced with a more novel or complex task, my consciousness would show its true potential. My prefrontal parietal network activity would reflect an engaged working memory, a focused attention, and a ravenous search for patterns in order to conquer whatever mental obstacle was in my way. Meanwhile, my specialist regions of cortex—for example, areas that store knowledge about objects at the front of the temporal lobes—would take turns to support my consciousness by providing the specific contents to my experiences.
The next challenge for consciousness researchers, in the decades to come, is to discover exactly how neurons collectively represent the information they do and what forms of neuronal interaction generate consciousness. For instance, just how is information transmitted between the fusiform face area and the prefrontal parietal network, via these high gamma waves, to generate my experience of my daughter’s face? And what is the precise code that neurons use to represent information? Such questions may be answered by simultaneously recording the activity of each of thousands of neurons in multiple regions. At present, the state of the art is limited to dozens of simultaneous electrodes (in the macaque monkey, the closest species to us where these studies are routinely carried out), so the technology falls considerably short of the kind of data collection required. But there’s every reason to assume that in the next decade or two the methods will be sufficiently advanced for us to discover and extract the precise neural signature of consciousness.
In the meantime, many scientists have created detailed theories based on the existing empirical picture. Admittedly, there was a rather wild crop of early theories in the final decade or two of the twentieth century—for instance, one seemed to rely on the impeccably argued syllogism that because consciousness is mysterious and quantum mechanics is mysterious, then quantum mechanics must explain consciousness. But now the story is very different, with theories linking closely with the latest empirical findings. What is striking about the most prominent current crop of theories is how they are all broadly converging on the same overall position.
The three most popular serious theories of the day all, at their heart, see consciousness as a particular flavor of dense information transmission across a large cortical network. But each theory differs subtly in its particular perspective on this general view.
Victor Lamme’s
recurrent processing model
starts with the stark assumption that we may think we know when we are conscious of something, but we couldn’t be more wrong. According to Lamme, there are many times when we are actually conscious but we don’t even realize it. So he abandons talking about psychology, and what experiences we can or cannot report, and so on, and instead centers entirely on what is happening in the brain. Sometimes one brain region will feed information to another, but the second brain region won’t talk back to the first. Other times, there will be “recurrent processing,” where both brain regions are entering into a proper back-and-forth, two-way dialogue as they exchange information. Lamme believes that it is only when this second kind of neuronal chatter is taking place, with information bouncing between regions, that consciousness occurs. If this back-and-forth talk happens only between specialist areas, such as different visual cortical regions, then there will be some level of consciousness, but it will not be strong enough that we could say, for instance, “Ah, there’s a red rose in front of me.” But if this two-way communication stretches into the prefrontal parietal network, then we have a full, deep consciousness and can report on what we’re seeing.
Lamme’s notion that recurrent processing is required for conscious levels of information transmission to take place is a very plausible suggestion. But I find his insistence that we are still conscious even when we are quite convinced that we are not to be a deeply unpalatable stance. In order to build a coherent theory of consciousness, it’s fine to be suspicious of the edges of what we report about our experiences, but it is not sensible completely to ignore the very event you are trying to explain. Partly because of Lamme’s rejection of the experiential intricacies that make up how we are aware of the world, his model fails to capture much detail about the nature or purpose of consciousness.
The model most closely aligned with the existing data, and the view of consciousness I’ve been describing throughout this book, is the
global neuronal workspace model
proposed by Stanislas Dehaene and Jean-Pierre Changeux. This model is largely the neuronal extension of the global workspace theory put forward by Bernard Baars. In Baars’ theory, consciousness is roughly equated with working memory. It’s a spotlight on a stage, or scribbles on a general-purpose cognitive white board, which lasts only a second or two, but which can contain and manipulate working memory items by drawing them from our vast unconscious reservoirs of knowledge in specialist nonconscious systems.
In the global neuronal workspace model, the brain also divides along specialist and generalist lines. First there are the specialist, content-dedicated areas at the edge of the collective brain network, which store our memories, crunch data from our senses, and so on. The neurons here have short to medium connections with each other and are all that’s needed when we perform an effortless, automatic, largely unconscious task. The inferotemporal cortex, processing visual objects, is one example of such a region. Then there are the general-purpose regions at the densest center of the network, comprising the prefrontal parietal network and thalamus, which “ignite” in dramatic activity whenever an effortful task is required, so that this entire core can become fully activated simultaneously. This central core includes lots of long-range connections between neurons, enabling this neuronal workspace to draw in specialist knowledge from the content-dedicated regions at the thinner outer edges of the network. If necessary, the prefrontal parietal network and thalamus can also control and modify the activity of these subordinate distant areas, so that complex information processing can occur and difficult tasks can be achieved. Activity in this core set of regions, particularly involving the prefrontal parietal network, is the locus of consciousness.
