Summary:
This paper presents the mathematical formulation for handling parallel RF transmission inside the magnetic field of an MRI. It gives mathematical evidence of the possibility of preserving image reconstruction using the parallel RF transmissions. They provide experimental evidence showing a prototype of their mathematical formulation in action.

Conclusions:
This paper makes it clear to me that there are still gaping holes in the depth of my knowledge of MRI technology. I need to fill those gaps so that I can really understand the details from the magnetic field generation to gathering data and the algorithms for image reconstruction. There’s way too many details that are missing in my knowledge for this paper to be much use to me mathematically. It does, however, present the idea that RF transmission is possible in conjunction with MRI and that the algorithms can be modified to account for the RF transmissions. Without spending much time mulling over the mathematical details, I can definitely postulate that ‘if’ we were able to use RF transmissions for remotely firing neurons that we could include those transmissions mathematically in the image reconstruction for the MRI images and not have the transmissions interfere with the imaging. If we were to construct a feedback loop using RF to transmit to the brain remotely and MRI to read normal brain activity as a response we could theoretically create a continuous scan without having the excitation RF interfering with the normal MRI function.

Ulrich Katscher and Peter Bornert – Parallel RF transmission in MRI – NMR Biomed. 2006; 19: 393–400

Summary:
This paper studies the use of low intensity, low frequency ultrasound to elicit neuron firing. The authors test their approach on a 2d culture of neurons taken from mice brains. They subjected the culture to ultrasound (US) at varying frequencies, intensities, repetitions, and durations. They analyzed the cultures’ response to the US by looking at Na and Ca quantities within the culture. Its understood that increases in Ca and Na relate to neuron firing. The experiments show that US was able to excite neurons into firing.

They also tested their approach on an entire extracted mouse brain to see if the US could penetrate deep into the brain tissue and have the same effect. They observed the opposite side of the brain that was being subjected to the US which showed neuron activity.

The authors cite mention research that suggests US has negative long term effects on neurons making the use of US for continual exposure potentially dangerous but they find no evidence of disruption in their cultured neurons.

Questions:
I was extremely interested in their testing of excitation through the entire brain, however, the approach doesn’t seem to present a way to excite a specific depth within the brain. The authors seemed to only test the firing of the far side of the brain area being stimulated. The paper seems to avoid the question of whether the US would effect firing of all neurons within the path of the US. Its likely they would require a more precise neuron firing detection method to analyze firings at depth. Use of fMRI would likely make sense for analyzing neuron firing in 3d but the ultrasound equipment would likely interfere with the fMRI scan without proper integration into the fMRI scanner.

Future Work:
One potential area for future work would be to investigate long term effects of US use at varying intensities frequencies. It is of particular interest to develop technologies to elicit neuron firing that can be used continuously for extended periods of time. It is extremely important to understand the long term effects of US at different intensities and frequencies so that we can potentially identify frequencies and intensities which minimize the negative effect of using US to fire neurons.

Another area of potential research would be attempting to use US in eliciting targeted neuron firing within 3d space. In particular, the firing of neurons deep within the brain without effecting the surrounding areas. The current research shows techniques on a mostly 2d plane of neuron culture and a general analysis of an entire brain but fails to show how US would be capable of targeting only neurons at specific depths within the brain rather than every neuron along the US path.

Conclusions, Interests and Reflections:
The authors conclude US is suitable for neuron firing which is true but the negative prolonged effects may outweigh the benefit of US neuron excitation over other methods. I was extremely interested to see evidence of precise neuron firing in the 3d space with their entire brain experiment but it seemed missing. The authors were focused on showing that US does elicit neuron firing and how it works. It was an interesting approach but the negative effects of US on neurons over time will be the biggest drawback to the adoption of this method. The authors found no evidence of neuron disruption but cite other research which does. Without identifying safe frequency and intensities at which to operate over long periods of time, the US usefulness for neuron excitation may be limited to procedures requiring minimal temporal US stimulation.

William J. Tyler, Yusuf Tufail, Michael Finsterwald, Monica L. Tauchmann, Emily J. Olson, Cassondra Majestic – Remote Excitation of Neuronal Circuits Using Low-Intensity, Low-Frequency Ultrasound – PLoS ONE 3(10): e3511 (2008).

