One of the delightful aspects of running an imaging facility is the sheer variety of projects coming through the door. Late last year my boss told me he'd been discussing with a group from Emory University about doing fMRI on trained dogs at our center. I'll confess to receiving the suggestion unenthusiastically, if only because I envisioned a mass of bureaucracy followed by a head-on logistical collision between the dog group and the dozens of human users. Activity at our center oscillates between hectic and frenetic, depending on the day. But, as it turned out I needn't have worried. The bureaucracy was handled admirably by the Emory folks while the logistical issues simply failed to materialize because of the professionalism of the dog fMRI team. It's been an enjoyable experience. And there are dogs. Many boisterous, happy, playful yet exceedingly well-trained dogs. Like these:
Greg Berns (on Twitter here) at Emory decided a few years ago to do something that few thought was possible: to scan dogs with fMRI while they are awake and behaving, using nothing more than the same tactics as we prefer to use for human MRI subjects, i.e. training. No sedatives, no anesthetics. Nothing but some good old-fashioned familiarization.
But why try to do dog fMRI at all? In Greg's case the initial question was what fMRI might tell him about his own pet dog's brain. A simple example: was his dog excited to see Greg come home from work because it was the prelude to dinner - a conditioned response - or was the dog genuinely pleased to see Greg, the person, and dinner was a nice bonus thank you very much? I'll let Greg take it from here, courtesy of a recent TEDx talk:
Greg's initial dog fMRI project also featured in a segment broadcast on CBS's 60 Minutes in October, 2014.
As mentioned in the TEDx video, the project that Greg wanted to run at my center uses service dogs-in-training. All the dogs are from Canine Companions for Independence (CCI), based in Santa Rosa, CA. Ignoring Bay Area traffic our location is sufficiently convenient to conduct scans on these dogs. We also happen to have the same scanner that Greg has at Emory.
In human fMRI research the vast majority of the time and effort goes into the data processing and statistics. For dog fMRI, on the other hand, there is a truly massive front end load to train the subjects to get them into the scanner in the first place. It's a huge, intricate, time-consuming undertaking with each dog going through up to three months of MRI-specific acclimatization to the sights, sounds and feel of the scanning environment. Learning the task they're to perform is trivial by comparison. But it's far from a burden. As service dogs-in-training these animals spend many hours of every day gleefully learning to locate correctly various objects left laying around the CCI campus, or how to open a door with a rope, or how to react to a fire alarm versus a door bell, or any number of other vital activities they will eventually perform out in the real world.
I got a tour of the mock scanner at CCI-Santa Rosa with Kerinne (on the right, below) and Erin, two of the awesome CCI dog trainers. You can also see Fritz, our volunteer for the day, in his kennel behind Erin's right elbow.
As with any human MRI the first task is safety. For dogs it's extra important to protect their sensitive hearing. Unlike humans, dogs tend to shake earplugs out of their ears unless the devices are literally strapped in, so the dogs are fitted with a sports wrap to hold the plugs in place:
Over the course of several weeks the dogs are trained to place their heads in a styrofoam muzzle rest positioned inside a wooden ring mimicking an RF receiver coil. They also learn a task, signaled by the trainer, that tells them when they can expect to get a small food reward. Eventually, the dogs learn to climb a set of steps and lie down with their muzzles on the chin rest while they lie still in a mock MRI, which beeps and clicks using recordings from the real thing. Unlike the real thing, however, it is perfectly safe for me to record videos from all angles and up close. Here's Fritz during a training session:
The dogs are trained in groups, typically 8-10 at a time, to be scanned over a single weekend. On scan day the dogs are chauffeured over to Berkeley with their trainers and assistants. Luckily, not only is Berkeley a dog-friendly campus but it also has many open spaces for the CCI handlers to exercise the dogs while they wait. As you might imagine, a day trip out with their friends can get dogs pretty excited so the CCI staff have a bonus challenge to keep their charges focused. Nobody said hard work couldn't also be fun!
The setup at the scanner matches very closely that in the mock scanner, except for the addition of mats and covers to protect the magnet and the scanner suite from bits of dog treat and dog hair. We don't get too much of the latter because all the subjects get a bath the day before. Each dog is introduced to the scanner suite for a quick familiarization and as soon as the humans are ready (most delays are for the humans!) the dog goes through its now familiar routine.
Interestingly, none of the dogs scanned so far seems to be bothered by the presence of the magnetic field. Whether they sense and ignore it or cannot sense it we don't know. In any event their reactions to the magnetic field are not appreciably different than the average human subject. The advantage for the dogs, as for humans who have been trained in a mock scanner, is that they are acclimatized to the dark, confining tube that makes lots of noise. The biggest distraction seems to be the novel environment they've just experienced - the car ride, the Berkeley campus, new humans around the imaging center - but going from play mode to work mode is a quality specifically selected for in service dogs.
After trying different coil options Greg settled upon the standard Siemens 2-channel human neck coil for the dogs. It's sufficiently large and open that the dogs can lie in the sphinx position to get their heads inside, with front paws either side, and the handler can stand behind the magnet to signal the behavioral task. The neck coil generates decent images. Here's a screenshot of an anatomical scan on the left and a mosaic of EPIs on the right:
There's plenty of contrast while the spatial resolution and SNR aren't too bad for a brain about the size of a lemon. Dogs have thick skulls as well as large muscles around the head. These dogs are either retrievers or Labradors about a year old and are all fit and healthy so subcutaneous lipid signal tends to be similar to what I'm used to seeing with human heads. Fat suppression is used for EPI just as for human fMRI. Other parameters are described in this recent PeerJ paper:
Functional scans used a single-shot echo-planar imaging (EPI) sequence to acquire volumes of 24 sequential 3 mm slices with a 10% gap (TE = 28 ms, TR = 1,400 ms, flip angle = 70°, 64 × 64 matrix, 3 mm in-plane voxel size, FOV = 192 mm). Slices were oriented dorsally to the dog’s brain (coronal to the magnet, as, in the sphinx position, the dogs’ heads were positioned 90° from the usual human orientation) with the phase-encoding direction right-to-left. Sequential slices were used to minimize between-plane offsets from participant movement, and the 10% slice gap minimized the crosstalk that can occur with sequential scan sequences.
