stuff of nightmares part 2

Apologies for continuing with the experiential renderings, but sometimes our own interactions with people and their machines can prove very interesting indeed….

In the follow up to my sleep study, I was told by my doctor that I have “sleep architecture that displays several indicators of depression”, and he proceeded to try to convince me that I am depressed despite my assertions to the contrary. In some ways this resonates with the discussion of the convincing power of visual data in Modeling Proteins, Making Scientists. Studies of sleep architecture may not produce models per se (though like Morrison and Morgan’s ‘renderings’ (quoted on page 64), its legitimacy is derived from its performance), but through these visualization practices, they do produce convincing data that is taken for the thing in itself (at least by this particular doctor) rather than the product of a certain experimental apparatus statistically correlated with particular experiences.

If you follow the link below, you will find an interactive graph depicting the sleep architecture of a “normal” individual:

http://www.osrmedical.com/en/themes-lies-au-sommeil/

By way of contrast with this “normal” subject, a depressed person has short REM latency (they go into REM sleep more quickly – which, while presumably undesirable as far as these researchers are concerned, is intentionally cultivated by “sleep hackers” like this guy: http://dustincurtis.com/sleep.html through intentional sleep deprivation). Other such indicators include:  i) sleep continuity disturbances (e.g. prolonged sleep latency, nocturnal awakenings, and early morning awakening);  ii) diminished slow wave, delta sleep (stages 3 and 4);  and iii) an altered intranight, temporal distribution of REM sleep, with increased REM sleep time and REM activity earlier in the night (Reynolds and Kupfer 1987). Another indicator to add to this list is time spent sleeping, with those with unipolar depression sleeping less per night than either “normals” or those with bipolar depression. I’m sure anyone who read my previous post would be surprised if I didn’t have at least some of these (especially those dealing with REM – though dreams and REM sleep aren’t as correlated as we’re usually told to believe), after my descriptions of the experimental apparatus, how difficult that made it to fall asleep and the nightmares and frequent awakenings that resulted. These patterns were not understood as resulting from the particularly fraught intra-action that I described previously, but were taken to be indicative of how I sleep generally, and by consequence of previous studies into mental illness and sleep, what my moods are. As such, I question in what ways diagnostic practices serve to animate the charts and statistics produced through research. It strikes me as dangerous that charts and statistics regarding structures of sleep can be taken as more authoritative as to the suffering of the patient than the patients own experiences. Such presumptions not only subordinate the patients experiences to medical categories, but, through equating prediction with certainty (roughly 70% of those with these features are depressed according to Fleming), serves to homogenize the experiences of all individuals with features of this architecture.

Joseph Dumit’s 2003 ethnography, Picturing Personhood, elaborates on how “normal” subjects are selected for PET scans according to gender, race, handedness, age etc such that women, racial and sexual minorities, lefties, and those not within a particular age group become eliminated from the category of “normal” (61-63). Graduate students (regardless of how white, male, heterosexual and righthanded), I suspect, would fail the ‘normal’ test too.

Dumit, Joseph

2003 Picturing Personhood: Brainscans and Biomedical Identity. Princeton NJ: Princeton University Press.

Fleming, Jonathan

1988 Sleep Architecture in Depression: Interesting Finding, or Useful? In Progressive Neuropsychopharmacology and Biological Psychiatry 13: 419-429.

Myers, Natasha

(forthcoming) Modeling Proteins, Making Scientists: Rendering Molecular Life in the Contemporary Biosciences.

Reynolds, CF. And Kupfer DJ

1987 Sleep research in affective illness: State of the art circa 1987. Sleep -1 0: 199-215.

This is the stuff that nightmares are made of….

