5/ ✅ When memory is scarce, people chunk even more—they reduce their response time more when they have to remember more items (Ns=6).
💡𝗧𝗵𝗲 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: chunking is an efficient and adaptive strategy to conserve cognitive resources.

4/ ✅ Our model also predicts (and our data confirm) that chunking in structured environments 𝗿𝗲𝗱𝘂𝗰𝗲𝘀 𝗽𝗼𝗹𝗶𝗰𝘆 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 (the memory demands of the policy) while 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗶𝗻𝗴 𝗲𝗮𝗿𝗻𝗲𝗱 𝗿𝗲𝘄𝗮𝗿𝗱.

3/ We tested the predictions of our model in behavioral experiments and found that:
✅ People chunk by leveraging temporal structure in the environment, making action selection 𝙡𝙚𝙨𝙨 𝙢𝙚𝙢𝙤𝙧𝙮-𝙞𝙣𝙩𝙚𝙣𝙨𝙞𝙫𝙚, 𝙛𝙖𝙨𝙩𝙚𝙧, 𝙖𝙣𝙙 𝙢𝙤𝙧𝙚 𝙖𝙘𝙘𝙪𝙧𝙖𝙩𝙚!

2/ We proposed that people learn and utilize action chunks because they are easier to store in memory. We formalized this idea in a model of 𝙘𝙤𝙣𝙙𝙞𝙩𝙞𝙤𝙣𝙖𝙡 𝙥𝙤𝙡𝙞𝙘𝙮 𝙘𝙤𝙢𝙥𝙧𝙚𝙨𝙨𝙞𝙤𝙣:

apply to the FREE Okinawa Computational Neuroscience Summer School where you can hang out with cool people (incl. me!) at the beach 🏖️☀️ while learning computational neuroscience through lectures, tutorials, and independent projects!!! Deadline: Jan 31 groups.oist.jp/ocnc

3/8 But factors such as time constraints or mental fatigue can often steer us towards past choices, such as choosing to eat the same thing for lunch every day.

entering a glorious era of my phd where chatGPT writes my code for me