Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

This is your brain on sentences

15.08.2016

Researchers at the University of Rochester have, for the first time, decoded and predicted the brain activity patterns of word meanings within sentences, and successfully predicted what the brain patterns would be for new sentences.

The study used functional magnetic resonance imaging (fMRI) to measure human brain activation. "Using fMRI data, we wanted to know if given a whole sentence, can we filter out what the brain's representation of a word is--that is to say, can we break the sentence apart into its word components, then take the components and predict what they would look like in a new sentence," said Andrew Anderson, a research fellow who led the study as a member of the lab of Rajeev Raizada, assistant professor of brain and cognitive sciences at Rochester.


These brain maps show how accurately it was possible to predict neural activation patterns for new, previously unseen sentences, in different regions of the brain. The brighter the area, the higher the accuracy. The most accurate area, which can be seen as the bright yellow strip, is a region in the left side of the brain known as the Superior Temporal Sulcus. This region achieved statistically significant sentence predictions in 11 out of the 14 people whose brains were scanned. Although that was the most accurate region, several other regions, broadly distributed across the brain, also produced significantly accurate sentence predictions.

Credit: Andrew Anderson/University of Rochester

"We found that we can predict brain activity patterns--not perfectly [on average 70% correct], but significantly better than chance," said Anderson, The study is published in the journal Cerebral Cortex.

Anderson and his colleagues say the study makes key advances toward understanding how information is represented throughout the brain. "First, we introduced a method for predicting the neural patterns of words within sentences--which is more complex than previous studies, which have almost all focused on single words," Anderson said. "And second, we devised a novel approach to map semantic characteristics of words that we then correlated to neural activity patterns."

Finding a word in a sentence

To predict the patterns of particular words within sentences, the researchers used a broad set of sentences, with many words shared between them. For example: "The green car crossed the bridge," "The magazine was in the car," and "The accident damaged the yellow car." fMRI data was collected from 14 participants as they silently read 240 sentences.

"We estimate the representation of a word 'car,' in this case, by taking the neural brain activity pattern associated with all of the sentences which that word occurred in and we decomposed sentence level brain activity patterns to build an estimate of the representation of the word," explained Anderson.

What does the meaning of a word look like?

"Coffee has a color, smell, you can drink it--coffee makes you feel good--it has sensory, emotional, and social aspects," said senior author Raizada. "So we built upon a model created by Jeffrey Binder at the Medical College of Wisconsin, a coauthor on the paper, and surveyed people to tell us about the about the sensory, emotional, social and other aspects for a set of words. Together, we then took that approach in a new direction, by going beyond individual words to entire sentences."

The new semantic model employs 65 attributes--such as "color," "pleasant," "loud," and "time." Participants in the survey rated, on a scale of 0-6, the degree to which a given root concept was associate with a particular experience. For example, "To what degree do you think of 'coffee' as having a characteristic or defining temperature?" In total, 242 unique words were rated with each of the 65 attributes.

"The strength of association of each word and its attributes allowed us to estimate how its meanings would be represented across the brain using fMRI," said Raizada.

The model captures a wider breadth of experience than previous semantic models, said Anderson, "which made it easier to interpret the relationship between the predictive model and brain activity patterns."

The team was then able to recombine activity patterns for individual words, in order to predict brain patterns for entire sentences built up out of new combinations of those words. For example, the computer model could predict the brain pattern for a sentence such as, "The family played at the beach," even though it had never seen that specific sentence before. Instead, it had only seen other sentences containing those words in different contexts, such as "The beach was empty" and "The young girl played soccer."

The researchers said the study opens a new set of questions toward understanding how meaning is represented in the brain. "Not now, not next year, but this kind of research may eventually help individuals who have problems with producing language, including those who suffer from traumatic brain injuries or stroke," said Anderson.

###

The Intelligence Advanced Research Projects Activity and the National Science Foundation supported the research.

Media Contact

Monique Patenaude
monique.patenaude@rochester.ed
585-355-7906

 @UofR

http://www.rochester.edu 

Monique Patenaude | EurekAlert!

More articles from Life Sciences:

nachricht Solving the efficiency of Gram-negative bacteria
22.03.2019 | Harvard University

nachricht Bacteria bide their time when antibiotics attack
22.03.2019 | Rice University

All articles from Life Sciences >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: The taming of the light screw

DESY and MPSD scientists create high-order harmonics from solids with controlled polarization states, taking advantage of both crystal symmetry and attosecond electronic dynamics. The newly demonstrated technique might find intriguing applications in petahertz electronics and for spectroscopic studies of novel quantum materials.

The nonlinear process of high-order harmonic generation (HHG) in gases is one of the cornerstones of attosecond science (an attosecond is a billionth of a...

Im Focus: Magnetic micro-boats

Nano- and microtechnology are promising candidates not only for medical applications such as drug delivery but also for the creation of little robots or flexible integrated sensors. Scientists from the Max Planck Institute for Polymer Research (MPI-P) have created magnetic microparticles, with a newly developed method, that could pave the way for building micro-motors or guiding drugs in the human body to a target, like a tumor. The preparation of such structures as well as their remote-control can be regulated using magnetic fields and therefore can find application in an array of domains.

The magnetic properties of a material control how this material responds to the presence of a magnetic field. Iron oxide is the main component of rust but also...

Im Focus: Self-healing coating made of corn starch makes small scratches disappear through heat

Due to the special arrangement of its molecules, a new coating made of corn starch is able to repair small scratches by itself through heat: The cross-linking via ring-shaped molecules makes the material mobile, so that it compensates for the scratches and these disappear again.

Superficial micro-scratches on the car body or on other high-gloss surfaces are harmless, but annoying. Especially in the luxury segment such surfaces are...

Im Focus: Stellar cartography

The Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) at the Large Binocular Telescope (LBT) in Arizona released its first image of the surface magnetic field of another star. In a paper in the European journal Astronomy & Astrophysics, the PEPSI team presents a Zeeman- Doppler-Image of the surface of the magnetically active star II Pegasi.

A special technique allows astronomers to resolve the surfaces of faraway stars. Those are otherwise only seen as point sources, even in the largest telescopes...

Im Focus: Heading towards a tsunami of light

Researchers at Chalmers University of Technology and the University of Gothenburg, Sweden, have proposed a way to create a completely new source of radiation. Ultra-intense light pulses consist of the motion of a single wave and can be described as a tsunami of light. The strong wave can be used to study interactions between matter and light in a unique way. Their research is now published in the scientific journal Physical Review Letters.

"This source of radiation lets us look at reality through a new angle - it is like twisting a mirror and discovering something completely different," says...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

International Modelica Conference with 330 visitors from 21 countries at OTH Regensburg

11.03.2019 | Event News

Selection Completed: 580 Young Scientists from 88 Countries at the Lindau Nobel Laureate Meeting

01.03.2019 | Event News

LightMAT 2019 – 3rd International Conference on Light Materials – Science and Technology

28.02.2019 | Event News

 
Latest News

Solving the efficiency of Gram-negative bacteria

22.03.2019 | Life Sciences

Bacteria bide their time when antibiotics attack

22.03.2019 | Life Sciences

Open source software helps researchers extract key insights from huge sensor datasets

22.03.2019 | Information Technology

VideoLinks
Science & Research
Overview of more VideoLinks >>>