SDDb Upgrade

At long last, after many twists and turns, a new and improved version of the Sleep and Dream Database (SDDb) has been released, just in time for spring! Many thanks to the Elsewhere.to team–Gez Quinn, Kat Juncker, Dan Kennedy, and Victoria Philibert–for their help in the upgrade process.  The SDDb is a growing archive of dream reports and survey data, with analytic tools designed to be used by anyone, from curious newcomers to advanced researchers. The SDDb offers two basic methods of studying dreams. One is to analyze the database’s collection of 18 demographic surveys to discover patterns of sleep and dreaming in relation to variables like age, ethnicity, sex assigned at birth, and religious beliefs. The second is to search the database’s collection of more than 45,000 dream reports gathered from many sources and available to study using built-in tools for identifying, analyzing, and comparing the frequencies of different categories of content.

Many features still need attention, along with better labeling for various questions and categories. Soon I will create written and video tutorials to help users navigate the SDDb’s collections and tools. With so much focus on the upgrade, I’ve been waiting to upload a few new series, and those should now get into the database in the very near future. If you have any suggestions to offer and/or problems to point out, I’d be grateful to hear them.

Dreaming of the Future: The Anticipatory Function of Dreams

Throughout history, people have believed prophetic dreams can give us glimpses of future events. Is there any reason to believe such dreams are possible?

It would seem not. Most instances of a dream predicting a significant event in waking life are probably just coincidences. For example, people periodically dream of car crashes, so at some point a person will dream of a car crash the night before actually getting in a car crash. That’s not prophecy, that’s just the law of averages. The claims people make about future-telling dreams are most likely to be fantasies, fabrications, or failures of causal reasoning.

That may be the safest position to take. It’s not the most scientific position, however, because it isn’t based on evidence, just a resolute skepticism. The actual evidence in support of anticipatory dreaming is not so easily dismissed, and merits more serious attention than it typically receives.

As far as evidence from history, the material presented in Lucrecia the Dreamer: Prophecy, Cognitive Science, and the Spanish Inquisition (2018) offers the best documented case study of dreams that accurately predicted a major event in waking life. In the late 16th century a group of Spanish priests carefully recorded and transcribed the dreams of an illiterate young woman, Lucrecia de Leon. Over a period of nearly a year, several of her dreams predicted the failure of the Spanish Armada in its attack on England, despite all signs of Spain’s superiority in the upcoming battle. When the Armada suffered a shocking and humiliating defeat in 1588, Lucrecia’s dreams were proven right in the most spectacular way possible. Unfortunately, this did not prevent her from being arrested by the Inquisition and charged with treason and heresy.

A case study like this has to do with just one person, so it’s hard to know how far we can legitimately generalize from Lucrecia’s experiences to other people. But we can draw on additional sources of information about contemporary people. In the “2015 Demographic Survey” in the Sleep and Dream Database, one of the questions asked whether the individual had ever had a dream that seemed to anticipate or predict a future event. Out of 2,303 total participants (1,304 female, 999 male, all American adults) responding to an online survey administered by YouGov, 30% of the females and 19% of the males answered yes, they had experienced such a dream at least once in their lives. The results of this survey can be viewed here.

The findings from this survey suggest that most people do not recall having a predictive dream, but a significant number of people (considerably more women than men) do claim to have had such dreams. Prophetic dreaming is not just a historical oddity, or a pre-modern superstition. Future-oriented dreams play an active role in the lived experience of many, many people in contemporary society.

The question is often raised of how to explain such dreams in terms of current scientific knowledge. The best answer, I believe, comes from looking at anticipatory dreaming as a special case of dreaming in general. To summarize a great deal of research, dreams have a broadly adaptive function in the mind and brain: promoting healthy growth, stimulating creative energies, and helping people respond to challenges, threats, and opportunities. The content of dreams typically revolves around the most important emotional concerns in the individual’s waking life, and dreaming becomes especially intense and meaningful at times of crisis and uncertainty.

If we recognize these features of natural, normal dreaming, then it becomes easier to appreciate how and why dreams can anticipate future possibilities. In waking life our minds do this all the time—we plan, predict, rehearse, and prepare for important events coming in the future. Our minds continue to do this when we sleep at night, but with fewer distractions from external stimuli and more cognitive freedom to explore alternative, “what if?” scenarios. There is nothing supernatural or fanciful about this. Indeed, this ability to imagine and think about the future has given our species an enormous advantage through the course of evolutionary history. This is the best explanation for what people have traditionally called prophetic dreaming: the forward-thinking capacity of the human mind operates in both waking and dreaming.

The Swiss psychologist Carl Jung was an early advocate for this idea. He proposed a “prospective” function for dreams, in which various impressions from daily experience are brought together in the unconscious and used to envision possible aspects of the individual’s future (an idea which can be traced back to the ancient Greek philosopher Aristotle). In some cases, the dreaming anticipations are more prescient than what the waking mind can apprehend. Jung said that dreams provide

“an anticipation in the unconscious of future achievements, something like a preliminary exercise or sketch, or a plan roughed out in advance… The occurrence of prospective dreams cannot be denied. It would be wrong to call them prophetic, because at bottom they are no more prophetic than a medical diagnosis or a weather forecast. They are merely an anticipatory combination of probabilities which may coincide with the actual behavior of things but need not necessarily agree in every detail. Only in the latter case can we speak of ‘prophecy.’ That the prospective function of dreams is sometimes greatly superior to the combinations we can consciously foresee is not surprising, since a dream results from a fusion of subliminal elements and is thus a combination of all the perceptions, thoughts, and feelings which consciousness has not registered because of their feeble accentuation… With regard to prognosis, therefore, dreams are often in a much more favorable position than consciousness.” (“General Aspects of Dream Psychology”)

Perhaps there is a transcendent capacity of the human mind at work in these dreams. Perhaps our souls are tuning into other metaphysical realities, or being visited by spiritual beings who share with us their knowledge of the future. Whether or not these beliefs have ultimate merit, Jung’s point is valid in terms of current psychological knowledge of brain-mind functioning across the cycle of waking, sleeping, and dreaming.

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This was first posted in Psychology Today, November 22, 2019.

 

 

1,001 Nights of Dream Recall

Between January 8, 2015 and October 4, 2017, I remembered and recorded a dream every night for 1,001 consecutive nights.  Now I’m studying the dreams and trying to find insights that can help in exploring the dream series of other people.  I don’t expect anyone to accept my personal dreams as conclusive evidence for any general theory of human dreaming.  Instead, I offer them as way of being transparent about the experiential grounding of my research pursuits.  This is one of the ways I get ideas for new projects.

All of the dreams are available online for further study in the SDDb, in the “Sample Data” section.

From a scientific perspective, the value of an introspective project such as this is to generate working hypotheses for future studies.  Trying to study another person’s long diary of dreams can be very challenging, especially at the outset when the researcher is facing a huge mass of texts with multiple dimensions of meaning.  I appreciate anything that can provide some initial orientation and help to steer the direction of the analysis.  By studying my own dreams, which I know from both a first- and third-person perspective, I can quickly and easily identify some patterns of meaning that seem worth further exploration.   Maybe they will apply to someone else’s dream series, maybe they won’t; either way, it helps the analytic process get going.

Remembering and Recording the Dreams

The method I use for keeping my dream journal is fairly typical.  I keep a pad of paper and a pen by my bedside, and when I wake up in the morning I immediately write down whatever dreams I can remember, before getting out of bed or turning on the light.  Then later in the morning I type the dream into a digital file, along with associations, memories, and thoughts about what the dream might mean.

During the three years of recording this series of 1,001 dreams, I did my best to wake up slowly each morning, so the images and feelings from the preceding dreams could coalesce in my memory.  I don’t believe I dreamed more during this time than I did in previous periods of my life; rather, I devoted more energy to remembering the wispier, more evanescent kinds of dreams that, in previous years, had not crossed the threshold into waking memory.  I made a more determined effort to protect the space around the transition from sleeping to waking, even during circumstances when that was difficult to do (e.g., on international plane flights, during family holidays).  Often it took a few moments of quietly lying in bed with my eyes closed before the vague feeling “I know I was just dreaming,” could eventually take form into a specific memory of what I was just dreaming about.  Often there were “aha!” moments when suddenly a whole long dream came back to me, which I surely would have forgotten if I had immediately leapt out of bed upon awakening.

