Paper:

doi.org/10.1016/j.co...

Data/code:

We think this helps clarify decades of debate:
Inhibitory demands in false belief tasks aren't monolithic.

Some subprocesses matter more than others, and only some link tightly to theory of mind growth.

Bottom line:
False belief understanding isn’t just about knowing that minds can misrepresent reality.

It’s also about which cognitive control processes get recruited, and how those demands change as kids' theory of mind develops.

Adults, by contrast, showed a surprise:
They actually initiated faster on false belief trials than true belief ones.

Maybe because being asked about a true belief is so pragmatically weird: everyone knows it already.

Our big finding?

Children’s conflict monitoring didn’t differ between true vs. false belief trials.

But conflict resolution did.

As kids' theory of mind improved, they needed less conflict resolution effort to pick the correct (false belief) answer: more adult-like.

We used 3D manual reach tracking to do just that.
Kids (and adults) made belief judgments by reaching to screen locations while we tracked their finger movement in space.

Two key measures:
– Initiation latency (conflict monitoring)
– Curvature deviance (conflict resolution)

Inhibitory control isn't just one thing.

It includes:
- Monitoring for conflict (realizing your belief conflicts with someone else’s)
– Resolving that conflict (choosing the other’s perspective, not your own)
Can we tease these apart?

For decades, research has shown that 4- to 6-year-olds begin to succeed at false belief tasks, predicting that someone will act on a mistaken belief.

But success depends on more than knowing others have minds.

It also takes inhibitory control.

But what kind?

These results challenge copyright doctrine around AI derived artworks: what matters most to people isn't who made the source, but how it's changed.

Read more here:

dgk-law-and-cognition-lab.github.io/AICopyrighta...

We find:
1) Modification level matters most — dramatic edits = more transformative
2) Creator attribution (AI vs. human) barely moved judgments
3) Less effort was sometimes seen as more creative

This is because AI is assumed to be incompatible with qualities that define human authorship. We empirically test lay intuitions related to these assumptions in two studies (N = 235, N = 119) by investigating how creator attribution of initial source material.