Transcranial focused ultrasound (tFUS) for neuromodulation: What's the role of blood vessels?

The mechanisms behind transcranial focused ultrasound (tFUS) for neuromodulation remain elusive. There are several hypotheses, but conflicting results across a range of experiments in both animals and humans have hampered a nice, clean model which permits simple predictions. Some studies report inhibitory effects, others facilitatory effects. Some studies suggest tFUS has effects which persist for minutes to hours following sonication, while others report little to no activity at all. What’s going on? Might a lot of the confusion be coming from multiple sensitivities to ultrasound within the brain?

I’ve been pondering the involvement of the vasculature in tFUS experiments. Many papers seem to assume that tFUS triggers neurons in such a way that the standard neurovascular coupling model should follow, with a causal chain of events leading to functional hyperemia the way we think of task fMRI. But what if the vasculature is also impacted directly by ultrasound? Or, in the limit, what if it’s the vasculature which has the dominant sensitivity to ultrasound and we have vascular-neural coupling, not the reverse? Might tFUS produce transient vasodilation or brief, local ischemia in the tissue? Shouldn’t these possibilities be explored?

While cell culture experiments have demonstrated that neurons are directly sensitive to ultrasound, in a live animal the presence of vasculature complicates the potential mechanisms. Notably, arteries are responsive to changes in global and local blood pressure. They’re compliance vessels responsible for regulation of blood flow within the brain and mechanosensitive ion channels are widely expressed in vascular smooth muscle cells (VSMCs). Given this natural sensitivity to pressure, it is reasonable to speculate that tFUS may have some direct effects.

All this has got me thinking about the sorts of experiments which could separate neurovascular (neuron-first) from vascular-first mechanisms. Cererebrovascular reactivity (CVR), e.g. the response to hypercapnia, might be a good candidate probe of vascular involvement. So for the rest of this post I will develop some potential experiments which might help clarify the actions of ultrasound applied to the human brain.

Experimental components

For what I have in mind we will need the tFUS perturbation of interest, a CVR challenge, and some sort of simple task to assess neural effects.

The tFUS perturbation could be any protocol someone thinks is interesting. Targeting the motor cortex offers several attractive features, including reaction time as a behavioral measure, a robust BOLD response to be exploited in a task fMRI experiment, and the option to use transcranial magnetic stimulation (TMS) as a probe of tFUS activity outside the MRI, if desired.

For CVR we need a vascular challenge and a way to detect it. If we use hypercapnia as the challenge then we would ideally target a specific inspired CO2 over a subject’s end tidal CO2, but a simple breath holding task might suffice. To keep things simple, I’ll ignore the details and stick with the basic concept: that we have a way to produce hypercapnia in a controlled fashion. I’ll also assume that the hypercapnic response time can be measured until it attains a steady state maximal value.

BOLD is a convenient probe for assessing CVR, although ASL could be used. Again, for simplicity I’ll assume a BOLD time series with typical parameters, e.g. a repetition time (TR) of 2 seconds and voxels of around 3-mm on a side. The TR is sufficient to resolve the temporal dynamics of both CVR and task fMRI, and the voxel dimensions should permit evaluation of the brain response to a smallish focal target of ultrasound.

These considerations make a visuomotor task a good, basic fMRI experiment for evaluating both the neural and vascular consequences of CVR and tFUS. For example, we might employ a visual task in which the subject must press a button when a certain target appears, allowing a reaction time measurement. The BOLD response in visual cortex would presumably be unaffected by tFUS applied to the motor cortex.

Thought experiments

Now that we’ve got the basic tools, let’s develop some experimental designs and think through the implications of each part.

The first step is to determine the CVR to the hypercapnic challenge alone. In this initial test we are most interested in the responses in visual and motor areas, for comparison with later steps, but many other regions could also be evaluated as controls. We would want to evaluate both the CVR response timing as well as the magnitude. Then, once we know the baseline CVR we can apply our tFUS protocol before and then during periods of hypercapnia. How long before hypercapnia should tFUS be applied? The exact timing would presumably be related to the expected response to the tFUS protocol of interest. Certain tFUS paradigms might be expected to have persistent effects lasting minutes or tens of minutes.

