The exploration of the mind has always been the center of intense research interest. The brain is the least understood organ in the body, and nobody knows exactly how it works. One approach to solving the brain puzzle is looking at neuronal activities of different brain regions. This strategy has led to important insights within the field of cognitive neuroscience, allowing for investigations into the biological mechanisms of brain function. Even more excitingly, such an analysis of brain activities may allow us to some day be able to delve into a person’s mind and gain access to their deepest thoughts — science fiction transforming into tangible reality. But how can we build a mind reading machine?
The mind is essentially the by-product of the brain. Through intricate computational processes the brain uses sensory input from the external world to generate actions and behaviors that respond to changes in the environment.
For example, when you see an image of a flower, the eyes detect information about the colors and shapes of the object. These sensory cues are then sent into the brain for higher-order processing, leading to abstract thoughts such as appreciation of beauty.
How can we study such abstract thought processes on a biological level? Sophisticated medical imaging techniques have paved the way towards addressing this question. One important technique is functional magnetic resonance imaging (fMRI), which correlates increased cerebral blood flow with neuronal activity.
In other words, areas of the brain that are active will light up, allowing us to localize certain cognitive functions within a specific region of the brain.
For instance, when people listen to music, areas that process sound such as primary auditory cortex will glimmer and light up like fireworks on the Fourth of July.
Jack Gallant at the University of California-Berkeley has taken this cognitive neuroscience approach to the next level. First he recruited volunteers to watch segments of a movie while their brains are imaged by fMRI.
As different scenes and objects flash on the screen, the brain lit up in certain areas. By corresponding what the subjects see with the patterns of brain activity, Gallant and his team generated a method to predict what individuals are thinking about just on the basis of fMRI data alone.
In the next round the team was able to partially recreate the movie scenes that the subjects had watched using just the brain recording data from the fMRI machine.
This work is one of the first to demonstrate the possibility of analyzing cognitive processes using patterns of brain activity and pushing us towards the reality of using machines to read people’s minds.
Even more intriguing is the question of whether or not it is possible to read someone’s dreams. Similar to works by Gallant and colleagues, a group of scientists in Japan used fMRI recording to “read” what subjects were dreaming about. Although the objects that the machine could read were very simple, such as a man or a chair, the work still provides a proof-of-concept that can lead to further improved experimental designs to read minds.
What are some of the current limitations that prevent us from deeply reading someone’s mind? First there’s the problem of temporal resolution since neuronal activity happens on the scale of microseconds. This is a problem since fMRI machines record in seconds. As a result, the fMRI skips over a lot of potentially important information.
Secondly, although the fMRI does allow us to pinpoint bursts of neuronal activity to macroscopic regions of the brain, information processing occurs in micro neural circuits that cannot be picked up by the fMRI.
As a whole, what does an improved, future mind reading machine look like? First, the machine needs to be able to record patterns of brain activity with higher temporal and spatial resolution. Secondly, there must be a very smart algorithm that can correlate these brain imaging data with what the subject is thinking.
The big problem is that although current machines can read very simple objects, they cannot process something as complex and abstract as creativity, artistry and appreciation of music.
