New Open dataset alert:
🧠 Introducing "Spacetop" – a massive multimodal fMRI dataset that bridges naturalistic and experimental neuroscience!

N = 101 x 6 hours each = 606 functional iso-hours combining movies, pain, faces, theory-of-mind and other cognitive tasks!

🧵below

🎉 The upshot: Even casual "small talk" has deep structure! Conversations follow predictable patterns as people jointly navigate semantic space to build connections.

Check out our full paper & data here: osf.io/69yw2/

#CogSci #Conversation #NLP

🔍 Why does this matter? It suggests strangers aren't just chatting randomly – they're systematically exploring "topic space" together, starting with safe common ground before venturing into more personal territory.

Think of it as conversational foraging!

🌊 Key finding #2: Conversations have NESTED specificity! Both within individual topics AND across entire conversations, people start general and get increasingly specific – like waves within waves – demonstrating fractal conversation structure. 🌀

🎯 Key finding #1: Topics aren't random! We found systematic patterns in how people transition between conversation themes. Some topics cluster at conversation beginnings (introductions), others toward the end (politics, relationships).

🔬 Our approach: We had 1,505 people annotate topic shifts in stranger conversations from the CANDOR corpus. Then we used semantic embeddings to track how meaning changes throughout conversations.

The validation was solid – annotated topic shifts = sharp drops in semantic similarity!

🤔 The big question: When people chat, are they just randomly jumping between topics? Or is there actually a method to the conversational madness?

We suspected conversations have a fractal-like structure – getting more specific at multiple nested levels.

🗣️ New paper alert! Ever wonder how strangers navigate the messy world of casual conversation? We analyzed 200+ video calls to uncover the hidden structure behind "idle talk" – and found it's way more systematic than you'd think!

Thread 👇

A collection of modules, datasets, and other resources for learning to program in R, geared toward students in psychology and neuroscience: ritcheym.github.io/ppn/

Thrilled to share that my first, first-author paper is out now!

Using an episode of 'Survivor', we find that distinct features of conversation – semantic similarity, emotional tone, and confidence – strongly inform observers about underlying social relationships.

link.springer.com/article/10.3...

New haunted house paper out led by Steven Martinez exploring the language we use to recall high and low threat experiences!

link.springer.com/article/10.3...

Very excited to share our new emotion regulation use and forecasting paper in JEP:G

We studied ER using high-intensity settings (e.g., haunted houses) and stimuli (e.g., horror movies) and with subjects not trained in ER strategies or even prompted to regulate in some cases.

#30DayMapChallenge Day 5: A Journey 🏃🏼‍♀️

Such a fun challenge to recreate the route from my first time running the Cherry Blossom 10 Mile race in D.C.!

🙋‍♀️

Day 3: Polygons 🧱

Thoroughly enjoyed creating my own Lego bricks!

Day 2: Lines 📏

Ancient geoglyphs mapped in modern day R

Day 1: Points 📍

So excited to participate in my third #30DayMapChallenge!

Thrilled to announce that I received the notice of award for my NRSA F31! I'll be exploring behavioral, neurocognitive, and cardiovascular signals that support social-relational learning, with the goal of reducing loneliness across the lifespan. Huge thanks to my mentorship team!