Monday, June 3, 2013

Current Study

A current study examined sleep mentation (dreaming) during NREM (non-rapid eye movement) sleep in relation to brain activation (measured using functional imaging). The general findings suggested that by using machine-learning models for decoding neural activation, it is possible to determine the content of dream imagery by examining brain activation (Horikawa, Tamaki, Miyawaki, & Kamitani, 2013). How might this be useful in research, clinical practice, or popular culture?

60 comments:

  1. By examining brain activation in and relating it to types of dream, it can give us a more non subjective interpretation of a dream which may be helpful in research especially in psychology. What is interesting is that if we can understand what neural activity stimulates types of dreams can we induce a dream from stimulating part of the brain? Christine dunn

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  2. Using machine-leanring models for decoding neural activation to determine the content of a dream would be very interesting. This would be useful in that most people don't remember their dreams if they're either not told how to or just aren't able to. By using these machine-learning models, the content of our dreams could be more accurately ascertained and therefore provide more accurate detail for either research purposes or for clinical practice. This type of technology would provide great material for popular culture movies or television. It puts me in mind of the movie Inception, where they're able to plant dreams deep enough in peoples minds for them to believe that they're the ones creating it. If we can pull information like this from the human mind, who's to say we can't, as Christine states, induce a dream for someone?

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    1. Jenn!
      You have a very interesting comment related to popular culture. I could not think anything about the machine-learning model relation to popular culture on my discussion. I am glad you shared your idea about the usefulness of this model for the popular culture.

      As you mentioned about planting dreams to people in the movie, maybe we can use this idea in the clinical settings. We might be able to manipulate negative emotional dreams for those people with depression or anxiety disorders to help them to reduce any emotional effect from their dreams or increase sleep quality.

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    2. I agree with Mijung and Jenn. By using machine-learning models to decode the contents of dreams from neural activation will greatly expand research in both subjective and objective manners based on commonalities and differences in dreams.

      With regards to clinical practice, Mijung highlighted an important point by mentioning the positive manipulation of dreams physiologically in order to improve sleep quality for certain individuals. I think that it is beyond our us now but will be a significant step intro the future of dream psychology. In terms of pop culture, decoding dream contents will provide individuals more subjective understand of their own dreams. More analytical and factual contents will be revealed in such a way that the dreamer themselves could not do.

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    3. I guess I will finally have to watch the movie Inception to see how this technology could be used, but it is great that you could find this reference!

      This is a very interesting, and useful finding! It could be utilized to analyse the dreams of those who cannot often remember their dreams. This could also be used to make sure a client was giving an accurate representation of their dream. There could be a lot of issues with this new tool because it is a very large invasion of privacy. Dreams reveal a lot of personal information, and if someone can view the content of your dream it could be rather invasive.

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  3. I find this extension to be interesting, yet somewhat frightening. If we knew which parts of the brain were activated during different types of dreams, and what Jenn is saying actually happened, that we could then pull information from the human mind, who is to say when it would stop? If we can pull information FROM the mind, who is to say we could not eventually put information back INTO the mind? This would be a very effective, and if used for less than honourable means, truly scary, way of brainwashing large groups of humans as they sleep. Frightening.

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    1. I completely agree with Christine Dunn as she stated above; it can give us a non-subjective interpretation to dream imagery. This would be beneficial to researchers because they will be able to gather direct answers rather then individual interpretations. The method of a science-based research is used rather then focusing on theory and different methods used when interpreting dream imagery. Like Jenn Kerswill stated, most people do not remember their dream imagery. By using these machine-learning models, the person will not have to remember their dream. Researchers will be able to monitor their brain activity to eliminate this problem. I think this method will ensure reliable results rather then personal opinions. Perhaps, researchers could use this method to treat depression by placing patients in a false reality. As James Phillips said, this is a very frightening thought and one could perceive this as brainwashing people.

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    2. According to scientists the ability to dream is a fascinating aspect of the human mind. Scientists are in fact able to measure dream contact through the neuronal activation in the brain. However, the images and emotions that we experience so intensively when we dream form in our heads remains a mystery. However, the fact still remains that it is possible to measure dream content.
      The measuring of dream imagery by examining brain activation can be done by methods like functional magnetic resonance imaging which have enabled scientists to visualise and identify the precise spatial location of brain activity during sleep. Scientists are able to measure the entry into REM sleep, and with the help of the subject’s EEG to detect the beginning of a lucid phase. Typically brain activity measured from this point onwards corresponds with what the dreamer is dreaming, and regions such as the sensorimotor cortext of the brain which is responsible for the execution of movements may be activated during the dream. Thus with the combination of sleep EEGs, imaging methods and dreamers, simple movements during sleep as well as activity patterns in the brain during visual dream perceptions can be measured.
      This may be useful in research because it allows us to be more aware that activities in the regions of the brain are relevant to the dream content that we dream about. In addition, in clinical settings those who suffer from depression, anxiety, mood disorders, personality disorders, or have particular deficits …it may be reflected in their neuronal brain activation during dreams. The onset of nightmares may be present in those with certain brain activation's, etc. It would be interesting to look at the neuronal activation in those types of patients.

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    3. The idea that brain imaging techniques can be used to determine the content of dream imagery is interesting and important in terms of research and clinical practice in a number of ways. Pertaining to the research aspect this is important because we can more accurately understand the type of dream someone is having before they even wake up and recall it. This allows for comparison between dream recall and what the brain activation patterns are telling us, which adds to overall reliability of the research. Also, this information can be related to the early textbook studies where researchers presented certain stimuli while the person was sleeping (e.g. auditory stimuli) in order to produce certain dreams and dream imagery. Can we stimulate certain areas of the brain and get the same imagery that we predict? Like Christine mentioned, can we induce a dream? This may also assist research in determining a way to prevent or stop any negative dreams or nightmares from disrupting the sleep of many individuals. This last point can be related to the area of clinical practice because we can measure brain activation in terms of dreaming, this allows us to predict what certain patients may dream about while or before it actually happens based on this activation. With that, we can predict the type of dream patients may have. Because nightmares often have negative side effects for those who experience dreams, it would be essential for clinical and treatment practices to find ways to stop or reduce the negativity in these dreams and allow patients who already suffer enough with depression, anxiety etc to have a peaceful sleep. Overall, finding a way to reduce nightmares would be very beneficial to many.

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    4. I also agree with previous comments that this type of finding can be useful in doing research on the connection between mood disorders such as depression, anxiety, PTSD and dream imagery. I believe the types of dreams we have are greatly influenced by our mood states and/or mood disorders we may or may not have.

      By measuring the brain activity during dreams, we can differentiate nightmares from pleasant dreams and possibly find reasons for why some people have more nightmares than pleasant dreams and vice versa. This could also be connected back to physical health and/or mood states and disorders.

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    5. As Jen Kerswill has said, this technique would be extremely useful in research for patients who have trouble remembering their dream imagery. Furthermore, even for people who frequently remember their dreams, this could be used to record all dream imagery created over the course of a night, whereas people may remember and report only a couple of the many dreams they may have had that night. This method would thus provide a more accurate depiction of one’s dream imagery and therefore allow them to attain more benefits from its interpretation. Thus, this finding would be very useful in clinical practice as it would increase the accuracy of the dream the patients are interpreting. As Samantha Baynton mentioned, the use of this technique to treat depression would be very interesting and, if it were to work, would have great clinical applications. It could also be extended to the treatment of anxiety, PTSD, and other disorders.

      However, as both Samantha Baynton and James Phillips have mentioned, this technique does have darker applications and could in fact be seen as brainwashing if we reverse the process and inflict certain dream imagery upon a person. This could drastically alter popular culture and influence the minds of many people as they unknowingly slept.

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    6. Examination of brain activity to form a visual image of dreams is a great next step in dream research, as it will aid with individuals remembering dreams. It can also allow therapist an objective view on their patient’s dreams. However, with this type of advancement in research, issues may rise. In current practice therapist do not tell their patient’s the meaning of their dreams; instead they help guide them to discovery. With visual images it will be harder to reframe from therapist opinions on the meaning of dreams. As well, with depiction of dreams the emotional context of it may be left out. Emotion is an important factor of dream interpretation. In a pervious post, Christine Dunn brings up a good point on being able to stimulate specific dreams. This future research is very interesting but contradicts the functions of dreaming. Dreams are usually trying to tell us something about our current waking life.

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    7. I agree with the issues that Jessica has brought up. This new technology could change the current practice of the therapist. I think if they were not just being told the dream from the patients perspective as they are now, it would be rather hard not to put their own bias on it. The therapist might jump to conclusions once they see the content of the dream, when really it could be about something else.

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  4. Researchers have been studied visual imagery during sleep by measuring the brain activity for many years. The results shown that brain activity occur during waking, REM and NREM. Now, the current breakthrough of measuring brain activity by Horikawa et al (2013) discovered the links between human functional magnetic resonance imaging.
    This breakthrough can very useful in a future research, clinical practice or popular culture. As Hannah Roche mentioned in her comments that this breakthrough will help us to differentiate nightmares…why some people have more nightmares than others. It will also help the medical professionals to properly diagnosis mental health problems.

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  5. I believe that the ability to use functional imaging to determine the content of dream imagery will be extremely useful in dream research. For starters, the biggest problem with dream interpretation is that people often fail to remember their dreams. With machine learning models that can measure dream content however, it will be less important for patients to remember their dreams since researchers will know what the dream imagery consisted of. Additionally, I believe that this finding will benefit psychologists working with mental illnesses. With fMRI information of the activated brain areas, researchers will be able to tell if there is abnormal activity in relation to what the dreamer was dreaming. I also believe that treatment through dream interpretation can improve with these findings, as perhaps there is a way to manipulate one’s brain activity which would in turn change what one dreams. For example if a person with depression was having dark dreams only involving inanimate objects, perhaps researchers could find a way to influence brain activity to change these dreams to colorful dreams full of human interactions.

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    1. Chelsea!
      It is interesting because your comment is very similar to what I have replied to Jenn Kerswill. Jenn described about a movie on implanting dreams to people. I thought we can possibly be able to change dream imagery by using transcranial magnetic stimulation (TMS). As we know that different brain parts have different functions. Since we have developed the way of predicting dreams while the dreams are still dreaming, we might be able to manipulate the dream (if they are suffering for nightmares) by using TMS. If this works, it will be really helpful for those people who have nightmares.

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    2. Dream content can be remembered more easily using machine learning models (stated by Chelsea). Also, it may be possible to have an unbiased report of dreams and more detailed content for other dream researchers to analyze. It can help many clinicians, therapists, and nurses understand how to approach their patient and what treatment options are more effective for them.
      The influence of brain activity on dream imagery has many applications and it's up to further research to exploit the relationship between physiology and dream states/imagery.

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  6. The ability of machine-learning models to decode the content of dream imagery with the measurements of functional imaging would be extremely useful in clinical aspects as the coding of dreams could take place whether or not the dreamer can actually remember what was dreamed about. This could be used to assess the dream imagery that occurs with specific mental illnesses as mention in the comment above, and further help with possible diagnoses if certain dream imagery is associated with specific mental illnesses.

    In regards to popular culture, accurate verification for decoding dreams and exploring discovery within dreams could become educated to the public—which can correlate with clinical practice uses in helping people to interpret their dreams accurately. Furthermore if we have the ability of determining the content of dream imagery perhaps those suffering from nightmares and other dream traumas could be treated to assist in the elimination of these to ensure a proper sleep and peaceful dreams.

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    1. I agree that being able to determine dream imagery by examining the neural activation would be of great use in understanding dreams. Having the ability to decode dreams through this process would assist in the ability to remember and understand possible meaning of dreams. Personally, I know that I have a hard time remembering my dreams on a regular basis. So I also find that it is hard to understand the meaning behind dreams when I do remember them. Therefore, I think that being able to remember you dreams when using this technique is very appealing.
      I think that in order for pop culture to use this method of decoding dreams, individuals need to understand why dreams are so important and what dreams could possibly be telling you.
      Many different groups of individuals would benefit from remembering and understanding their dreams by using this technique.

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  7. As many have mentioned before, being able to determine dream imagery by studying brain activation could be a very positive step for dream and sleep research. I agree that it could be very beneficial for researchers and therapists to have an objective component of dream imagery. This could enhance our understanding of dream imagery as well as aid individuals with interpreting their dreams, especially for those who have difficulty with dream recall. All they may need is a detail or image to trigger their memory. It would also be interesting to study how different people interpret the same sort of imagery, and what influences these differences whether it's mood, personality, experience, spirituality, culture, illness, etc.

    As several people have already mentioned, there is also potential for this to have a negative impact. Researchers and therapists may begin to rely too much on objective information rather than subjective interpretation from the individual dreamers themselves, which is imperative to dream interpretation.

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    1. Angelica Palillo-BucknallJune 4, 2013 at 5:29 PM

      I completely agree with your ideas about the positive and negative impacts around machine learning models. My concerns in regards to this model is the confidentiality of dream content. When we use the models, even the projective method, we are able to keep dream content private and confidential, sharing only what we choose to share. In this model, I would be concerned that confidentiality would be compromised.

      In research, it would be especially beneficial for those dreamers and those in dream research with people who have numerous dreams throughout the night. It can save a lot of time for the dreamer because he/she would not have to record and complete all of the written steps for each individual dream (which could be time consuming). The researcher is able to access the dream imagery faster than waiting for the dreamer to interpret the imagery as well. This is a great benefit for this model, as researchers can more quickly and efficiently study dream imagery. In clinical practice, this is also a great benefit because clinicians can access the imagery quickly and efficiently, saving many steps in helping dreamers work through their dream imagery. In popular culture, learning what people's dream imagery entails would allow the media to play on popular dream imagery or desires. For example, the media may see that women dream about shopping or buying new clothes and use this to their advantage by playing on these wants or desires. The media can continue to use dream imagery to make movies or books. As we know, many books, movies, songs, and popular media have used dream imagery as an influence in creating the ideas behind all types of popular media. For example, Stephanie Meyer created the popular "Twilight" series all from a dream. Imagine she did not get the credit for this because someone used her dream imagery to create the books and movies? This are some concerns I would have with using machine-learning models.

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    2. I agree that using machine-learning models for decoding neural activation during sleep is an efficient way to monitor not only brain activity, but also dream activity as well. This has important implications for research and clinical practice because it allows researchers to gain a deeper insight into how and why we dream, as well as insight into any brain irregularities or abnormalities that occur during sleep. In regards to dreams, this method may prove to be extremely useful as it may eliminate the need for dream diaries to record the content of dreams, thereby rendering the process of seeking to remember one's dreams virtually unnecessary, and nonexistent. All of the above factors combine to create a much more efficient way to analyse sleep and dreams.

      ~ Ellen Coombs

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  8. Shadiya GouldbourneJune 4, 2013 at 12:51 PM

    This is very fascinating research though I cant really understand how the content of dream imagery can be known through these models. The content of our dreams is our true desires acted it in an environment non threatening to others, if it is so easily pulled from our consciousness for others to know, I can only think that the effects would be bad. For popular culture, the benefits would be marketing. If peoples' desires are known then corporations know what to supply. For clinical practices it would be beneficial to have an unbiased account of the imagery in the dream. All in all, I believe that content of dream imagery should be left alone to the dreamer. Anyway its all about how the person interprets the dream and the imagery as opposed to the imagery itself.

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    1. I think it's very interesting and amazing that researchers can determine the content of dream imagery by measuring brain activity. This could be very useful in research and clinical practice in that if people don't remember their dreams necessarily this may be a way to help and guide them to remember.If the point of dream therapy is to help people understand what their dreams mean and to take the meaning of the dream and apply it to real life, this may be a way for the therapist to help them to do that.
      As many pepole have also said above, this research and the results of the study, as fascinating and possibly as accurate as they are, should be used by a dream therapist with caution because as it has been discussed in the course several times, the meaning of particular dream imagery can only be truly understood by the dreamer and there is no one meaning of specific dream imagery across all individuals.

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    2. I agree with Holly in that this is a very exciting prospect in dream research, and that it may be useful to researchers. I also agree with the point that Holly made regarding utilizing this information carefully with people. I wonder if we were able to extract this information and try to use it for dream therapy how useful it would really be?
      For instance, through completing the lab work so far, I feel as though I have experienced some useful discovery. If, however, I was just given this dream written down and told to do the lab work with it, I don't know that it would be the same experience. Even if the dream came from me, if I could not remember having it at all, I don't know that I would connect with the material in the same way.

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  9. It is really exciting that we can predict dream imagery seen in sleep by using a functional imaging machine while the dreamer is still sleeping. The Storytelling Method, 2A Method, and Projective Method are clinically proven dream interpretation methods but they are required the dreamer to either write their dreams or describe their dreams verbally in their waking lives. It can be challenging if you do not remember what you dreamt. However, this machine-learning model does not need the dreamers to recall their dreams in their waking lives.

    There are two things that I am really excited about this model. First, we do not have to worry about recalling dreams in waking life. This will be beneficial for those people who have difficulty with recalling their dreams. Many people think that they do not dream because they cannot recall in their waking lives. It would be helpful because we can gather as many dreams as we can for any types of dream researches for statistic matters. Secondly, we can be able to see people's dream imageries who no longer to speak. For example, post stroke aphasic patients or vegetative state patients. I am really curious to know if people with vegetative state have dreams like us. If we find a result whether they dream or not, it could be helpful to add another way to differ the vegetate state in the criteria. I am not so sure how it can be useful for popular culture.

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    1. It is amazing to see how far along research has come that researchers are able to now predict dreams with machines without the subject even knowing. This can be done with machines that can tell which parts of the brain are activated during a dream and therefore can tell maybe the theme/ subject of the dream. This is because certain areas of the brain are only activated when certain objects/feelings, etc are being thought of such as in a certain dream.

      This is an interesting advancement in the research of dreams because it opens up many possibilities. Researchers and clinicians can now have a better understanding of what people dream about and exactly what areas of the brain are activated for people when they dream. As many have said above, it is also useful for people who cannot remember their dreams. A therapist who uses dream interpretation to help patients would now be able to use interpretation for patients who have a hard time remembering their dreams. WIth using brain imaging machines to determine dream content many more experiments and much more research could be conducted to better understand dreams. However, like others have said, this could also lead to clinicians not emphasizing the patients feelings and thoughts on the dreams. If every dream is different and pertains to a person's certain waking life then researchers and clinicians need to remember to always take into account what the subject's thoughts/ feelings are about the dream if they remember. More knowledge will have to be known about the person if these machines are going to be used more.

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    2. This is a very interesting finding, and if it is possible to determine the content of dream imagery then there will be benefits, and most likely advancements for research, clinical practice and pop culture. In research, being able to determine the content of dream imagery without depending on the dreamer to recall this dream can give the research full pictures of the dream instead of the pieces the dreamer remembers. Also, the non-subjective view of the dream takes away any biases, or short-cuts from the dreamer. In clinical practice, it can create more opportunities for therapists to allow people to interpret dreams, as they no longer would have to depend on the dreamer's ability to recall the dream. Also, the therapists can get a full picture of the dream, giving them an ability to aid the person more in the interpretation stage (although this could allow for biases from the therapist). Finally, in pop culture, Van de Castle gave examples of movie directors using their dreams to create their films, using this model can allow for directors to see more of their subconscious imagination. Although this advancement seems wonderful, there are some privacy concerns that may have to be addressed.

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    3. Courtney FriedrichJune 5, 2013 at 5:48 AM

      Like Kathleen mentioned, this discovery will allow for us to determine dream content without relying on the dreamers interpretation. This is useful for people who have difficulty remembering their full dreams, or even to help avoid mis-interpretations of the dream by the dreamer. This can allow for the researchers to gather all the information they need, and right from the source, the brain.
      I believe this can greatly help with interpretations in clinical settings, as it allows for a more clear picture as well as help those who have difficulty describing their dreams.
      As for the research aspect, it think this would be very useful in allow the dreams of so many more patients to be interpreted. This can make it much easier for children's dreams to be analyzed because we are no longer relying on them to tell the therapist what happened in their dream. I also think it would be very interesting to conduct this research on people such as the elderly, deaf, blind, down syndrome patient, and even a schizophrenic patient. This would allow us to delve deeper into the minds of these patients without relying on them to relay what the can remember.

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  10. For research purposes, this new finding can further research that will continue to connect the physiological aspects of dreaming both in NREM and REM sleep stages (mind-body connection). Since brain activation patterns can also infer dream imagery, it can be used to find out differences physiologically and mindfully between neuropsychiatric disorders (e.g. depression, and anxiety). If brain activations can be stimulated to occur in a specific manner that may mean that dream imagery could be induced for therapeutic purposes. The therapeutic purposes of examining dream content by decoding neural activation would be helpful to clinicians in diagnosing patients. If neural activations could be controlled and manipulated it may be helpful to patients with depression and anxiety to overcome there fears/emotions to increase quality of life. The link between waking day events and dream imagery may allow clinicians to get a better understanding of a patient instead of just relying on subjective information. These findings may help the popular culture, in a sense that there may be daily routines that may help with dream imagery or neural activations. Certain foods, vitamins, or minerals may affect the neural activations resulting in different dream imagery. It might also allow popular culture to prevent nightmares and sleep disorders that impact many of us.

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    1. Like Aaron mentioned, this type of technology may be useful in the study of psychological disorders. Clues to physiological ailments sometimes make their way to our dreams and this may be true of psychological disorders as well. If the study of brain activation were connected with the classification of different disorders then diagnosis may become more accurate. A better understanding of dream imagery and psychological disorders could also lead to better methods of treatment. As Aaron stated, this type of technology could result in treatments such as induced brain activation for therapy. This could be beneficial for patients who do not wish to be treated with medications. On that note, children with psychological disorders and sleeping disorders could be treated in a method which does not require medications. I agree with Aaron that this type of technology may be beneficial for those who suffer from nightmares and sleep disorders. in addition to this, this technology may become beneficial for the common citizen who does not suffer from any disorders. Many people use dream books to help receive guidance, therefore this technology may become popular because of its accuracy.

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    2. It would be very interesting and a huge step in the field of dream interpretation for this technique to be used. Reading and interpreting the content of a dream from neural activity could definitely change the way that dream interpretation is done. It would be a very helpful tool for those people who are unable to remember their dreams and then would be able to gain insight from the codes that their neurons produce during sleep.
      This process could also be helpful for people who have recurring dreams to see how many times they actually dream about that certain situation.
      This seems like a futuristic technology to me. Does everyone have the same parts of the brain stimulated by the same neurons and then we are able to know for sure what the content of the dream is? I am interested in seeing how this technology will change how we research and interpret dreams.
      There may be too much variations and deviations in the millions of people to say concretely that neuronal activity provides certain specific dream contents.

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    3. Wow Aaron, your post was very interesting. I never considered the flip side to this finding.. that by connecting the dots between neural activity and dream imagery doctors may be able to stimulate dreams that could aid in their patients' recovery.

      I also found it interesting when you suggested using food, vitamins, or minerals that stimulate a particular pattern of neural activity to potentially alter dream imagery. This concept could be further expanded to incorporate pretty much anything that elicits the desired neural activity; for example, listening to certain types of music while falling asleep/throughout the night.

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  11. For research, being able to determine the content of dreams by brain activation will be very beneficial. Using this method, researchers could determine what brain regions are activated in bad dreams versus good dreams. This will help in our overall understanding of the brain, as well as dreams’ role in the brain. Similarly, using this method researcher could have clients’ recall their dream content and then compare this to the dream content derived from the brain activation, to see similarities/differences in recall versus brain activation. This method may also be useful in clients who cannot communicate their dreams such as clients who are mute.

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    1. Using machine-learning models to determine dream imagery is quite interesting. Because many people don’t remember their dreams, this technology may help recall dreams some people have. In research, this model will allow us to understand what dreams have an association with what part of the brain. This technology will aid in helping patients will mental disorders like depression that suffer from negative dreams or emotions. I agree with Jenn Kerswill about pop culture benefiting from this model in movies and television. Overall, it is quite interesting how far research has come, and the usefulness of this method.
      Prabhjot Dhaliwal

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    2. I agree with the comments that this research can be beneficial for clinicians and researchers because we will learn a great deal of information from investigating the neural activity of the brain during NREM. However, we should take caution with this methodology until there is concrete information regarding the neural activation in specific areas because of the complexity of the brain and the complexity of dreams. I agree that the difference between identifying nightmares versus pleasant dreams may help individuals who are suffering from PTSD, anxiety and depression by understanding and being able to manipulate certain neural pathways to achieve a specific outcome with a dream. Interpreting dreams using this methodology is the new wave of the future and will be very beneficial for individuals looking for answers in their dreams. We just need to be certain of the research and the science behind it before we start trying to interpret dreams using this method because of the complexity and intricacy of the dream process via neural activation interpretation. Once this method has went through further testing and has been investigated and analyzed by various other researchers then the diagnosis and interpretation of people’s dreams could be very beneficial to helping people live better lives through guidance from their dreams.

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    3. Being able to use neural imaging techniques could drastically change the way we are able to look at dream analysis. On of the big problems that occurs during dream analysis is the inaccurate or inability to recollect dreams. With the use of machine based techniques, patients feel less pressured to be aware of their dream as it can simply be recorded as they are experiencing it. This could be especially useful to those going through dream therapy for a repetitive dream that they are unable to recall the details of or for patients with depression or anxiety to better understand the basis of their condition. I find that this method of analysis would greatly reduce the self report bias that accompanies dream therapy as it takes the report of the dream into the hands of a reliable source rather than a person who may be biased on their report due to embarrassment and so forth. It leaves room for collecting more accurate data and providing more relevant therapy and responses. As said by Rebecca, it is also useful for patients that are unable to properly communicate their dreams such as children, those who are mute, autistic and so forth.

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  12. Determining dream content from the decoding of neural activation can be useful for a variety of reasons. First, individuals who have difficulty remembering their dreams would benefit from the ability to develop dream content from their own non-remembered dreams and make important discoveries. Secondly, linkage between dream imagery and neural activity can prove new or different relationships between images. For example, two of the same images may produce different neural activity or alternatively, different images may produce the same neural activity. These responses would be most beneficial when comparing nightmares to pleasant dreams allowing individuals to see what aspects of the dream instill fear and which aspects do not. This discovery may also be useful in providing a greater reference for our dreams, much like a dream diary. On the pop culture side of this discovery movies and TV shows will probably eat this up, creating movies and shows based on the implantation of fake dreams or even stealing other individual’s dreams.

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  13. Breanne McErlean post revealed an interesting idea that using the machine-learning models to decode neural activation, could possibly help one to determine what specific aspects of a nightmare causes fear in an individual. I found this idea very interesting. It got me thinking what other things could a machine-learning model offer. Possibly it could help one to understand further sleep disorders, such as sleepwalking. For example, the machine could further determine why one sleepwalks; possibly due to dream imagery or brain activation. In addition, I also agree that pop culture would explore this idea with more movies such as inception, where they enter another people’s dreams.

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  14. Carly, I understand where you're coming from with the fear/nightmare question related to machine-learning models. But I don't know if we can tell with technology whether the nightmare (or subjective perceived experience) is the cause of the fear or the feeling of fear is causing the nightmare. I think the feeling would likely come first, activating the medulla to trigger nightmare-like images. Like Van de Castle points out, animal images are associated with aggression (1994). This would lead me to think that the machine-learning models would be able to detect when aggression is being triggered, leaving us to figure out the why and how.
    I think that machine-learning models would be an excellent tool for individual's with limited communication abilities and multiple co-morbidities. If we can detect illness progression in a patient who cannot relay their subjective experiences, it would be a benefit to the treatment plan - like having an spy on the inside.
    That being said, there are potential ethical issues with this type of treatment. I think the media would really like to twist that into something.

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  15. Maureen PartridgeJune 5, 2013 at 5:33 PM

    Being able to determine the content of dream imagery by examining brain activation could be useful in many areas of research including continuing the study of mood disorders, depression, bi-polar disorder, anxiety disorder etc and dream imagery, comparison studies between dream imagery in males and females, cultural and age related studies as well as delving into studying dream content in those with limited verbal capacity who don't have the verbal skills to discuss their dreams. This could [erhaps lead to identification of psychological or physical illnesses.
    In clinical practice it could be useful in helping patients who have difficulty in remembering their dreams, or, believing they do in fact dream, complete the methods of dream interpretation thus leading to discovery regarding their physical, emotional and relationship issues.
    For the general population it may lead to a renewed interest and acceptance in dream interpretation, thus propelling the need for continued research. This idea may be not necessarily primarily for our Western culture, but in cultures where discussing dreams and imagery is considered evil, or unacceptable. I also agree with the above post regarding media, and possibly, other scientific platforms twisting the results and practice of using machine-learning models into something negative.

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  16. I have to agree with Stephanie, I think the machine-learning models could help with treatment or detections of particular illnesses. However, since the dream interoperation still involves the individual decoding their own dream, I feel this form of method would not help individual's with limited communication abilities, for they would still have to convey what they discovered. Though, professionals could potentially be able to detect possible signs of illness through dreams, the dreamer would still have to communicate a fair bit to localize where the illness originates.
    I also believe there would be many ethical issues involved and a new step of rules would have to be written between the therapist whom is using the machine-learning models and their patients. For instance, if the machine-learning model recorded someone planning on committing a serious crime or conveyed a plan to hurt someone or themselves, would this be taking as seriously as if the person spoke the words or would it not because the individual wasn't conscious?

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  17. Using machine-learning models for decoding neural activation to determine the content of a dream could be useful tool in research, clinical practice and pop culture in that it could lead to identifying how certain dreams affect individuals, or the types of dreams had by individuals suffering from illness (both mental and physical). I would have to completely agree with Nicole Drumm on the ethical issues that can occur between the therapist and the patient. As safety is paramount for the client receiving dream therapy, there would have to be clear outlines on how the machinery is used and what will be done with the information interpreted from the machine.

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  18. Elizabeth SalisburyJune 5, 2013 at 7:01 PM

    The concept of using machine-learning models for decoding neural activation to determine the content of dream imagery is fascinating. As we have learned, humans are constantly dreaming throughout their sleep whether they remember it or not. Through our lab exercises I have come to recognize that it is not always easy to remember my dreams. The use of machine learning models to determine the content of dream imagery could be a useful tool for clinicians and dreamers to gather and monitor dream imagery data from individuals who are not able to recall their dream or the full details of their dream. As we also know, the dreamer is the expert. Therefore, although this device may assist dreamers and clinicians in gathering information regarding the content of the dream, it is important to remember that the dreamer them self will have the most accurate interpretation of their dream. 

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  19. Being able to determine dream content from using machine detection of brain activation could be extremely useful in clinical practice, research and popular culture, but I believe it could also be risky and quite the slippery slope. One interesting way this could be used is to research the dreams of coma patients, and discover if they really do dream. This may lead to interesting insights regarding what coma patients are aware and unaware of regarding their external stimuli and environment. Also, this may be able to help therapists use dream therapy more effectively with children and other people who have troubles remembering, or describing, their dreams.
    An risk, or an issue, I see with this is that therapists could abuse this to go against the safety of the patient. A main point of dream therapy is that privacy and safety should always be provided to the patient. If the therapist is able to determine the patient's dream content through brain activation, then their might be trust issues between the patient and the therapist.

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  20. Using imaging to determine dream imagery by examining the brain activations would be extremely beneficial. This type of examination has the potential to be used with individuals who may not be able interpret their dreams due to a cognitive limitation. Examples of an ideal population would be children, people with autism, people with Alzheimer’s or other debilitating neurocognitive disorder as a form of interpreting their dreams. It can give insight to thoughts and behaviours that others may be unaware of because restrictions with self-interpretation. There is also the potential to identify areas of the brain that are involved with dreaming, exploring the physiological explanation of dreaming in healthy individuals.

    Clinically, it may be helpful deciphering dreams especially in individuals who have had trauma, phobias, or other abnormal psychopathology. It would be interesting to investigate their dreaming mind and look for better ways for dream therapy to be a form of treatment or preventative roles for worsening of the mental illness.

    I think this technological advance may be of great interest for the general public. Some might find the use of imaging to be more superior then self or therapist guided dream interpretation. It may be of interest to investigate the validity and reliability of using imaging techniques for dream interpretation. This new finding might provide more focus and much needed attention to the benefits of using dream to lead to discovery for all individuals as well.

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  21. Being able to observe the contents of an individual's dreams could be useful in research because researchers could monitor the direct effects of certain external stimuli on dreams. Another great benefit in research would be that they would be able to observe transformations in the complexity and content of children's brains during crucial steps in development.
    In clinical practice, it would be useful because therapists would be able to easily interpret their patients' dreams or aid them in finding discovery. Also, it might allow therapists to record the dreams which would be beneficial to the dreamers in terms of recall and interpretation. Instead of keeping written logs of the patients' dreams, therapists would be able to keep dreams on electronic files.
    If dreams were able to be recorded and viewed by the other people, people would be able share them with their friends. Sharing dreams might be viewed as entertaining so the appearance of dream videos on popular social media might come about. Celebrity dreams would most likely be a focus of magazines. Access to their own, or others, dreams could be a large source of inspiration for artists or filmmakers.

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  22. As Brandon mentioned, the idea of recording and viewing other people's dream is very scary for me. Dreaming is such a personal part of me that I would be uncomfortable both sharing my own and viewing others. If this is the direction that research takes, I worry about the privacy of these celebrities. A dream only has significance for the dreamer, so it seems unnecessary for personal dreams to be widely available. As a society, we are already so interested in the personal lives of celebrities that I think that broadcasting dreams, would be one step too far. I hope this research is never applied to the celebrity world.

    Within a clinical setting, this research could aid interpretation for those with difficulty expressing or describing the elements of their dreams. It could be useful when dealing with individuals struggling to express themselves or children that do not have the vocabulary to describe their dream.

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  23. I agree with the above statement. I find dreams to be too personal to be displayed for others to see. I believe dreams can be beneficial to understand why individuals feel certain ways. Yes I feel that researchers conducting experiments have the right to observe other patients dreams through brain activity imaging. From a clinical point of view, this could be very helpful for certain individuals whom cannot express themselves. An example of this would be an individual with autism, this person could not express or explain their dreams, however through brain activity perhaps researchers could investigate into what and how much brain activity occurs throughout a sleep session with a patient of this condition. Another clinical practice that could be important is using this method for children. Children have a difficult time expressing their dreams and even understand dreams from reality. With this technique perhaps researchers could develop a system to help aid young people to understand why and what they are dreaming and connect that with their waking life.
    As for popular culture, I feel there is already enough out there to keep society occupied. I do not feel our dreams should be displayed for others to see, dreams are unique to the individual. We already know enough about some people in today's world, We don't need to know about their dreams. There are positive and negative sides to this like anything, however I feel the positive out weigh the negative. For clinical, and further research for this highly interesting topic, dreams.

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  24. I also agree with the above statements, dreams can reveal ones most inner thoughts which are very personal and should not be displayed for others to see. Although, like mentioned above they can be very beneficial to understanding how a person feels and why they are feeling that way, so as long as there is a confidentiality agreement between the dreamer and the clinician I don't see anything wrong with observing a dreamers dream through their brain activity. I also agree that this would be very beneficial for clinicians who have patients that are unable to express themselves. Using brain activity imaging on a child would definitely prove to be beneficial because sometimes children have a hard time expressing themselves during their waking day let alone expressing their dreams and any imagery that they remember. I also agree with the above statement that dreams are unique to the individual, therefore i think it would be up to the individual if they wanted their dreams displayed for others to see. Overall I think that this would be extremely beneficial for researchers, clinicians and popular culture to gain a better understanding of dreams and their content.

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  25. Emily Reavie (0487529)June 6, 2013 at 4:10 PM

    I believe that viewing other people’s dreams through machine-learning models that decode neural activation which leads to uncovering dream content is acceptable. Some people disagree, however, as long as consent is collected from the participator – there should be no reason to not carry out the study. Realizing the content of people’s dreams will help with clinical practice in ways such as sleep difficulties and so on through positive manipulation. Also, this would be very helpful for people who cannot fully express themselves through their dreams. Giving the researcher the internal insight would be very helpful. This way, dream records could be made so that the individual can better interpret their dream and not have to rely heavily on dream recall – it will already be recorded. As for popular culture, they could use these studies in order to understand their dreams. Making the public aware is a great first step. In sum, I believe that this method is a great idea for numerous positions in the field of psychology.