Summary:

This paper describes a technique for using RF magnetic fields to heat an aqueous solution of nanoparticles bound to fluorophores within a culture of genetically engineered neurons to fire individual neurons. The fluorophores act as a thermometer by lighting as the nanoparticles are heated. They experimentally measured the temperature of the bulk solution without the cells as they target a local nanoparticles with RF magnetic fields to heat them locally. They concluded that the nanoparticle heating was concentrated locally and didn’t result in an increase in temperature for the bulk solution. The temperature of the local heated nanopartical did not radiate enough away from the target of the RF magnetic field to effect the bulk temperature. They genetically engineered neurons to contain the fluorophores they tested in the bulk solution so that the nanoparticle binds to it.

Applying the RF to the nanoparticles heated the cells locally and they measured the calcium concentration using a calcium sensor and voltage using voltage sensitive dye within the culture showing that it increases meaning the neurons have fired.

They provide experimental evidence of initiating a physical response in worms. They tested heating nanoparticles injected into the worms motion control area and when RF was applied the worms reversed their forward movements. RF waves without nanoparticles had no effect. This experiement showed that the RF magnetic field did heat the nanoparticles and subsequently triggered neurons to fire within the worm.

Questions:

Why was this type of worm selected? Does it have specific characteristics that were ideal for experimentation of this kind?

What other nanomaterials behave similarly?

How locally targeted was the RF field? Early in the paper its suggested the RF field was applied locally to observe heat difussion in an aqueous solution of nanoparticles but later in the paper its mentioned that RF fields have a problem targeted specific cells. I’m confused. Is ‘locally’ a relative term with respect to the medium? Local in the bulk solution meaning an inch which seems reasonable if a solution is 12 inches in diameter but an inch with respect to neurons in the brain is enormous.

Future Work:

The article mentions difficulty in targeting specific cells for heating using RF magnetic fields. The ability to more precisely target specific cells would open the possibilities for neuroscience research immensely. An important area of research is more precise targeting of RF magnetic fields. This might be an intractable problem, however, with RF fields in general. Perhaps if a nanoparticle would heat only when a magnetic resonance of a certain threshold is created we could then potentially use existing MRI technology to both image the brain and elicit neural firings at a higher spacial resolution than the RF waves themselves can provide. Research into different types of nanoparticles which are heated only when magnetic resonance is within certain ranges and no heating otherwise would be ideal. My knowledge of magnetic resonance isn’t deep enough to know if this is even feasible however. Some research currently uses fiber optics inserted into the brain to isolate individual neurons for firing. I’m not sure if they use light or heat but I think its light. If photons of light can trigger neurons to fire, it seems reasonable that the photons emitted from MR could potentially either directly or indirectly fire neurons as well.

One area of future work would be applying this technique in more complex organisms. In addition, it would be extremely useful if the nanoparticles could be intravenously given to the organism and effectively expand response potential over the entire brain. Effects of the nanoparticles themselves on normal brain function and other biological function would have to be thoroughly evaluated.

Conclusions, Interests and Reflections:

I read a review of this article which seemed to hype up the results. While extremely interesting, it goes without saying that we are a little ways away from being able to apply this type of method to a human brain to target individual neurons anywhere in the brain. This research shows the potential of RF magnetic fields and nanoparticles to expand the possibilities of non-invasively interacting with neurons.

Heng Huang, Savas Delikanli, Hao Zeng, Denise M. Ferkey and Arnd Pralle – Remote control of ion channels and neurons through magnetic-field heating of nanoparticles – Nature Nanotechnology Volume: 5, (2010)

I just came across this article on remote control of neuron firing using RF waves and nanoparticles. The article summarized a few papers that just came out this summer which are pushing the limits of our understanding of the brain. I’ve been studying fMRI technology recently and it allows neuroscientists to observe oxygen in the blood inside the brain which happens to occur just after neurons are fired. Using that technique, we’re able to identify which areas of the brain are active during certain thoughts or when provided various stimuli either visual or audible.

My brief study of fMRI lead me to the question of whether or not we can make a neuron fire without having to cut open the brain. Cutting open the brain is extremely invasive and complex and thus requires a highly specialized team of surgeons and neuroscientists to conduct it. Research opportunities for invasive neuroscience are extremely small compared to non-invasive techniques and as a result non-invasive techniques are more tangible by most researchers. I was extremely excited to find this article which explains at a high level how the remote neuron firing procedure works. I’ll try to summarize it here.

A nanoparticle is injected intravenously which flows through the blood into the brain. An RF pulse is sent to the brain in a similar way that MRI works, targeting a specific local area. The RF pulse heats up the nanoparticles in the local area which causes the neuron to fire.

