Nicole Rust

Yes! *This* will make it great. Authenticity!

I hope this discussion doesn’t send anyone into an existential tailspin of the type that I was having before I sat down to write Elusive Cures (decades into my career). On the other side of sorting out what’s what, I’m “all in” re how this works. But it was a process & I don’t take it for granted.

I agree! Same for the papers we *write* - one goal is to keep iterating. A second goal is to efficiently get close enough to the truth so that We can deliver benefits to society - eg insights for new therapies and new tech don’t always require many decimal place precision.

Under this definition of wrong, wrong is inevitable and we should not fear it - progress requires it! We have to start somewhere and refine our way to better answers. (But let’s shoot for direct-ish paths).

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Where do you think this is *not* the case? (i.e. what parts of theoretical neuro today are truly new?)

Where do you think this will not be the case in 20 years? (i.e if research progresses in a direction you think it should, what will be the new stuff we’re not talking about today?)

Equations that model emotions and moods on par with the rest of systems and computational neuroscience.

I like that example b/c you can probably go back and explain that same data very nicely with thermodynamics (perhaps even better than with the caloric model). But the conclusion of the study was arguably not "wrong" per se.

Here's a fun one: there was an era of debate about whether temperature was governed by the existence of heat matter (caloric) or cold matter (figorific radation) that transferred from one thing to another. Let's say that in an expt, caloric was determined more likely. Was that wrong? 😉

Here's a simple case: let's say that a study's conclusion boils down to: during a task, brain area X is more correlated with behavior than Y, established with a linear brain/behavior relationship. Later, it's revealed that it's true but there are also nonlinear terms. Was that study wrong?

I'm authentically curious. In the context of "all models are wrong but some are useful", they're all wrong, but I bet that's not what you mean. Where do you draw the line? I can imagine many possible dimensions to it. /1

we can meaningfully study emotion in animals b/c there's no behavioral task or signature that's clearly indicative of emotion existing. eg When chatGPT says it "loves", we don't regard that as emotion. But if it recalls something about the past, that's memory.

is the issue of whether a subject has awareness of a solution (eg blindsight). The two are related but not the same.

For emotion, the core phenomena of interest that exist separate from the subjective experience are less clear. Hence the big debates about whether /2

More: How a brain solves a memory task is a core phenomenon of interest; if an animal performs a memory task, there's no question that their brain performs that memory computation — and many are interested in how (for good reasons). *Also* of interest /1

A call for more clarity around causality in neuroscience In neuroscience, the term ‘causality’ is used to refer to different concepts, leading to confusion. Here we illustrate some of those variations, and w…

(Playing on www.sciencedirect.com/science/arti...)

I endorse: please do! A call for more clarity around confusion in objective & subjective measures of brain & mental function.

Understanding the debate around terms in emotion research requires appreciating why emotions are more challenging to study than other brain functions. To investigate memory, for example, researchers often design a memory test for which there are ground-truth correct and incorrect answers to the questions posed. In contrast, emotion is a subjective experience for which there is no ground truth—no one but you really knows how happy, anxious, scared or disgusted you are. This subjectivity makes emotions much more difficult to measure than other brain functions, especially in animals, because we cannot ask them how they feel. The most extensively used measure of emotions is applied by simply asking people questions about their feelings, such as: “On a scale from 1 to 5, how upset are you?”. However, measures of subjective experience are limited to humans who can communicate and cannot be applied to nonhuman animals or young children. A second type of emotion measure probes biological reactions triggered by emotions, including facial expressions or galvanic skin responses; often, however, these responses do not map cleanly onto subjective reports. Other versions of physiological measures seek to quantify how emotions are reflected in dynamic patterns of brain activity (or their proxies, such as fMRI results). A final way to measure emotion is to induce an emotion and measure how it changes a person’s behavior on a well-defined task, such as a paradigm for risky decision-making. These different ways of measuring emotions set the stage for debates about what these measures should be called, centered around the evidence they provide.

This piece was seemingly about the words we use to describe emotions but behind it is a discussion about what makes them harder to study than other brain functions. From a philosophy of science perspective, it's a fascinating (measurement) problem!

www.thetransmitter.org/the-big-pict...

Can’t tell you how often I’ve had to ask critics what measure they think is better than self-report to know how someone subjectively feels

recently reviewers even asked us how people could possibly rate how good they felt 🤪
As if other a pulse measure or something would be better 😜

In other words, we are very far short of the emotion research community erring on spelling these issues out too many times!

I hope you write it!

And even more broadly: I expect it's time to raise more awareness about what makes emotion research so much harder (than say memory) & the different visions to tackle that challenge. It's unfortunate that every brain mind researcher isn't aware the first (if not the second).

Wow! I realize that researchers outside the field (like memory) don't understand the need for subjective report (not everyone realizes emotion is a fundametally a scientifically different problem). But I wasn't aware that it was controversial inside the field too. Yes, it's time for that review!

A microbiome-dependent gut–brain pathway regulates motivation for exercise - Nature It is demonstrated that the brain circuitry involved in regulating the motivation for physical activity is not strictly central nervous system autonomous but is shaped by peripheral influences that or...

In mice:
www.nature.com/articles/s41...

Fascinating!

Got it! That would be a great review indeed. I’d love to see it include mood as well as emotion.

As for my own take, keeping subjective experience in the loop is key!

www.biorxiv.org/content/10.1...

Emotion research has a communication conundrum In 2025, the words we use to describe emotions matter, but their definitions are controversial. Here, I unpack the different positions in this space and the rationales behind them—and I invite 13…

That was my impression after sifting through all the different perspectives to write this:
www.thetransmitter.org/the-big-pict...

Honest question: given that there is no ground truth for emotion (unlike, say, memory which can be defined relative to task performance), what form would that evidence take? For emotion, won’t this always boil down to a different end goals and varied definitions?

Aspiring scientist communicators: this! It speaks to changing the narrative that scientists only engage in scicomm as emeritus professors, as well as how to seize your own way of doing it.

Jenna Levin interviewed &
@seanmcarroll.bsky.social

www.preposterousuniverse.com/podcast/2018...

That sounds like a terrific book! I’d love to read it someday.

My second year in college, I read a book subtitled “The Scientific Search for the Soul” and I realized, for the first time, that you can get paid to do that. I enlisted.

www.thetransmitter.org/summer-readi...