Navigation Links
Carnegie Mellon study identifies where thoughts of familiar objects occur inside the human brain
Date:1/2/2008

PITTSBURGH A team of Carnegie Mellon University computer scientists and cognitive neuroscientists, combining methods of machine learning and brain imaging, have found a way to identify where peoples thoughts and perceptions of familiar objects originate in the brain by identifying the patterns of brain activity associated with the objects. An article in the Jan. 2 issue of PLoS One discusses this new method, which was developed over two years under the leadership of neuroscientist Professor Marcel Just and Computer Science Professor Tom M. Mitchell.

A dozen study participants enveloped in an MRI scanner were shown line drawings of 10 different objects five tools and five dwellings one at a time and asked to think about their properties. Just and Mitchells method was able to accurately determine which of the 10 drawings a participant was viewing based on their characteristic whole-brain neural activation patterns. To make the task more challenging for themselves, the researchers excluded information in the brains visual cortex, where raw visual information is available, and focused more on the thinking parts of the brain.

The scientists found that the activation pattern evoked by an object wasnt located in just one place in the brain. For instance, thinking about a hammer activated many locations. How you swing a hammer activated the motor area, while what a hammer is used for, and the shape of a hammer activated other areas.

According to Just and Mitchell, this is the first study to report the ability to identify the thought process associated with a single object. While earlier work showed it is possible to distinguish broad categories of objects such as tools versus buildings, this new research shows that it is possible to distinguish between items with very similar meanings, like two different tools. The machine-learning method involves training a computer algorithm (a set of mathematical rules) to extract the patterns from a participants brain activation, using data collected in one part of the study, and then testing the algorithm on data in an independent part of the same study. In this way, the algorithm is never previously exposed to the patterns on which it is tested.

Another important question addressed by the study was whether different brains exhibit the same or different activity patterns to encode these individual objects. To answer this question, the researchers tried identifying objects represented in one participants brain after training their algorithms using data collected from other participants. They found that the algorithm was indeed able to identify a participants thoughts based on the patterns extracted from the other participants.

This part of the study establishes, as never before, that there is a commonality in how different peoples brains represent the same object, said Mitchell, head of the Machine Learning Department in Carnegie Mellons School of Computer Science and a pioneer in applying machine learning methods to the study of brain activity. There has always been a philosophical conundrum as to whether one persons perception of the color blue is the same as another persons. Now we see that there is a great deal of commonality across different peoples brain activity corresponding to familiar tools and dwellings.

This first step using computer algorithms to identify thoughts of individual objects from brain activity can open new scientific paths, and eventually roads and highways, added Svetlana Shinkareva, an assistant professor of psychology at the University of South Carolina who is the studys lead author. We hope to progress to identifying the thoughts associated not just with pictures, but also with words, and eventually sentences.

Just, who directs the Center for Cognitive Brain Imaging at Carnegie Mellon, noted that one application the team is excited about is comparing the activation patterns of people with neurological disorders, such as autism. We are looking forward to determining how people with autism neurally represent social concepts such as friend and happy, he said. Just also is developing a brain-based theory of autism. People with autism perceive others in a distinctive way that has been difficult to characterize, he explained. This machine learning approach offers a way to discover that characterization.


'/>"/>

Contact: Anne Watzman
aw16@andrew.cmu.edu
412-268-3830
Carnegie Mellon University
Source:Eurekalert

Related medicine news :

1. Carnegie Mellon Establishes Ray and Stephanie Lane Center for Computational Biology
2. Carnegie Mellon neuroscientist proposes new theory of brain flexibility
3. Carnegie Mellon algorithm identifies top 100 blogs for news
4. SuperArray Bioscience Corporation Licenses RNA Interference Patent From The Carnegie Institution
5. The Bank of New York Mellon Recognized as Change Agent Shaping the Direction of Healthcare Transaction Processing
6. Penn study finds pro-death proteins required to regulate healthy immune function
7. New study shows promise in reducing surgical risks associated with surgical bleeding
8. Study, meta-analysis examine factors associated with death from heatstroke
9. Study suggests loss of 2 types of neurons -- not just 1 -- triggers Parkinsons symptoms
10. Study says COPD testing is not measuring up
11. Preclinical study suggests organ-transplant drug may aid in lupus fight
Post Your Comments:
*Name:
*Comment:
*Email:
(Date:2/20/2017)... FL (PRWEB) , ... February 20, 2017 , ... ... gift from Constellation Brands to purchase a new ultrasound-enhanced thrombolysis machine, a state-of-the-art ... waves. The gift was facilitated by the Pepin Family Foundation. , “We greatly ...
(Date:2/19/2017)... (PRWEB) , ... February 19, 2017 , ... Braun Industries ... JEMS Conference & Exposition, the event will take place February 23-25, 2017 at the ... will be in Booth #909 with three new ambulances on display. ...
(Date:2/19/2017)... ... February 19, 2017 , ... ... result in better care, and MEDfx and the Delaware Health Information Network (DHIN) ... , As the nation’s first state-wide health information exchange, DHIN stores and shares ...
(Date:2/18/2017)... ... February 17, 2017 , ... ... by Axendia, **FDAnews Free Webinar**, March 1, 2017 — 1:30 p.m. – ... their regulatory burden? Pay dividends in enhanced and predictable product performance? Streamline ...
(Date:2/18/2017)... ... , ... Butler Mobility invited Ken Matthews to visit its manufacturing facility and ... was impressed with the safety and reliability of the Stannah Stairlift as well as ... This endorsement by Ken Matthews can be heard on News Radio WHP 580 weekdays ...
Breaking Medicine News(10 mins):
(Date:2/20/2017)... Feb. 20, 2017  This report analyzes the worldwide markets ... Million. The report provides separate comprehensive analytics for the ... , Europe , ... and Rest of World. Read the ... and forecasts are provided for the period 2015 through ...
(Date:2/20/2017)... Feb. 20, 2017 Research and Markets has ... Insights, Opportunity, Analysis, Market Shares & Forecast 2017 - 2022" ... ... nearly USD 2 Billion by the year end of 2022 growing ... Market growth can be attributed to factors such as ...
(Date:2/20/2017)... -- Seal Shield LLC ( Jacksonville, FL ... management and disinfection, the ElectroClave™, to the exhibit floor ... Orlando, Fla. from February 20-23, 2017 ... commonplace in today,s healthcare landscape, but with this progression ... the disinfection and tracking of these devices.  The ElectroClave™ ...
Breaking Medicine Technology: