Exploring emotions, the brain, and free will with Dr. Lisa Feldman Barrett

Neuroscience and psychology could be the most self-reflective fields of scientific inquiry that humans explore. To study the physiological processes in our brains and the mental processes that lead to behavior — and all the philosophical curiosities that result — is to examine the foundations of what it is to be human. 

Unsurprisingly (and ironically), the thinking brain often gets things wrong when studying itself. Being the source of human bias, it is particularly vulnerable to that bias in a unique way. Compounding matters is the fact that, while any scientific observation has the potential to cause us discomfort, no field sits closer to sacrosanct concepts of the soul and of human autonomy than does neuroscience. 

Misconceptions abound. For example, much of what the general public understands of how the brain works is rooted in pop-science myths that, despite long being discredited, still deeply permeate culture. In this way, the challenge of communicating developments in neuroscience to a large-scale audience remains a notable one. 

The late Robyn Dawes, a highly-influential psychologist who helped establish the field of behavioral decision research, once wrote that “True scientific demonstration involves convincing an observer who is outside the process, particularly one not deeply and emotionally enmeshed in it.” 

While Dawes was writing in the context of his critique of clinical approaches in psychotherapy, we can apply this concept to the dissemination of scientific knowledge with some generosity. Helping those who know little about a field like neuroscience better understand the nature of the brain is no small achievement. 

In this respect (among others), Dr. Lisa Feldman Barrett succeeds more than most. 

Dr. Barrett, a University Distinguished Professor of Psychology at Northeastern University, is a prolific writer and science communicator. She has published over 250 peer-reviewed scientific papers in leading psychology and cognitive science journals, has written numerous, highly-praised books on the subject of the brain and the mind, including How Emotions Are Made and Seven and a Half Lessons About the Brain, and her multiple TED Talks have garnered millions of views over the years.  

She is also said to be in the top one percent of most-cited scientists globally due to her transformative and, at times, controversial research in neuroscience and psychology. Among her contributions to these fields is her work on emotion. In the early 2000s, she challenged the prevailing scientific wisdom that emotions are universal patterns that can be reliably traced back to particular circuits in the brain.  

Interesting Engineering recently had the pleasure to speak with Dr. Barrett over a video interview to discuss her thoughts on how a better understanding of the brain can contribute to healthier lifestyles, the current state, and future of the scientific disciplines and communities she is a part of, and how prediction shapes everything we do as humans. 

The following has been lightly edited for clarity and flow. 

Interesting Engineering: You have had a long and impactful career as a neuroscientist. What figures inspired you when you were just starting out in the field? 

Dr. Lisa Feldmann Barrett: When I was a graduate student, I was very influenced by a cognitive scientist named Robyn Dawes, who was a no-nonsense kind of a guy. He was very well-known for work he had done on decision making, countering the idea that clinicians had this sixth-sense ability to read people well. He struck me as a quintessential scientist. He wasn’t political, he just followed the data. 

I’ve been influenced by Kurt Danzinger, who is a historian of psychology, by William James, who was a founder of American psychological science, and Richard Lewontin, the evolutionary biologist. Also Ernst Mayer, another evolutionary biologist. And by my own advisor, Michael Ross; 30 years later, we’re still very close. There are a lot of people.

IE: You often get a fair amount of pushback from scientists when you publish your research. Do you think the scientific community should be more open to entertaining new evidence about the brain? 

Yes. I don’t court controversy, and I’m not a contrarian by nature. I do have a particular dislike for people lying to themselves in my presence. We all have deeply-held beliefs. Sometimes we pay more attention to information that confirms those beliefs and less attention to information that challenges those beliefs. That’s why I’ve always taken the scientific method really seriously, despite its flaws. Every way of gaining knowledge has some drawback to it. 

"The views that I put forth are not always seen as so controversial when they’re put forth by a man."

Over and over again in my career, I’ve been surprised at the extent to which scientists allow themselves to be led by belief. I’ve also been wonderfully surprised when they are guided by data to change their views.

To be fair, the incentive structure in professional science is not set up for people to admit when they’re wrong. Our behavior is as much influenced by the context that we are in or create as it is by our own desires and beliefs. So, [that structure] makes it hard for scientists to admit when they’re wrong, even when the evidence is crystal clear (which it rarely is). 

I suppose I have taken controversial positions, but they’re controversial only because they challenge the status quo. In any position I take, I am always guided by the evidence. I also don’t think it’s an accident that the views that I put forth are not always seen as so controversial when they’re put forth by a man.

IE: Let’s talk about predictive processing. We see it in every sensory system; we're also starting to see that it could play a significant role in higher-level cognitive functions like language processing, as shown by Martin Schrimpf and his work at MIT’s Brain and Cognitive Sciences department. Why is there this primacy of prediction in the brain? 

I don’t think we know the answer to that question. Scientists, in general, are wary of the “why” question, preferring to focus on the “how” question. But the evidence suggests that prediction is more energy-efficient than reaction. Brains, when predicting, are being more metabolically efficient.