I also put more conscious intention into the other end of the transition, from waking into sleeping, as I carefully set up my journal and pen each night before turning out the light.  I did not set specific dream incubation questions during this time, but simply tried to signal to myself that I was ready and willing to record whatever dreams might come during that night’s sleep.

These were not extreme or burdensome behaviors; they required consistency of purpose, but no heroic feats of will.  I never set any long-term goals or numerical targets.  Instead, I just focused on each new night and each new dream, figuring the time would come when I could survey the series from a broader perspective.

About a month ago I finally did the math, and realized that October 4th would mark 1,001 nights of dream recall in a row, an enchanting milestone.  This seemed like a large enough collection of dreams to pause, look back, and see what I could learn.

Patterns of Word Usage

The reports comprise a total of 93,050 words, with an average length per dream report of 93 words, and a median length of 73 words.  The shortest dream in the series has 9 words, and the longest has 728 words.  The average length of these dreams is not unusual, compared to other people whose dreams have been analyzed in this way.  Some people have much longer dreams than I do, and some people have much shorter dreams.  This series of 1,001 dreams, then, includes mostly dreams of middling length.

To highlight the patterns and themes in a series like this, I start by comparing it to what I call the “SDDb baselines,” two large collections of male (N=2,135) and female (N=3,110) dreams that have been systematically gathered and analyzed using a template of 8 classes and 40 categories of word usage.   I use the baselines a measuring stick for identifying possible continuities and discontinuities between the dreams and the individual’s waking life.

The results of this comparative analysis are presented in an accompanying spreadsheet, “1001 Nights Data.”  Some of the discussion below draws on an earlier analysis I wrote about an overlapping set of my dreams.

In relation to the SDDb baselines (an average of 100 words per report for the females and 105 for the males), my dreams are a little shorter than average (93 words per report).  The results for each of the 8 classes of word usage are summarized below.  Compared to the male and female baselines, my 1,001 dreams have:

  1. Perception: More references to vision and colors.
  2. Emotion: Many more references to wonder/confusion, and more to happiness.
  3. Characters: Fewer references to family characters (although the word “wife” is mentioned very frequently), more references to animals (especially cats), and slightly more references to females than males.
  4. Social Interactions: Slightly more references to sexuality.
  5. Movement: Fewer references to death.
  6. Cognition: More references to thought, fewer to speech.
  7. Culture: Fewer references to school, food/drink, religion, somewhat more to sports (especially baseball and basketball).
  8. Elements: More references to water, somewhat more to earth.

These findings provide the basis for a “blind analysis,” which means making predictions about continuities between these patterns of word usage in dreaming and the individual’s waking life activities, beliefs, and concerns.  If I pretend I knew nothing about the dreamer of these 1,001 dreams, and I only had these word usage frequencies to consider, I would infer this individual:

  1. Is visually oriented
  2. Often experiences wonder/confusion
  3. Is relatively happy
  4. Is married
  5. Cares about cats
  6. Has fairly equal relations with men and women
  7. Is sexually active
  8. Is not concerned about death
  9. Is not highly verbal
  10. Is not highly involved with schools
  11. Is not highly concerned about food/drink
  12. Is not highly concerned about religion
  13. Has lots of interactions with water and earth

Most of these inferences—I’d say 11 of 13—are unmistakably accurate in identifying a continuity between a pattern of dream content and an aspect of my waking life concerns.  The two I would question are numbers 10 and 12.  Regarding the low frequency of dream references to school, I do in fact engage in a great deal of teaching and educational work, but it’s almost entirely online, and I rarely set foot inside a traditional school any more.  Also, I no longer have school-age children living at home.  So it seems my dreams are continuous with my physical behaviors relating to schools, but not with my computer-mediated educational activities.

Regarding the low frequency of religion references, I most certainly do have great interest in religion, going back to my masters and doctoral studies at the Divinity Schools of Harvard and University of Chicago.  So the inference seems very wrong at this level.  And yet, at another level it seems more accurate.  I was not raised in a religious household, I do not personally identify with any official religious tradition, and I rarely attend religious worship services.  Compared to other people I’ve studied with very high frequencies of references to religion in their dreams, I am a much less personally pious person.  Perhaps what this suggests is that the dreams are accurately reflecting the fact that religion may be an important intellectual category for me, but it is not a personal concern.  My spiritual pursuits are more likely to be expressed in dreams with references to other word categories like water, art, sexuality, animals, and flying.