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  26. I agree with the other comments that have mentioned that dreaming is very personal. However, as Emily mentioned, as long as proper consent is gathered from the individual, I do not see a problem with using machine-learning models that decode neural activation, to determine dream imagery in those that are willing to undergo the process. I believe this method could be very useful in clinical practice to help those suffering from anxiety disorders that are unaware of the source of their nervousness or worry. I think this method could also be valuable in helping clinicians treat those with memory disorders such as amnesia to discover clues to their identity.

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  27. The concept of using machine-learning models for decoding neural activation to determine the content of dream imagery is extremely interesting and could lead to advancements in treating mental disorders such as Anxiety. As stated by others this technique could be helpful for individuals struggling with anxiety, to understand the root causes or triggers. By learning what triggers their anxiety the individual can then try to avoid said trigger or have a plan to handle the trigger. Again, ethical issues do arise, such as consent, as long as the individual gives informed consent I think that this technique could be very useful.

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  28. It is a fascinating concept that it is possible to determine dream imagery by examining brain activation. This is a great thing for research and clinical practice because it is a chance to gain objective information as opposed to subjective descriptions from dreamers. Also, seeing as the brain still is and always has been very mysterious, the notion that we are beginning to understand how the brain works well enough to interpret dream content is a great thing. It is absolutely a step in the right direction towards a more complete understanding of our most important organ.

    Another benefit of this is that people who have trouble remembering their dreams have a great way of finding out what they are dealing with in their subconscious if prior attempts to remember through meditation and the like aren't working. This way they can get insight into their subconscious that they otherwise aren't able to get. This could help people in many ways, dealing with a multitude of issues.

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  29. By using machine-learning models for decoding neural activation, it has been found that it is possible to determine the content of dream imagery by examining our brain activation. This could be very useful for many different reasons. For starters it is known we can dream in all four stages of sleep but our most vivid and ones we recall most frequently are in REM. With this being said it is probably safe to say then that most of the research on dreams is during this stage of sleep. By being able to view our dreams in NREM sleep we are able to expand our knowledge as researchers. I feel that it is possible that in doing so we are able to now compare and contrast different types of dreams. It is quite possible that the dreams we experience and the emotions surrounding them are different in each stage and between REM and NREM. I also feel that from a clinical standpoint it gives the clinician the ability to draw on more information and be able to confirm if the person if giving an accurate description of their dreams. It is also effective because in many cases people cannot remember their dreams, even those in REM. By being able to pull information from different areas we are able to make up for this loss of memory when we awake from our dreams. In popular culture if the content of our dreams is more accessible than it is quite possible more clinics will be set up leading to more individuals being analyzed.

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  30. These findings would be useful in research as they would scientifically prove the accuracy of an individual’s dream recall. Such knowledge would ensure the accuracy of the research and allow researchers to move forward with confidence.
    These findings would also be useful in clinical practice as there are many who have difficulty remembering their dreams. This technique would ensure that there is an equal opportunity for all to take part in dream interpretation. I’m sure that it would also prove beneficial to those who sub-consciously block out what they have dreamed so that they do not have to revisit painful events or emotions.
    The development of a universal ability to practice dream interpretation could influence pop culture. Dream interpretation would become much more prevalent within society if anybody who so desired could utilize its potential. Furthermore, I believe that dream interpretation could become more prevalent if dream imagery were proven by functional imaging, as members of modern society may feel more comfortable trusting a process in which some of the perceived ‘guess work’ is removed. Scientific processes of verification are highly valued.

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  31. this may be extremely useful since those who are looking for a degree of dream interpretation, yet are unclear of exactly what dreams they are having can use this to see exactly what they are dreaming. this also eliminates any subjectivity of dream studies and makes it more objective.

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  32. I think this method of using machinery to determine brain imagery by examining brain activation could be extremely useful because many people have several dreams a night and are quite often unable to remember all of them, or even just one of them. If we were able to determine what people were dreaming about while they were still asleep I think this would give psychologists and other physicians the ability to discover the meaning and impactions of patients dreams in ways that they were unable to before, because before they had to solely rely on the patients memory- as well as only what the patient is willing to share.

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  33. I agree that by identifying the content of peoples REM patterns they would be able to benefit from a more objective analysis of their dreams and thus apply this gained insight into their waking lives.

    While I do agree that it would be beneficial, I think that it would be difficult to determine exactly what it is that the data would be providing aside from the specific content. Peoples lives are very complex and just because you can identify what the content is doesnt mean that you are going to be able to determine exactly what relationship it has in their waking lives without having discussed it with them and they many be choosing to suppress the dreams for a reason which is why they do not remember the content on their own.

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  34. The new concept of using machine learning models for decoding neural activation has a huge psychological and every day practical implications for individuals.

    From a psychological perspective, we can see that certain criteria for personality disorders fall into the realm of dreaming. For instance, people who experience high amounts of nightmares have been suggested to be at a higher risk for developing certain types of personality disorders. By using the examination of brain activation and linking it to certain dream imagery/content, we could potentially help people suffering with post traumatic stress disorder (PTSD). In addition, it would also help individuals who may not be able to depict what sort of emotions they feel during their regular dreams.

    At the same time, I also think its important for this type of observation to only occur in a clinical setting. Dreams tend to reveal very personal thoughts and concepts about peoples everyday waking lives. Without having some sort of ethical guidelines for use, we could be putting people at risk for embarrassment and long term negative psychological effects.

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