The metabolic argument to me is very profound because, even though we don’t experience our metabolism as a major motivator of our own behavior, it is. Every action has a metabolic consequence, and it turns out that’s a major selection factor for health and illness in an individual over their lifespan. It’s also important to the evolvability of a species. That, to me, is a very serious source of evidence. 

"I don’t think that any complex system, if it’s sufficiently complex, has consciousness."

There’s also a logic to it. Think of the brain in the box argument: your brain is trapped in this dark silent box — your skull. It’s receiving the signals that are the outcomes of some changes [in the world], but it doesn’t have access to the causes, only the outcomes. A loud bang could be thunder, a car backfiring, a door slamming, a gunshot.

The cause matters because it dictates which action you’d take to keep yourself alive and well. But your brain doesn’t know the causes of sense data, it only knows the data itself — the bang — so it has to guess the causes. And those guesses are predictions.  

IE: You’ve said that there is a tradition for scientists of a particular age to write books tackling grand topics about the human condition. Do you ever feel tempted to write such a grand narrative, given your long and successful career as a neuroscientist? 

No, I’m doing something less sensible than that [laughs]. I’m always learning new things. For example, I’ve been hanging out with engineers for the past ten years, and they’ve been teaching me systems theory. That’s influenced me quite a bit, actually. Barb Finlay, who’s an evolutionary and developmental neuroscientist, has been teaching me [lots of] things.

So now, I’m writing a book about the evolution of the vertebrate nervous system for the purposes of understanding the mind. Not necessarily consciousness, per se. 

It’s not a book that’s meant to answer any questions as much as to pose different questions. I’ve been learning embryology, for example, so I can understand how a nervous system is set up in an embryo because it turns out that it’s really important to understand the functioning of your or my brain. Unlike people who write about what they know, I come at these literatures not knowing much at all and trying to learn.

The advantage is that I don’t have preconceived notions, really, so I’m open to learning things, even if they are counter-intuitive. Ignorance serves you well as an opportunity to learn [laughs]. I’m fortunate, too, because I usually get help along the way.”

IE: You mentioned consciousness — what do you think the most compelling mysteries of consciousness are, from both a neuroscientific and personal perspective? What are your thoughts on the various theories that attempt to explain its origins, like Guilio Tonini’s Integrated Information Theory?

Regarding Tononi’s IIT, I understand what he’s driving at. But I don’t think that any complex system if it’s sufficiently complex, has consciousness, which seems to be what he’s suggesting. But that is the question, right? 

Here’s how I think about it. Your brain isn’t really detecting things in the world or in your body. Physical signals — electrical, chemical, etc. — hit the sensory surfaces on or in your body. Those surfaces send signals to your brain, and your brain constructs features that make sense of those signals. Your brain isn’t running a model of the world, it’s running a model of its body.

You could say your brain is running a model of your body in the world. It only knows the world through the sensory surfaces of the body. That’s the first piece that’s really important. 

Somehow, out of all this construction, we get actual consciousness. I really don’t know how it happens. And I’ve never read anything I find compelling that I think explains it. Why does the brain make itself aware of some features and not others? How does the brain create a feeling of pleasure or discomfort? I’m humbled by those questions, but I cannot pretend to have an answer and I’m very skeptical of the answers people have given. 

"The anatomy of your brain requires that feelings are part of rationality."

Maybe with the exception of a neuroscientist by the name of Bjorn Merker, who has pointed out some things I think are really important. He wrote a commentary on the Tononi work that was published in Behavioral and Brain Sciences, and I thought his points were pretty cogent. 

IE: The psychiatrist Iain McGilchrist believes hemispheric differences in the brain matter greatly, saying that Western society is largely a product of the analytical left brain, and that the ability of the right brain to contextualize and make connections between ideas and institutions is woefully underutilized. What are your views regarding hemispheric differences in the brain relating to how they color the world we build and inhabit? 

I’ll make a sweeping and therefore, probably false statement — there is an over-valuing of rationality in Western civilization. Or maybe there’s an undervaluing of sentiment, an under-realization that sentiment contributes to rationality. It’s not separate from it. It physically can’t be separate from rationality. Your brain is always regulating your body. 

Your body is always sending sense-data back to your brain. And your brain makes itself aware of these sensory signals as feelings. So a typically wired brain is never without feeling. This means that the anatomy of your brain requires that feelings are part of rationality. 

As a way of knowing the world and gaining knowledge, McGilchrist may be correct that we probably overvalue math and science and maybe undervalue poetry and art and other ways of knowing the world. I could be persuaded that that’s the case, although, again, it’s a sweeping statement you could challenge. You and I right now are probably alive because of science. People have worked really hard on things like vaccines, for example. 

But the idea that that has something to do with the left and the right brain, I have a hard time with that. Other than language, it’s hard to find evidence for lateralization of any function. Logically, I’ve always had a problem with this “left-brain, right-brain” stuff, and empirically, the findings are not as consistent as you’d imagine them to be.

The lyrical, philosophical, historical observations are interesting to talk about, but trying to locate them in something anatomical and functional — I just think that’s a huge stretch. 

