Amyvid, a drug that binds to a marker for Alzheimer's disease, gives physicians a new tool with which to differentiate between normal (left) and Alzheimer's (right) individuals.

Pharmaceutical giant Eli Lily just got FDA approval on a chemical that would enable clinicians to detect a biological marker for Alzheimer’s disease. They can detect the marker now, but currently quantifying it can only be performed during autopsy. Detecting it early, during a person’s lifetime has the potential to not only identify people at risk for Alzheimer’s before they show symptoms, but it could help researchers searching for a cure.

The chemical, called florbetapir or its brand name Amyvid, binds to the protein, beta-amyloid, thought to be a hallmark of Alzheimer’s disease. The drug, which is radioactive, is injected into patients which are then imaged with a Positron Emission Tomography (PET) scan that detects the radioactive signal. A positive scan means there are at least a moderate amount of amyloid plaques, the aggregates of amyloid protein thought to disrupt neuronal function and lead to cognitive decline and dementia associated with Alzheimer’s disease.

Right now Alzheimer’s disease is diagnosed by individual physicians who detect cognitive and behavioral changes in the patient. But by the time behavioral changes are evident, scientists think, the disease is already very advanced. They think that the disease actually begins years before symptoms start to show. If there was a way to detect the disease, such as a PET scan that detects an increase in amyloid protein, doctors could identify high risk patients years before they begin to show symptoms.

Unfortunately, that won’t help the patients very much as there is currently no cure for Alzheimer’s disease. But the real strength of the test rests in its ability to differentiate Alzheimer’s patients who have amyloid with those who do not.

Between 10 and 20 percent of patients diagnosed with Alzheimer’s disease do not show abnormal levels of amyloid at autopsy. The cause of the disease may be different in these patients than in the patients with elevated levels of amyloid, and thus different treatments may be required. Conducting separate studies on these two groups could be a better way to finding a cure.

Researchers also estimate that in some communities a third of patients with mild symptoms but nonetheless have Alzheimer’s disease go undiagnosed. If these patients also show increased levels of amyloid doctors may be quicker to the diagnosis.

Deaths due to Alzheimer's disease continue to rise while falling for other major diseases (source: Alzheimer's Association).

Research seeking treatment for Alzheimer’s also stands to benefit from detecting amyloid earlier. Nowadays people have to already show signs of cognitive decline to qualify for clinical trials. The problem is, the damage is already done by the time outward symptoms begin to show. If it turns out that the amount of amyloid increases appreciably before they show cognitive decline, these people at risk to develop Alzheimer’s could be enrolled in clinical trials earlier. And clinical trials aside, just correlating the timing of amyloid increase to the onset of behavioral symptoms could help researchers understand how the two are related.

Amyvid adds to the recent growth of the Alzheimer’s diagnosis toolkit. Tests, shown to be extremely accurate in differentiating Alzheimer’s and normal individuals, are already commercially available to measure amyloid from spinal fluid. A bit less traumatic than a spinal tap, a blood test was developed last year that correctly identified over 80 percent of Alzheimer’s patients based on the levels of nine hormones and proteins including amyloid. And GE Healthcare is currently developing another PET approach that uses a different tracer to bind amyloid, [(18)F] Flutemetamol. Phase III trials for the drug are underway.

Eli Lily said Amyvid will be available this June in “limited quantities.” Side effects from the drug include headache, fatigue, muscle pain, and nausea.

Alzheimer’s disease affects 54 million Americans and is the sixth-leading cause of death in the US. It is a devastating disease, not only for the victims, but their friends and family. Last year unpaid caregivers gave an estimated 17.4 billion hours towards caring for Alzheimer’s patients.

A point that is unfailingly raised in discussions about diagnosing Alzheimer’s disease is the fact that there is no cure. The few drugs that doctors prescribe are only meant to treat symptoms by improving cognitive function or decreasing anxiety. There’s a lot of people who don’t want to know if they’re at high risk for Alzheimer’s disease if they know it can’t be reversed. Fair enough. But whether or not you want to know right now, when there is a cure for Alzheimer’s, it’ll be nice to know we have tools to detect it and detect it early.

