You could lie there in the scanner and watch your brain light up. Then you could watch your brain light up some more in response to seeing your brain light up, and watch it light up even more upon seeing your brain light up in response to seeing itself light up... like putting your brain between two mirrors and getting an infinite tunnel of activations.Ok, that would probably get boring, eventually. But there'd be some useful applications too. Apart from the obvious research interest, it would allow you to attempt fMRI neurofeedback: training yourself to be able to activate or deactivate parts of your brain. Neurofeedback has a long (and controversial) history, but so far it's only been feasible using EEG because that's the only neuroimaging method that gives real-time results. EEG is unfortunately not very good at localizing activity to specific areas.
Now MIT neuroscientists Hinds et al present a new way of doing right-now fMRI:
Computing moment to moment BOLD activation for real-time neurofeedback. It's not in fact the first such method, but they argue that it's the only one that provides reliable, truly real-time signals.
Essentially the approach is closely related to standard fMRI analysis processes, except instead of waiting for all of the data to come in before starting to analyze it, it incrementally estimates neural activation every time a new scan of the brain arrives, while accounting for various forms of noise.
They first show that it works well on some simulated data, and then discuss the results of a real experiment in which 16 people were asked to alternately increase or decrease their own neural response to hearing the noise of the MRI scanner (they are very noisy). Neurofeedback was given by showing them a "thermometer" representing activity in their auditory cortex.
The real-time estimates of activation turned out to be highly correlated with the estimates given by conventional analysis after the experiment was over - though we're not told how well people were able to use the neurofeedback to regulate their own brains.
Unfortunately, we're not given all of the technical details of the method, so you won't be able to jump into the nearest scanner and look into your brain quite yet, though they do promise that "this method will be made publicly available as part of a real-time functional imaging software package."
Essentially the approach is closely related to standard fMRI analysis processes, except instead of waiting for all of the data to come in before starting to analyze it, it incrementally estimates neural activation every time a new scan of the brain arrives, while accounting for various forms of noise.
They first show that it works well on some simulated data, and then discuss the results of a real experiment in which 16 people were asked to alternately increase or decrease their own neural response to hearing the noise of the MRI scanner (they are very noisy). Neurofeedback was given by showing them a "thermometer" representing activity in their auditory cortex.The real-time estimates of activation turned out to be highly correlated with the estimates given by conventional analysis after the experiment was over - though we're not told how well people were able to use the neurofeedback to regulate their own brains.
Unfortunately, we're not given all of the technical details of the method, so you won't be able to jump into the nearest scanner and look into your brain quite yet, though they do promise that "this method will be made publicly available as part of a real-time functional imaging software package."
Hinds, O., Ghosh, S., Thompson, T., Yoo, J., Whitfield-Gabrieli, S., Triantafyllou, C., & Gabrieli, J. (2010). Computing moment to moment BOLD activation for real-time neurofeedback NeuroImage DOI: 10.1016/j.neuroimage.2010.07.060
6 comments:
WOW! This is so cool! Now I just have to win the lottery and then I can fund the rest of the research and buy me one of those things. If the research pays off.
Really I hope they do more research with this though. If it actually helps people it would be amazing.
Neuroscientist Prof. C. deCharms of Omneuron says that "you can control your brain to control your pain." He designed a 'Real Time fMRI Machine' lying in which a patient with chronic pain can see the pathways of neuronal firing in his/her brain and modify the firing consciously (taking help of a few cues provided) so that he/she is relieved of the pain. Patients reported 44% - 64% reduction in their chronic pain in clinical trials by this method.
(See tedcom a 3-min demo lecture of his.)
Blog Post: http://beyond-advaita.blogspot.com/2009_05_01_archive.html
Whilst fascinating it does put an enormous trust in the accuracy of the mathematical model, the correct linkage of signal/location/action and the software.
Would a real bummer if at some point you are neurofeedbacking pain away and at the same time reducing impulse control for example turning you into a raving serial killer.
I guess i wish the testsubjects all the best, but i won't volunteer
What does "real-time" mean exactly? AIUI any NMR/MRI signal evolves over several seconds. I expect even in the best case there would be a ~10 second delay between initiation of measurement and display. There would be a similar delay between images since you can't start one until the previous one is finished.. In contrast, EEG response is near-instantaneous and has time resolution of <10 miliseconds.
None of this implies that this research isn't really nifty, of course.
Yes, this is cool!
Not sure what "real-time" means, but neurofeedback has been successfully demonstrated using clunkier, slower fMRI. Despite there being a ~10 sec delay, it does provide sufficient feedback for subjects to learn self-regulation.
A study that demonstrates activation of a motor cortex area trained by fMRI neurofeedback:
Neurofeedback fMRI-mediated learning and consolidation of regional brain activation during motor imagery
Immediate response (as in EEG) is not necessary for biofeedback. In the 70's, biofeedback research was conducted wherein subjects learned to self-regulate hand temperature (there was some success in treating Raynaud's disease with this method.) Feedback was based on hand/finger temperature, which obviously is not instantaneous - the vasodilation responsible for it is rapid, but the increase in temperature - the variable upon which feedback was based - was more gradual. Self-regulation of hand temperature was achieved despite the delay.
Search for "biofeedback hand temperature" on PubMed will pull up a bunch of these, but here are two-
Biofeedback vs. instructional control of skin temperature.
Temperature regulation training in a cooling environment.
I do wonder about the placebo effect in deCharms employment of fMRI neurofeedback. Does he control for this? (is he for real?)
Ella: Thanks for the response.
Now that I've thought about it. I wonder if it would be possible to interlace measurements of different slices of the brain. You could stagger the initiation of measurement of the various slices and effectively update the results faster. I have onle a vagur theoretical understanding of how MRI works (I was a chemistry major) and this may be technically infeasible* but it would be sooooo cool.
*MRI signals are extremely complicated and require powerful computers to produse useful images. Deconvoluting adjacent signals could only be harder.
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