Recently I was admitted to a sleep clinic where I spent the night in a strange bed, with electrodes attached to my head (EEG), around the eyes (EOG), legs (EMG) and heart (ECG). The electrodes were attached to correspond with the frontal, central and occipital portions of my brain using a paste that conducts current from my scalp’s electrical potentials. The EEG records oscillations at a variety of frequencies, which represent synchronized activity over a network of neurons, and is then displayed on a computer screen in the control room. Ensnared in these contraptions for 9 hours, I managed to glean about three hours of sleep, during which time I had nightmare after nightmare separated by brief moments of consciousness that I intentionally induced to escape the dreams. Unfortunately I was unable to get my hands on the EEG readings from my sleep study, so this picture copied from the wikipedia page on REM sleep will have to suffice as an example of how my dream states were rendered visible to the sleep technicians in the control room:

Through EEG monitoring, sleep has been rendered visible, and has been the subject of a great deal of research since the 1930s when Alfred Lee Loomis first identified stages of sleep, which he classified into 5 stages (A-E), later classified as 4 numerical stages plus REM when REM was identified in 1957, and more recently reclassified into three stages plus REM as the distinction between stages 3 and 4 were deemed inconsequential, partly as a way to make the scoring of sleep cycles less laborious for the scorer, though this is seen by some as problematic due to the increase in intra-state variability. The way sleep stages are classified, therefore, has been relatively unstable, and there has been a considerable amount of research done recently to argue for altering the hertz at which different stages are delineated and to argue for dividing the stages further. Included in these studies are arguments that the entire system might need to be reworked due to the digitalization of recordings which allow for more automation of the process as algorithms can replace the scorer, who would only then be needed for surveillance and artifact decontamination. Sans labour issue, there are considerably less impediments to integrating the recent critiques for more heterogeneous analyses of recordings and the dismantling of categories such as the stages of sleep, and classes of sleep (the delineation of macrostructures – the 4 stages, and microstructures – shorter-lived events recognized on the EEG). Arguments against such automation center around human labour also: namely that readings are actually quite variable from individual to individual and that well-trained humans are more able to adapt to such modifications (Schulz 2008).

Beyond issues in classifying and interpreting the data, the apparatus itself encodes assumptions about the brain at rest. Firstly, there were only 6 electrodes attached to my scalp, which reflects the assumptions of what areas are necessary for recording sleep. Secondly, the electrical activity recorded reflects that which occurs in the more superficial layers of the cortex, which combined with placement, leaves significant amounts of the cortex (particularly in the basal and medial areas) unrecordable. And then there is the issue of artifact decontamination.

Both the character of my sleep that night and the way my sleep will be reported to the sleep specialist cannot be understood except in relation to this process of debate, the standardization of a particular way of classifying sleep for the purposes of quantification, and most importantly (as far as my nightmares are concerned) the recording apparatus itself. I am thus going to invoke Karen Barad’s notion of intra-activity in order to try to do justice to the efforts of sleep technicians to capture sleep for the purpose of diagnosis and treatment. Such an endeavor has the potential to become a never-ending russian doll of phenomena, so many of the intra-actions present in this scenario will necessarily be neglected. I do not often have nightmares and rarely choose to wake up before my alarm (what an appalling notion!), so what was being recorded was in no way representative of how I normally sleep. It was instead the intra-actions of tactile sensitivities with sticky goo and medical tape; nervousness and being in a sterile room that strangers had access to; being watched and the instruments that watched me – not only superficially through the cameras but on a minute scale as every eye twitch was being digitally rendered as waves visible and enduring for the technician’s purposes. This is the observer-effect exemplified. The faux hotel room appearance, awful Dali print (which may or may not have contributed to the nightmares) on the wall and the promotional materials that assured me that my sleep would be comfortable and “as if you were in the comfort of your own home”, all were complicit in presenting a view that the sleep that would be recorded would be nearly indistinguishable on paper from the sleep that I normally get. Moreover, pictures of various waves, coded, quantified, and presented in a report to the specialist are viewed as accurate and authoritative rather than the outcome of the intra-actions of particular understandings of what counts in sleep, the electronic apparatus’ that since the 1930s have been defining these understandings, and the nervous subject. I must admit to being frightened of discovering whether these renderings are taken to be more authoritative on my sleep than my accounts are when I go for my follow-up. Realism and mechanical objectivity may prove very frustrating indeed.

Barad, Karen

2003 Posthumanist Performativity: toward an understanding of how matter comes to matter. In Signs 28(3): 802-831.

Schulz, Hartmut

2008 Rethinking Sleep Analysis. In Journal of Clinical Sleep Medicine 4(2): 99-103.