[image credits: Alzheimer's Association and modified from Journal of The American Medical Association]
[video credit: Alzheimer's Association]
images 1 and 2: JAMA
image 3: Alzheimer’s
video: Alzheimer’s by the numbers

A brain scan of a 6-month old with autism showing abnormal neuron pathways (red and yellow).

Autism is normally diagnosed in children at around 18 months to 2 years of age, when parents see odd behavior and take their child to the doctor. Unfortunately, by the time outward symptoms are apparent much of the faulty brain architecture underlying autism has already taken form. Corrective therapies that last a lifetime are all too often powerless to reverse the damage that occurred in those first two years. But a new study offers hope that autism could be detected in children as young as 6 months old and give treatments that much more of a head start.

Researchers at University of North Carolina’s Institute for Developmental Disabilities imaged the brains of 92 children who were at high risk for autism. Scans were performed when the children were 6 months, 1-year, and 2-years old. At 2 years, the age when children are typically diagnosed, 30 percent of the children were found to have autism. The researchers then compared the brain images of the autistic children with the others. They saw differences in the brain’s white matter, the axon-laden pathways that transmit electrical signals to distant parts of the brain. Of the 15 pathways analyzed, 12 were significantly different between autistic and non-autistic children.

Autism remains a poorly understood disorder even after a century since it was first diagnosed.

Other researchers have performed an analogous experiment in which they monitored the growing infants’ behaviors in an attempt to identify tell-tale behavioral abnormalities, but as far as the UNC researchers are aware, they are the first to uncover brain imaging differences at such an early age. The study, which was published recently in the American Journal of Psychiatry, extends other brain imaging research that has shown that toddlers 2- and 3-years old have larger than normal brains and post-mortem measurements that show autistic adults have larger brains as well.

Autism is a complex disorder the biological cause of which continues to elude scientists. It’s main symptoms include impaired social interaction and restricted and repetitive body movements. We know it has a genetic component because two identical twins are more likely to share the disease than two fraternal twins. Although autism affects one in 110 children on average, children born into families with a history of autism have an almost one in five chance of being autistic. The children in the current study were considered high risk because they had older siblings who’d already been diagnosed with the disorder.

Treating autism, understandably, is a work in progress. Behavioral strategies such as placing the child in visually stimulating surroundings, speech-language therapy, physical therapy, medications and other therapies are used but no silver bullet has been found as yet. What is well established, however, is that beginning treatment early and intensively greatly improves the child’s chances of making progress. The promise of the current study is the possibility of beginning therapy long before outward behavioral symptoms begin to manifest themselves.

Not all are as hopeful. An issue being raised by some is the subject-to-subject variability in the study’s brain images. They question whether or not the differences in white matter between autistic and normal children will be robust enough in future diagnoses to overcome that variability. The study’s lead author, postdoctoral fellow Jason J. Wolff, acknowledged that the study is “preliminary” in a UNC news report. He also called it a “great first step” in uncovering a new indicator that could be used to diagnose even younger children.

Whether or not differences in white matter tracts will prove a useful to future diagnoses, it stands on its own as a discovery of the autistic brain. If clinicians don’t find the study useful, researchers surely will.

[image credits: UNC, Topnews]
image 1: brain scan
image 2: autism

Combining fMRI and a new computational technique researchers can scan a person's visual cortex and recreate roughly the movie they're watching.

Scientists at the University of California, Berkeley can now read your mind and project the images you think of onto a video screen. What sounds like science fiction may one day allow clinicians to “see” what a person in a coma is thinking, allow sleep researchers to watch dreams, or improve brain-machine interfaces that control robotic limbs.

Led by neuroscientist Jack Gallant, the researchers combined brain scanning technology with sophisticated computation to read their subjects’ visual minds. Functional magnetic resonance imaging (fMRI), which measures blood flow in the brain, was performed while three different subjects watched movie trailers from the Apple QuickTime gallery and YouTube. The scans focused on the visual cortex, the part of the brain that processes visual information. The first time the trailers were shown the computer simply recorded the corresponding brain activity. In this way it “learned” what the screen images look like in terms of brain activity patterns. The subjects were then shown a different set of movie trailers. This time the computer had to read the brain activity and try to “guess” what it was seeing. The computer then used a reconstruction algorithm of the 100 trailers most likely being viewed by the subject and merged them into a single display. The following video shows a subjects’ trailer alongside the computer’s best guess amalgam. I think you’ll agree that the match is pretty remarkable.

