Deep Image Reconstruction – Visualizing Human Thought Using AI
Machine learning has previously been used to study brain scans (MRIs) and generate visualizations of human thought in case of simple geographic shapes or binary images. Past methods to reconstruct an image seen by a person have assumed that an image consists of pixels or simple shapes. But it is known that our brain processes visual information hierarchically extracting different levels of features or components of different complexities.
Deep Image Reconstruction
New research by four Kyoto University scientists uses neural networks as a proxy for this hierarchical human brain structure. Using the scientific platform BioRxiv and deep neural networks (DNN), the new technique lets thoughts involving sophisticated images to be decoded by a computer, producing images remarkably close to what a person is thinking.
Over 10 months, three subjects were shown natural images, artificial geometric shapes and letters for varying periods. Brain activity was measured either while the subject was looking at an image (Experiment 1) or later, when the subject was asked to think of an image shown earlier (Experiment 2).
Once the brain activity was scanned, a computer reverse-engineered the information to generate visualizations of the subject’s thoughts.
Interestingly, visual imagery could be reconstructed, albeit to a lower accuracy, even in Experiment 2. This is possibly because it is more difficult for a human to remember an image exactly as it was seen.
The mind-boggling range of possibilities, as the accuracy of this technology improves, includes:
· Making art by imagining something
· Visualization of dreams
· Visualizations of hallucinations of psychiatric patients
· Communication using thoughts
Other Research Activities
The Japanese researchers aren’t alone in this seemingly futuristic work to connect the brain with computing power. A former GoogleX-er is working to build a hat that could make telepathy possible within a decade, while another entrepreneur is working to build computer chips to implant in the brain to improve neurological functions.
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