States of Consciousness Research Paper

This sample States of Consciousness Research Paper is published for educational and informational purposes only. If you need help writing your assignment, please use our research paper writing service and buy a paper on any topic at affordable price. Also check our tips on how to write a research paper, see the lists of psychology research paper topics, and browse research paper examples.

The term consciousness has a long history in psychology. One way to assess the concept is to consider how it has been addressed in our discipline’s gateway—introductory psychology texts. The first edition of the classic R. C. Atkinson and R. L. Atkinson textbook appeared in 1957. The tenth edition of this text was published in 1990. The topic of consciousness occupies a chapter in a section of the text titled Consciousness and Perception; the specific chapter that deals with the topic is titled Consciousness and Its Altered States. The breadth of topics in this research-paper is similar to what we find in more recently published textbooks (e.g., Davis & Palladino, 2007; D. H. Hockenbury & S. E. Hockenbury, 2006) and includes subtopics such as aspects of consciousness (conscious, unconscious, subconscious), divided consciousness, dissociation and multiple personality, sleep and dreams, psychoactive drugs, meditation, and hypnosis. The authors begin their chapter with these words:

As you read these words, are you awake or dreaming? Hardly anyone is confused by this question. We all know the difference between an ordinary state of wakefulness and the experience of dreaming. We also recognize other states of consciousness, including those induced by drugs such as alcohol and marijuana. (R. L. Atkinson, R. C. Atkinson, Smith, & Benn, 1990, p. 195)

Despite the apparent clarity of the opening of the Atkinson et al. (1990) chapter on consciousness, the topic is perhaps one of the more difficult ones for the discipline, as its history reveals. Wilhelm Wundt’s (1832-1920) founding of the first psychological laboratory in 1879 heralded his attempt to identify and categorize elements of conscious experience using the method known as introspection, or examination of one’s own mental state. Wundt’s student, Edward Bradford Titchener (1867-1927), brought Wundt’s approach to the United States and initiated a perspective known as structuralism. Another early psychologist, William James (1842-1910) also expressed interest in consciousness. He wrote about the stream of consciousness and described it as continuous, changing, and having depth. In contrast to Wundt and Titchener, James did not focus on analyzing and reducing conscious experience to its supposed elements. To him, attempting to divide this stream would distort the unity of conscious experience.

Despite the close connection between consciousness and the founding of the discipline, the topic of conscious-ness would fall into disfavor for quite some time. The development of the behavioral movement, led by John B. Watson (1878-1958), focused on observable behaviors; there was no allowance for the nonscientific discussion of what could not be observed—conscious experience. In 1913 Watson wrote, “Psychology as the behaviorist views it is a purely objective experimental branch of natural science. Its theoretical goal is the prediction and control of behavior. Introspection forms no essential part of its methods” (p. 158). Thus, the study of consciousness was, if not banned, certainly placed firmly on the back burner for several decades.

Nevertheless, advances in techniques and monitoring equipment have made it possible to conduct more sophisticated research than Wundt or Titchener would have ever thought possible. For example, in 1929, Hans Berger developed the electroencephalograph (EEG), which monitors and records brain activity through electrodes attached painlessly to the skull. The common belief that the EEG provides electrical stimulation to the brain is a myth. The brain’s electrical signals are amplified and printed out, producing a record of brain waves. Several commonly observed brain waves are alpha, beta, theta, and delta (more on brain waves later in this research-paper).

Although the EEG was a major advance, it does have several limitations. For example, although brain waves provide some evidence of activity occurring in the brain, this information is generally an imprecise picture of brain activity. One could compare the information obtained from an EEG to what we know when we pass outside a football stadium and hear the crowd noise as they react to the game. You might have a general notion of what occurred but you would find it difficult to provide specifics concerning the activity that is occurring inside that stadium.

Nonetheless, the EEG does have its uses—for example, it is helpful in diagnosing epilepsy, in identifying certain sleep disorders such as narcolepsy (National Institute of Neurological Disorders and Stroke, 2006; Honma et al., 2000), and in sometimes providing information on the presence and location of brain tumors. An EEG also can be used to confirm a state called brain death, in which a flatline EEG tracing indicates the absence of brain activity (Afifi & Bergman, 2005). The more recently developed and highly sophisticated magnetoencephalography (MEG) measures the brain’s magnetic fields and can determine levels of electrical activity in a more precise manner than a standard EEG (Huettel, Song, & McCarthy, 2004).

The development of computers has been responsible, in part, for a major leap forward in the understanding of brain activity during various states of consciousness. Scientists interested in consciousness no longer have to rely on measures such as the EEG. In fact, “Where questionnaires, interviews, and observations of behavior once reigned supreme, fancy machines now create portraits of brains at work” (Bower, 2002, p. 251). Newly developed techniques can even record the activity of a single neuron; however, in general practice they produce various images of the brain (some static and some of ongoing activity). These brain-imaging techniques are significant advances for diagnosis and research, especially in comparison to the EEG and the X-rays of the brain that have been used in the past. Here is a list of some of these advanced brain-imaging techniques:

Positron emission tomography (PET): a dynamic scan that can provide evidence of ongoing brain activity by measuring the brain’s metabolic activity.

Computerized axial tomography (CT or CAT): a brain-imaging technique that involves computer interpretation of a large number of X-rays.