What might these initial CVR experiments reveal? Perhaps tFUS prior to hypercapnia will reduce the subsequent cerebrovascular reactivity in the motor cortex. Alternatively, it might facilitate a greater subsequent CVR if VSMCs or pericytes are relaxed by tFUS. And of course it might make no difference at all.

When tFUS is applied during steady state hypercapnia we might see nothing at all if the primary mechanism of tFUS is also to produce vasodilation, or we might see a focal reduction of regional blood flow if the ultrasound acts primarily as a vasoconstrictor. We might even see a slight enhancement of vasodilation in the motor cortex if the ultrasound triggers neurovascular coupling there.

Next, we need to evaluate the effects of hypercapnia on the visuomotor task. The task response must first be assessed during regular breathing, and then in the presence of steady state hypercapnia. Our primary ROIs are the responses in the motor and visual cortices. We need to assess the task-induced functional hyperemia in the presence of vasodilation - is it additive? - and assess whether task performance, e.g. the reaction times in the motor task, is affected by hypercapnia. 

Now we can combine all the parts. First, we should apply tFUS to motor cortex during task blocks and assess visual and motor cortical responses, as well as task performance, with normal breathing. We should expect the visual cortex to have the same response with or without tFUS, while the motor cortex should be perturbed according to the tFUS protocol being evaluated. And finally, we can repeat the experiment during steady state hypercapnia. Responses in the visual cortex should again be the same with or without tFUS. In the motor cortex we will see the combined effects of tFUS and hypercapnia on the task performance and on the functional response to the task. Does the tFUS paradigm work in the same way in the presence of vasodilation from hypercapnia, or have we managed to alter things somehow?

There are other approaches we might consider. If hypercapnia produces interesting effects, perhaps it would be useful to test hyperoxia and see if opposite effects can be produced, for example. Or, it might prove to be more interesting to try titrating the effects of varying degrees of hypercapnia if it turns out the vasculature is involved but not in an all-or-nothing manner.

Complicating issues

What about confounds? It’s well known that tFUS can produce auditory effects, so we would need appropriate masking and a good sham for control blocks. A more interesting confound might arise from the magnetic field. Lorentz effects inside the MRI may alter the dominant tFUS mechanism, suggesting that the entire experiment might need to be repeated outside the MRI. In that case we would need to replace BOLD as the measure of CVR if we want to measure directly the effects of tFUS in the vasculature. Alternatively, the effects of tFUS on task performance could be evaluated with and without hypercapnia while assuming vasodilation, and the task design modified or extended to include other brain regions.

Something else I’ve been pondering is the involvement of large versus small vessels. Large feeding arteries are highly reactive compliance vessels, and I’m wondering if tFUS intentionally targeted on an artery might produce interesting results across an entire vascular territory. I would like to see someone try sonicating an artery and measuring an angiogram and a CBF map, e.g. with ASL. Few studies map the vascular system prior to applying tFUS, so it would be all too easy to sonicate a rather large artery inadvertently and, if it reacts, alter the vascular dynamics of a sizable region of the brain. A hypercapnic challenge could also be employed, to test whether tFUS alters the reactivity in that vascular territory.

And then what?

Whatever the results, there are clear implications for tFUS. At a minimum, demonstrating no significant vascular effects would have safety implications, especially for certain populations with compromised blood flow who might be prime candidates for tFUS therapies. But the complete absence of direct vascular effects from tFUS would be a surprise to me. Right now, my suspicion is that there should be some interesting vascular effects. They might even be separable from neuron-first perturbations, offering the possibility of tunable responses. Neuroscientists might be disappointed, but those of us with an interest in neurophysiology would perk right up!

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PS I haven't included references yet. I may add them at a later date. I'm not totally up to speed on the tFUS literature so what references I do eventually include will likely be incomplete. Apologies if that puts anyone's nose out of joint!

 

 

Single slice EPI to visualize brain pulsations

 

We talk a lot about head motion in fMRI. As much as head motion can be limiting, it’s also important to remember that there is real brain motion, too, distinct from whatever the head might be doing. And whereas printed head cases or bite bars might reduce head motion to a large extent, the real brain motion occurs inside the skull in a way that is inaccessible to anything we can do during data collection. (In principle, one could gate acquisitions to the cardiac cycle, but this would invoke its own set of complications.) Instead, we are forced to deal with real brain motion as best we can during post-processing. The problem here is that our image processing tools usually work at the voxel level, leaving any sub-voxel motion unaddressed. 

A few years ago I was involved with a project to assess vibrations measurable on the skull. To relate what could be measured outside with what was happening inside the head, we used a single slice EPI sequence collected at a TR of 40 ms; a frame rate of 25 images per second. At this speed, all the dynamics produced by the arterial blood pressure wave - the mechanical force which propels the blood from the aorta - are visible in quite spectacular fashion right across the brain. Here are a couple of example scans:

 

 

Apart from the very obvious fluctuations in the lateral ventricles, note how the CSF in sulci also fluctuates with each heart beat. If you look very closely you’ll be able to see the brain tissue deforming, too. Several vessels, mostly veins, are visible. Pulsation in the superior sagittal sinus is especially prominent in the sagittal scan. In the transverse scan there are also large changes in the overall image intensity every few heart beats, and this is almost certainly due to breathing (which we didn't track).

Note that this type of contrast isn’t replicated precisely in your fMRI scans. Use of a single slice with a relatively high excitation flip angle (30 degrees) relative to the short TR (40 ms) means that we have considerable within slice and inflow T1 weighting, in addition to the T2* changes you’re used to thinking about for BOLD. But some scaled down version of these apparent T1 changes are in your fMRI data, especially if you’re not in the habit of using a small flip angle. (See this post and Gonzales-Castillo et al. (2013) for more information on setting the flip angle to minimize motion effects via image contrast.)

Perhaps more importantly, think about what’s happening at the tissue level. Even if we somehow magic away all the CSF and large vessel fluctuations, we’re still left with considerable non-linear movement of the brain tissue itself. This motion is greatest at the base of the brain, but displacement and shearing of many cortical areas can be seen in the above cine loops with the naked eye. Maybe ponder real brain motion the next time you click the button to apply a motion-correction or physiological noise reduction step in your processing pipeline. How well do you think your “motion correction” steps are tackling these low-level perturbations? Don’t forget they’re also working simultaneously on the (usually larger) displacements and rotations from real head motion and pseudo-motion produced by respiration (i.e. chest movements perturbing the magnetic field across the head). 

PS If you want to see more dynamic images of brain motion, check out the motion-amplified scans developed by Samantha Holdsworth's group: 2D, 3D, quantitative 3D. Not fMRI but still powerful reminders that the entire brain is moving almost all the time.

Could MSM be a useful tracer for determining CSF flux in the human brain?

 A few years ago I was involved in a project to develop a better chemical shift reference for in vivo MR spectroscopy (Kaiser et al. 2020).  As often happens in science, life, logistics and money conspired to change the directions of those involved and this project got put on the shelf to gather dust. We no longer have either the people or the capabilities to pursue it further. Perhaps someone else would be able to take it on and see whether there are more uses than as a chemical shift reference.

One of the angles we were considering in 2020 was the possibility of using MSM as a tracer for measuring CSF flux in the brain. Various approaches have been developed using MRI, but they are all rather difficult. One involves an intrathecal injection of a gadolinium contrast agent and then looking for signal losses depicting where the Gd contrast diffuses to (Iliff et al. 2013). Negative contrast is always a complication for MRI because signal voids often arise from imperfections in the magnetic field. Another method uses an arterial spin label (ASL) and long post-labeling delays to assess the amount of water passing from the vascular compartment to the tissue compartment, i.e. through the blood-brain barrier, as an index of what is assumed to represent the inflowing part of the glymphatic system (Gregori et al. 2013, Ohene et al. 2019). These methods are low sensitivity and highly prone to motion. A third approach uses low diffusion-weighted imaging to try to differentiate CSF from other water compartments (Harrison et al. 2018). But again the method is inherently sensitive to bulk motion and it's not entirely clear to me how well the signals represent the CSF to interstitial fluid flux versus other microscopic compartments. So, would MSM offer simultaneously positive contrast and improved sensitivity? And would its clearance give an indication of the CSF flux through brain tissue?