Anatomical studies of how the brain is wired put the lateral prefrontal cortex, one of the main regions of the prefrontal parietal network, at the top of the league in terms of how many other regions it is connected to, although the posterior parietal cortex and thalamus are not far behind. So in terms of brain wiring, the prefrontal parietal network, in concert with the thalamus, constitutes an “inner core” of regions that are ideally suited to collect information from the rest of the brain, carry out the most complex tasks we are capable of performing, and generate our sense of experience from this central hub of information processing.
But because Dehaene’s model is so closely wedded to the empirical neural details that are associated with awareness, he has opened himself up to the charge of not more ambitiously capturing the mechanistic essence of consciousness.
The third and final theory, Giulio Tononi’s
information integration theory
, travels in the opposite direction, only discussing mechanisms while refusing to get its hands dirty with too many tawdry details about the brain. Information integration theory is also by far the most abstract and ambitious of the current crop of consciousness models.
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An entirely mathematical theory, it tries to distill consciousness into its informational essence. Whereas the previous two models were rooted in the real cortical networks of the human brain, Tononi’s theory applies to any network of nodes whatsoever, be they a connected series of neurons, computer transistors, or any other information-carrying object one would care to imagine. For Tononi, a network’s capacity for consciousness is directly related to how many different kinds of information it can represent and how well those pieces of information can be combined. The more nodes there are in a network—as long as they are sufficiently connected to each other—the more varied the possibilities for combined forms of information and the greater that network’s capacity for consciousness.
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This simple yet powerful recipe for awareness can map quite neatly onto concepts such as attention, with its drive to combine information about an object into a unified whole, or even the previously mentioned global neuronal workspace model, which also cares about a dense central network to carry combined forms of information.
Under the information integration theory, regions like the cerebellum can never support much consciousness, as they have few connecting internal wires. Specialist brain regions, such as the primary visual cortex, can play only a minimal role in consciousness, again being at the edges of the main network. In contrast, the prefrontal parietal network, being so densely interconnected and also linked to many specialist regions, is just the kind of network shape that can support high levels of consciousness.
Without the prefrontal parietal network, we are really just processing an independent collection of facts in parallel—for instance, the color of Angelina Jolie’s dress as one datum, the sound of her voice as a completely separate feature, and so on. But when there is some highly interconnected network involved, such as the prefrontal parietal network, with attention combining those facts within it, the richness of that information far exceeds the sum of each individual piece of data, and consciousness ensues.
And just how much information of this merged form a network can contain is the same as how many different states of activity it can be in. In practical terms, this means how many different kinds of experiences we are ever capable of. I might have inferior senses to a dog, and therefore at best a matched level of information input, but because I can combine the data from my senses in so many different ways, due to the powerful analytical machine of my prefrontal parietal network, the range of experiences I can have far exceeds that of a dog.
Two questions concerning our inner mental life have, for centuries, obsessed philosophers: (1) Why is consciousness inherently subjective? and (2) How can a physical lump of matter give rise to the glorious variety of sensations we can experience, from seeing a red rose to hearing a Beethoven symphony? Tononi ambitiously claims to be able to address both of these issues.
For Tononi, the inherent subjectivity of awareness, where my experiences are private to me alone, impenetrable to anyone else, is an essential component of consciousness, because that is precisely what the mathematics of his theory predict. If consciousness is just the activity in the densest part of the network of my brain, how could my consciousness extend outside my brain—for instance, to another person? There are no network connections to make this possible, for a start. But even if these connections somehow were present—for instance, I had some sort of neural graft connecting my brain with another’s—if this connection was too weak, then there would be two dense networks and two consciousnesses, with a very weak experiential connection between the two. This situation would be broadly similar to that of the conjoined twins Tatiana and Krista, who are very much two different people, but who just happen to share the occasional feeling. So subjectivity, far from a philosophical conundrum, might simply be a product of the way that closed networks generate their compound, unified items of information—a mathematical, computational process that we happen to call consciousness.
And what imbues my awareness with all the different sensations that I can experience? Why do my baby daughter’s dark brown eyes appear that particular color to me? Why does her sweet, high babbling voice have that precise sound? And why does my stroking her soft cheek as I send her to a night of sleep have that particular feel? According to Tononi, whatever we experience is permeated by its specific sensation because of the precise point it takes up in this huge space of possible forms of combined information we can represent. The dark brown shade of my daughter’s eyes feels like it does because of the informational contrast it makes with all the other colors I could possibly see, which evoke similar experiences for their similar informational content. But that particular experience of color is also in contrast to all the other experiences I could have in my other senses and beyond, which feel less similar because of their greater informational distance. So every experience we could possibly have, as a unique set of pooled information, gets its distinct perceptual characteristics from its relationship to all our other possible experiences.