Magnetic resonance Imaging (MRI): uses a strong magnetic field and radio waves to produce very detailed pictures of the brain. Functional magnetic resonance imaging (fMRI) is a modified version of the MRI that is capable of providing both excellent structural views of the brain and ongoing changes in brain activity. (Huettel et al., 2004)

What Is Consciousness?

A common definition of consciousness is “personal awareness of feelings, sensations, and thoughts at a given moment” (Davis & Palladino, 2007, p. 133). Our consciousness, or awareness, can be said to vary across a continuum ranging from complete awareness at one end of the spectrum to coma, vegetative states, and brain death or complete lack of awareness at the other end. Throughout the day, we experience changes in our consciousness, from full involvement and engagement in a task to states of drifting consciousness (How many of us have no memory of having driven ten miles since the last exit?) and finally to sleep or perhaps other loss of consciousness such as during surgery, a coma, or a vegetative state.

Various forms of fantasy and imagination are common examples of changes in our level of awareness. The change in consciousness we call daydreaming is one such common experience. The frequency of daydreaming is highest among children and tends to drop with age (Giambra, 2000). In children, fantasy life may extend to the creation of imaginary companions, which is quite common (Bower, 2005).

Who have not found themselves daydreaming while driving or listening to a lecture? Most daydreams are spontaneous images or thoughts that pop into our mind for a brief time and are quickly forgotten. Some people can use their daydreams to solve problems or to rehearse a sequence of future events. Nevertheless, most daydreams are related to everyday events such as deciding what we will eat for dinner later in the day or thinking about the sports car we would love to drive if only we could afford it! In fact, about two thirds of daydreams are connected to our immediate situation and surroundings. Contrary to popular belief, only a small portion of daydreams involve sexual content (Klinger, 1990), although approximately 95 percent of men and women report having had sexual daydreams at some time (Leitenberg & Henning, 1995).

Daydreams would seem to be rather elusive phenomena to study because they are hard to predict and hard to capture. Consequently, researchers have had to be creative in devising methods to study daydreams. One especially useful technique involves equipping people with beepers designed to sound at random intervals to signal them to report their daydreams in written form (Klinger, 1990). Researchers have also used physiological measuring devices to study daydreams; daydreaming seems to be associated with changes in the ratio of different brain waves (Cunningham, Scerbo, & Freeman, 2000).

Hypnosis

One of the most controversial topics in psychology may be hypnosis. The connection to stage hypnosis often makes the public wonder if there is anything behind what is often perceived as just stage effects designed for entertainment purposes (Streeter, 2004). We can trace the history of hypnosis to Franz Anton Mesmer (1734-1815), an Austrian physician, who captured the imagination of residents of Paris by claiming that he could cure anything that was ailing them. He believed the atmosphere was filled with invisible magnetic forces he could harness for their curative powers; people with a variety of ailments sought his supposed healing powers. His efforts to harness those supposed magnetic forces became known as a technique called mesmerism. Despite numerous testimonials in support of his treatment efforts, in 1784 a scientific commission chaired by Benjamin Franklin determined that what Mesmer seemed to achieve was the result of his patients’ imagination, not invisible magnetic forces. Nevertheless, his techniques survived in the hands of James Braid (1795-1860) a Scottish surgeon who changed the name from mesmerism to hypnosis. Although the word is derived from the name of the Greek god of sleep, hypnosis is not sleep. The French physician Jean-Martin Charcot (1825-1904) studied hypnosis, and as a result it developed a degree of respectability as an area of medicine. Sigmund Freud learned to use hypnosis from Charcot, and used it as a treatment technique early in his career.

A common definition of hypnosis is “a social interaction in which one person, designated the subject, responds to suggestions offered by another person, designated the hypnotist, for experiences involving alterations in perception, memory, and voluntary action” (Kihlstrom, 1985, p. 385). Historically, researchers have used the concept of suggestibility or susceptibility to explain phenomena subsumed under the term hypnosis. The term reflects the degree to which a person follows suggestions offered by the hypnotist. In a typical hypnotic treatment, the hypnotist creates a situation in which the hypnotized person is more likely to follow his or her suggestions. The process of putting someone in a hypnotic state, called a hypnotic induction, usually involves having the person stare at an object (such as a watch), inducing relaxation, and encouraging drowsiness. A person’s degree of suggestibility to hypnosis can be assessed by using measures such as the Stanford Hypnotic Susceptibility Scale, which consists of a series of 12 activities designed to assess the depth of the hypnotic state. For example, the person may be told that he or she has no sense of smell, then the hypnotist will wave a vial of ammonia under the person’s nose. The person’s subsequent reaction to the ammonia reveals his or her responsiveness to hypnosis (Nash, 2001). Scores on measures of suggestibility or susceptibility follow a normal curve (Patterson, 2004) and tend to be quite stable across time (Nash, 2001). What’s more, “Hypnotizability is unrelated to personality characteristics such as gullibility, hysteria, psychopathology, trust, aggressiveness, submissiveness, imagination, or social compliance. The trait has, however, been linked tantalizingly with an individual’s ability to become absorbed in activities such as reading, listening to music, or daydreams” (p. 49).

There are numerous claims surrounding hypnosis, including its ability to reduce pain, to treat addictions such as smoking and alcoholism, to overcome shyness, and to treat insomnia (Streeter, 2004). A review of 18 published studies of hypnotic pain relief indicated that 75 percent of the participants obtained substantial pain relief from hypnotic techniques (Montgomery, DuHamel, & Redd, 2000). Nevertheless, the mechanisms responsible for the reported pain reduction associated with hypnosis are not clear (Nash, 2001).

