bkFeb 17

New #neuroforecasting research out in #PNASNexus : "Brain activity reveals how wildlife imagery evokes engagement on social media"!

Partnering with #NationalGeographic, we found that group brain activity in the Medial PreFrontal Cortex (MPFC) forecast image popularity on their social media feed (as did subjects' "like" ratings).

Further, correlated activity in #face processing (FFG) and #mentalizing (rTPJ) implied that socioemotional features might drive image popularity, verified by modeling the impact of these features on the popularity of out-of-sample images.

Thus, beyond forecasting, brain activity helped to clarify which image features drive popularity. Congratulations to steadfast coauthors Tara Srirangarajan , Nik Sawe , Cynthia Wu , and Tierney Thys and deep thanks to the #Stanford Woods Institute for continued support.

P.S. The news alert below illustrates our findings with the winning wildlife image, and links to the article:

https://www.eurekalert.org/news-releases/1116282

Brain imaging reveals how wildlife photos open donor wallets

Brain imaging identifies the social and emotional features of wildlife photos that drive engagement on social media. Tara Srirangarajan and colleagues scanned the brains of 34 adults while the participants viewed 56 wildlife images from National Geographic’s Instagram feed and made decisions in a matter of seconds about whether to “like” posts and/or donate to depicted species. 

EurekAlert!
bkFeb 25, 2025

Now out in @[email protected] :
"#Neuroforecasting reveals generalizable components of choice" (link below)!

Led by the intrepid Alex Genevsky , we examined how deep brain activity (in the Nucleus Accumbens or #NAcc ) can forecast choices out of sample in much larger groups (e.g., in #crowdfunding and #videoviewing markets).

We found that while behavioral forecasts depended on demographic match, neural forecasts (from the NAcc) did not, potentially supporting inferences from smaller samples. So, beyond considering #representativeness of a sample, researchers might also benefit from considering representativeness of different choice components.

Thanks to the Wu Tsai Neurosciences Institute #Neurochoice Initiative for support, to the reviewers for constructive suggestions, and to #PNASNexus for a smooth publishing experience!

https://academic.oup.com/pnasnexus/article/4/2/pgaf029/8016018

Simon MooijaartDec 4, 2024

Disagreement on foundational principles of biological #aging

This survey published in #PNASNexus reveals that aging researcher experts disagree on:
1️⃣ definition of aging?
2️⃣ when does it start?
3️⃣ is it a disease?

#ageing #geriatrics #medmastodon

🔗 https://doi.org/10.1093/pnasnexus/pgae499

Show threadNick Byrd, Ph.D.Aug 11, 2024

👆 Now published in #PNASnexus: "Language models, like humans, show content effects on reasoning tasks"

https://doi.org/10.1093/pnasnexus/pgae233

"like humans, models answer more accurately when the semantic content of a task supports the logical inferences ... across three logical reasoning tasks: natural language inference, judging the logical validity of syllogisms, and the Wason [card] selection task."

#decisionScience #AI #logic #language #bias #semantics #psychology #cogSci #PhilMind #linguistics #computerScience #LLMs #openAccess

Language models, like humans, show content effects on reasoning tasks

Abstract. Abstract reasoning is a key ability for an intelligent system. Large language models (LMs) achieve above-chance performance on abstract reasoning

OUP Academic
Jennifer Mach (she/they)May 2, 2023
Cool new #PlantScience research out from #PNASNexus about the tiny flowering plant Wolffia australiana. https://academic.oup.com/pnasnexus/advance-article/doi/10.1093/pnasnexus/pgad141/7130197
Plant-on-Chip: core morphogenesis processes in the tiny plant Wolffia australiana

Abstract. A plant can be thought of as a colony comprising numerous growth buds, each developing to its own rhythm. Such lack of synchrony impedes efforts to de

OUP Academic