How Dogs Love Us: A Neuroscientist and His Adopted Dog Decode the Canine Brain

by Berns, Gregory

  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.

  “Go!” I exclaimed.

  Kat released her and Callie darted to the plate. Without any hesitation, she licked up the hot dog first and then the pea. So far, so good.

  “Hot dog!” I called out.

  Feeling very pleased with my ingenuity, we set up to try again, except this time I reversed the location of the hot dog and pea. I nodded to Kat, and she released Callie. Once again, she made a beeline to the plate.

  And lapped up the pea.

  Okay, I thought, we can’t expect perfection. Maybe she was just excited.

  “She ate the pea,” I called out. “Let’s try again.” Kat rolled her eyes, but humored me anyway. We repeated this ten times, and every single time Callie went to the left side of the plate, which is where the hot dog was located on the first trial.

  “Maybe she knows that she will get both treats
, and that’s why she goes to the same side,” Kat said.

  Yes, of course. Must think like a dog. If I were Callie, I would just scoop up whatever was closest and move on to the next one since I would be getting both anyway.

  “What if I picked up the treat she doesn’t choose first?” I said. “That way, she will have to make a choice.”

  We reloaded the plate, and Kat let her go. Just like before, Callie lapped up the pea on the left side of the plate. This time, I snatched the hot dog away just as she started to make a move toward it.

  If a dog could shrug its shoulders, Callie surely would have. She trotted back to Kat and waited for another round. But in the end it didn’t seem to make any difference. Callie just kept going to the left side, where the pea was placed. How could she prefer a pea to a hot dog? The hot dog was loaded with carnivorous goodness, perfectly suited to her Paleolithic instincts.

  After about ten trials with the pea on the left, she finally paused and noticed the hot dog on the right side. In fact, this was the first time I had ever seen her pause with food in front of her nose. As if to say, Hey, where did this come from? she went for it.

  And then she was stuck on the right.

  Hot dog or pea, it didn’t make a difference. No matter how many times I placed a pea on the right, she wouldn’t track the hot dog.

  Kat shook her head and said, “Do you still need me?”

  “No,” I said. “I have another idea.”

  I looked at Lyra, who had been watching the experiment from the sidelines. She had long gotten used to seeing Callie work for treats. If she waited long enough, she too would get to partake in the spoils, just for looking pretty. She perked up when I turned to her.

  “Lyra, come here, sweetie!”

  The three of us—Callie, Lyra, and I—padded into the kitchen.

  Now, with the plate on the counter, I placed a pea on the left side of the plate and a hot dog on the right. Both dogs were rapt with anticipation. Quickly, I placed the plate on the floor.

  As expected, Callie lurched for the right side, where she was still fixated. Before she could nab the hot dog, I grabbed it away and fed it to Lyra. A momentary look of confusion flashed across Callie’s face. Lyra was delighted and started to drool.

  Surely, I thought, this would make Callie think about her choice.

  It didn’t. Even now, with Callie’s usual avarice, she continued to perseverate on one side of the plate. Either she really didn’t care about the difference between hot dogs and peas, or her brain was executing a simple rule: stick with the same side as long as it has something good.

  The next day, I asked Mark about Callie’s tendency to stick to one side.

  “That’s common,” he said. “Some dogs are naturally right- or left-sided. Other dogs will remain with whatever attracted them first. Some will remain with wherever they were rewarded last. Other dogs will relax and cognitively evaluate each situation or wait for a cue.”

  In fact, the development of a side preference was documented in a series of cognitive experiments in dogs in 2007. Researchers at the University of Michigan were attempting to determine if dogs had a concept of quantity. Does a dog know that two pieces of food are better than one? It seems obvious to us humans, but if you think about it, “quantity” is really quite an advanced concept. It requires some knowledge of the physics of the world, that larger volumes hold more stuff, and that more is better. Although there is some evidence that infants can discriminate basic differences between, say, one and two objects, the cognitive skill called numeracy doesn’t fully develop in humans until early childhood.

  The researchers wanted to know if dogs had abilities similar to human infants. They tested twenty-nine dogs on a task very similar to what I had concocted in my kitchen. Plates with different amounts of food were offered to the dogs, and it was observed which plate the dogs chose. Most of the dogs chose the plate with more food, although not all the time. It was not clear whether the dogs actually had a sense of quantity or whether they were responding to perceptual cues of bigger piles of food. Either way, it was also noted that eight of the dogs had to be excluded from the analysis because they developed a side preference regardless of the quantity presented.

  So Callie had a strong tendency for side preference, which seems to be a normal variant among dogs. Still, I was disappointed that my feisty rescue wasn’t an Einstein. I had no idea about McKenzie’s preferences, but since at least one of our subjects couldn’t tell us the difference between peas and hot dogs, a change in the experiment was in order.

  The next day, I reported my findings to the lab.

  Andrew was disappointed. “If they don’t care about the difference between peas and hot dogs, how will our experiment work?”

