This morning, I had the pleasure on being a guest host for one of the more entertaining, informative neuroscience podcasts of today’s smart technology society: On Your Mind. We talked about the job market, my new book–Meathead: Unraveling the Athletic Brain, and wrapped up with discussion of some peer-reviewed literature.

ResearchBlogging.orgIt turned out that I gave the show hosts–Kathryn Vaillancourt and Liam Crapper–the wrong but related paper out of the same collaboration. I meant to give them this one which focused on sleep deprivation, while the one that I sent was actually more focused on disease: insomnia. It worked out beautifully  though because there was much overlap in the results, presentation of data, and technique as this is where my initial confusion actually arose.

The group of researchers used a very sophisticated form of magnetic resonance imaging that we have yet to fully comprehend. The three of us–Kathryn, Liam, and myself–decided that this technology known as “31-Phosphorus Magnetic Resonance Spectroscopy Study at 4 Tesla” is basically a hybrid of MRI and PET imaging coupled with analysis similar to mass spectrometry to quantify amounts of phosphorus-containing compounds. I think Figure 1 of both papers nicely helps the reader visualize the technique.

4 Tesla technology



The researchers were interested in specific cellular energy metabolites that have long been forgotten about or fully considered in the field of sleep–ATP, ADP, phosphocreatine–as well as constituents of the cell membrane like phosphocholine. In the insomnia paper, these cellular constituents were examined in a group of individuals with clinically diagnosed insomnia. In the sleep deprivation paper, changes in these cellular constituents were quantified before and after a brief bout of sleep deprivation as well as across a two day recovery period from sleep deprivation. The researchers also dissected differences in these cellular constituents between the grey and white matter of the brain which are very different in architectural makeup: the former containing the nerve cells with the latter containing glia.

In both papers, there was a decrease in phosphocreatine which is required to keep up with energy demands in individuals diagnosed with insomnia or after a night of sleep deprivation. This was specific to the grey matter.

PCr changes in the grey matter


This is basically the most important and consistent finding of the two papers. In discussing the presentation of data, we all agreed that the data could have been presented better to separate out tissue-specific differences as well as interactions. The biggest hiccup is this general fitting curve to show the direction of change for both tissues regardless if one had a significant effect (grey matter) or not (white matter). This is a bit disingenuous. We also agreed that the title would have been perfectly fine up until the placement of the colon and mention of the technique. Sure, the technology adds to the attention grabbiness of the paper but is it really necessary? Anyways, I don’t want to take away from the impact of these two studies by focusing on minute details. It is awesome that we now have human data to support the animal work from 2010 in regards to how cellular energy metabolites change across a protocol of sleep deprivation or spontaneous sleep and wake. Truly there is more than just one function of sleep. Even more reason as to why we should take advantage of a good night’s sleep.

Harper, D., Plante, D., Jensen, J., Ravichandran, C., Buxton, O., Benson, K., O’Connor, S., Renshaw, P., & Winkelman, J. (2013). Energetic and Cell Membrane Metabolic Products in Patients with Primary Insomnia: A 31-Phosphorus Magnetic Resonance Spectroscopy Study at 4 Tesla SLEEP DOI: 10.5665/sleep.2530

Plante, D., Trksak, G., Jensen, J., Penetar, D., Ravichandran, C., Riedner, B., Tartarini, W., Dorsey, C., Renshaw, P., Lukas, S., & Harper, D. (2014). Gray Matter-Specific Changes in Brain Bioenergetics after Acute Sleep Deprivation: A 31P Magnetic Resonance Spectroscopy Study at 4 Tesla SLEEP DOI: 10.5665/sleep.4242