Book review: Elusive Cures

 I'm normally an avid fiction reader, but this summer I've been on a non-fiction kick. I just finished listening to Nicole Rust's new book, Elusive Cures. The premise of the book is the simple, important question: why haven't we made more progress on understanding brain disorders using basic neuroscience? Rust's argument is that the kind of "domino chain" causal model that we use to understand many neural systems is simply mismatched to the nature of how complex systems work. Rust is a cognitive neuroscientist who is known for her work on vision and memory, but she does not lean on these areas in the book, instead broadly surveying the neuroscience of disorders including Alzheimer's, Parkinson's, and depression. 

Although I'm mostly a cognitive scientist these days, Rust's description of the forward causal model for neuroscience immediately felt familiar from from my grad school neuroscience training. These kinds of causal systems are the ones we've made the most progress on in cognition as well: we have pretty strong models of how visual object recognition, reading, and language processing unfold in time. In contrast, processes that unfold interactively over time, such as mood, are much harder to understand this way. 

I have often been skeptical of the application of complex dynamical systems theory to cognition, though Rick Dale's nice intro for the Open Encyclopedia of Cognitive Science did win me over somewhat. I agree that cognition is a complex dynamical system, but in practice such formalisms can often feel unconstrained. Many researchers using dynamical systems theories don't – for whatever reason – engage in the kind of systematic model comparison and evaluation that I believe is critical for cognitive modeling. 

I heard that same kind of skepticism in Rust's own writing, which made it even more compelling when she made the case for the critical importance of understanding the brain as a complex dynamical system. Her discussion of the role of homeostasis in brain systems in particular was inspiring. It made me wonder why we don't apply the concept of homeostasis more to reason about social systems as well – for example, how communities maintain their educational standards in the face of policy changes or interventions. It's always a pleasure when a book sparks this kind of reflection. 

In sum, I strongly recommend Elusive Cures. I found it thought-provoking and broad, with good descriptions of both individual research findings and sweeping trends. The book feels like the rare "popular" book that also effectively makes a forceful scientific argument. 

Two summer book recommendations

After a long stint primarily reading fiction, I've been on a non-fiction kick recently and just read two books that I would definitely recommend!

Persuasion in Parallel (2022) by Alexander Coppock, a political scientist at Yale, is a scholarly monograph on how political persuasion works. It's a delightful combination of large-scale replications, strong emphasis on effect estimation and causal inference, and really thoughtful discussion of mechanisms. It starts from a replication and re-analysis of Lord, Ross, and Lepper (1979), the seminal work on political persuasion, and goes on to replicate a whole host of more recent studies. Across all of them, the key take-home is that arguments about controversial topics (e.g., gun control, abortion, etc.) operate very similarly across people with very different views: they cause small changes in attitude in the direction of the arguments, regardless of the recipient's initial views. 

In statistical terms, there's very limited heterogeneity across groups in the effect of persuasive arguments. I really appreciated evidence on this heterogeneity question because often students' intuition in psychology is that everything differs based on sociodemographic characteristics; yet this intuition is rarely quantified or challenged. Coppock's analyses take a really important step in this direction. 

The book is short and quite readable (especially given how data-rich it is). It's also very up front about the limitations of the work. There's also a thought-provoking final chapter on Bayesian inference and rational models of belief change that makes a number of connections to computational cognitive science that I enjoyed. Despite being an academic, I am not the sort of person who will sit down on a weekend with a monograph from another discipline for fun; this book was an exception for me because of how interesting, important, and thorough the work is.

On a heavier note, Doctored (2025), by Charles Piller (an investigative reporter with Science), is a screed about scientific misconduct in Alzheimer's research. I'm intimately familiar with replication issues in psychology, but I was still totally horrified to read about the impacts of scientific fraud in the Alzheimer's field. Piller makes a very well-researched and thorough case, working with experts on fraud and scientific reviewers. While a critique of the book by an Alzheimer's authority questions how central the fraudulent work was to the field (Lancet review), I was convinced by the later chapters of Doctored that show how pervasive image falsification has been within the Alzheimer's research enterprise. It's just awful to think that many people have been in dangerous clinical trials due to research misconduct. 

The book was clearly written very fast as there is some redundancy between chapters and a bit of unnecessary stage-setting around various researchers' grandparents (perhaps reflecting a pivot from an earlier vision of the book where certain people were more important to the narrative). But the substance of the scientific critique is so compelling – and honestly terrifying – that I was more than happy to overlook a few minor weaknesses in the prose. Definitely recommend.

Effect sizes and baby rearing (review of Baby Meets World)

In these first months of M's life, I've been reading a fair number of parenting advice or interest books focused on babies. My motivation is partially personal and partially professional. Regardless, it has been entertaining to sample the vast array of different theories and interpretations of what is going on in M's cute little head (and body).

I recently finished Baby Meets World: Suck, Smile, Touch, Toddle, by Nicholas Day, and it is my favorite of the scattered group I've read. Day is a clear, funny writer who also blogs entertainingly for Slate. Baby Meets World is a tour of the history and science of parenting, broken down by the four activities in its subtitle.

But unlike many books about developmental science it is also a cry of rage and despair by a new parent who has completely had it with parenting advice. This feels exactly right to me. Rather than urbanely walking through the latest research on sucking along with a Gladwell-esque profile of a scientist, Day shows us the absolute weirdness of its past - from deciding whether to use goats or donkeys as wet nurses to the purported link between thumb sucking and chronic masturbation.