If you're interested in the entire scan protocol, including some of the earlier approaches that have been improved upon in the current experiments, there's more information in this PLOS ONE paper from 2013.
Dealing with motion
Motion is the arch enemy of fMRI whatever the species. As already mentioned, the best approach is to have compliant subjects. Greg's muzzle/chin rest design serves twin purposes. It allows the dogs to relax in a position where the head is reasonably well restrained left-right and head-tail, and it is a mark for the dogs to return to whenever they move to get a reward. As with human fMRI, watching the inline display as the EPIs are acquired is highly informative. It's not uncommon for a dog to be able to go 60 seconds with motion effects visible only at the level of the N/2 ghosts, as for a motivated human subject. And as for returning to their marks, it has to be seen to be believed. I once spent several minutes being highly amused by the ability of one dog to get a treat, swallow it and then return to the same position such that a triangle of small blood vessels ended up in precisely the same position in the same EPI slice. I had my finger on the screen as a reference. Except for the contrast changes due to blood flow in those vessels there were no other signs of life!
The EPI is run continuously while the dog does the task and gets treats along the way. The entire run is thus contaminated by numerous intended movements - for rewards - as well as the occasional unintended movement - most often a dog licking/swallowing a few seconds after returning to its mark. An observer notes the times in the scan the dog is being treated, to assist in the elimination of motion in post processing, but as with human fMRI the effects of gross head motion tend to be unambiguous whether they're intended or not. Unlike humans, however, these dogs tend not to fidget with the rest of their bodies, not even wagging their tails when they are on task. And they don't fall asleep, either.
I'm not involved in the processing so I can't comment on how well or how poorly one can chop out motion-contaminated EPI frames and splice together the remainder for analysis. A major difference with most task-based fMRI is that Greg's team simply discard the majority of frames where motion occurs. The trick, then, is to decide the cutoff for discarding data. This is the procedure outlined in Greg's most recent PeerJ paper:
Because dogs moved between trials (and when rewarded), aggressive censoring was carried out, relying on a combination of outlier voxels in terms of signal intensity and estimated motion. Censored files were inspected visually to be certain that bad volumes (e.g., when the dog’s head was out of the scanner) were not included. The majority of censored volumes followed the consumption of food. On average, 51% of total EPI volumes were retained for each subject (ranging from 38% to 60%).
Other than aggressive censoring, the time series are also motion-corrected using a 6-parameter affine registration and the motion traces are used as regressors in the statistical analysis. Standard stuff. Whether this is better or worse than what is commonly done for human fMRI I'm not qualified to say. What I do like is the expectation that a lot of data will be discarded and this is budgeted for in the acquisition. With most human fMRI the motion issue tends to be considered post hoc and rarely do people expect to throw out a lot of data.
What could be done to improve dog fMRI? I'd like to test our ability to measure head movement with a peripheral device such as a pressure sensor placed on the chin rest. We have the equipment and we could probably incorporate the sensor, which in our case is a circular disk less than 2 cm diameter, into the chin rest in such a way that the dog doesn't even notice it. We record movement (usually chest movement for humans) using BIOPAC equipment which also records TTL signals sent once per TR during the EPI time series, so synchronization is trivial. Perhaps we could use such a measure to define automatically those segments of an EPI time series that should be thrown out, then motion-correct the remainder. We might then start to look at the effects of respiration and consider ways to further clean the time series.
There are also opportunities to upgrade the image acquisition. For a start we are using a two-channel (human) neck coil but the majority of the brain signal comes from the upper loop. This configuration negates the option to do simultaneous multislice (a.k.a. mutiband) EPI for fMRI. The size of the elements in the coil is suboptimal from a signal-to-noise (SNR) perspective, too. The open, circular geometry of the neck coil permits Greg to scan a wide range of dog sizes with the same equipment so I consider that a fixed specification for now. A coil mounted somehow to the dog's head has been considered and rejected because of the need for cabling. Cables would likely be too restrictive and/or get broken. An inductively-coupled head-mounted coil (which doesn't require a cable) might work, but it's a lot more complicated to design and getting multiple channels would be a problem. The option I've considered most seriously is a flexible "blanket" array coil, say 16 channels, that could be attached to a custom-built rigid former that allows the blanket to be mounted firmly as either a full or semicircle, easily mimicking the geometry of the current neck coil setup. A 16-channel array coil would permit a slice acceleration factor of at least R=2, perhaps even R=3 for SMS-EPI. It's something for me to consider as I see different RF coil designs become available.
I am also interested to know if we can acquire other types of functional scan from some of the better performing dogs. Both arterial spin labeling (ASL) and resting-state fMRI scans are highly motion-sensitive, but I'm fairly sure that some of the dogs would be able to remain as still as a human for the four or five minutes both of these types of scans require. Training in the mock scanner will tell us where the limits are. It might be appropriate to acquire ASL or rs-fMRI in shorter blocks with aggressive scrubbing of spoiled volumes. Scrubbing for rs-fMRI may change the nature of the data and I'm generally not a fan, unlike for task-based fMRI which can be considered as individual task blocks for statistical testing. But it could work for ASL. We shall have to try it and see.