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Scientists map brain to decode inner thoughts

Neuroimaging reveals detailed word maps criss-cross the human cerebral cortex, mapping our encounters and "sticking" experiences to verbal cues.

What if a map of the brain could help us decode people's inner thoughts?

Scientists at the University of California, Berkeley, have taken a step in that direction by building a "semantic atlas" that shows in vivid colors and multiple dimensions how the human brain organizes language. The atlas identifies brain areas that respond to words that have similar meanings.

The work was funded by the National Science Foundation (NSF). Volunteers brains were scanned while listening to stories from The Moth Radio Hour a Public Broadcasting radio show in which people recount humorous and poignant autobiographical stories. Results of the scans show that at least 1/3 of each participant's cerebral cortex — including areas dedicated to high-level thoughts (cognition) — were involved in processing language heard from the program.

The findings are published in the journal Nature, including a video of the brain map.

Notably, the study found different people have similar language maps."The similarity in semantic topography across different subjects is really surprising," said study lead author Alex Huth, a postdoctoral researcher in neuroscience at UC Berkeley.

Detailed maps show that our
brain organizes words by meaning.

The study might eventually help give voice to those who cannot speak, stroke suffers, people with brain damage or motor neuron diseases like ALS which restrict muscle flexibility. Charting language organization in the brain helps decode and bring these patients' inner dialogue a step closer to reality.

"This discovery paves the way for brain-machine interfaces that can interpret the meaning of what people want to express. Imagine a brain-machine interface that doesn't just figure out what sounds you want to make, but what you want to say."

Alexander G. Huth PhD, Helen Wills Neuroscience Institute, University of California, Berkeley, USA

Clinicians hope someday to track the brain activity of patients who have difficulty communicating, and match their data to semantic language maps to determine what they are trying to express. Or perhaps a decoder will ensue which translates what you say into another language as you speak.

"To be able to map out semantic representations at this level of detail is a stunning accomplishment," said Kenneth Whang, a program director in the NSF Information and Intelligent Systems division. "In addition, they are showing how data-driven computational methods can help us understand the richness and complexity of the brain that we associate with human cognitive processes."

Huth and six other native English speakers participated in the experiment, which required volunteers lay inside a functional Magnetic Resonance Imaging (fMRI) scanner for hours. Participants' brain blood flow was measured as they listened, with eyes closed and headphones on, to more than two hours of stories from The Moth Radio Hour.

This data was then matched against the same stories that had been time-coded and phoneme transcribed. Phonemes are units of sound that distinguish one word from another. That information was fed into an algorithm that scored words according to how closely they are related in either meaning of a word, or a phrase, or in a sentence — semantically. Semantic results were converted into a map that arranged words on an image of the flattened cortices of the left and right hemispheres of the brain.

Words were grouped under headings: visual, tactile, numeric, location, abstract, temporal, professional, violent, communal, mental, emotional and social.

Not surprisingly, maps showed many areas of the brain represent language describing people and social relations, rather than abstract concepts.

Added Huth: "Our semantic models are good at predicting responses to language in several big swaths of cortex. But, we also get fine-grained information that tells us what kind of data is represented in each brain area. That's why these maps are so exciting and hold so much potential."

Senior author Jack Gallant, a UC Berkeley neuroscientist, said that although the maps are broadly consistent across individuals, "There are also substantial individual differences. We will need to conduct further studies across a larger, more diverse sample of people before we will be able to map these individual differences in detail."

The meaning of language is represented in regions of the cerebral cortex collectively known as the ‘semantic system’. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is unknown. Here we systematically map semantic selectivity across the cortex using voxel-wise modelling of functional MRI (fMRI) data collected while subjects listened to hours of narrative stories. We show that the semantic system is organized into intricate patterns that seem to be consistent across individuals. We then use a novel generative model to create a detailed semantic atlas. Our results suggest that most areas within the semantic system represent information about specific semantic domains, or groups of related concepts, and our atlas shows which domains are represented in each area. This study demonstrates that data-driven methods—commonplace in studies of human neuroanatomy and functional connectivity—provide a powerful and efficient means for mapping functional representations in the brain.


In addition to Huth and Gallant, co-authors of the paper are Wendy de Heer, Frederic Theunissen and Thomas Griffiths, all at UC Berkeley.

This NSF-funded project is an example of how NSF invests in the frontiers of brain research
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May 16, 2016   Fetal Timeline   Maternal Timeline   News   News Archive   

Image Credit: University of California, Berkeley/Nature Video




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