The implication, drawn out very clearly in a recent New York Times blog post, is that our current developmental studies may not have much more to offer parents than Freud's hypotheses about thumb sucking:

... [E]xperiments have the most meaning within [their] discipline, not outside of it: they are mostly relevant to small academic disputes, not large parenting decisions. But when we extract practical advice from these studies, we shear off all their disclaimers and complexities. These are often experiments that show real but very small effects, but in the child-rearing advice genre, a study that showed something is possible comes out showing that something is certain. Meager data, maximum conclusions. (p299)

People often ask me how relevant my own work on language development is to my relationship with M. My answer is, essentially not at all. I am a completely fascinated observer; I continually interpret her behavior in terms of my interest in development. Nevertheless, I see very few - if any - easy generalizations from my work (and that of most of my colleagues) to normative recommendations for child rearing beyond "talk to your child."

While this kind of recommendation is without a doubt critical for some families, it's not necessarily the kind of thing that you need to hear if you're already in the market for baby advice books. For example, rather than telling me that M needs to hear 30 million words, you should probably counsel me to talk to her less (let the baby sleep, already!). One size doesn't fit all. There are some interesting applied studies that have near-term upshot for baby-advice consumers (e.g. work on learning from media). But overall this is the exception rather than the rule in much of what I do, which is primarily basic research on children's social language learning.

Parents who have read parenting books often say "you must do X with your child" or "you can't do Y," whether it's serving refined sugar, giving tummy time, or using the word "no" (don't, do, and don't, respectively - according to some authorities).  But the effect size of any child-rearing advice, whether reasonable or not, is likely to be small: the people who had parents that followed it aren't immediately distinguishable from those whose parents didn't. Consider the contrast between the range of variation in parenting practices across cultures and the consistency of having reasonable outcomes - nice, well-adjusted people. People grow up lots of different ways and yet they turn out just fine. This is the message of Day's book.

Of course there are real exceptions to this rule. But these are not the small variations in child rearing for your standard-issue helicopter parents - BPA-free tupperware or not? - or even the culturally-variable practices like whether you swaddle. They are huge factors like poverty, stress, and neglect, which have systematic and devastating effects on children's brain, mind, and life outcomes. Remediating them is a major policy objective. We shouldn't confuse the myriad bewildering details of babyrearing with the necessities of providing safety, nutrition, and affection.

Review: Democracy Despite Itself

I just finished reading Democracy Despite Itself, a book by Danny Oppenheimer and Mike Edwards. Oppenheimer is a social [edit] cognitive psychologist and Edwards is a political scientist (Danny is a good friend of mine; we've known each other since we sat across the hall from one another when I was an undergraduate research assistant and he was a graduate student).

The premise of the book is that, despite the myriad flaws of democracy, it nevertheless has a number of features that make it the most successful system of governance. Oppenheimer and Edwards split the book into two parts. The first part describes four flaws of democracy: 1) voters typically don't know about the issues at stake in elections, 2) voters are generally "irrational" decision-makers even when they do have some knowledge, 3) it's very hard to design a representative democratic system (because of biases inherent in e.g. districting, election dates, etc.), and 4) for the elected representatives, it can be very hard to know what voters really want. Nevertheless, as the second part discusses, democracies are very successful overall--in terms of peace and prosperity for their citizens--compared with other systems of government, mostly because they set up good incentives for voters and representatives.

This general account sounds very reasonable overall, and DDI is a fun, easy read. It's filled with straightforward and clear examples (often from sports) that make the phenomena easy to understand. Danny wanted to call his book "DemoCrazy," and that nicely captures both the thesis and the tone of the book.

Despite how much I liked the book, I want to make two slightly critical points. First, DDI spends only a short amount of time on how to solve the problems it outlines (or even whether they are soluble). This is fine for a short book, but at times I worried that the two-part organization--"democracy is surprisingly crazy but yet works surprisingly well"--made the authors equate different kinds of problems that should be distinguished. While the quirks of human cognition--like our susceptibility to framing effects--aren't something that we can correct, other problems can be addressed, such as flaws in redistricting. While, as Oppenheimer and Edwards point out, there are many different metrics by which to assess the fairness of a redistricting scheme, some redistricting schemes aren't fair. There not be one single perfect solution, but we can definitely do better.  If redistricting choices are made by partisan groups, then they are especially likely to be unfair.

Second, DDI doesn't distinguish between problems that cause bias and those that cause variance. Consider elections as a method for estimating what governance a group of people wants. (This is potentially problematic but let's go with it for now). Let's start with the simplest case. Imagine Alice, a single individual. Alice has perfect knowledge of the policy landscape. She is a rational decision-maker. Presented with an infinite array of possible representatives who vary in their stated policies, she can then easily choose the one whose policies minimize her regret.

Now move away from this world in a few different directions. Imagine that she has only a random sample of a few possible representatives in each election. And she has only partial knowledge of each representative's position (assuming facts are sampled at random). Now finally, imagine there are thousands of Alices, each making their own decisions in accord with their own interest based on their own partial knowledge of the issues. It's easy to see that each of these lead to higher average regret for Alice (variance). But there is no systematic bias in the system yet. This seems like a reasonable model of some of the issues that DDI discusses, especially problems of imperfect knowledge on the part of the voters and representatives.

But there are other problems that would lead to bias, rather than variance. Imagine that the election is rigged, Alice's district is gerrymandered, her access to information is systematically manipulated. All of these systematically change the long-run fairness of the system. Of course we would want to reduce variance if we could, but these kinds of biasing factors seem much more dire. Distinguishing between the two feels important.

Outside of these minor concerns, DDI is a clear and engaging look at the topic. It's very well written also. I recommend it to anyone curious about the intersection of psychology and politics.