One of the most controversial aspects of hypnosis is the claimed ability to improve memory, especially for criminal activity or cases of abuse. Despite claims for its effectiveness, evidence indicates that hypnosis can lead to a situation in which false memories can be created, whether intentionally or unintentionally (Yapko, 1994). As a result, most hypnotically elicited testimony is now excluded from our court system (Newman & J. W. Thompson, 2001).

The controversy concerning hypnosis lies in attempts to explain it. One argument notes that what we label hypnotic behavior is simply a person following what he or she believes is the role of a hypnotized person. Thus, this cognitive-social explanation argues that hypnosis does not involve an alteration in consciousness; it is simply acting out a role. As Ernest Hilgard (1991) noted, “I would be more comfortable for the investigator if there were some precise indicator of the establishment of a hypnotic condition” (p. 30). An alternative explanation, offered by E. R. Hilgard (1904-2001), posits a process of dissociation in which there is a splitting of conscious awareness, which may well resemble the splitting of consciousness that occurs during everyday activities as simple as driving a car while one’s mind seem to wander. More recently, researchers using PET scans (Kosslyn, W. L. Thompson, Costantini-Ferrando, Alpert, & Spiegel, 2000) asked hypnotized and nonhypnotized individuals to imagine that brightly colored shapes were actually gray; they were also shown gray shapes and asked to imagine that they were brightly colored. Under hypnosis, there were observed changes in both hemispheres rather than a change only in the right hemisphere, which suggests that there are actual brain changes that occur during hypnotic inductions. In other words, the subjective experience that occurred under hypnosis was accompanied by a distinct change in the brain. It is difficult to imagine that such changes in the brain could be due to efforts to enact a role.

Anesthetic Depth

Although daydreaming is quite common, the next example of a change in consciousness is quite uncommon.

Consider the following: Jeanette awoke on the operating table, her hernia surgery still underway. She could hear her surgeon discussing the shape of her breasts and body while experiencing “a blow torch in my stomach.. .every tissue tearing like a piece of paper” (Willwerth, 1997). Paralyzed from the muscle relaxants administered along with her anesthesia, she was powerless to tell her surgeons that she was suffering the humiliation of their conversation along with the agony of the procedure they were performing. “You’re screaming as loud as you can inside your head. It’s like being raped and buried alive” (Willwerth, 1997). This story may read like the opening of a horror film but it is a reality for what some estimate to be as many as 40,000 surgery patients a year (Beyea, 2005). Paradoxically called “anesthetic awareness,” it reportedly occurs in 1 of every 1,000 surgical patients (Molyneux, 2000). The paradox lies in the very definition of anesthesia. Prys-Roberts (1987) defined anesthesia as a state of drug-induced unconsciousness in which the patient neither perceives nor recalls a noxious stimulus. By definition, therefore, anesthesia assumes a lack of awareness. Indeed, this paradox points to a critical point in understanding anesthesia and consciousness: As we have noted, states of consciousness represent a continuum, not an all-or-nothing state of consciousness or unconsciousness (except perhaps at extreme ends of the continuum).

Early investigations of the value of inhaled anesthetics described anesthesia as a series of stages characterized by levels of analgesia and lack of awareness (Guedel, 1937). As anesthetic awareness indicates, however, determining accurately the level of consciousness during surgery is easier said than done. Historically, physicians have relied on measurement of respiratory rate, blood pressure, and other autonomic responses as measures of anesthetic depth. It may seem like an odd choice when one considers that anesthetics suppress activity of the reticular formation, thalamus, and the cerebral cortex, considered to be the most important area involved in awareness (Steriade, Amzica, & Contreras, 1994). Though researchers consider autonomic responses to be an indirect measure of anesthetic perfusion in the brain, we need a more direct measure allowing for the quantification and prediction of awareness (Daunderer & Schwender, 2001).

To that end, researchers have developed a number of techniques over the past decade to more directly monitor awareness during anesthesia. One of the first, bispectral analysis, emerged as a means of quantifying awareness in patients. Bispectral analysis operates by converting an electroencephalographic signal into a power spectral analysis (March & Muir, 2005). The measure, abbreviated BIS, is derived from three factors measured by the EEG. The first is the extent to which EEG waveforms show biocoherence, which is the level of variability displayed in brain waves. The less variable the brain waves produced, the more bioco-herence, and vice versa. Biocoherence is generally seen as a measure of slowed brain activity (Andreassi, 1995). Indeed, the amount of biocoherence increases with increases in anesthetic depth (March & Muir, 2005). The second factor in the BIS calculation is the amount of power in the delta activity versus that in the beta activity. Delta waves generally are characteristic of a lower level of consciousness, whereas beta waves typically reflect increased levels of brain activity, like that which might occur during a problem-solving task (Andreassi, 1995). As anesthetic depth increases, the brain activity begins to be dominated by more and more delta activity at the expense of beta (March & Muir, 2005). The third criterion for BIS calculation is the proportion of isoelectric activity. Isoelectric activity is characteristic of no brain activity. As one would expect, therefore, as anesthetic depth increases, so does the proportion of isoelectric activity (March & Muir, 2005). The BIS algorithm results in a number ranging from 0 (no brain activity) to 100 (fully awake). Glass and Johansen (1998) suggest that to avoid awareness, values between 40 and 60 BIS should be maintained to achieve sufficient anesthetic depth to prevent awareness. These claims were put to the test in an extensive experiment of 2,463 surgical patients. Myles, Leslie, McNeil, Forbes, and Chan (2004) compared traditional anesthetic monitoring to use of the BIS in preventing awareness of surgical patients. They found a reduced risk of awareness of 82 percent when using BIS monitoring. Of the over 1,200 BIS assigned participants, only 2 had an episode of awareness compared to 11 such cases in the non-BIS assigned condition (Myles et al., 2004).

The value of the BIS demonstrates a cardinal point regarding consciousness. Consciousness is not a binary, all or nothing, phenomena. Indeed, it is a continuum, where varying levels of brain activity manifest similarly in degrees of awareness.

The idea of awaking on the surgical table, unable to protest, is frightening; however, the topic of measuring consciousness has captured the attention of scientists, politicians, and religious leaders alike. What level of consciousness is required to represent human life? When does life end? Who has the right to make that determination? Are people in comas still aware, still conscious?

Disorders of Consciousness

The much-publicized and politicized death of Terri Ann Schiavo thrust issues of consciousness after brain injury back into the public spotlight. Despite proclamations by both sides, the issue is not a simple one. Indeed, assessment of consciousness in brain injury patients has been a source of concern and research by neurologists at least since the 1940s (Bernat, 2006). Researchers have described consciousness as having two separate components: wakefulness and awareness (Plum & Posner, 1980). Wakefulness is largely governed by the reticular formation, a series of chemical networks operating to arouse higher brain function via neurotransmitters such as acetyl-choline, and its related thalamic regions (Zeman, 1997). Awareness appears to be largely a function of higher brain structure functioning. The thalamus and its white matter connections to the cerebral cortex appear to be the key structures in the awareness portion of consciousness (Bernat, 2006). Differential damage to one or both of these systems results in various disorders of consciousness.

Jennet and Plum (1972) were the first to describe a disorder of consciousness that is produced by damage to the thalamus, cortex, or its white matter connections—the persistent vegetative state—as wakefulness without awareness (Bernat, 2006). Though the patients appear to lack the ability to feel or to perceive themselves or their environment, they do demonstrate a number of behaviors that can lead to confusion regarding this point. Those exhibiting a persistent vegetative state demonstrate a normal sleep-wake cycle with associated eye movements and sexual arousal, the primary difference between this state and coma. Furthermore, they typically exhibit reflexes maintained via the cranial nerves such as blinking, roving eye movements, brief visual pursuit, and nystagmus (Bernat, 2006). Sufferers often demonstrate auditory startle, withdrawal from noxious stimuli, and grimace to pain. Due to the wide range of demonstrated behaviors, it is not surprising that physicians and families alike have demanded additional evidence for the loss of awareness necessary for the diagnosis. Specialists use neuroimaging and electrophysiology to provide further confirmation of this devastating diagnosis. CT and MRI of those diagnosed with a persistent vegetative state show “widespread cortical and thalamic atrophy that increases in severity after months to years” (Bernat, 2006). Further, use of PET scans has shown a decrease in metabolic activity of the cerebral cortex by 40 to 50 percent of normal activity, with damage especially focused in the prefrontal and posterior parietal regions that researchers believe are necessary for attention (Bernat, 2006). Electroencephalography of a vegetative state is typically characterized by slowed background activity, with delta activity that does not react to external stimuli (Bernat, 2006). Reemergence of alpha activity—low-voltage, mixed frequency activity—is typically associated with recovery of awareness (Anch, Browman, Mitler, & Walsh, 1988).

Evidence for some recovery of awareness from diffuse neuronal injury does exist. Patients diagnosed with a minimally conscious state show intermittent, though limited, self-awareness (Bernat, 2006). Patients in a minimally conscious state may potentially demonstrate ability to follow simple commands, make verbalizations, sustain visual pursuit, and demonstrate appropriate emotional reactions (Bernat, 2006). Electroencephalography in these cases is characterized with a nonspecific slowing but contains periods of all normally associated brain activity.

As we’ve seen, whether it is brain injury or anesthesia, awareness is not an all-or-nothing proposition. Levels of consciousness lie on a continuum that is demonstrated not only in the behavioral repertoire available but also the imaging and electroencephalographic record of brain activity. Alteration in the level of consciousness is not a rare event, however. Indeed, each of us spends an average of eight hours a night in an altered state, asleep.