Shorter versus Longer Dreams

Earlier this year I looked at different set of my dreams to get some idea about possible differences between shorter and longer dreams.  This question rose in relevance when I realized, as noted earlier, that my increased recall seemed to depend in part on the recollection of relatively shorter dreams that in the past I did not fully remember or write down.

There were two main findings of that earlier study.  First, most of the patterns in content appeared in dreams of all lengths, from the shortest (less than 50 words per report) to the longest (more than 150 words per report).  Here’s a summary of what I found:

“The results of this analysis suggest that shorter dreams are not dramatically different from longer dreams in terms of the relative proportions of their word usage.  The raw percentages of word usage do rise from shorter to longer dreams, of course, but the relative proportions generally do not.”

Second, the longer dreams did have proportionally more references to a few word categories, chiefly Fear, Speech, Walking/Running, and Transportation. Another quote:

“These are the word categories that seem to be over-represented in longer dreams.  They are significant contributors to what makes long dreams so long.”

Returning to the present collection of 1,001 dreams, I divided the series at the median point into two groups: the shorter dreams (72 words or less, 500 reports total) and the longer dreams (73 words or more, 501 reports total).  I used the same SDDb word searching template with each of the two groups as I used with the full series, and then I compared their frequencies of word usage.  The biggest variations between the shorter and longer dreams appeared in the following categories:

  • Touch
  • Fear
  • Anger
  • Physical aggression
  • Walking/Running
  • Speech
  • Transportation
  • Water

This list adds a few other categories that may be characteristic of longer dreams.  Each of these categories has a dynamic quality.  Touch is a physical interaction.  Fear and anger are strong and unpredictable emotions, usually prompted by something in the external environment.  Physical aggression combines the previous categories (touch, fear, anger) and possibly intensifies them.  Walking/Running and Transportation both involve physical movement from one place to another.  Speech implies a context of interpersonal communication, people talking with each other.  Water, the “universal solvent,” is ever-shifting in its states (gas, liquid, solid) and its movement through human life.

When these elements appear in my dreams they seem to have the effect of expanding the range of experience, stimulating more interactions, and lengthening the narrative.

Conclusion

I don’t know if any of this applies to anyone else’s dreams.  I do, though, believe that several of the insights gained here can provide working hypotheses for studying other series of dreams.  I will be keeping these ideas in mind as I explore new dream series:

  • The recall and recording methods of the dreamer influence the types of dreams included in the series.
  • Personal relationships are an area of especially strong continuity between waking and dreaming life.
  • The use of religion-related words in dreams may be discontinuous with spiritual interests in waking life.
  • Shorter dreams have mostly the same general proportions and patterns of content as found in longer dreams.
  • Longer dreams tend to include more dynamic elements.

 

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Notes:

The accompanying spreadsheet can be found here:

https://www.academia.edu/35024762/1001_Nights_Data.xlsx

More description of the SDDb baselines can be found in Big Dreams: The Science of Dreaming and the Origins of Religion (New York: Oxford University Press, 2016).

The earlier study of short versus long dreams can be found here:

Short vs. Long Dreams: Are There Any Differences in Content?

 

What Kinds of Technology Do People Dream About Most Frequently?

50.ford_.crestlinerThe past one hundred years of human history have been dramatically transformed by the invention of several new technologies, each of which has impacted people’s lives in profound and complicated ways.

In light of empirical research showing strong continuities between waking and dreaming, we can hypothesize that modern technologies have also made a tangible impact on the content of people’s dreams.

And indeed, there is evidence in support of that idea. By analyzing a collection of more than 16,000 dream reports available for study on the Sleep and Dream Database (SDDb), it becomes possible to examine which kinds of technology have most influenced people’s dreams in terms of their frequency of appearance.

The results suggest the newest technologies are not necessarily the most important ones in the world of dreams.

To explore this question I looked at all the dream reports on the SDDb of 25 words or more in length for Females (N=10,168) and Males (N=6,590), and selected the “Technology and Science” category from the 2.0 word search template.

This is a quick and dirty approach, but it has the virtue of providing an easy and relatively straightforward means of getting an evidence-based response to the question.

The results for the Females were 990 dream reports with at least one reference to a word in the “Technology and Science” category, approximately 10% of the total number of dreams. The figures for the Males were 602 and 9%.