Because the computer is choosing from a group of already-made movie clips it is not actually reading brain activity and producing an image de novo – which explains the random numbers and other seemingly nonsensical imagery in the videos. That amazing feat still remains for future researchers to achieve. But using fMRI to accurately encode realtime motion pictures is already a breakthrough.

Although fMRI is routinely used to measure brain activity, it isn’t actually capable of detecting the activity of neurons directly. What it does detect are changes in blood flow within the brain. Because active neurons need energy, blood flow will increase in areas of high neuronal activity. fMRI has been a useful tool to neuroscientists, but one drawback is its low time resolution. Changes in blood flow can’t keep up with the much faster changes in the activity of neurons. This is why past attempts to produce images from brain activity have been mostly focused on still images. The major advance in the current study was to create a computational model that translates the fMRI signals into neuronal activity, rather than simply measuring the changes in blood flow.

Dr. Gallant thinks his advancements could lead to visualizing another, more mysterious type of movie. “This is a major leap toward reconstructing internal imagery,” he said in a press release. “We are opening a window into the movies in our minds.”

The authors of the report hope that accurately modeling dynamic thought processes could be used one day to help diagnose psychiatric disorders or provide the basis for brain-machine interfaces. “Our natural experience is like watching a movie,” Shinji Nishimoto, the study’s lead author, said in the press release. “In order for this technology to have wide applicability, we must understand how the brain processes these dynamic visual experiences.”

Earlier this year researchers at Washington University in St. Louis implanted a net of electrodes on the surface of patients’ brains that detected neuronal activity and transmitted the signals to a computer. With this brain-computer interface the patients were able to manipulate a cursor on the computer screen using just their minds. While the participants in the current study don’t perform any active manipulations, the study demonstrates that fMRI signals might do the trick. If so, it would be a major advance for mind-controlled prosthetic limbs. Because fRMI is non-invasive – as opposed to a sheet of electrodes across your brain – it can harmlessly be used to read signals from any part of the brain.

Of course, until they get a lot smaller, walking around with an MRI machine strapped to your head is not feasible. Nor is casually toting a magnet so incredibly powerful it turns paperclips into projectiles.

Regardless, combining the time resolution necessary to reproduce movies with fMRI’s global scanning capabilities, the technique could be soon be used to scan the more esoteric happenings inside a person’s brain such as their daydreams, emotional state, or intentions.

I can just see it now.

[video credits: gallantlabucb via YouTube]
video: Gallant Lab

(1) Emotiv EPOC wireless EEG headset (2) Receiver mod- ule with USB connector (3-4) USB connector and adapter , and (5) Nokia N900. (Right) Touch-based interaction with a 3D model of the brain using the smartphone .

Human brains are like wild animals, you learn more when you can watch them in their natural habitat. That’s why five scientists in Milab at the Technical University of Denmark (DTU) have combined the brain scanning power of the Emotiv EEG headset with a Nokia N900 smart phone. With their setup you can simply wear the Emotiv and the data from your brain scan will be processed and displayed on the phone in a cool looking 3D reconstruction you can rotate. The smart phone app will also give you information about your brain states and can of course pass your raw data onto a storage device or computer for further processing. Watch a short demonstration of the Milab Emotiv app in the video below. Emotiv’s brain scanning technology doesn’t provide nearly as much data as more complex EEG cap devices or fMRI, but the mobility could be a game changer. There’s much to be learned by observing brains in their natural habitat, and the Milab setup (or devices like it) may even help us monitor and treat patients with neurological disorders in their own homes.

While the following video doesn’t have any audio, it does step you through the basics behind Milab’s concept. The touchscreen on the Nokia allows you to interface with the Emotiv headset, clearly displaying your brain activity in a 3D model. The phone can also be used to provide stimulus (such as a picture, video, or piece of music) for simple studies on brain behavior. With multiple headsets and multiple phones you can track neurological trends in group settings in almost any environment:

The specs of the smart phone app are actually quite impressive. Able to handle all of Emotiv’s 14 channels simultaneously, the app can run for 7.5 hours with local logging of data or about 3.5 hours with remote logging. The 3D model is rendered at 30 frames per second, with only a 150 millisecond delay. The connection between the two devices is completely wireless, allowing you to freely use your hands or move in a small area without the need for portable power supplies, wires, or other encumbrances. On the whole, the system is really unobtrusive.

