The Ways to Control Dreaming

In 2008, Isaac Katz, a civil service officer, passed away just before reaching his 78th birthday. He had been struggling with cardiovascular problems for some time. His son, Arnon Katz, now a 47-year-old tech entrepreneur, was beside himself with grief, and frustrated by the fact that he would never speak to his father again.

At the time, the younger Katz had been training himself to lucid dream—a phenomenon in which the dreamer becomes aware they are dreaming and can potentially control their actions as well as the content and context of the dream. But despite keeping a dream journal and diligently practicing other techniques, hadn’t had any success. All that changed, though, a year after his father’s death.

Katz recalled in a recent phone interview that he was mid-dream when his mother suddenly warned him in a voiceover, “Hey, you’re dreaming right now, so don’t take what your father is saying too seriously.”

Katz told me, “Suddenly everything slowed down and became incredibly vivid and real. I knew I was dreaming, but I felt I was with my father and could choose what to say as if I was awake. When I woke up, I realized that our brains are capable of creating an entire reality apart from waking life.” Many other lucid dreamers have said something similar.

Katz said the experience allowed him to finally “close the circle.” The frustration he felt in the year following his father’s death was gone.

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Why does the brain remember dreams?

Some people recall a dream every morning, whereas others rarely recall one. A team led by Perrine Ruby, an Inserm Research Fellow at the Lyon Neuroscience Research Center (Inserm/CNRS/Université Claude Bernard Lyon 1), has studied the brain activity of these two types of dreamers in order to understand the differences between them. In a study published in the journal Neuropsychopharmacology, the researchers show that the temporo-parietal junction, an information-processing hub in the brain, is more active in high dream recallers. Increased activity in this brain region might facilitate attention orienting toward external stimuli and promote intrasleep wakefulness, thereby facilitating the encoding of dreams in memory.

The reason for dreaming is still a mystery for the researchers who study the difference between “high dream recallers,” who recall dreams regularly, and “low dream recallers,” who recall dreams rarely. In January 2013 (work published in the journal Cerebral Cortex), the team led by Perrine Ruby, Inserm researcher at the Lyon Neuroscience Research Center, made the following two observations: “high dream recallers” have twice as many time of wakefulness during sleep as “low dream recallers” and their brains are more reactive to auditory stimuli during sleep and wakefulness. This increased brain reactivity may promote awakenings during the night, and may thus facilitate memorisation of dreams during brief periods of wakefulness.

In this new study, the research team sought to identify which areas of the brain differentiate high and low dream recallers. They used Positron Emission Tomography (PET) to measure the spontaneous brain activity of 41 volunteers during wakefulness and sleep. The volunteers were classified into 2 groups: 21 “high dream recallers” who recalled dreams 5.2 mornings  per week in average, and 20 “low dream recallers,” who reported 2 dreams per month in average. High dream recallers, both while awake and while asleep, showed stronger spontaneous brain activity in the medial prefrontal cortex (mPFC) and in the temporo-parietal junction (TPJ), an area of the brain involved in attention orienting toward external stimuli.

Why Some Remember Dreams, Others Don’t

People who tend to remember their dreams also respond more strongly than others to hearing their name when they’re awake, new research suggests.

Everyone dreams during sleep, but not everyone recalls the mental escapade the next day, and scientists aren’t sure why some people remember more than others.

To find out, researchers used electroencephalography to record the electrical activity in the brains of 36 people while the participants listened to background tunes, and occasionally heard their own first name. The brain measurements were taken during wakefulness and sleep. Half of the participants were called high recallers, because they reported remembering their dreams almost every day, whereas the other half, low recallers, said they only remembered their dreams once or twice a month.

When asleep, both groups showed similar changes in brain activity in response to hearing their names, which were played quietly enough not to wake them.

However, when awake, high recallers showed a more sustained decrease in a brain wave called the alpha wave when they heard their names, compared with the low recallers.

"It was quite surprising to see a difference between the groups during wakefulness," said study researcher Perrine Ruby, neuroscientist at Lyon Neuroscience Research Center in France.

The difference could reflect variations in the brains of high and low recallers that could have a role in how they dream, too, Ruby said.

Who remembers their dreams

A well-established theory suggests that a decrease in the alpha wave is a sign that brain regions are being inhibited from responding to outside stimuli. Studies show that when people hear a sudden sound or open their eyes, and more brain regions become active, the alpha wave is reduced.

In the study, as predicted, both groups showed a decrease in the alpha wave when they heard their names while awake. But high recallers showed a more prolonged decrease, which may be a sign their brains became more widely activated when they heard their names.

