Since you typically know more about your *own* past than your future, this affects what you say and do. And your "biased" knowledge of your own autobiographical timeline is transmitted to other people when you communicate!.

From examining millions of real and fictional human conversations, we found that people refer to past events ~1.5 more often than future events, on average. This affects what other people *learn* (or infer) from our conversations.

This was surprising, since most other statistical learning studies we've seen find that people are *equally* good at guessing about the previous and next parts of sequences. We think the key difference is that our "sequences" involved *other people*.

We looked at people's guesses about what would happen before or after scenes taken from different parts of a TV show. We found that people were almost always better at guessing about the unknown past than the unknown future.

Now out in @NatureComms (lead: @Xu_Xinming)! How do conversations shape how (and what) people guess about the unknown past and future (e.g., in other people's lives)?. Paper/code/data:

Fun writeup of one of our group's recent papers (-- thanks @PsyPost!.

We also did some digging to get at the specific networks that seem to exhibit this mode switching process most strongly (DMN!) or weakly (primary sensory cortex!) and also used some cool @neurosynth analyses to help us interpret the results.

When we are less engaged, our brain switches to a mode that prioritizes flexibility in favor of reliability.

When we are engrossed in a challenging or highly engaging task, our brain switches to a mode that prioritizes its ability to distinguish one moment’s activity patterns from other moments’ patterns.

Our study’s core finding is that the brain reconfigures itself from moment to moment to maintain a tradeoff between computational complexity and robustness to noise, according to ongoing cognitive demands.

For context, let's appreciate for a moment that our brains are responsible for every human thought, story, relationship, artwork, and scientific discovery EVER. Meanwhile, they're packed into a volume of under 1.5L and they run on less power than a standard incandescent 💡!

New study out in @PNASNews (lead: @LucyLongOwen)!. Our brains comprise billions of tiny components interact via trillions of connections, changing at sub-ms timescales. How is it so robust to injury and noise?. Paper: Code/data:

We've been doing some @LeetCode together to help hone our coding skills. We've set up a project for going through the daily problems: We welcome participation from "outsiders" too; instructions are at the link above if you'd like to participate! 🧑‍💻.

RT @jeremyRmanning: I'm feeling very happy, lucky, and grateful to have reached this next career milestone (tenure!) with the support of my….

We've (lead: @paxt0n4) added an awesome new system for automatically managing dependencies, that's isolated from the runtime environment. Davos now turns your notebook into a "fully enclosed" + shareable doc (w/ code/figures/data/text) that installs its own dependencies!.

Excited to announce the latest release of our "Davos" Python package (v0.2.3)! 🎉🥳. Add Davos to a Jupyter notebook by inserting a new cell with this code at the top:. %pip install davos.import davos. Then replace all uses of "import" with "smuggle".

RT @comp_mind_ss: MIND is in the news today! 📰🗞️

We're also grateful to @OpenAI, @huggingface, and @Meta, whose awesome LLM wizardry gives Chatify its brain powers 🧠💕🪄, and to the developers of @ProjectJupyter, LangChain, and GPTCache for providing a solid foundation for creating such neat tools!.