This means we were able to 𝐝𝐢𝐚𝐠𝐧𝐨𝐬𝐞 whether a room will serve as an effective memory scaffold 𝐁𝐄𝐅𝐎𝐑𝐄 objects are placed in the room! (10/11)

In accordance with our predictions, we found that we were able 𝐭𝐨 𝐮𝐬𝐞 𝐞𝐚𝐜𝐡 𝐢𝐧𝐝𝐢𝐯𝐢𝐝𝐮𝐚𝐥 𝐩𝐚𝐫𝐭𝐢𝐜𝐢𝐩𝐚𝐧𝐭’𝐬 𝐫𝐨𝐨𝐦 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 (measured before they saw the newly placed objects) 𝐭𝐨 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐭𝐡𝐞 𝐝𝐞𝐠𝐫𝐞𝐞 𝐨𝐟 𝐨𝐛𝐣𝐞𝐜𝐭 𝐫𝐞𝐢𝐧𝐬𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭 𝐝𝐮𝐫𝐢𝐧𝐠 𝐯𝐞𝐫𝐛𝐚𝐥 𝐫𝐞𝐜𝐚𝐥𝐥! (9/11)

…then, we placed an object randomly in each of the rooms and had participants go back into VR to learn the room-object associations. Finally, we scanned their brains again while they verbally recalled the objects and the rooms. (8/11)

Treating each room video as a ‘localizer’, we quantified the reliability of each room representation by comparing the neural pattern similarity of a room to itself vs other rooms… (7/11)

To test this, we built a 23-room virtual reality (VR) environment that participants explored with a head-mounted display. Afterwards, we scanned their brains while they watched two sets of videos of the rooms they visited. (6/11)

…we would predict that when a new experience occurs (such as encountering a yummy banana), he would be better at encoding his experience and consequently, better at retrieving it later. (5/11)

So, we hypothesized that a 𝐡𝐢𝐠𝐡 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 (𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞) 𝐫𝐨𝐨𝐦 𝐫𝐞𝐩𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 (one that is stable and distinct) 𝐰𝐨𝐮𝐥𝐝 𝐥𝐞𝐚𝐝 𝐭𝐨 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐦𝐞𝐦𝐨𝐫𝐲 𝐟𝐨𝐫 𝐨𝐛𝐣𝐞𝐜𝐭𝐬 𝐬𝐮𝐛𝐬𝐞𝐪𝐮𝐞𝐧𝐭𝐥𝐲 𝐩𝐥𝐚𝐜𝐞𝐝 𝐢𝐧 𝐭𝐡𝐞 𝐫𝐨𝐨𝐦. For example, if the typing minion has a reliable room representation… (4/11)

🔔𝐍𝐄𝐖 𝐏𝐑𝐄𝐏𝐑𝐈𝐍𝐓 𝐀𝐋𝐄𝐑𝐓🔔 Beyond excited to present our new work showcasing 𝐡𝐨𝐰 𝐰𝐞 𝐜𝐚𝐧 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐡𝐨𝐰 𝐰𝐞𝐥𝐥 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐫𝐞𝐢𝐧𝐬𝐭𝐚𝐭𝐞 𝐚 𝐧𝐞𝐰 𝐦𝐞𝐦𝐨𝐫𝐲 𝐛𝐞𝐟𝐨𝐫𝐞 𝐭𝐡𝐚𝐭 𝐦𝐞𝐦𝐨𝐫𝐲 𝐢𝐬 𝐟𝐨𝐫𝐦𝐞𝐝! Wait what? Exciting collab w/ @ptoncompmemlab.bsky.social & @chrisbaldassano.bsky.social Link: www.biorxiv.org/content/10.1... (1/11)