The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning (33 page)

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Authors: Daniel Bor

BOOK: The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning
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As usual, the sequences that could be chunked, because of strategies involving either memory or mathematics, were easier for the subjects to recall compared with the unstructured sequences. And both kinds of chunking sequences, as before, lit up the prefrontal parietal network considerably more brightly than did the unstructured sequences, where chunking wasn’t an option. Additionally, the condition involving mathematical sequences still robustly activated the prefrontal parietal network compared to its matched control condition (where subjects carried out equivalent mental arithmetic tasks, but without any chunking component). A similar pattern of prefrontal parietal activity was seen when the condition involving the memory-based chunking sequences was compared to its own matched control (with the same level of memory recall, but no chunking aspect to the task). This demonstrated that these regions were not just being driven by mental arithmetic or memory recall when subjects carried out the chunkable sequences, but something more—quite specific to the act of chunking. I was most struck, though, that the condition involving mathematical chunks
still
robustly activated the prefrontal parietal network when compared to the memory-based chunking condition. This placed the mathematical chunking task as the firm winner in the game of driving activity in the prefrontal parietal network. Ask a scientist in the field to generate a list of those processes that will most reliably activate the prefrontal parietal network, and she will most likely include working memory, long-term memory, and mental arithmetic. But in this experiment, the mathematical chunking task activated the prefrontal parietal network more strongly than all of these, as well as compared to the memory-based chunking condition. In other words, this experiment demonstrated that the prefrontal parietal network will activate for many complex tasks, but it will be most excited when subjects are actively searching for and finding entirely new patterns.
Other research groups have also linked chunking with the prefrontal parietal network. In the long-term memory domain, Cary Savage and colleagues showed that chunking will both light up the prefrontal cortex and boost performance if a group category strategy is applied to word-list memorization (for instance, remembering all plants together in one group and all metals in another). Similar results have been found in the working memory field. For instance, Vivek Prabhakaran and his coworkers presented letters to participants with the instructions that these stimuli had to be recalled over a short delay. If volunteers chunked the letters using a strategy that involved binding a spatial location to each letter, then prefrontal activity increased. In another working memory task, Christopher Moore, Michael Cohen, and Charan Ranganath demonstrated that extensive training involving the categorization of abstract shapes enabled memory-based chunking for such stimuli, which improved subjects’ performance and increased activity in the prefrontal parietal network.
One recent intriguing, related study by Stanislas Dehaene and his team actually showed the transition from consciously spotting the pattern to then using it in a routine, automatic manner. Subjects had to discover a novel sequence from the letters ABCD. For instance, a participant might first try “A” and be told this was wrong; then she might try “B” and be informed that this was correct—so now she would know that the first letter in the sequence was “B.” She might try “C” for the second letter and be given feedback that this was wrong. At this point, she would have to start the sequence all over again, but at least she would now know to start with “B” and explore the second letter. Eventually, by trial and error, she would work out the sequence, which she would have to repeat between three and six times—now a very easy task for her. Then there would be a new sequence for her to work out, and the cycle would continue. During the initial search phase for each trial, there is massive prefrontal parietal network activity, but this quickly dies down as soon as the task becomes routine. The prefrontal parietal network then becomes virtually silent as the task is automated in the volunteers’ minds, and they need very little consciousness to complete the well-learned sequence. In other words, this is a beautiful illustration of the distinction between the conscious search for patterns, carried out in the prefrontal parietal network, and our largely unconscious automatic habits, which require specialist brain areas alone.
 
