It has been just reported that AI is now able to read to daydreams. Here’s how this amazing idea works.
Researchers have developed new methods that use fMRI and machine learning to predict emotions in spontaneous thoughts.
They created personalized narratives that participants read aloud while their brain activity was monitored, aiming to decode the emotional dimensions of thoughts.
By analyzing the fMRI data, the team identified key brain regions involved in processing personal relevance and emotional valence.
This breakthrough offers insights into the emotional undertones of daydreams and could revolutionize the way mental health is diagnosed.
AI can read your daydreams
A group of researchers, led by KIM Hong Ji and WOO Choong-Wan at the Center for Neuroscience Imaging Research (CNIR) within the Institute for Basic Science (IBS), collaborated with Emily FINN at Dartmouth College to gain a deeper understanding of the human brain.
In a recent study, they used functional Magnetic Resonance Imaging (fMRI) and machine learning algorithms to predict the subjective feelings of people’s thoughts while reading stories or in a state of free thinking. This breakthrough could help us gain new insights into the workings of the human mind.
The brain is always active, and spontaneous thoughts occur even when we’re resting or sleeping. These thoughts can be memories of the past, aspirations for the future, or anything in between. They are often connected to our emotions and personal concerns.
However, studying spontaneous thoughts is challenging because they happen without any constraint of consciousness.
Simply asking people what they’re thinking can change the nature of their thoughts, which makes researching them difficult.
Recent research has suggested that it may be possible to create models that can predict the emotional content of spontaneous thoughts by combining personal narratives with fMRI scans.
Personal narratives and spontaneous thoughts share similar characteristics such as rich semantic information and unfolding nature over time.
To obtain a diverse range of thought patterns, participants were interviewed individually to create personalized narrative stimuli based on their past experiences and emotions.
While reading their stories inside an MRI scanner, participants’ brain activity was recorded in order to analyze the relationship between their emotional states and brain activity.
“Several tech companies and research teams are currently endeavoring to decode words or images directly from brain activity, but there are limited initiatives aimed at decoding intimate emotions underlying these thoughts,” stated Dr. WOO Choong-Wan, associate director of IBS, who led the study.