MSM is methysulfonylmethane, the trade name for what a chemist would call DMSO2. It is labeled by the FDA as GRAS: "generally regarded as safe." As such, there are few regulations for its use and so you can find it in everything from dog food to ointments for a bad knee. You may well be consuming it and not have a clue. But the good news is you can buy pills of MSM for your experiments. There's no special permission needed, you can get these at your local pharmacy. (A word of caution: the amount listed on the package may not match what is actually in the pills! Do your own assay!) Then, once you've got this past your IRB, you can dose subjects with acute or chronic doses and see what happens to the MSM level in the brain.

MSM is a small, polar molecule which probably distributes throughout biological tissues with approximately the same concentration profile as water. The more water content in the tissue, the higher the MSM concentration is likely to be after a few hours. But this is a guess. What we do know is that entry into the brain is rapid. We can see MSM in a brain spectrum within 10 minutes following an oral dose. The MSM signal then remains fairly stable for several hours, which is a property we wanted for our chemical shift reference. 

But what is driving the clearance rate? In our early tests, we observed a half life in normal brain of about 3 days. This was for a single acute dose. In later tests (not included in the 2020 paper) we saw about the same washout time for a single 6 g dose as for a single 2 g dose. We also had a subject (me!) take a 1 g dose every day for 30 days to ensure steady state concentration, then observed the washout. Again, a half life of about 3 days. 

 

For clearance, we assume the MSM partitions and clears down its concentration gradient. Presumably the MSM distributes into the brain via the blood. Once we stop giving new oral MSM the blood concentration falls to near zero, and presumably clearance of the MSM in the body then occurs via the kidneys. If the routes out of brain tissue include the blood and perhaps CSF clearance, then what matters is the concentration gradients between brain tissue and blood and, perhaps, brain tissue and CSF.

This is where the idea of using MSM as a CSF flux (glymphatic system) tracer comes in. If the half life is around 3 days in normal brain, does the rate of clearance change with sleep deprivation, bouts of vigorous exercise or other challenges to an individual? What about differences between individuals? Do older subjects clear MSM more slowly than younger subjects on average? Women faster than men? Is the density of aquaporin channels a prime determinant of the clearance rate from brain, or is MSM able to diffuse across all membranes with approximately the same rate? And is CSF flux through brain tissue an important determinant of the clearance rate, or incidental to it? We were never able to test these ideas. 

As a practical matter, MSM can be observed easily in a 1H MR spectrum. Its chemical shift of pi (3.142 ppm) and sharp line makes it easy to fit separately from brain metabolites. We also never tested the ability of chemical shift imaging (CSI) to observe MSM, but there's every reason to think that a CSI method which can reliably image the NAA, creatine and choline singlet peaks will be able to map MSM perfectly well, too.

So, there you have it. A free idea for someone to explore and perhaps exploit for the purposes of assessing CSF clearance, sleep, dementias and so on.

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Functional connectivity, ha ha ha.

 

If you do resting-state fMRI and you do any sort of functional connectivity analysis, you should probably read this new paper from Blaise Frederick:

https://www.nature.com/articles/s41562-024-01908-6

I've been banging the drum on systemic LFOs for some time. Here's another example of how not properly thinking through the physiology of the entire human can produce misleading changes in so-called FC in the fMRI data. That said, I don't think Blaise has the full story here, either. For one thing, the big dips in his Fig 1b suggest that something is being partially offset with the on-resonance adjustment that is conducted automatically at the start of each EPI time series, so I have a residual concern that there are magnetic susceptibility effects contributing here somewhere. (Perhaps the magnetic susceptibility effects are what's left to drift higher after RIPTiDe correction, as in Fig 6b, for example.) The point is that not having independent measures of things like arousal, or proper models of physiologic noise components like sLFOs, or a full understanding of what's happening in the scanner hardware (including head support) during the experiment can lead to an assumption that things are neural when there are better explanations available. 

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Link added on 6/23/2024: Blaise Frederick discussing systemic LFOs on "Coffee Break!"

 

Core curriculum - Cell biology: synapses and neurotransmitters

 

The action potential from one neuron may or may not trigger further action potentials in neurons it connects to via synapses. A typical neuron with its single axon may make thousands of synapses to the dendrites of these "downstream" neurons. The locations of the synapses matter, in the sense that position relative to the downstream neuron's cell body provides a sort of weighted importance to any one synapse, as does the type of synapse. For fMRI we don't need to get too deep into the details of these connections, but we do need a basic understanding of the differences between excitatory and inhibitory connections. For the most part, whether a connection is excitatory or inhibitory is determined by the type of neurotransmitter released at the synapse.

First, let's get an overview of types of synapse and neurotransmitter, and the difference between excitatory and inhibitory neurotransmission:

Next, a little more detail and some context: 

In case it wasn't already clear, here's a nice explanation linking the pre-synaptic neuron's electrical potential to neurotransmitter release at the synapse:

Categorizing any one neurotransmitter as excitatory or inhibitory is a reflection of its usual effect on the electrochemical potential in post-synaptic neurons. The actual effect on any one post-synaptic neuron - whether that neuron is rendered closer to or farther away from its threshold voltage - can depend on the location of the synapse as well as the neurotransmitter(s) released in the synaptic cleft. Still, we can usefully categorize neurotransmitters according to their broadly different functions around the body:

In case you're interested in the structure of these neurotransmitters - perhaps because you are researching the effects of exogenous compounds ("drugs") on brain activity - here's a little more biochemistry:

Most of the videos above have focused on the neurotransmitter in the synaptic cleft. Naturally, the receptors on the post-synaptic neuron are critical to signaling. So let's take a slightly closer look at receptor types: 

And finally, a little more detail on the importance of synaptic location, not just type, in determining the type of action produced by a neural circuit:

That should suffice as a basic introduction to neurotransmission for the bulk of fMRI experiments, where we are looking at the collective effects of millions of neurons and trillions of synapses in any given voxel. Additional videos suggested by YouTube should provide good branches for those of you wanting more detail.

At this point, I want to shift to looking at the axon structure and its myelin sheath because this is an important distinction at the level of the fMRI voxel. We will tend to categorize any given voxel as containing mostly white matter (myelinated axons) or mostly gray matter (cell bodies). We will look at these in turn.

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Post-publication bonus video! I came across this video on some recent discoveries on dendritic activity while hunting for introductions to myelin structure. It's well worth a watch.

 

 

Core curriculum - Cell biology: the neuron's action potential

 

The last post reviewed the origins and properties of the resting membrane potential. Specifically, we are most interested in the membrane potential of neurons because they have an activated state that leads to signaling between neurons. Signaling from one neuron is achieved via an action potential from the cell body (soma) down its axon to synapses with other neurons. There are several good summary videos available online. Try them all to reinforce your knowledge.

Finally, in this post we get our first real look at synapses and excitatory and inhibitory neurotransmitters as part of a graded potential:

Now that you've seen the electrochemical action potential, in the next couple of posts we can dig more into neuron-neuron signaling, including synapses and the role of chemical neurotransmitters.

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BONUS: a speedy review. All familiar stuff now, right?

Core curriculum - Cell biology: cell membranes and the resting potential

 

A lot of the important functions of neurons (and glia) happen at their cell membranes. In the case of neurons, in addition to the membrane around the cell body (the soma), we also need to understand what happens along the neuronal processes (aka neurites): the dendrites (inputs) and the neuron's axon (the output). 

Let's begin this section by reviewing the structure of the cell membrane.

 

 

Transport across the cell membrane was introduce above. There are different mechanisms of membrane transport, each establishing certain behaviors of a cell.

The sodium-potassium pump is one of the most important membrane transport mechanisms for neural signaling. Let's take a closer look.

 

The cell's resting membrane potential was mentioned in the last two videos. The resting potential is an important starting point for understanding neuronal signaling via action potentials. For the last part of this post, we will look in more detail at the origins of the electrical potentials and electrostatic gradients across a cell membrane at rest.

In the next post we can start to look at cell signaling. Specifically, we are most interested in a neuron's action potential, which is the main way neurons communicate with each other.

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