Looking in more detail at which terms appeared most frequently (these include singular and plural uses of the term), the results for the Females were these:

Phone, 3.55%

Movie, 3.18%

Video, 1.26%

Computer, 1.2%

Machine, .91%

Radio, .65%

Camera, .62%

Television, .26%

And for the Males:

Phone, 2.69%

Movie, 2.47%

Video, 1.27%

Computer, 1.03%

Machine, 1.02%

Radio, .47%

Camera, .49%

Television, .36%

I did a parallel search with the same two sets using the SDDb 2.0 word search template category for Transportation. These results—24% of the dream reports for both Females and Males had at least one reference to a Transportation word—are much higher than the Technology and Science frequencies.

Looking more closely at specific forms of transportation appearing in people’s dreams, these were the results for the Females:

Car, 9.12%

Boat, 1.92%

Bus, 1.81%

Airplane, 1.49%

Truck, 1.26%

Elevator, 1.16%

Bicycle, .86%

And for the Males:

Car, 8.18%

Boat, 2.12%

Bus, 1.65%

Bicycle, 1.56%

Airplane, 1.46%

Truck, 1.37%

Elevator, .67%

The first thing to note is the remarkable gender balance. On almost all the categories and word clusters, the Female and Male frequencies are extremely close. (The main exceptions are slightly more Bicycle references for the Males, and slightly more Phone, Movie, Car, and Elevator references for the Females.) This consistency across so many terms suggests that modern technologies have impacted men and women about equally.

Secondly, the analysis indicates that the most frequently appearing modern invention in dreams is the automobile. It seems that technologies of transportation have had more of an impact on people’s dreams than have technologies of communications and entertainment.  Add in trucks and buses to cars, and the predominance of the internal combustion engine in dreaming becomes even greater.

Why might this be? I’m not sure, but I wonder if technologies of transportation have more of a visceral impact on people’s lives. Telephones, movies, videos, and computers can be fascinating and absorbing, but they do not directly affect a person’s body with the kind of sensory intensity that people feel during a car ride.

Whatever the explanation, the results of this brief study indicate that the most frequently appearing type of modern technology in dreams is one that was invented more than one hundred years ago. Newer technologies like computers and videos have not (yet) made as big an impression on the dreaming imagination.

Maybe future developments in virtual reality will enable a more powerful stimulation of people’s physiological responses, prompting a rise in VR-related dreams. But that remains a far-off possibility.

Until then, cars remain for most people the dream technology of choice.

 

Note: here are the word strings for the specific technology and transportation searches:

Phone: phone phones telephone telephones iphone iphones. Video: video videos. Computer: computer computers. Machine: machine machines machinery. Radio: radio radios. Camera: camera cameras. Television: television televisions tv tvs.

Car: car cars auto autos automobile automobiles. Boat: boat boats ship ships. Bus: bus buses. Bicycle: bicycle bicycles bike bikes. Airplane: airplane airplanes plane planes. Truck: truck trucks. Elevator: elevator elevators.

Big Data and the Study of Religion: Can a Google Search Lead to God?

Google religionA recent essay in the Sunday Review Section of the New York Times made several observations about religion in contemporary America by analyzing a huge collection of Google search data. In “Googling for God,” economist Seth Stephens-Davidowitz examined the search results for various religious terms and questions in relation to where the people lived and when they performed the searches. Stephens-Davidowitz’s work offers an excellent illustration of the pros and cons of using big data analytics to study religion. Three quotes from his essay show where the biggest challenges can be found.

  1. “If people somewhere are searching a lot about a topic, it is overwhelming evidence those people are very interested in that topic.”

This is the key methodological principle used in Stephens-Davidowitz’s analysis: the frequency of Google searches correlates to the intensity of personal interest. At one level this seems like a reasonable premise. In fact, this principle is very close to the “continuity hypothesis” used by dream researchers to correlate frequencies of dream content with personal concerns in waking life. Many dream researchers, myself included, have pursued studies of dream content using the continuity hypothesis to make inferences about people’s waking lives—if a person dreams a lot about sports, for example, we can confidently predict that sports are an important concern in the person’s waking life.

