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- 2024-03-26: One Step Closer To Inception
2024-03-26: One Step Closer To Inception
building the electronic memory palace
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😳 One Step Closer To Inception
Researchers at Wake Forest built an AI model to read brain memory signals:
Patients participated in a visual memory task (Delayed Match to Sample or DMS): They were shown a sample image, and after a short delay, they were asked to identify the matching image from a set of several images.
Researchers recorded the electrical activity from the patients' hippocampus using surgically implanted electrodes. They captured the neural firing patterns associated with the encoding and recall of specific visual memories.
The recorded neural data was then used to train the Memory Decoding Model AI model. The model learned to associate certain patterns of hippocampal activity with specific image categories from the DMS task (e.g., animals, buildings, tools, etc.).
Once trained, the AI could take in new hippocampal activity patterns and decode which image category they likely represented. In other words, it could predict what kind of visual information the brain was processing based on the neural firing patterns.
The researchers then used the AI to generate unique electrical stimulation patterns for each patient and image category. These stimulation codes were designed to mimic the natural neural activity patterns associated with successful memory encoding and recall of that specific type of information.
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DMS: Trial is started by patient touching a focus ring which causes the sample image to be presented (SP). After patient responds by touching the sample image there is a delay and then the match image is presented (MP). Patient touches one of the images in the match phase to end the trial.
Then they successfully wrote to active recall.
They set up a Delayed Recognition task, where the patient would be shown 3 images, 2 of which had been seen before, of which one was the “target“ image they were supposed to remember.
Using the same electrodes that they’d used for recording, the researchers then applied electrical stimulus to the brain to assist the patient in recalling the correct image.
The AI model-directed stimulation, ie applying the model-generated stimulation codes during the encoding phase helped some patients better recognize the target images later on, demonstrating an improvement in memory recall.
They tested this on Alzheimer’s patients who already had implants, and had a 22% increase in memory recall, increasing to 38% for patients where they stimulated both sides of the brain.
These are all baby steps towards a memory implant, which at this point post Neuralink, seems like just a matter of time.
The great and exciting thing about the era that we live in is that our data analysis tools have finally caught up with the complexity and resolution of the data in the real world. We can finally do stuff, like recording and replaying brain wave patterns to improve memory. Finally.
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🗞️ Things Happen
Holograms just became possible. Courtesy of Voxon Photonics. Yet another pathway to a holodeck-like experience.
Ready for Actual Holograms!?
Voxon Photonics have been hard at work for a few years, and this just takes holograms to the next level.
Here is all you need to know
— Linus ●ᴗ● Ekenstam (@LinusEkenstam)
4:08 PM • Mar 25, 2024
🖼️ AI Artwork Of The Day
Fruit With Human Faces - u/GremlinBobby from r/midjourney
![](https://media.beehiiv.com/cdn-cgi/image/fit=scale-down,format=auto,onerror=redirect,quality=80/uploads/asset/file/0e0158b6-b9cc-47dd-91d1-e485f8582d9b/Screenshot_2024-01-22_at_2.13.39_PM.png?t=1705950837)
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