Who said watching movies all day can’t be educational? Scientists have just unveiled the most detailed functional map of the brain we’ve seen yet, and they got there using scans of people’s brain activity taken while they watched clips from Hollywood blockbusters and independent films.
“Our work is the first attempt to get a layout of different areas and networks of the brain during naturalistic conditions,” said first author and MIT neuroscientist Reza Rajimehr in a statement.
In order to power the high-level functions we humans need, distant regions of our brains need to interact and work together. Inside the human cerebrum is a web of connections that link disparate areas up into functional networks.
Much of our knowledge of this complex maze comes from resting-state functional MRI (fMRI) studies, where people’s brain activity is monitored in the absence of any external stimuli – essentially, people are asked to lie in an MRI machine and try not to think about anything in particular (without falling asleep!).
While the scans will show parts of the brain “lighting up”, “With resting-state fMRI, there is no stimulus – people are just thinking internally, so you don’t know what has activated these networks,” Rajimehr explained. We also know that lots of bits of the brain remain inactive when there are no external stimuli, so at best, we’re probably only seeing part of the picture. That’s where the idea of using movie clips came in.
Rajimehr added, “with our movie stimulus, we can go back and figure out how different brain networks are responding to different aspects of the movie.”
The dataset the team used for their new study had previously been collected as part of the Human Connectome Project. The 176 subjects watched an hour’s worth of clips from a range of different types of movies – including a scene from The Empire Strikes Back, episode V of the Star Wars franchise; the moment protagonist Kevin realizes his family has left for vacation without him in Home Alone; and a mind-bending sequence from 2010’s Inception. There were documentaries and independent films included too, and scenes with and without dialogue.
As the subjects watched, whole-brain scans were obtained. The team took this data and used machine learning to pull out the brain networks, particularly in the cerebral cortex, and then matched network activity to different aspects of the movie scenes that the subject was watching at the time – the animals, people, objects, speech, music, and narrative.
In the authors’ words from their paper, what they were able to achieve was to “functionally parcellate the entire cerebral cortex.” They identified 24 different brain networks associated with specific cognitive processes, like recognizing human faces, or landmarks within a scene.
They also found that the brain tends to switch to more generalized executive control networks, rather than networks with more specialized functions, when the cognitive load is higher.
“It looks like when the movie scenes are quite easily comprehendible, for example if there’s a clear conversation going on, the language areas are active, but in situations where there is a complex scene involving context, semantics, and ambiguity in the meaning of the scene, more cognitive effort is required, and so the brain switches over to using general executive control domains,” said Rajimehr.
“What is the importance of cortical parcellation?” the authors ask in their conclusions, perhaps echoing some questions the reader may be asking; but they quickly go on to explain that understanding the physical organization of these brain networks could be the key to better understanding how the brain functions, and how neurological damage, injury to the brain tissue, and psychiatric or developmental disorders could disrupt these connections.
The data the team had access to represent an average of the subjects’ brain activity, so future research could look to map things out at the individual level, allowing comparisons to be made between people of different ages, for example, or between subjects with different psychiatric conditions.
Rajimehr said that the team is already starting a more in-depth analysis: “Now, we’re studying in more depth how specific content in each movie frame drives these networks – for example, the semantic and social context, or the relationship between people and the background scene.”
This author can only lament that “watching movies for science” was, for some reason, never offered as an option when she was a student.
The study is published in the journal Neuron.
