Tag Archives: fMRI

Project Final

Here is a link to our group’s final project on: The Physics of Mind-Reading

Preliminary Data- Current Research in Thought Detection

Cerf, M., Thiruvengadam, N., Mormann, F., Kraskov, A., Quiroga, R.Q., Koch, C. and Fried, I. (2010). On-line, voluntary control of human temporal lobe neurons. Nature, 467, 1104-1108

Dr. Moran Cerf and colleagues have been able to connect the activity of single neurons to images on a computer screen. Participants are then able to fade these images in and out based on what they are thinking about. Initially, the study participants looked at hundreds of images in order for the researchers to build a database of image-neuron associations. The researchers then instructed participants to focus on one of two superimposed images. They were, with great accuracy, able to determine which picture the participants were looking at based on only their thoughts.

Naselaris, T., Prenger, R.J., Kay, K.N., Oliver, M. and Gallant, J.L. (2009). Bayesian reconstruction of natural images from human brain activity. Neuron, 63(6), 902-915

This pioneering experiment involved the use of a newly developed machine that can recreate a moving image from the brain activity of a participant watching a video. While the results are grainy and crude, the researchers were able to make out, for instance, the outline of a man in a white shirt from the brain activity of a participant watching a video with Steve Martin. Dr Gallant, the principle researcher, feels that his technology is close to becoming a practical form of mind reading, in which doctors can look into the mind of schizophrenic patients or judges can look into the minds of criminals.

Kamitani, Y. and Tong, F. (2006). Decoding seen and attended motion directions from activity in the human visual cortex. Current Biology, 16(11), 1096-1102

This research group proposed that the areas of the brain used to deconstruct visual information is also involved with processing memories associated with this information. Using this basis, the researchers conducted a study in which volunteers were shown two different patterns, and told to remember their pattern for a short period after viewing. Based on fMRI brain activity patterns, the researchers were able to detect which pattern a participant was thinking about.

Mitchell, T.M., Shinkareva, S.V., Carlson, A., Chang, K., Malave, V.L., Mason, R.A. and Just, M.A. (2008). Predicting human brain activity associated with the meanings of neurons. Science, 320, 1191-1195

Mitchell and colleagues designed a computational model that predicts fMRI neural associations with words for which fMRI activation information is not yet available. This is one of the first forays into mind-reading that does not require the subject to be looking at a picture of what he/she is thinking about. Their new model integrates the use of a trillion-word text corpus and observed fMRI data associated with several dozen concrete nouns. From this initial information, the researchers are able to, with a high degree of accuracy, predict fMRI activation for thousands of different concrete nouns.

Haynes, J.D., Sakai, K., Rees, G., Gilbert, S., Frith, C. and Passingham, R.E. (2007). Reading hidden intentions in the human brain. Current Biology, 17(4), 323-328

Dr. Haynes and colleagues are interested in reading an individual’s intentions rather than simply decoding information about a concrete object. In this study, the researchers allow the subjects to choose one of two tasks to complete. From fMRI readings, the researchers are able to reliably pick which task will be completed before the subject initiates the task. These results suggest that covert goals or intentions can be represented by patterns of activity in the pre-frontal cortex, which researchers are then able to decode using fMRI.

Samantha Gross, “Intel Shows Off ‘Mind-Reading’ Brain-Scan Technology,” The Huffington Post, April 8th, 2010, accessed April 19th, 2011, http://www.huffingtonpost.com/2010/04/08/mind-reading-brainscan-so_n_530009.html

Mind-reading research is not only being assessed in an academic research setting. Large corporations are researching the technology, and developing advanced machines that can decode fMRI information faster than humans. Intel Corporation showed off its own software that can quickly decode fMRI information, and reliably predict what an individual is thinking about based on neuronal activity. Researchers from Intel Labs believes this is the first step towards one day being able to control technology with our minds.

(Above video from www.dailymotion.com/video/x9pzcq_the-present-future-of-mind-reading_news)

Applications of mind-reading research

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Group 13: Data!

Quick recap: We’re investigating the science of “mind-reading.” Each of us selected a specific topic to research. Maddy is looking into how fMRI works. Adam is examining current research being done. I (Jackie) am going to talk about applications of all this technology.

