by Zareen Afridi | 21 NOV 2017
A recent study has recorded the functioning of human brain with the help of artificial intelligence. The technique used was FMRI scan, a type of mind reading technology used in real time. Here it was used when people were watching videos. An algorithm named convolutional neural network was used. This algorithm enables computers and smartphones to recognise faces, objects and activities. This advanced effort has helped artificial intelligence improve and lead to new insights into the human brain.
Zhongming Liu, an assistant professor in Purdue University’s Weldon School of Biomedical Engineering and school of Electrical and Computer Engineering comments that the type of network used has enormously affected the field of computer science. He says that the technique used in the research makes use of neural network which is capable of understanding what the eye sees.
Convolutional neural network is a type of deep-learning algorithm that is used to map the brain. When the subject sees visual images, the brain processes static images and other visual stimuli. The idea to use this algorithm was to understand how the brain comprehends moving images of natural scenes. This is a huge step in decoding brains processing speed and making sense of complex and dynamic visual surroundings, said doctoral student Haiguang Wen. He is also the lead author of a research paper which has published online in the journal, Cerebral Cortex.
The study comprised of 11.5 hours of MRI data from each of 3 women candidates that saw 972 video clips of varying duration. The clips were from diverse subjects like people or animals in action or nature scenes. The data was used to train the new algorithm model so that it can predict the activity which occurs in brain's visual cortex when subjects were watching clips.
Then the new model was used to decode fMRI data from the subjects to rearrange the sequence of video clips and images. Even the clippings which were not played were arranged to find better accuracy. The result was successful; the new algorithm was able to accurately decoded the fMRI data into specific image categories. The actual video images were laid side by side as to compare the similarities between computer integrated images.
When comments that the speciality of this research is that all coding is done in real time. The images are mapped from the human brain as and when they are watching the clips. The brain is scanned in every 2 seconds and the model rebuilds the visuals as the subjects see it. The research also highlights how certain parts of the brain get activated to process the information that it sees. Neuroscience maps which parts of the brain are taking part to execute different functionalities. Wen ponderous that this is a landmark goal of neuroscience.
For example, a scene where a car approaches a building is dissected into pieces by the observers brain. Images with car, building and road are mapped into the system that catches the visual stimuli of the subject. Various parts of the brain were responsible to store and interpret the images and forming them into action. This new technique plays an active role here as it extracts information from the cerebral cortex of the brain and divides the visual scene into pieces and reassemble them to create motion picture.
Inputs of one subject were also compared to those of others to see how one process data. Liu says that we are entering a new era of Artificial Intelligence and news spheres of neuroscience are explored. He says that the mission is to advanced AI using brain concepts. He plans to advance in both AI and brain anatomy and correlate both fields to find astonishing results. This strategy will help in achieving new goals which would otherwise be impossible if approached separately.
The research was funded by National Institute of Mental Health and the work is affiliated with Purdue University for Integrative Neuroscience. Data reported in this paper is available publicly in the website of Laboratory of Integrated Brain Images.
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