These are good questions and important ones. Seeing a pulse wave during optical imaging is well established. In fact, the signal is so large that you can see it on individual pulses very easily. Historically it has been treated as an artifact that should be eliminated, since it often covers up the signal you’re interested in. Other researchers have used other methods, such as Doppler sonography, to look at how the shape of the pulse wave corresponds to health parameters, such as elasticity, but typically measure from the carotid artery or other arteries since it is difficult to measure through the skull using that method. Our lab is showing that instead of getting rid of the pulse as an artifact in the optical data, we can use the shape of the signal to make inferences about elasticity as these other researchers have done in the past outside of the brain. In fact, we have recently been comparing the pulse measurements using the same method on the carotid artery to show that the measurements are correlated.

The main source of artifact is that we go through the skin in order to reach the brain, so the pulse in the skin can be included in our signal. Another problem that we’ve had is that if the pulse is larger in general (reflective of higher blood pressure), it tends to last longer, which adds noise to the measure of latency that we use to infer elasticity. We are still working on improving our analysis to improve our accuracy, but as a first pass, we’ve used sufficient source-detector distances to reach the cortex, and we calibrate the latency measure by dividing by each participant’s pulse pressure.

I would love to see this sort of technology used in the future to potentially flag risk factors involved in vascular diseases of the brain, or even for a fast, portable screening for strokes. However, I think that the implementation of this technology is still limited before it can be adapted for these clinical purposes.

What I find most exciting about this work is its potential to give us new insights into the vascular mechanisms that contribute to cognitive aging. This technology allows us to see directly into the brain, whereas before brain vasculature as a whole was estimated using measurements of the carotid artery. Moreover, it would be interesting to see if regional differences in vascular health in the brain played a role in the regionally specific cognitive declines that we see with aging. If the health of the brain vasculature is involved in cognitive decline, then this method will give us a powerful tool to assess to what degree vascular health affects cognition, how much different interventions or preventative measures impact the vascular contribution to cognitive aging, and insights into what aspects of cognitive aging are not related to vascular health.

You’ve hit upon the most exciting part of this work for me! If age affected everyone’s brains and vasculature the same way, then there would be no variation to study. However, as you know, there is a huge range of both genetic, behavioral and environmental factors that play a role in the trajectory that these biological systems take. The fact that this variation exists shows that there are factors at work that accelerate or prevent cognitive and physiological aging. Using this method, I would like to explore exactly what sort of cognitive domains can be correlated to neurovascular health, and I would like to discover what sorts of differences, especially in behavior and environment, lead to the best outcomes in aging individuals.

We have seen a significant general decrease of elasticity across the whole brain that occurs with age. However, so far in the study, we haven’t been able to look at very specific regions-of-interest to do these types of correlations. Right now we are working on incorporating the brain regions from free-surfer (which is software that includes tools for doing MRI anatomical analysis) into the software that we use to analyze the optical data, so hopefully I’ll be able to give you that answer soon. We want to correlate the elasticity data specific to these smaller ROI’s to the participant’s cognitive performance as well as their anatomy.

The shaved head is not necessary, but it helps with getting a good signal because the melanin found in hair and skin absorbs a lot of near-infrared light. Normally, we have to push the hair away in each of the detector holes before putting in the detectors.

Ah, I see :)

Hey Carlos. The “near-IR” light is defined by a window of wavelengths of light that can penetrate relatively deeply compared to other wavelengths of light in biological tissue and includes both red and invisible light. We can get a few centimeters deep. Actually the thickness of the skull doesn’t matter as much as whether or not there is a large blood vessel present, since the skull doesn’t absorb near-IR light, but blood absorbs significant amounts of it.

Thanks, Matt!