Here’s what I’ve found so far:

Applications of mind-reading technology

Applications of “mind-reading” technology
- Overview, previous approaches, limitations – deCharms (2008) discusses how real-time brain imaging (e.g., with fMRI) allows access to both subjective experience (to an extent) and to objective observations and quantitative measurements of brain activity. He outlines some past approaches to “mind-reading” as well as limitations to current approaches. This leads to a discussion of the applications of current neuroimaging research:
Lie detection
- Langleben (2008) argues that blood oxygenation level-dependent (BOLD) fMRI could be sensitive to differences between lies and truth. The key, he claims, is that BOLD fMRI can only compare states rather than positively identify deception. He discusses how many popular science articles conflate how much fMRI can do.
- Mertens & Allen (2008) discuss whether ERP-based procedures could detect deception, instead of or in addition to fMRI.
- Moreno (2009) discuss ethical issues in lie detection and how the law should be influenced by cognitive neuroscience, specifically in cases where neuroimaging could be used to determine truth, lies, and guilt.
Pain detection
- Marquand et al. (2010) suggest that supervised machine learning algorithms can be used to decode fMRI data. They use this kind of technique to show that fMRI can be used to predict participants’ subjective pain ratings and propose that it will be a useful method for producing qualitative predictions about brain states.
Brain-computer interfaces
- Direct brain communication in paralysis, motor restoration in stroke – Birbaumer & Cohen (2007) evaluate the use of EEG and fMRI in brain-computer interfaces, focusing on applications for paralyzed patients and for motor restoration in the case of stroke. Although currently, our understanding of the information flow in the brain that is required for such interfaces to work is incomplete, such interfaces will eventually be able to be used for direct brain communication and will allow otherwise “locked-in” patients to interact with the world.
- Daly & Wolpaw (2008) also discuss advances in the analysis of brain signals and training patients to control those signals, focusing on EEG techniques specifically for patients with severe motor disabilities.
Pattern analysis and future research
- Norman et al. (2006) argue that fMRI data can be used in conjunction with sophisticated pattern-classification algorithms to decode the exact information represented in a patient’s brain at a particular moment in time. They discuss factors that would boost the performance of this method — it is possibly the most promising research toward actual mind-reading.
In the press: Where the reporters think this research is headed.
- Biever (2008) – to record and read people’s dreams
- Debrosse (2010) – as a counter-terrorism technique
- Masterman (2009) – in court, for lie-detection
- Graham-Rowe (2011) – brain-computer interfaces useful to the disabled
- BBC News (2005) – to read unconscious thoughts, attitudes, preferences

References (credible)
Birbaumer, N., & Cohen, L. (2007). Brain-computer interfaces: communication and restoration of movement in paralysis. Journal of Physiology, 579.3: 621-636.

Daly, J., & Wolpaw, J. (2008). Brain-computer interfaces in neurological rehabilitation. The Lancet Neurology, 7: 1032-43.

deCharms, C. (2008). Applications of real-time fMRI. Nature Reviews Neuroscience, 9: 720-729.

Langleben, D. (2008). Detection of deception with fMRI: Are we there yet? Legal and Criminological Psychology, 13: 1-9.

Marquand, A., Howard, M., Brammer, M., Chu, C., Coen, S., & Mourão-Miranda, J. (2010). Neuroimage, 49(3): 2178-2189.

Metens, R., & Allen, J. (2007). The role of psychophysiology in forensic assessments: Deception detection, ERPs, and virtual reality mock crime scenarios. Psychophysiology, 45 (2): 286-298.

Moreno, J. (2009). Future of neuroimaged lie detection and the law. Akron Law Review, 717-737.

Normon, K., Polyn, S., Detre, G., & Haxby, J. (2006). Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10(9): 424-430.

Popular science news

BBC News. (2005, April 25). Bran scan ‘sees hidden thoughts’. BBC News: Health. Retrieved April 19, 2011, from http://news.bbc.co.uk/2/hi/health/4472355.stm.

Biever, C. (2008, December 12). ‘Mind-reading’ software could record your dreams. NewScientist: Tech. Retrieved April 19, 2011, from http://www.newscientist.com/article/dn16267-mindreading-software-could-record-your-dreams.html.

Debrosse, J. (2010, March 15). Mind-reading technology being researched for foil terrorist attempts. McClatchy – Tribune Business News. Retrieved April 19, 2011, from ABI/INFORM Dateline. (Document ID: 1983690351).

