What we learn from mapping migraine aura

24 November 2012 by Markus Dahlem, posted in Uncategorized

Some time ago, we published a paper in PLoS ONE on early migraine symptoms called migraine aura. These symptoms can be mapped onto the human cortical surface. We used individual drawings of the visual field defects in visual migraine aura and MRI scanner readings from the same person.

(The annotation is in German. "rechtes Gesichtsfeld" means "right visual hemifield" and "linke Sehrinde" menas "left visual cortex")

A neurologist at the University of Utah, KC Brennan, reports now that once we understand the "mechanism or what triggers this early symptom, perhaps we can head it off at the pass and prevent the whole rest of the migraine cycle".

This is what we also just proposed based on a mathematical model in a new article available on ArXiv.

We investigated statistical properties of transient waves of cortical spreading depression (SD) in a canonical mathematical model. SD is what underlies migraine aura.

Our approach is a system theory approach, that is, we study properties of signals in systems but we do not pay to much attention to the particular physiological realization. Simply said, this is what "canonical" means. (Some call it generic or normal form model, just for the experts.)

According to this model, SD takes characteristic forms (shape, size, duration) similar to the patterns we have observed in this PLoS ONE article.

As we explain in our new manuscript in detail (though our theoretical body of work is certainly not very penetrable for a broader clinically interested audience, hence the post), the model provides a dynamical understanding of ictogenesis of migraine aura and supports the controversial idea that SD can have a causal relationship with the headache phase in migraine with aura (MA).

Furthermore, we predict that at least some cases of migraine without aura (MO) share the same pain phase with migraine with aura (MA). We named these MOSD. Therefore, our computer-simulations and statistical analysis resolve the seemingly contested notion of MO attacks with silent aura.

These maybe funny sounding silent cases---something without it (aura) and yet with it (SD)---are simply cases where SD activity does not break away from its ictogenic focus. SD can, even without breaking-away, still be large enough to possible release enough noxious substances that cause pain.

Surprisingly, the larger the initial form of SD (pain causing) the less likely that it can break away (causing aura). Therefore, the model also can explain why, at least on average, the headache would be less severe in MA than in MO and, as a rare limit case, the subtype MA without headache.

These model predictions need to be tested with further non-invasive imaging. I hope we are not that far away from this. Here is the KSL TV report from yesterday:

With an eerie almost shadowy wave that moves across the brain, University of Utah neuroscientists have now imaged what happens during an aura, an early visual symptom of this painful disorder.
[read more on KSL TV]

The simulation mentioned in this TV clip is based on our article: M. A. Dahlem, R. Engelmann, S. Löwel, and S. C. Müller: Does the migraine aura reflect cortical organization, Eur. J. Neurosci. 12, 767 (2000).


4 Responses to “What we learn from mapping migraine aura”

  1. chronic pain symptoms Reply | Permalink

    According to this model, SD takes characteristic forms (shape, size, duration) similar to the patterns we have observed in this PLoS ONE article.

  2. online pain management Reply | Permalink

    According to this model, SD takes characteristic forms (shape, size, duration) similar to the patterns we have observed in this PLoS ONE article..

  3. silviu Reply | Permalink

    Hello,
    i am a young psychologist specialized in Analytical Psychotherapy. I was just wondering if there are some researches or if it can be done some mathematical model of the schizophrenics products (such as paintings, drawings, sand representations, etc.) based on different criteria - colors, shapes, spatial, relations between variables, etc., so that we can identify a mathematical pattern of their pathological theme which can help - through probabilities theory or any other analysis (sorry i am not a mathematician :)....) - to predict or to anticipate future development of the schizophrenics products and based on that perhaps to develop therapeutic instruments to eliminate those potential developments.

    Thank you!

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