In all the examples above, the chunks tended to be so obvious that volunteers couldn’t help but be aware of them. What would happen, though, if the participant couldn’t consciously spot the chunks for some reason? Would the prefrontal parietal network fail to activate for these undetected structured sequences? Serendipitously, I was able to answer this question via a fascinating person who was effectively blind to all such number chunks. Daniel Tammet is a prodigy with a few similarities to the incredible Russian mnemonist Sherashevski, discussed in Chapter 2. For one thing, Tammet has a rather extreme form of synesthesia, just as Sherashevski did. Those with synesthesia commonly associate colors with specific single digits they read. Tammet, however, has a different experience for not just the first ten numbers, but the first ten thousand. Not only this, but he also adds not just color, but texture, shape, height, and even touch to his perception of numbers. This creates an incredibly vivid, structured experience for him whenever he reads a stream of digits. He is also diagnosed with a high-functioning form of autism known as Asperger’s syndrome.
When I tested him, Tammet was able to cram far more numbers into his short-term memory than any other volunteer I’d ever tested (though this was somewhat reduced when I deliberately confused him by coloring the numbers in ways that clashed with his synesthetic inner eye). He had just set the European record for memorizing the most decimal places of pi: 22,514—which he claimed was quite easy to do, the most difficult part simply being the 5-hour stint needed to recite all the numbers from memory. He also has prodigious mental arithmetic skills—for instance, being able to divide one double digit by another and give the answer to 100 decimal places. And he claims a deep facility for languages, with the ability to learn a new language in a single week. Although his Asperger’s syndrome probably allows him to concentrate more deeply than most, his exceptional abilities mainly arise from the intensely multisensory inner numerical world he experiences, with every number seeming so very vivid and distinct to him. Memorizing or mentally manipulating numbers comes easily and naturally, and to recall them, he simply has to convert the inner psychedelic mountain terrain back into digits.
We decided to investigate his brain activity when he carried out one of our chunking tests—where 8 single digits are presented to be retained in memory over a few seconds, with half the sequences structured, like 8 6 4 2 9 7 5 3, and half random and unstructured. When I asked him after the experiment whether any trials were easier than any others, he unsurprisingly said that they all were just as easy—because for him, unlike normal people, remembering only 8 digits really is very straightforward. But when I probed further, it turned out that, surprisingly, he’d completely failed to realize that some of the trials involved highly structured sequences of digits. He was in fact completely blind to the external structure. His brain activity reflected this: Totally unlike normal volunteers, he showed absolutely no increase in activity for the structured sequences compared with the unstructured sequences. He was neither aware of the structures nor in any way exploiting these patterns to chunk the sequences and reduce his working memory load. So Tammet showed, by failing to notice these chunks, and failing additionally to activate his prefrontal parietal network for these obvious forms of external structure, that you really do need to be aware of and use the chunk in order for the prefrontal parietal network to kick into action.
But for Tammet, it certainly wasn’t as if absolutely no structure was imposed on these sequences. He might not have noticed any additional structure for the mathematically chunkable sequences, but for him, because of his rich form of synesthesia, in a sense every trial was highly structured—it’s just that the structure resided in his head, in the multisensory mountain range of his mind’s eye that appears whenever he thinks of a stream of numbers. Reflecting this, for all trials, on average, whether they were structured or not, he had markedly increased activity in the prefrontal part of his prefrontal parietal network compared to the normal volunteers. This is because, for him, every trial, not just the structured trials, were being chunked at least to some extent. So, in two unexpected ways, this experiment reconfirmed the links between chunking, consciousness, and the prefrontal parietal network.
 
This collective evidence, then, shows that consciousness is most closely connected with the prefrontal parietal network, which supports not only attention and working memory processes but also any kind of novel or complex task. But if you want to activate this network the most powerfully, and by extension engage your consciousness to its most intense heights, you need to detect some useful pattern. These chunking processes are an embedded part of our advanced conscious cognitive machinery. They are also perhaps the essence of what it means to be conscious. They are the mechanisms by which we convert awkward obstacles into innovative solutions and initial, error-prone fumblings into adept automatic habits.
HARMONIOUS EXPERIENCES
 