Graham-Rowe, D. (2011, April 12). Dialing with your thoughts. Technology Review. Retrieved April 19, 2011, from http://www.technologyreview.com/communications/37357/?a=f.

Masterman, J. (2009, April 23). Current debates about fMRI research methods bear on policy questions. Science progress. Retrieved April 19, 2011, from http://www.scienceprogress.org/2009/04/fmri-mindreading-studies/.

What is fMRI?

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Image of a human brain produced by fMRI scan.

Magnetic Resonance Imaging, or MRI, is used in many medical applications to gain an image of what is going on inside a patient’s body. It works because of humans’ unique molecular makeup. Because our bodies contain so much water, we are approximately 63% Hydrogen atoms. The protons in these atoms each possess a unique ‘spin’, or angular momentum. During an MRI scan, a radio wave pulse is sent through a large metal tube, which produces a very strong magnetic field ranging from 0.5 to 2.0 Teslas. This magnetic field interacts with the angular momentum of the Hydrogen atoms and aligns their spins in one direction (this is called ‘resonance’). At this point, the atoms are in a higher energy state, so when the field is removed, the atoms return to their lower energy resting state and give off a signal that is converted into a physical image.

Functional Magnetic Resonance Imaging, or fMRI, is a similar process, but rather than relying on atomic manipulation, fMRI measures changes in blood flow within the brain. It is known that when a particular region of the brain is actively firing, blood will flow there to supply needed energy. Because this blood is supplying energy, it comes from the lungs and contains a high level of oxygen, as opposed to blood that has been in circulation already and given off much of its oxygen content. This rush of highly oxygenated blood behaves uniquely in that it does not give off a magnetic signal, like other blood (it becomes ‘diamagnetic’). When an fMRI is performed and the strong magnetic field is applied to a patient’s brain, the diamagnetic blood interacts with the field much differently than the other surrounding blood. This allows scientists to map out exactly which regions of the brain are actively firing.

Learn more:

Raichle M. E., (2000) A brief history of human functional brain mapping. In Brain Mapping: The systems edited by Toga A.W. and Mazziotta J.C., Academic Press, pp33-75

http://www.radiologyinfo.org/en/info.cfm?pg=fmribrain

http://www.cis.rit.edu/htbooks/mri/inside.htm

http://www.physicscentral.com/explore/action/fmri1.cfm

http://www.radiology.mcg.edu/MRI_Physics/SpinGymnastics.pdf

http://www.fmrib.ox.ac.uk/education/fmri/introduction-to-fmri/

http://health.howstuffworks.com/medicine/tests-treatment/mri.htm

http://health.howstuffworks.com/medicine/tests-treatment/fmri.htm

The Science of Mind-reading, part II

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Group 13: Project Plan

Our project, as described previously, is to investigate the science of “mind-reading.”

We will perform a review of primary literature as found through the library’s many databases to understand where this technology is today and where it may go in the future. Most of this research will be done independently; we will meet weekly (the day will vary week to week based on our individual schedules) to compile the information we find. Relevant data and results from recent fMRI studies will be presented in our poster.

Each of us will focus on a specific topic:

Maddy: How fMRI (the primary tech used for “mind-reading”) works
Adam: Current research being done
Jackie: Applications of “mind-reading” technology

We expect to find that although no one can currently “read” a person’s thoughts, memories, or dreams, researchers are working on this — right now, you need to obtain template images of a person’s brain during different activities for later comparisons and predictions about what the person is thinking. Reading “abstract” thoughts isn’t yet possible.

The science of mind-reading

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girl wearing an EEG cap, with white electrodes in a hair-net-like cap over her head

Jackie, member of Group 13, in Vassar's EEG lab

Group 13: Project Abstract

Memory manipulation and the idea that one’s thoughts could be recorded and “read” by another person show up in many science fiction films, such as Eternal Sunshine of the Spotless Mind, Inception, and Minority Report. These films inspire our project: We intend to explore the science of “mind-reading.” We will look at primary literature in the field to investigate how technology such as fMRI and electroencephalography (EEG) can be used to measure the electrical and magnetic activity of brains. Applications of such technology, if it works reliably to access people’s thoughts, memories, and dreams, would be widespread, from assessing psychological conditions to lie detection in criminal cases. We will present the results of our investigation in a poster.