As this technology is refined, I’m interested in understanding how we can transmit more complex ‘thoughts’ or ‘stimuli’ to the brain remotely. We’re able to fire individual neurons within the brain so this isn’t too far off. I’d estimate we’ll have a method for remotely sending more complex and meaningful signals to the brain within the next 5 years if not sooner. The poor spacial and temporal resolution with this method and the need for more parallelism in firing individual neurons is probably what needs to be addressed to get to a point where we can send more complex and meaningful signals.

Since I’ve decided to return to school to get my PhD, I figured it would be a good idea to start reviewing research papers again. I must admit that its been a while since I’ve reviewed a research paper and I’ve never reviewed a neuroscience paper before. None-the-less, here is my attempt at a review.

Summary: The paper presents research using fMRI analysis of subjects’ brain patterns when viewing various 10×10 block images. The method uses multiple points of analysis of the brain and the image reconstruction algorithm requires training to select voxel weights.

They present analysis of random image identification using a subset of all possible random images and show the rate of successful identification declines as the size of the potential image set increases. The authors explain their voxel selection method and perform tests to determine the quantifiable benefit of their voxel selections over other methods. Next they explore their image reconstruction technique to determine how well their multiscale method performed over single scale methods. My guess is the multiscale method was an after-thought once they reviewed the performance of the single scale data. The multiscale image did perform better at correctly matching the presenting image, however, I didn’t understand how they were actually calculating ‘performance’ or ‘eccentricity’ despite relying on it in the analysis. It could be common knowledge in the field that I’m just not familiar with yet.

The authors do an excellent job at reviewing their own work in the discussion section and present a handful of potential future areas of research. They finish with a detailed explanation of their experimental procedures which I found particularly interesting because it covered details of their data gathering, filtering, and processing using different sources such as correlating retinotopy mapping to the fMRI data (though I didn’t understand it completely). It gave me a good insight into the experimentation process used in neuroscience.

Questions: I’m not sure if its just my lack of knowledge about the type of data the fMRI and retinotopy mapping produces or if the authors were just vague but their observations of the “Weight Distribution on the Cortical Surface” seemed a bit sparse. It didn’t seem to suggest why the weights one way or another were more or less beneficial to their experimental results. Perhaps this is an area for future research or perhaps my knowledge in the field is showing itself. They did follow that section up with experimenting with different methods and it might seem more obvious why if I knew a bit more about retinotopy.

Future Work: It would be interesting to see if similar techniques could be used to identify the main component of a larger picture. My thinking is that if they can reconstruct a 10×10 image what ability could the same or an adapted technique have at reconstructing a 10×10 piece of a bigger picture? For instance a picture in which a contrasting foreground image of 10×10 was placed against a larger random background. What happens when the test data is three dimensional instead of a simple 2d image?

Could a similar technique be used to identify simple shapes in more complex scenes? Would other areas of the brain come into play when using actual objects or more complex scenes? How well does this technique scale up beyond the 10×10 images? How can we identify color?

It would be interesting to see the effectiveness of various types of multivoxel pattern decoder methods in relation to to same experiment or even with scaling it up. The selected technique worked for this instance of 10×10 block images but will it still work if the image becomes more complex like 100×100 or even 1000×1000? What is the effectiveness of different methods as the image complexity increases? Perhaps other reconstruction methods work better for more complex images. I’m curious what the most complex reconstruction is to date and what methods were used.

One of their conclusions is that the multiscale image combination method contributed to the positive results. It seems highly coupled with the voxel selection technique. It would be interesting to explore other image combination techniques in relation to different voxel selection methods. Perhaps another voxel selection / image combination technique would produce more accurate results.

Conclusions, Interests and Reflections:
The authors mention they used a statistical learning algorithm called “sparse logistic regression” to train the weights of voxels. I haven’t come across this learning algorithm before and am interested in learning more about it.

It has become clear to me that I know far too little about brain imaging technology to understand this paper completely. I intend to study different brain imaging technologies like fMRI next so that I can better understand some of the details in future papers.

Overall I think this was an extremely well researched paper. The results were clearly presented and the authors seemed to give a thorough analysis of their methodology.

Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders – Yoichi Miyawaki, Hajime Uchida, Okito Yamashita, Masa-aki Sato, Yusuke Morito, Hiroki C. Tanabe, Norihiro Sadato, and Yukiyasu Kamitan

I was just browsing my Google Analytics data today when I noticed the map of Florida looked really weird. Growing up in Florida I knew this was obviously incorrect so I took a screenshot.