  “It won’t,” I replied. “If peas and hot dogs are the same to the dogs, then the hand signals convey no useful information. As long as they put their head on the rest, they know they will get a treat. They don’t care which.”

  Nobody could understand why the dogs didn’t discriminate between the two foods. We were all stuck thinking like humans. We had to think like a dog.

  “What if we just get rid of the peas?” I mused.

  “You mean a reward versus no-reward experiment?” Andrew asked.

  “Exactly. Even if the dogs don’t care about hot dogs versus peas, surely they care about hot dogs versus nothing.”

  Andrew nodded in agreement.

  It wouldn’t even require any new training. We already had the two hand signals. Left hand up meant “hot dog.” Now, two hands pointing toward each other would mean “no hot dog” instead of “pea.”

  “Don’t you think the dogs will get irritated and stop doing the task?” Andrew asked.

  It was a good question. If it were me in the MRI simulator, I would scoot right out of there as soon as I realized I wasn’t getting food all the time. Psychologists call this extinction, which means that if you stop rewarding a previously learned behavior, the behavior will eventually stop.

  But dogs might see it differently. Not rewarding every trial might increase their motivation. This is called variable reinforcement—VR for short. VR is very common in animal experiments. A VR10 schedule means that sometimes the subject is rewarded but, on average, only once every ten trials. The unpredictability of VR tends to make animals more attentive and work harder to obtain the reward.

  Something as drastic as VR10 would not work in our experiment. I just couldn’t see Callie sitting still for ten repetitions of hand signals to get just a tiny cube of hot dog. If I were in her position, I would begin to wonder after the third repetition without a treat. By about the fifth repetition without food, I would probably give up entirely and quit the experiment. I suspected Callie wouldn’t put up with it either. More important, it would result in an imbalance in the number of observations collected in the scanner. If we had ten trials of the no-reward hand signal to every one of the reward hand signal, it wouldn’t be an even comparison. We needed an equal number of rewarded and unrewarded trials for this to work. The solution was simple: VR2.

  A VR2 schedule means that roughly half the trials will be rewarded (two trials for every one that is rewarded). This would give an equal number of observations for both hand signals. As long as we didn’t simply alternate, which would make it completely predictable for the dogs, then they should stay highly motivated.

  That evening, I tried VR2 on Callie.

  As usual, the rustling of the hot dog bag called her to the kitchen.

  “Wanna do some training?” I said in my high-pitched doggie voice.

  Callie cocked her head and tore off into the living room. When I got there, she was already in the tube with her head in the chin rest. To warm up, we went through several trials as usual. Left hand up, hold it for ten seconds, and then reward. When she seemed settled in, I flipped the two-hand signal that had previously meant peas. This time, after ten seconds, instead of giving her a pea, I just touched her forehead. She thought a pea was com
ing and tried to lick my hand. With nothing there, she looked puzzled.

  I pointed to the chin rest and said, “Touch.”

  Callie quickly placed her head down. To make sure she wasn’t confused, I immediately showed her the reward hand signal, and rather than wait ten seconds, rewarded her right away. The next trial, I gave the two-handed, no-reward signal and quickly ended the trial with a touch on the head. We repeated this for about five minutes, and amazingly, she didn’t get bored or leave the simulator. Instead, her posture and attentiveness improved. Her head positioning became more consistent, and her eyes were fixed in attention on my hands. Now when I showed the reward signal, I could see her pupils dilate, indicating a high level of positive arousal. And she remained motionless.

  VR2 was a success! If Callie could catch on so quickly, I was sure McKenzie would too. And with her pupils dilating, it was clear that Callie now cared about the hand signals.

  If this didn’t work, nothing would. We were ready.

  18

  Through a Dog’s Eyes

  WE DIDN’T HAVE MUCH TIME to get Callie and McKenzie trained on the new version of the task. We could have taken longer with the training, but the logistics of finding a day when Mark, Melissa, Rebeccah, and the scanner were all available dictated the schedule, and the next available time that everyone could meet again was only two weeks away. If we missed the window in two weeks, we would have to wait another month to book a large chunk of time at the scanner. The pressure was on.

  At least we knew the dogs could do this. Each time we had gone to the scanner, we had accomplished more than I had expected, and I was counting on this next time to be no different. The dogs knew what they had to do. The real uncertainty was how much data we would be able to collect and whether it would be enough to demonstrate caudate activity.

  The fMRI signal is very weak. We measure activity as the relative change in signal intensity from some baseline level. But even in the best of circumstances the signal intensity rises by less than 1 percent. To make matters worse, the fMRI signal is noisy. The noise, which comes from heart rate variability, breathing, and even the electronics of the scanner, causes fluctuations in the signal that are ten times as much as the thing we are looking for. The signal-to-noise ratio (SNR) of fMRI is therefore quite low. Fortunately, the noise is random. If we collected enough repetitions during the experiment, we could average the fMRI signals from each, and the effects of noise would be diminished.