In other words, high recallers may engage more brain regions when processing sounds while awake, compared with low recallers, the researchers said.

While people are asleep, the alpha wave behaves in the opposite way —it increases when a sudden sound is heard. Scientists aren’t certain why this happens, but one idea is that it protects the brain from being interrupted by sounds during sleep, Ruby said.

Indeed, the study participants showed an increase in the alpha wave in response to sounds during sleep, and there was no difference between the groups.

One possibility to explain the lack of difference, the researchers said, could be that perhaps high recallers had a larger increase in alpha waves, but it was so high that they woke up.

Time spent awake, during the night

The researchers saw that high recallers awoke more frequently during the night. They were awake, on average, for 30 minutes during the night, whereas low recallers were awake for 14 minutes. However, Ruby said “both figures are in the normal range, it’s not that there’s something wrong with either group.”

Altogether, the results suggest the brain of high recallers may be more reactive to stimuli such as sounds, which could make them wake up more easily. It is more likely a person would remember their dreams if they are awakened immediately after one, Ruby said.

However, waking up at night can account for only a part of the differences people show in remembering dreams. “There’s still much more to understand,” she said.

The study is published online (Aug. 13) in the journal Frontiers in Psychology.

Scientists Decode Dreams With Brain Scans

It used to be that what happened in your dreams was your own little secret. But today scientists report for the first time that they’ve successfully decoded details of people’s dreams using brain scans.

Before you reach for your tin hat, you should know that the scientists managed this feat only with the full cooperation of their research subjects, and they only decoded dreams after the fact, not in real time. The thought police won’t be busting you for renting bowling shoes from Saddam Hussein or whatever else you’ve been up to in your dreams.

All the same, the work is yet another impressive step for researchers interested in decoding mental states from brain activity, and it opens the door to a new way of studying dreaming, one of the most mysterious and fascinating aspects of the human experience.

In the first part of the new study, neuroscientist Yukiyasu Kamitani and colleagues at the Advanced Telecommunications Research Institute International in Kyoto, Japan monitored three young men as they tried to get some sleep inside an fMRI scanner while the machine monitored their brain activity. The researchers also monitored each volunteer’s brain activity with EEG electrodes, and when they saw an EEG signature indicative of dreaming, they woke him up to ask what he’d been dreaming about.

Technically speaking, this is what researchers call ”hypnagogic imagery,” the dream-like state that occurs as people fall asleep. In the interest of saving time, Kamitani and colleagues chose to study this type of imagery rather than the dreams that tend to occur during REM sleep later in the night. They woke up each subject at least 200 times over the course of several days to build up a database of dream reports.

In the second part of the experiment, Kamitani and colleagues developed a visual imagery decoder based on machine learning algorithms. They trained the decoder to classify patterns of brain activity recorded from the same three men while they were awake and watching a video montage of hundreds of images selected from several online databases. After the decoder for each person had been trained, the researchers could input a pattern of brain activity and have the decoder predict which image was most likely to have produced that pattern of brain activity.

But that much has been done before. Where Kamitani’s team went beyond previous work was in feeding the decoder patterns of brain activity collected while the subjects were dreaming. This enabled them to correctly identify objects the men had seen in their dreams, they report Apr. 4 in Science. Or rather, they could identify the type of object a subject had seen: it could predict that a man had dreamt about a car, not that he’d been cruising around in a Maserati. And the decoder only worked when the researchers gave it a pair of possible objects to chose from (whether it was a man or a chair, for example).

“Our dream decoding is still very primitive,” Kamitani said.

Decoding color, action, or emotion is also still beyond the scope of the technology, Kamitani says. Also, it only seems to work for imagery that occurred — at most — about 15 seconds before waking up.

Finally, the decoder is unique to each person. To decode the dreams of another person, the team would have to train up a new decoder by having that person view hundreds of images.

Even so, it’s remarkable that it works as well as it does, says neuroscientist Jack Gallant of the University of California, Berkeley and a pioneer of decoding mental states from brain scans. ”It took just a huge amount of non-glamorous work to do this, and they deserve big props for that,” Gallant said.

With refinements, Gallant says the method could be useful for studying the nature and function of dreams.

“There’s the classic question of when you dream are you actively generating these movies in your head, or is it that when you wake up you’re essentially confabulating it,” Gallant said. “What this shows you is there’s at least some correspondence between what the brain is doing during dreaming and what it’s doing when you’re awake.”

Kamitani is thinking about the possibilities too. ”One theory states that dreaming is for strengthening memory, but another theory states dreaming is for forgetting,” he said. “We could record the frequency of decoded dream contents for each memory item and see the correlation between the frequency and the memory performance.”

