Winter Brain, Summer Brain: Seasonality in Brain Responses?

By Neuroskeptic | February 13, 2016 4:39 am

A new paper in PNAS raises the interesting suggestion that our brain function goes through yearly cycles. According to authors Christelle Meyer and colleagues, their findings reveal new evidence of seasonal effects in human cognitive brain function “that could contribute to cognitive changes at specific times of year.”

However in my view, the study is too small to be conclusive.

Meyer et al. used fMRI to scan 28 young participants. Each of the volunteers spent 4 1/2 days in a laboratory “devoid of seasonal cues”, which included a period of sleep deprivation, before being scanned.

meyer

During the fMRI, participants performed two cognitive tasks, one measuring sustained attention, and another executive function. Meyer et al. examined whether the season in which the fMRI scan took place was correlated with brain activity during the tasks (this study took place over the course of 18 months, between May 2010 and October 2011.) It turns out that there were some significant correlations. Across several brain areas, neural activity followed a seasonal cycle. Here’s the executive function task:

exec_season

However, I’m a little skeptical. I’m not sure if the impressive sinusoidal cycles seen in parts B and D of the image above are an instance of the voodoo correlations effect, but my main concern is the sample size of just 28. That seems small for a between-subjects study intended to measure subtle correlations of this kind.

Presumably the sample size was limited because an impressive five days of work went into testing each participant. It can’t have been easy (or cheap) to keep each volunteer in the lab “under strictly controlled conditions, devoid of seasonal cues” for that long. These precautions which were meant to ensure that factors, associated with the seasons, such as the temperature and light level, were controlled for, to reveal the effects of the season per se.

But I’d be more convinced if the authors had shown that seasonality effects were also (albeit perhaps weakly) present in a large sample of normal scans. For instance, last year, it was discovered that the size of the human brain changes over the course of each day. That study had a sample size n=9383, pooled from two large studies of MRI scans that took place at different times of day.

Perhaps something similar could be tried in this case? Around the world, neuroscientists run fMRI scans in all seasons. Maybe it would be possible to pool together a database of fMRI scans, using the same task, to look to see whether the date of the scan had any effect. An alternative approach would be to scan a small number of participants multiple times each, spanning the course of the year. Such a within-subject design would increase the statistical power.
ResearchBlogging.orgMeyer C, Muto V, Jaspar M, Kussé C, Lambot E, Chellappa SL, Degueldre C, Balteau E, Luxen A, Middleton B, Archer SN, Collette F, Dijk DJ, Phillips C, Maquet P, & Vandewalle G (2016). Seasonality in human cognitive brain responses. Proceedings of the National Academy of Sciences of the United States of America PMID: 26858432

CATEGORIZED UNDER: fMRI, papers, science, select, Top Posts, voodoo
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  • Ibn
  • diadrometry

    For most of our species’ development the brain had different responsibilities due to the different seasons of the year. Hunting, gathering, and then farming would have needed different “modes” throughout the year, depending on the season, to survive. I can imagine that that (given the time-scales of the brains development and responsibilities) is still measurable.

  • practiCalfMRI

    In addition to the small sample size (and lack of task performance differences?), to be sure that it’s actually brain-based at all one would want to have measured the scanner stability across the seasons, too. Three biggies: (i) the stability of the power to the scanner, which will vary with other loads on the same supply and change especially strongly with high heat or cold outside (i.e. air con), (ii) thermal stability of the scanner suite, and (iii) any change in secondary water cooling for the gradients. The first issue – voltage instability – translates directly into gradient instability unless the scanner has a dedicated UPS/conditioner. The second issue affects air-cooled RF amplifiers, which this almost certainly was because it was an old Siemens Allegra, head-only scanner. The third issue also affects gradient/signal stability directly (e.g. scanner “drift”) and may vary if the chilled water supply to the heat exchanger for gradient cooling changes with season. In many locations the “cold water” temp varies as the outside air and surrounding ground temp, albeit with a lag.

    would also add an additional scan to the protocol, because BOLD is a non-ideal way to measure physiology over long time frames. I would add an arterial spin labeling scan and check for changes in resting perfusion. Indeed, one could use ASL for the fMRI instead of BOLD, thereby largely subtracting out the scanner instability effects (provided the subtraction of tag-control images is equally good, which it may not be if the RF amplifier is particularly unstable). These are critical data to record if one is going to do anything long term on an NMR or MRI scanner.

    • practiCalfMRI

      Another way to account for scanner instabilities is multi-echo BOD, e.g. http://www.ncbi.nlm.nih.gov/pubmed/25449746

    • http://multiplecomparisons.blogspot.com/ Chris Filo Gorgolewski

      A similar study looked at relation with environment temperature and did not find anything: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0140134 (I know it’s only one of many things you raised, but I though it’s worth mentioning).

      • practiCalfMRI

        But we can’t infer anything from site to site. Each site must determine their stability and any seasonal fluctuations if they are planning on assessing seasonality effects. I can regale you with interminable stories of weird and wonderful “seasonal” scanner effects that have been found over the decades.

  • Thomas Kraynak

    Check out: http://www.ncbi.nlm.nih.gov/pubmed/25394737 N=404. The MyConnectome dataset could also be useful for this.

  • Pingback: 2 – Winter Brain, Summer Brain: Seasonality in Brain Responses?()

  • http://www.cmadan.com Chris Madan

    Some stability data from scanning phantoms across the seasons should also be useful in ruling out scanner-related artifacts.

  • Pingback: Seasonality effects under fMRI | What is behavioral?()

  • http://www.mazepath.com/uncleal/qz4.htm Uncle Al

    If you are having problems with scanners (including headaches and nosebleeds) , prescribe Ephemerol.

  • disqus_xk55NgnmR2

    I concur about seeing a more globally diverse set of participants (& possibly a greater age range). What happens if you’re in an area that’s perpetually cold, snowy, rainy, dry, sunny or hot? What if the typical 4 season breakdown (Spring, Summer, Fall, and Winter) isn’t applicable (e.g., rainy and dry season)? Would you still see similar corresponding effects?

  • Pingback: Invierno y Verano: La estacionalidad en el Cerebro -()

  • minas s

    Maybe this has some connection:
    Sakellakis M, Koutras A, et al. Identification of a seasonal pattern to brain metastases. Neuropsychiatric Disease and Treatment. 2016 Mar 7;12:609-10.

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Neuroskeptic is a British neuroscientist who takes a skeptical look at his own field, and beyond. His blog offers a look at the latest developments in neuroscience, psychiatry and psychology through a critical lens.

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