IE: Let’s talk about brain imaging technology, like fMRI (functional magnetic resonance imaging). What are some of the more frustrating limitations of brain imaging technology?

fMRI picks up on blood flow changes, which are supposed to be linked to metabolic fluctuations in neurons. Most of the metabolic cost of neurons is not in the maintenance of the cell but in axonal firing. When a neuron fires, it might be exciting other cells or it might be inhibiting those cells. fMRI imaging can’t really distinguish between the two very well.

How you’d infer excitation from inhibition requires combining the patterns you see from brain imaging with a deep knowledge of anatomy. 

When I trained as a neuroscientist, I was being trained by neurologists, initially. They started me learning neuroanatomy, not brain imaging. That’s how I train all my students. They have to learn anatomy along with the fancy brain imaging. Imaging tools are all well and good, but you really have to understand the literal structure of what you’re dealing with. 

Are brain imaging techniques better than they were before? Yes, they are. For example, we now use a seven Tesla magnet instead of a three Tesla magnet, which helps a lot with spatial precision and a little with temporal precision. [Now] we can see sub-nuclei in the brainstem, for example. 

But if you consider that the best temporal window we can manage with brain imaging right now with fMRI is 500 milliseconds, maybe, or a second if you’re looking at the whole brain — and that is an order of magnitude different from what would you need to capture the scale of actual neural firing.

If you’re trying to answer the question from the actual, physical reality of the brain, we’re miles away from where we need to be. But things are much better than where they were even ten years ago. 

IE: In your latest book, Seven and a Half Lessons About the Brain, you address the idea of free will. By thoughtfully curating one’s behavioral habits on a scale that’s larger than those of single decisions, you argue, you can cultivate an ability to more frequently be in greater control of your actions. This is quite an empowering idea. Why is it inspiring to you?

I think all of us have had the experience of desiring to do or say something different in the moment than we did. We’ve all snapped at our kids or lovers or mothers and wished we hadn’t. If you only think about control as inhibiting a response you, in retrospect, wish you hadn’t engaged in, if that’s what control is, then we’re doomed [laughs]. It’s very hard to execute control in those circumstances, particularly when things are stressful. 

"We need a change in our ontology, not just in our epistemology."

But all animals engage in niche construction, a niche being the part of your environment that matters to your health and well-being. Your ability to modify your niche can have a profound impact on the way your predicting brain predicts. That gives you the opportunity to have more control over your actions before the heat of the moment. I find that very helpful and comforting, actually. 

IE: Where do you see the future of neuroscience in the next five, ten, or fifteen years? What research directions have galvanized and excited you lately? 

This is a really hard prediction to make. If I were in a cynical mood, I’d say it’s not going to go anywhere. The basic assumptions are the same as they’ve been for a hundred or so years. In the absence of a major revolution in the philosophy of science we are using, we’re not really going to get very far.

New technology and fancy modeling techniques allow us to feel better about what we’re doing, but what we really need to do is use those fancy tools to ask different, game-changing questions. When I’m really cynical, that’s how I feel. In psychology and neuroscience, we misunderstand the phenomena we are studying, and therefore we need a change in our ontology, not just in our epistemology.

For example, right now there’s this big discussion about sample sizes in brain imaging experiments and how studies don’t replicate unless you have thousands of subjects. And that’s true, but what they’re talking about is combining everyone’s data and doing group analysis and then wanting one group finding to generalize to or replicate with another group. 

But that sort of replication won’t change the fact that an abstract group summary tells you nothing about the individuals in that sample. Your ability to take a group average and predict an individual’s behavior won’t improve because the group average is an abstraction that does not apply to any single person. It's like assuming that if there are 3.13 people in the average middle-class family, then every middle-class family has 3.13 people in it.

This is what Ernst Mayer called population thinking, and it’s something that really comes directly from Darwin. It’s not what Darwin is most famous for, mind you. If you read Darwin’s On the Origin of Species, what he’s saying is that variation among individuals is real and a statistical summary of those individuals is an abstraction that does not exist in nature. And for natural selection to work, it must have variation to select on.

"There is a profound truth lurking here, I think."

And I think a lot of scientists in psychology, biology, and neuroscience want their science to be like physics — they want to discover a law that will apply to everybody under all conditions. But even in physics, Newtonian laws only apply under certain conditions. Until these kinds of philosophical issues are really dealt with, I don’t know that we’re going to make much more progress. 

What will we see in 15 or 20 years? I think we’ll see ambulatory brain imaging. I think that maybe a person will be able to walk around with an MEG or even an fMRI on their head. But are these techniques really going to fix the problems or answer the questions that we currently face? I don’t think so.

And in fact, they could make them worse, in a way. The kind of science that I think would really be productive is not likely to happen soon. It’s too expensive, and it requires a major adjustment of perspective.

There is a profound truth lurking here, I think. Humans like variation in the things we eat, in the clothes we wear, in where we travel — we like variation in everything except in other humans. We undervalue variation in scientific ways. A well-controlled laboratory study is usually attempting to isolate certain forms of variation and extract it from the larger complex ensemble of varying signals to which it belongs.

That’s a problem if you really are dealing with complex phenomena. What you find will never really generalize to the real world, where ecologies are more complex. And I don’t think there is any fancy technology that’s going to fix that. This requires a change in mindset.