Sleep

Connie, a reporter for a local paper, has no trouble falling asleep. In fact, she spends a good portion of her day fighting the urge to close her eyes and take a nap. She retires for bed regularly at ten o’clock at night, falls asleep with ease, but struggles to waken eight hours later when her alarm sounds. How is it a woman who sleeps eight hours a night can still be so tired? To answer this or any question regarding an individual’s sleeping habits, one needs two things. The first is an understanding that sleep is not a simple thing. Indeed, there are several different types of sleep, each of which has its own pattern of physiological activity. Second, we need to be able to distinguish between these different types of sleep by measuring the activity of the brain and body during sleep. The recording of physiological activity is called polysomnography (poly means “many,” somno means “sleep,” and graph means “write”). The name reflects that polysomnography detects physiological activity during sleep in many different parts of the body and represents that activity graphically. The body operates electrochemically. Interconnected neurons produce tiny electrical signals, called action potentials, which propagate and travel. These action potentials are the means by which neurons carry out the communication necessary to keep the organism running. The signals produced are tiny, ranging from one microvolt to one millivolt (Anch et al., 1988). Bioelectric sensors attached to the sleeper amplify the signals and produce a waveform that can be interpreted to determine the type of sleep the individual is undergoing. Electrodes of this type are placed on the scalp to measure brain activity (EEG-electroencephalogram), the orbital muscles to detect eye movements (EOG-electrooculogram), and on the muscles of the chin, leg, or both to detect neuromuscular disorders (EMG-electro-myogram). Sleep researchers may also use electrodes or other measuring devices to assess core body temperature, breathing, heart rate, blood pressure, and so on.

Using polysomnography, researchers and physicians can look at real-time changes in a sleeper’s physiology as they happen. This procedure allows researchers to track an individual’s sleep pattern. Like waves of light or sound, brain waves can be described using two primary characteristics: amplitude (or voltage, typically measured in microvolts, pV) and frequency (measured in cycles per second; Andreassi, 1995). Some patterns of voltage and frequency are so common that they are given names. Alpha waves are characterized by a frequency of 8 to 12 Hz with a magnitude of approximately 20 to 60 pV and are primarily seen over the occipital cortex. Alpha waves are very common in a wakeful, relaxed brain. When the brain begins to become more active it typically produces what are called Beta waves. Beta waves have a frequency that is nearly double that of alpha waves and a voltage that ranges between 2 and 20 pV. The Delta wave is much different; it is a high-amplitude, low-frequency wave. With a frequency ranging between a much slower 1 to 2 Hz,

it is the lowest frequency wave produced. The amplitude can be as large as 200 pV. Delta waves generally indicate that a person is in deep sleep; they are also associated with certain sleep disorders such as sleepwalking and night (or sleep) terrors. Theta waves are an additional wave used to discriminate the type of sleep being experienced. Theta waves occur at a frequency of approximately 4 to 7 Hz and at an amplitude ranging between 20 and 100 pV (Andreassi, 1995).

By detecting changes in these patterns of brain activity as well as observing additional changes in the behavior of the organism during sleep, researchers have been able to divide sleep into a series of stages.

Stage 1 Sleep

Not surprisingly, the first stage of sleep is a transitional one. In fact, some debate still exists as to whether Stage 1 is actually sleep (Anch et al., 1988). The EEG during Stage 1 sleep is typified by a mixture of low-amplitude waves including a large amount of alpha activity. It is not uncommon for individuals in this stage to experience an altered state of consciousness often referred to as hypnogogic hallucinations. Sleep-induced sensory distortions, they are often experienced as floating, falling, or as a presence looming over the sleeper. Some researchers have suggested that hallucinations of this type are to blame for legends such as the incubus, a nighttime demon that was believed to mount the chest of a sleeper.

Stage 2 Sleep

The transition from waking to deep sleep continues in Stage 2 sleep. EEG activity in the first and second stages is similar, save two oddities that occur only in Stage 2 sleep. EEG events known as sleep spindles and K complex are unique to Stage 2 sleep. Sleep spindles are defined as bursts of activity between 12 to 14 Hz that last at least half of a second. K complex, also half of a second in duration, has a large negative component followed by a positive deflection (Anch et al., 1988).

Slow Wave Sleep

Stages 3 and 4 often are combined under the name slow-wave sleep— a sensible name, as both stages are characterized by high-amplitude, low-frequency delta waves. The two stages differ only in the proportion of delta waves that manifest. Stage 3 sleep is defined as being < 50 percent delta, whereas Stage 4 is > 50 percent delta. As noted earlier, delta wave activity indicates a low level of brain activity, and indeed, Stage 4 is the deepest stage of sleep.

REM Sleep

Stage 4 may be the deepest stage of sleep but it isn’t the final stage experienced by a sleeper. That distinction goes to REM, or rapid eye movement sleep. The EEG of REM sleep differs greatly from the preceding slow wave sleep and appears more like mixed low-amplitude activity associated with Stage 1 sleep. So how does one distinguish between REM and Stage 1? The EEG provides one clue in the form of a “saw tooth” pattern of activity that exists in REM but not in Stage 1. The second distinction lies in the name of the stage itself, eye movements (Siegel, 2005). Whereas the first four stages of sleep show little eye muscle activity, EOG measurement during REM shows episodes of darting, saccadic eye movements. Measurement of EMG is also helpful in distinguishing REM from the other stages of sleep. During REM sleep, EMG is at much lower levels than during Stages 1, 2, 3, and 4. What is the source for this difference? Muscle immobility. Motor activity is suppressed during REM, leaving us nearly paralyzed (Siegel, 2005). Additionally, REM sleep is the stage of sleep in which dreaming most often takes place. These three significant differences between REM and the previous stages led to describing Stages 1, 2, 3, and 4 as non-REM (NREM) sleep.

Why Sleep?