And here is what Florida is supposed to look like.

Take a look at the bottom past Miami near the Keys. The Google map has no land there at all and the shape is all wrong. It looks like someone took a big bite out of south Florida. Maybe they’re just predicting water levels to rise soon and just saving themselves the extra effort of redoing their map after that happens. A bit of proactive thinking perhaps or completely obvious blunder.

I’ve been writing a lot about how great Bing is and made the switch to use Bing regularly but here I am in day 1 with using Bing full time and have run into problems. I am working on a Rails project doing some http requests and screen scraping. Basically, I’m extending the contacts gem to include AOL support. I wanted to see a quick reference to refresh my memory on the get / post syntax in Rails. I search Bing for “rails get http” and the first result is a link to rubyonrails.org. How useless. I search the entire first page and find absolutely nothing related to what I’m looking for. I’m beginning to second guess my previous whole-hearted support of Bing. Its good for general searches but it seems program related searches are crap with Bing. I do the same search in Google and the first result is what I wanted. Just a quick reference of someone using the Ruby get method. I tried a few other searches like ‘rails contacts gem’ and Bing doesn’t really give me much to work with in the results. I did have to dig down to the 8th result with Google but the Rails contacts gem project page is at least on the first page of the search results. Google wins when it comes to programming related searches in my opinion. Time for me to switch back to Google for the time being.

I have numerous SEO clients and one thing that I’ve noticed in the past few months is a drastic improvement in Microsoft’s Bing search engine’s quickness to respond to on-site content changes. All my clients are performing extremely well on Microsoft’s Bing search engine first and then the others follow. Yahoo and Google seem on par with each other as far as quickness to update and in rankings in general. Yahoo does seem to occasionally throw in huge random ups and downs but on the most part its in sync with Google’s rankings for most of my clients. Bing’s results however all outperform the other search engines in terms of quickness to respond to content updates as well as its ability to maintain high rankings for new content over time.

I’m not sure what Microsoft did to their search engine when they rebranded it as Bing but it does appear to behave differently as far as rankings for my clients. Despite the low amount of traffic it sends it is positive news either way. Now if only they offered some quality free tools like Google’s Webmaster Tools and Google Analytics it might start making some converts.

What I would personally like to see is for a top search engine to publish a detailed description for how to get them to view your site positively. They all keep it behind a black box and let the magic behind SEO consultants do the research but why? Why not just come out and explicitly say here is how to get your site ranked well. Here is what we don’t like. Here is what we do like. Then provide useful tools for optimizing your site to make it better. Offer a free set of SEO tools direct from the search engine. Then have a paid version that goes a lot deeper. I’m sure I’d have all my clients on the paid version in no time. Its not paying for rankings, its paying for the tools to get the site ranked better.

Its a whole new twist on SEO that who ever takes advantage of first might just become the next king of search.

Note: Microsoft didn’t pay me to write this but they should. They need all the positive publicity they can get.

The Wall Street Journal is reporting on the FTC’s recent decision to fine bloggers for not explicitly stating any compensation received for writing a blog. The FTC will now supposedly fine bloggers for writing reviews of products or services without specifying that they’ve been compensated for it. While the FTC has much bigger problems they should be dealing with like metered cell phone usage, misleading multi-year cell contracts, and software patents in general they are now focused in a direction they have absolutely no jurisdiction over. Will we now have federal blog readers employed with US tax dollars to just read blogs all day and make sure no one is writing reviews without specifying compensation for the review?

The whole logistics of enforcement of such fines is laughable in my opinion. First, what if I host my site in another country? Will these fines still apply? Second, a lot of blog sites have multiple authors with no realistic way for a site owner to ensure every writer is following the rules. Who will be responsible if a writer blogs against the rules? Finally, what will the FTC do if my site in another country and I am marketing specifically for US customer? Are they planning a great US firewall like China so they can excerpt more control over our online commerce and enforce penalties like blocking overseas sites?

Why the FTC even care? Marketing companies have been hiring bloggers to write reviews for years on sites like Pay per Post. My guess is the FTC is really less interested in protecting consumers and instead focused on brainstorming ways to help potentially generate more revenue for the US government and themselves. Its a laughable waste of tax dollars in my opinion.

NOTICE ON COMPENSATION: I received no compensation from the Wall Street Journal or the FTC for writing this blog.

Here is Micah Friedline with another screencast. This time it’s about The World’s Oyster, a self-updating address book. Stay in touch with friends, business contacts, and more with the easy to use address book that keeps itself updated as you move.