Sleep and dreaming: The how, where and why

Within a few hours of reading this you will lose consciousness and slip into a strange twilight world. Where does your mind go during that altered state – or more accurately states – we call sleep? And what is so vital about it that we must spend a third of our lives sleeping? In these articles, we review the latest ideas on why we sleep and look at new ways to enhance its benefits.

Decoding Dreams

“[I was] somewhere, in a place like a studio to make a TV program or something,” a groggy study participant recounted (in Japanese). “A male person ran with short steps from the left side to the right side. Then, he tumbled.” The participant had recently been awoken by Masako Tamaki, a postdoc in the lab of neuroscientist Yukiyasu Kamitani of the ATR Computational Neuroscience Laboratories in Kyoto, Japan. He was lying in a functional magnetic resonance imaging (fMRI) scanner, doing his best to recall what he had been dreaming about. “He stumbled over something, and stood up while laughing, and said something,” the participant continued. “He said something to persons on the left side.”

At first blush, the story doesn’t seem particularly informative. But the study subject saw a man, not a woman. And he was inside some sort of workplace. That fragmented information is enough for Kamitani and his team, who recorded dream appearances of 20 key objects, such as “male” or “room,” and used a machine-learning algorithm to correlate those concepts with the fMRI images to find patterns that could be used to predict what people were dreaming about without having to wake them. Such information could help inform the study of why people dream, an elusive question in neurobiology, Kamitani says. “Knowing what is represented during sleep would help to understand the function of dreaming.”

Analyzing more than 200 dream reports—some 30–45 hours of interviews with each of three participants—Kamitani and his colleagues built a “dream-trained decoder” based on fMRI imagery of the V1, V2, and V3 areas of the visual cortex. “We find some rule, or mapping, or pattern between what the person is seeing and what activity is happening in the brain,” Kamitani explains. And it worked, according to Kamitani, who presented the results at the Society for Neuroscience meeting in New Orleans in October 2012, predicting whether or not the 20 objects occurred in dreams with 75–80 percent accuracy.

But while Kamitani’s dream-decoding study is interesting, says neurobiologist David Kahn of Harvard Medical School, the algorithms used are quite primitive, only providing a handful of clues about the dream’s content. “We still have a long way to go before we can actually re-create the story that is the dream,” he says. “This is almost science fiction, because we’re way, way far from it … [but] this is an added tool.”

“Decoding is very primitive,” Kamitani agrees, “but I think there are a lot of potentials.” One way to get a more complete picture of the dream is to increase the complexity of the decoder, he notes. In this first study, for example, the researchers focused on nouns representing visual objects, but going forward, Kamitani says he hopes to include other concepts, like verbs. “By analyzing that aspect we may be able to add some action aspects in the dream.”

Furthermore, researchers might not have to fully interpret the dream themselves to benefit from the new decoder. Instead, the clues gleaned from the fMRI images could simply be used to jog participants’ memories. “We know that dreams—even the most vivid dreams we remember, [like] nightmares or lucid dreams—are really fragile memories,” says Antonio Zadra, an experimental psychologist at the University of Montreal. “Unless you wrote it down or told it to someone in the morning, usually even before lunch, that memory will start fading. And by night, you might just have the essence.”

Unfortunately, that failing memory was the only resource for researchers studying dreams. Now, with a little bit of supplemental information, they may be able to help participants recall dreams more precisely. “The subjective reports are never complete,” Kamitani says. “By giving the subject what we reconstructed, they may remember something more.”

At an even more basic level, the decoder could help scientists understand what’s happening in the brain during dreaming. “To create this whole virtual world out of nothing—with no visual input or auditory input—is quite fascinating and undoubtedly very complex,” Zadra says. “This research will certainly help us better understand what brain areas are doing what, to even allow for this to happen.”

In Kamitani’s study, for example, the researchers found that areas of higher-level visual processing, which respond to more abstract features, were more useful for interpreting dream content than lower-level processing areas. This makes sense, given that those lower areas of the visual cortex are more closely connected to the direct input from the retina. But, Kamitani notes, this could simply have to do with the way the study was designed. “We didn’t train the decoder with low-level visual features,” such as shape or contrast, he says. “We just used the semantic category information.”

Indeed, given the richness of the dreaming experience, such visual qualities may well be encoded during sleep. “Your brain creates a whole virtual world for you when you are dreaming, complete with characters, settings, interactions, dialogues,” says Zadra. “But you’re actually in your bed asleep; there is no visual input. So your brain is literally creating this virtual world from A to Z.”