It seems a sensible question. Why would we spend one-third of our lives in bed? Surely there is a better use of that time? So what function does sleep serve? One way researchers and physicians have sought to answer this question is by studying what happens when a person doesn’t sleep. The question is a practical one as well. It was recently reported that 20 percent of Americans sleep fewer than 6.5 hours per night (Dinges, Rogers, & Baynard, 2006). What’s more, a telephone survey of 1,506 adults sponsored by the National Sleep Foundation indicates that they sleep less on weekdays than on weekends. Forty percent reported sleeping fewer than seven hours per night on weekdays; 25 percent got fewer than seven hours of sleep on weekends. The difference in weekday and weekend sleep suggests that they are attempting to overcome a “sleep debt” (National Sleep Foundation, 2005). Research suggests that chronic sleep deprivation of this type can produce significant effects on an individual. Noted sleep researcher James Maas (1998) writes, “The third of your life that you should spend sleeping has profound effects on the other two thirds of your life, in terms of alertness, energy, mood, body weight, perception, memory, thinking, reaction time, productivity, performance, communication skills, creativity, safety, and good health” (p. 6). One large-scale experiment investigated the cognitive effects of sleep deprivation (Van Dongen, Maislin, & Mullington, 2003). Truck drivers were assigned to a week of controlled sleep duration (three, five, seven, or nine hours) each night. Participants displayed a decrease in mean response speed and an increase in the number of lapses in the psychomotor vigilance task (PVT) that worsened throughout the sleep restriction schedule (Van Dongen et al., 2003). Participants assigned to nine hours of sleep showed no decrease in reaction time or increase in lapses. Chronic sleep deprivation clearly has significant affects on vigilance and reaction time. This is especially troubling when you consider that these participants were truck drivers who drive tons of machinery for a living in the lane right next to you and your Dodge Neon. A second study bolsters this concern by reporting that one night of sleep restricted to five hours produced a decrease in performance and an increase in accidents on a driving simulator (Dinges et al., 2006). The effects of chronic sleep loss aren’t limited to reaction time, with studies suggesting endocrine, immune, cardiovascular, and metabolic disturbances may also emerge as a result of poor sleep (Dinges et al., 2006).

Sleep loss clearly has profound effects on the individual, leading some researchers to propose a model that draws connections between sleep physiology and cognitive/behavioral abilities during waking. Borbely (1982) proposed the two-process model as a means to explain the function of sleep. The model proposes that sleep has two primary components.

The first component is homeostatic. Homeostasis refers to the means and methods by which the human body attempts to maintain a balance. The model suggests that there is a strain on the body during wakefulness that builds as the waking day goes on. This strain is then quickly lowered during sleep, allowing for the process to repeat itself from zero the following day. Indeed, scientists have recognized a pattern of chemical buildup and breakdown tied to the sleep-wake cycle for many years. One chemical often considered as a possible player in this process is adenosine (Thakkar, Winston, & McCarley, 2003). The body uses adenosine triphosphate (ATP) as a source of energy in all cellular metabolic processes. Metabolism of ATP results in the production of energy and of adenosine as a “waste” product. As a result, adenosine builds up to higher and higher levels during wakefulness, when the body is most active. In fact, researchers have reported that adenosine levels are correlates with perceived sleepiness. During sleep, adenosine levels rapidly decrease and by morning have returned to the levels of the previous morning (Thakkar et al., 2003).

The second component of the model is circadian. In the 1970s the suprachiasmatic nucleus (SCN), a small region of the hypothalamus, was discovered to be the center of circadian timing. Circadian, literally meaning “about a day,” refers to the endogenous changes of an organism that occur on an approximate 24-hour cycle. These daily rhythms occur in a number of physiological and neurobehavioral variables such as body temperature, hunger, and, most prominently, the sleep-wake cycle (Czeisler, Buxton, & Khalsa, 2006).

What Dreams May Come

Understanding of the underlying physiology of sleep may be a relatively new achievement but interest in dreams is perhaps as old as written human history. Dreams, perhaps more than any other domain, represent how powerful changes in consciousness can be. Though your body is lying paralyzed in your bed, you believe, however temporarily, that you are skating in Central Park, finishing your Christmas shopping, or perhaps taking that final exam that is coming up next week. The Judeo-Christian tradition is ripe with examples of the regard and curiosity in which dreams have been held throughout human history. The Torah and New Testament both contain multiple stories in which dreams are a means by which God communicates with man (Anch et al., 1988). It is perhaps this tradition that eventually led to dream interpretation as a means of discovering a dream’s “true meaning.”

Freud and Dreams

For Freud, the dream was not a window to God but instead a window to one’s self. Freudian psychology was built upon the notion of the power of the unconscious mind in driving behavior. Hidden from our own awareness lies the id, a powerful driving force of personality that seeks instant gratification. The id, subjugated by the ego during wakefulness, is free of restraint during sleep. This freedom allows the id to fulfill its wishes in the form of dreams. Those wishes are not clearly manifest, however, hidden in symbolism and inner meaning. Whereas the dream as we remember it was called the manifest content, it was, for Freud, the deeper hidden meaning that acted as a portent of the id’s wishes. With great training a therapist could come to decipher this hidden, latent content and from it gain greater understanding of the dreamer (Freud, 1900). Domhoff (2004) reviewed dream content in both children and adults to determine if evidence supports the role of wish fulfillment in dreaming. A longitudinal study failed to support the notion of wish fulfillment in children (Foulkes, 1982). Content analysis of all dreams recorded failed to show any evidence of wish fulfillment by any study participants. A further challenge to the wish fulfillment theory comes from the nightmare dreams that often accompany post-traumatic stress disorder (PTSD). Domhoff points out that these nightmarish dreams are very common following traumatic experiences such as rape, assault, natural disasters, and war. These dreams, clearly not related to wish fulfillment, provide strong evidence against Freud’s claims.