Stephens-Davidowitz does something similar when he connects Google search data to people’s religious concerns and questions. The problem, however, is defining “very interested.” What exactly can we infer about a person based on their entry of a Google search term? They are “interested,” of course, but interested in what way, and how strongly? What prompted their search? Is there anything distinctive about people’s searches for religious terms compared to non-religious terms?

Until these kinds of questions can be answered (ideally with lots of systematically analyzed empirical evidence, not just one-off studies), the use of Google search data to draw conclusions about religion remains on shaky ground.

In dream research we have many decades of studies that have helped us hone in on “emotional concerns” as a primary point of continuity between dreaming and waking. We also have statistical baselines of typical dream content to help us identify meaningful variations in the frequency of certain aspects of dreaming (see, for example, the Dreambank of G. William Domhoff and Adam Schneider, and the Sleep and Dream Database (SDDb) that I direct). If the use of Google search data included these kinds of analytic aids, the results would be much stronger and more convincing.

  1. “Sometimes Google search data, because of Google’s status as a kind of universal question service, is perfectly suited to give us fresh insights into our offline lives.”

The idea of Google as a “universal question service” has great appeal, not the least because so much of the information is easily accessible for public study. This is one of the great boons of the era of big data, and new studies of this treasure trove of information are bound to increase in future years.

A potential problem, however, is a tendency to blur the distinction between a) what Google offers its users and b) who those users are. The fact that Google enables people to ask all kinds of questions does not mean that all kinds of people are asking those questions. Google users are not necessarily representative of the US population as a whole, and we do not know how representative the Google users are who are searching specifically for religious terms. We do know that when people perform a Google search they are connected via technology to the internet, they are interacting with a global corporation, and they are being shown numerous commercial responses to their search. These circumstances should qualify our assumptions about who uses Google and how they engage with the search function.

  1. “There are 4.7 million searches every year for Jesus Christ. The pope gets 2.95 million. There are 49 million for Kim Kardashian.”

This quote comes at the end of the essay, and it perfectly encapsulates the difficulty of explaining the significance of Google search results. According to the findings cited by Stephens-Davidowitz, Kim Kardashian gets ten times the search results of Jesus Christ. What exactly does that mean? That Kim Kardashian is ten times more interesting than Jesus? That she is ten times more popular, or more important, or more influential?

The problem is that Google search data do not meaningfully measure any one thing, other than the tautological fact of having entered a specific search term. The results of analyzing these data seem admirably clear and quantitative—4.7 million vs. 49 million!—but they do not easily or self-evidently map onto the actual beliefs, feelings, and attitudes of the general population.

The good news is that these are tractable problems. Real progress can be made by more detailed studies and more systematic correlations of the data with genuinely meaningful aspects of people’s lives. This fascinating essay by Seth Stephens-Davidowitz helps people who study religion see where these new analytic endeavors can be most fruitfully pursued.

 

Note: first published September 24, 2015 in the Huffington Post.

Dream Incubation: An Interview with Arianna Huffington

UnknownThe Huffington Post recently published an interview I did with Arianna Huffington about dream incubation.  She has a long-standing interest in sleep and dreams, along with spiritual curiosity and an appreciation for scientific research–a perfect audience for what I’ve been working on over the past couple of years.  What I told her about dream incubation comes from chapter 15 of the book Big Dreams: The Science of Dreaming and the Origins of Religion (Oxford U. Press), due out in early 2016.  That’s the next-to-last chapter of the book, which starts with a section on the evolution of sleep, laying a scientific foundation for understanding how dreams have emerged in the human species.  The second section looks at empirical patterns in ordinary dream recall and content, drawing on research from the Sleep and Dream Database (SDDb).  The third section focuses on “big dreams,” i.e. rare but extremely vivid and memorable dreams that make a long-lasting impression on waking awareness.  I discuss scientific research on four prototypes of big dreaming that recur especially frequently, throughout history and in cultures all around the world: aggressive, sexual, gravitational, and mystical.  Finally, in the fourth section, I use this information about big dreams to shed new light on several kinds of religious experience found in many different traditions: demonic seduction, prophetic vision, ritual healing, and contemplative practice.  Dream incubation appears in the chapter on ritual healing, with lots of discussion of the Roman orator Aelius Aristides in the 2nd century CE, who wrote about his dream incubation experiences at a temple of the ancient Greek healing god Asclepius.