It seemed simple. But like everything else about the Dog Project, it was also completely wrong.

17

Peas and Hot Dogs

WITH THE APPARENT SUCCESS of the first scan session, Andrew quickly set to analyzing the data. We were giddy that we had not only captured images of the dogs’ brains, but that we had also succeeded in getting several runs of functional scans. These functional runs ranged in length from two to five minutes. At first glance, it looked like we had far exceeded our goal of acquiring a sequence of ten images. In McKenzie’s case, we had one run of 120 images. However, it soon became apparent that figuring out what we had actually captured was going to be far more difficult than we had imagined.

Once the excitement of looking at dog brains began to fade, the first thing we noticed was that the dogs didn’t keep their heads in exactly the same position. There were stretches of about ten seconds where the images appeared steady, almost as good as a scan of a human. And then the dog would move out of the field of view. This would be followed a few seconds later by the head reappearing, but not in exactly the same spot.

It was during these gaps that we had handed the treats to the dogs. Normally, a human would be lying on his back, nose up, almost touching the inside of the head coil. But because the dogs were in a sphinx position, they were facing toward the far end of the scanner, where Melissa and I were giving hand signals and dispensing the treats. At the end of each hand signal, we would grab either a pea or a tiny cube of hot dog and reach all the way to the dogs to let them eat it from our fingertips. Of course, there was no way the dogs could keep their heads still while eating, but they had seemed to settle down pretty quickly. Looking at the MRI images, it became apparent that the inconsistency of positioning was a bigger problem than we had expected.

Somehow, we needed to figure out a way to compensate for the different head positions. In the terminology of fMRI data processing, this is called motion correction. Normally, motion correction is done digitally with special computer software after all the data are collected. The software can figure this out automatically by shifting each image until it exactly overlays the first one of the sequence. For humans, it is pretty simple because they don’t move much, and the corrections are generally less than a few millimeters. Because the dogs didn’t return to the same position each time, the brain had shifted in location too much for the automated software to find it.

Instead, we reverted to an old-school approach of digitally defining landmarks in the brain. First, we identified blocks of scans in which the dog’s head was in a steady position, regardless of where it was in the field of view. For each of these blocks, we then placed four digital markers on identifiable landmarks: the olfactory bulb at the front of the brain, the left and right sides of the brain, and the brainstem at the bottom. Then we used software to shift the images until the landmarks were all aligned. The movement can be described by how far you slide it, which is called translation, and by how much it rotates. If the dog moved its head to the left, we digitally shifted it back to the right to keep it centered. If she pitched her nose up a little, we digitally rotated the image so her nose was level.

Amazingly, this worked. When we viewed the sequence of images in a rapid movie loop, the head now appeared to remain steady in one position. Even Callie, who was not as consistent as McKenzie, appeared stable in the motion-corrected images. We were ready to analyze the actual activation patterns.

Naturally, we assumed that a hand signal indicating hot dog would be much more exciting than one for peas and that this difference would be reflected in the dogs’ brains. To decode how their brains processed these hand signals, we needed to compare the brain responses for each dog to the hot dog and pea signals. Using a standard technique in brain imaging, we separated all the trials into groups of hot dogs or peas. Next, we calculated the average brain response to each of these signals and subtracted the average pea response from the average hot dog response. If our hypothesis was correct, the difference would show up in the parts of the brain that respond to reward.

Instead, we got nothing. No matter how many different ways we looked at the brain responses, it didn’t appear that the dogs distinguished between the hand signals at all.

Melissa had said from the beginning of the Dog Project that McKenzie preferred toys to food. But we couldn’t give her toys to play with in the scanner. Think of the head movement that would cause as she shook her head back and forth! There wasn’t any way around using food as the reward. Callie, of course, was highly food motivated. In fact, she might have loved food too much.

Callie’s food drive was a key factor in her learning the task so quickly. Although she still looked like a tightly wound spring, ready to uncoil in a burst of energy, the prospect of a hot dog could keep her still, at least for a minute or so. There was no doubt that she loved hot dogs, and I saw no reason to use anything else during training.

It didn’t seem to matter what brand of hot dogs I used. Kosher beef dogs seemed like a natural place to start, but then we started expanding her palate. We tried turkey dogs. One brand had a deep, smoky aroma, and this seemed particularly effective. It was so infused with smoke, in fact, that no amount of washing could remove the smell from my hands. But Callie really liked it. She could hear that particular package being opened from the other side of the house, and before the hot dog was fully removed from its plastic bag, she was there at my feet, wagging her whole rump, sweeping the floor with her skinny rat-tail. With that reaction, it was hard to imagine anything better for training.

But then again, Callie was an inveterate poo eater. Did she really prefer hot dogs to peas? What if she was completely indiscriminate and ate everything?

This was potentially a big problem. If the dogs didn’t care whether they ate hot dogs or peas, then the hand signals would be meaningless. They knew that they would get a treat for putting their head in the rest, so if it didn’t matter which treat, there would be no motivation to pay attention to the hand signals. We probably should have dealt with this before the first scan session, but science is imperfect, and you can’t predict how experiments will go.

Before we went any further in the Dog Project, I decided it would be worth testing Callie’s discrimination between hot dogs and peas. If Callie were a human, it would be a simple matter to ask her which one she liked better. Since she couldn’t speak, I was stuck with the classic problem of guessing what was in her mind by observing her behavior. The trick was to devise a series of tests that would force her to reveal whether she preferred hot dogs or peas.

My first idea was to give Callie a choice between hot dogs and peas. Thinking like a human, I reasoned that if I placed a hot dog and a pea on a plate, the one she ate first would have to be her favorite.

This was a two-person operation. Every time I opened a bag of food, Callie was right there at my feet, where she remained glued until I gave her what she wanted. I had to enlist Kat’s help to hold her off while I prepared the test.

While Kat held Callie on one side of the living room, I carefully placed a pea and a piece of hot dog on a plate at the opposite end of the room.