Despite little empirical evidence to support Freud’s view of dreams, it wasn’t until the 1970s that a powerful competing theory emerged (Hobson & McCarley, 1977). Titled the activation synthesis theory, Hobson’s theory was intended to combat the Freudian notions of hidden dream meanings. The theory holds that dreams are a result of random stimulation of brain activity beginning in the pontine region of the brain stem and ending in the forebrain. Hobson and McCarley (1977; Hobson, 2005) maintain that dreams are simply the side effect of the brain mechanisms involved in REM sleep. The narrative quality of dreams results from the forebrain attempting to make sense out of the random brain activity and not a means by which we can analyze the unconscious mind. According to Hobson and McCarley (1977), it is this process that is responsible for the often nonsensical nature of dreams. The activation synthesis hypothesis has garnered great support from the empirical dream research community, perhaps largely due to its being seen as an answer to Freud. However, recent empirical evidence has begun to bring into question some of the basic tenets of the theory. For instance, researchers have reported for a long time that some forms of dreaming take place outside of REM sleep, calling into question the view of dreaming as a side effect of REM (Foulkes, 1982). Further, the “bizarreness” of dreams is more rare than Hobson’s theory would suppose. Using multiple measures of “bizarreness,” Strauch and Meier (1996) analyzed 117 dreams. Bizarre elements, such as eccentric actions or unusual structure, were reported as not occurring at all in nearly 25 percent of dreams, whereas 39.3 percent of dreams contained only one bizarre element (Strauch & Meier, 1996).

Though no evidence exists to support dreams as wish fulfillment (Fisher & Greenberg, 1996), evidence is accumulating that dreams may be an expression of one’s waking life. Continuity theory postulates that the content of dreams is related to activities and events in an individual’s life. Snyder, Tharp, and Scott (1968) analyzed dream content in 58 normal participants. Dream content suggested that the vast majority of dreams (90 percent) involved real life experiences and everyday concerns. Continuity theory suggests that dreams act less as a means to disguise the wishes of the id and more as a means to express the same kinds of activities, worries, and concerns experienced by sleepers in their waking life.

References:

Anch, A. M., Browman, C. P., Mitler, M. M., & Walsh, J. K. (1988). Sleep: A scientific perspective. Englewood Cliffs, NJ: Prentice Hall.
Afifi, A. K., & Bergman, R. A. (2005). Functional neuroanatomy: Text and atlas. New York: Lange Medical Books/McGraw-Hill.
Andreassi, J. (1995). Psychophysiology: Human behavior & physiological response. Hillsdale, NJ: Lawrence Erlbaum Associates.
Atkinson, R. L., Atkinson, R. C., Smith, E. E., & Bem, D. J. (1990). Introduction to psychology (10th ed.). Orlando, FL: Harcourt Brace Jovanovich.
Bernat, J. (2006). Chronic disorders of consciousness. The Lancet, 367, 1181-1192.
Beyea, S. C. (2005). Addressing the trauma of anesthesia awareness. Association of Operating Room Nurses Journal, 81(3), 603-606.
Borbely, A. A. (1982). A two process model of sleep regulation.
Human Neurobiology, 1, 195-204. Bower, B. (2002). Spreading consciousness: Awareness goes global in the brain. Science News, 162, 251-252.
Bower, B. (2005). Possible worlds: Imagination gets its due as a real-world thinking tool. Science News, 167, 200-201.
Cunningham, S., Scerbo, M. W., & Freeman, F. G. (2000). The electrocortical correlates of daydreaming during vigilance tasks. Journal of Mental Imagery, 24(1), 61-72.
Czeisler, C., Buxton, O., & Khalsa, S. (2006). The human circadian timing system and sleep-wake regulation. In M. Kryger, T. Roth, & W. Dement (Eds.), Principles and practice of sleep medicine (4th ed., pp. 136-154). New York: Elsevier Saunders.
Daunderer, M., & Schwender, D. (2001). Depth of anesthesia, awareness and EEG. Anaesthesist, 50, 231-241.
Davis, S. F., & Palladino, J. J. (2007). Psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
Dinges, D., Rogers, N., & Baynard, M. (2005). Chronic sleep deprivation. In M. Kryger, T. Roth, & W. C. Dement (Eds.), Principles and practice of sleep medicine (4th ed., pp. 67-76). New York: Elsevier Saunders.
Domhoff, G. W. (2004). Why did empirical dream researchers reject Freud? A critique of historical claims by Mark Solms. Dreaming, 14(1), 3-17.
Fisher, S., & Greenberg, R. (1996). Freud scientifically appraised. New York: Wiley.
Foulkes, D. (1982). Children’s dreams. New York: Wiley.
Freud, S. (1900). The interpretation of dreams (J. Crick, Trans.). London: Oxford University Press.
Giambra, L. M. (2000). The temporal setting, emotions and imagery of daydreams: Age changes and age differences from late adolescence to the old-old. Imagination, Cognition, and Personality, 19, 367-413.
Glass, P., & Johansen, J. (1998). The bispectral index monitor: Monitoring patient consciousness. Surgical Service Management, 4, 50-52.
Guedel, A. E. (1937). Inhalational anesthesia: A fundamental guide. New York: Macmillan.
Hilgard, E. R. (1991). Suggestibility and suggestions as related to hypnosis. In J. F. Schumaker (Ed.), Human suggestibility: Advances in theory, research, and application (pp. 38-58). New York: Routledge.
Hobson, J. A. (2005). 13 dreams Freud never had: The new mind science. New York: Pi Press.
Hobson, J. A., & McCarley, R. W. (1977). The brain as a dream state generator: An activation synthesis hypothesis of the dream process. American Journal of Psychiatry, 132, 1335-1348.
Hockenbury, D. H., & Hockenbury, S. E. (2006). Psychology (4th ed.). New York: Worth.
Honma, H., Masako, K., Fukuda, N., Kobayashi, R., Sakakibara, S, & Koyama, T. (2000). Differences in electroencephalogram power densities between genuine narcolepsy and secondary narcolepsy. Psychiatry and Clinical Neurosciences, 54(3), 326-327.
Huettel, S. A., Song, A. W., McCarthy, G. (2004). Magnetic resonance imaging. Sunderland, MA: Sinauer Associates.
Jennet, B., & Plum, F. (1972). Persistent vegetative state: A syndrome in search of a name. The Lancet, 1, 734-737.
Kihlstrom, J. F. (1985). Hypnosis. Annual Review of Psychology, 36, 385-418.
Klinger, E. (1990). Daydreaming: Using waking fantasy and imagery for self-knowledge and creativity. Los Angeles: Tarcher.
Kosslyn, S. M., Thompson, W. L., Costantini-Ferrando, M. F., Alpert, N. M., & Spiegel, D. (2000). Hypnotic visual illusion alters color processing in the brain. American Journal of Psychiatry, 157, 1279-1284.
Leitenberg, , & Henning, K. (1995). Sexual fantasy. Psychological Bulletin, 117, 469-496.
Maas, J. B. (1998). Power sleep. New York: Villard.
March, P., & Muir, W. (2005). Bispectral analysis of the electroencephalogram: A review of its development and use in anesthesia. Veterinary Anaesthesia and Analgesia, 32, 241-255.
Molyneux, M. E. (2000). Awake during surgery. The Lancet, 335, 671-672.
Montgomery, G. H., DuHamel, K. N., & Redd, W. H. (2000). A meta-analysis of hypnotically induced analgesia: How effective is hypnosis? International Journal of Clinical and Experimental Hypnosis, 48, 138-153.
Myles, P. S., Leslie, K., McNeil, J., Forbes, A., & Chan, M. T. V. (2004). Bispectral index monitoring to prevent awareness during anaesthesia: The B-aware randomized controlled trial. The Lancet, 363, 1757-1763.
Nash, M. R. (2001, July). The truth and the hype of hypnosis. Scientific American, 47-55. National Institute of Neurological Disorders and Stroke. (2006). NINDS narcolepsy information page. Retrieved December 23, 2006, from http://www.ninds.nih.gov/disorders/narcolepsy/htm
National Sleep Foundation. (2005). Sleep library/Can’t sleep? Learn about insomnia. Retrieved July 30, 2005, from http://www.sleepfoundation.org/sleeplibrary.index
Newman, A. W., & Thompson, J. W., Jr. (2001). The rise and fall of hypnosis in criminal investigation. Journal of the American Academy of Psychiatry and Law, 29, 75-84.
Patterson, D. R. (2004). Treating pain with hypnosis. Current Directions in Psychological Science, 13, 252-255.
Plum, F., & Posner, J. B. (1980). The diagnosis of stupor and coma (3rd ed.). Philadelphia: F. A. Davis Company.
Prys-Roberts, C. (1987). Anesthesia: A practical or impossible construct? British Journal of Anesthesia, 59, 1341.
Siegel, J. M. (2005). REM sleep. In M. H. Kryger, T. Roth, & W. C. Dement (Eds.), Principles and practice of sleep medicine (4th ed., pp. 120-135). New York: Elsevier Saunders.
Snyder, F., Tharp, I., & Scott, J. (1968). Psychophysiology. Phenomenology of REM dreaming, 4, 375.
Steriade, M., Amzica, F., & Contreras, D. (1994). Cortical and thalamic cellular correlates of electroencephalographic burst-suppression. Electroencephalographic Clinical Neurophysiology, 90, 1-16.
Strauch, I., & Meier, B. (1996). In search of dreams: Results of experimental dream research. Albany: State University of New York Press.
Streeter, M. (2004). Hypnosis: Secrets of the mind. Hauppauge, NY: Barron’s.
Thakkar, M., Winston, S., & McCarley, R. (2003). A1 receptor and adenosinergic homeostatic regulation of sleep-wakefulness: Effects of antisense to the A1 receptor in the cholinergic basal forebrain. The Journal of Neuroscience, 23(10), 4278-4287.
Van Dongen, H. P. A., Maislin, G., & Mullington, J. M. (2003). The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep, 26, 117-126.
Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review, 20, 158-177.
Willwerth, J. (1997). What’s up doc? It’s every surgery patient’s nightmare: You’re awake enough to feel the knife but not enough to scream. Time, 150(8), 96.
Yapko, M. D. (1994). Suggestions of abuse. New York: Simon & Schuster.
Zeman, A. (1997). Persistent vegetative state. The Lancet, 250(9080), 795-799.