Admittedly, though, these are broad strokes in painting the details of how the brain creates consciousness. One way of looking at the problem in a deeper way is to ask how neurons communicate with each other in order to generate our experiences. Although this question was partially answered in the previous chapter, by my description of how attention equates to coalitions of neurons competing for dominance, another feature of neuronal communication is the waves of activity used to connect brain cells together. The main tool for examining this neural chatter is EEG, which lacks the fine-grained spatial resolution of fMRI but can collect data every millisecond, compared to the second or two it takes for an fMRI scanner to grab a picture of the brain’s activity.
Francis Crick was the main early champion in this area. One of the most famous scientists of the twentieth century, Crick codiscovered the structure of DNA in the early 1950s, and proceeded to contribute revolutionary findings in genetics for a generation before turning in the last two decades of his life to the science of consciousness, which he believed was the greatest unsolved mystery in biology.
Crick popularized the idea that when neurons act in harmony in a certain way, then consciousness ensues. The particular frequency bandied about for this love-in between neurons was originally the gamma band, roughly averaging to 40 cycles per second, one of the fastest frequencies that neuronal communication is capable of (and a frequency previously linked with attention).
Although there is solid support for the link between this gamma band and awareness, this thesis requires a couple of tweaks. For instance, in rats at least, these fast waves are observed, along with slow delta waves, when the animals are under general anesthesia. Rats can also generate these swift types of neuronal synchrony when in a deep sleep.
The resultant updates to this suggestion that the gamma band reflects consciousness suggest that local communication between neighboring neurons using these frequencies is not sufficient for consciousness to arise. What’s required is a gamma rhythm binding together the information between neurons that may be on separate neural continents—for instance, one region in the prefrontal cortex toward the front, and another in the posterior parietal cortex toward the back.
And perhaps gamma isn’t quite fast enough for consciousness—instead, what’s called “high gamma,” with frequencies from 50 cycles a second, possibly even up to 250 cycles a second, is currently a hot topic in consciousness research. This frequency band is too swift to study using conventional EEG because of the interference of the signal by the scalp. But some epileptic patients soon to undergo a brain operation to remove the locus of their epilepsy have EEG arrays implanted directly onto their cortex, under their scalp, in order to investigate where they are having their seizures. When the electrodes are immediately over neurons, then you can pick up such high frequencies with ease. Two independent labs, Stanislas Dehaene’s near Paris and Bob Knight’s at the University of California at Berkeley, have both shown, using this technique, that when the patients are free from seizures and normally awake, these ultrahigh waves of neuronal activity are exquisitely connected with consciousness, and might, in concert with and locked to lower frequencies, be the main neuronal signature of awareness. Why such high frequencies?
The answer follows from the purpose of awareness. In order for consciousness to carry out such complex tasks and generate insights, it needs to make connections in two ways: First, it needs attention, not just to select the most pertinent mental objects to place in working memory, but for all aspects of that object to be knitted together into a single, coherent whole. So when I see Angelina Jolie in that red dress on the silver screen, I don’t see her eyes as one object, her nose as a separate, disconnected object, her hands and name and voice as others. Instead, she is just a single, unified, though complex object, with many different components all connected together. Very importantly, I really can’t help consciously recognizing her
as Angelina Jolie,
as opposed to all these distinct parts.
The color of her dress may nevertheless be represented in my visual cortex at the back of my brain, her face in my fusiform face area at the bottom of my cortex, her name and various other facts about her in my semantic store, at the front of my temporal lobes, and so on. When I recognize Angelina Jolie, many specialist cortical areas, all over my brain, are involved in that recognition, as well as my prefrontal parietal network, which acts as a conscious, temporary manager of the information in working memory. Now, if all of these spatially disparate regions need to be joined together to represent the conscious mental object, Angelina Jolie, a slow neuronal rhythm, say of a few cycles a second, simply isn’t up to the task, since there is too much data to hold together in the time. This slow kind of rhythm, the delta band, is instead commonly found when someone is under general anesthesia. The conscious frequency, in contrast, is as fast as our brains can allow. High gamma waves of activity are initiated by the thalamus, the Grand Central Station of brain regions in the center, and then these ultrafast waves perpetuate through the relevant parts of the cortex and bind together all components of an object in consciousness.

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