Which is entirely the point. A great deal of brain studies today are performed using wired EEG caps or by placing someone inside an enormous fMRI machine. In either case you have a very contrived lab setting that may well be influencing how someone thinks. Now, the control of a lab is very often necessary, but sometimes you’re going to want to see how a brain functions when a patient goes about their daily life. That’s where the Emotiv-smart phone setup could really come in handy. You can have dozens of people interacting in real world environments each with their own EEG headset recording their brain activity on their phone. Such studies would have less resolution in their data (14 channels isn’t a whole lot in the grand scheme of things) but that limitation is offset by the vast improvements you have in the experimental setup.

Outside of research, Milab’s approach to brain scanning could have a powerful impact on patients with neurological disorders. The Emotiv headset is small enough, and the phone certainly portable enough, that you could wear it for long portions of the day. Monitoring your brain states may provide insight into the onset of seizures, or allow you to correlate events with neurological effects. Hours of continuous recording will certainly give patients the ability to collect more data for themselves no matter what end that data is ultimately applied.

When Tan Le demonstrated the Emotiv headset last year, she heralded it as an opportunity for developers all over the world to create new applications for inexpensive EEG. Most of the projects we’ve seen arise involve using the Emotiv as a controller. This work in Denmark shows that there is an entirely other side to the Emotiv vision. With a cheap SDK (~$500) and cheap devices (each headset is about $300) Emotiv continues to open up brain scanning to a wide range of new possibilities. While this headset (and frankly all EEG) is limited in what it can record, I still hope we’ll see many other universities explore this technology. In the future when fMRI or other approaches become miniaturized, projects like Milab’s will be able to guide them into how best to apply their mobility to learn the most we can about our brains.

[image credit: Arkadiusz Stopczynski, Jakob Eg Larsen, Carsten Stahlhut, Michael Kai Petersen, and Lars Kai Hansen at milab DTU]
[video credit: milab via J.E. Larsen on YouTube]
[source: milab at Technical University of Denmark]

Currently, ASD is diagnosed behaviorally. There is a list of potential symptoms for autism in the DSM, and anyone exhibiting a certain number of these symptoms can be diagnosed. It’s up to parents or family members to recognize signs of ASD, and to have the child observed by a doctor – only then are they diagnosed. If MRI scans can be shown to rapidly and reliably identify the disorder, it will radically change our diagnostic criteria from behavioral to anatomical.

Researchers at the Institute of Psychiatry (IoP) used MRI scans to evaluate the structure, thickness, and shape of the cerebral cortex (i.e. the outer layer) in subjects’ brains. The study looked at three different groups of males: 20 subjects were healthy controls, 20 had prior diagnoses of ASD, and 19 were diagnosed with ADHD. Each group underwent traditional diagnostic methods first: they were given an IQ test, a psychiatric interview, a physical exam and a blood test. Then the subjects were scanned to see if there were biological correlates to their diagnoses.

The researchers found that ASD patients had special cortical features that allowed their brains to be distinguished from the other two groups. By contrast, ADHD brains could not be distinguished from their healthy counterparts. Because of the small sample size, researchers were unable to distinguish between distinct diagnoses along the autism spectrum (e.g autism vs. Asperger’s). Future research will be needed to determine whether the new technique can tease out diagnostic subcategories of the disorder – and whether the same technique can find these differences in childrens’ brains.

Check out the BBC report:

The disorders of the autism spectrum are poorly understood, to say the least. ASD is largely determined genetically, but the actual mechanisms of its etiology are unclear; it affects the organization of the brain, but in ways we don’t really understand. A 2006 study at Drexel University estimated that a staggering 1 in 170 children have some form of ASD; that figure is more than ten times the estimate given in the 1980’s. Are we diagnosing the disorder more consistently, or is it really on the rise? Again, we don’t know.

The research is certainly groundbreaking – for the first time, a biomarker has been associated with autism, which has always been diagnosed behaviorally.  Still, the work is in its preliminary stages, and won’t be replacing behavioral diagnosis anytime soon (though it will undoubtedly disrupt the DSM-5 revisions of autism’s definition).  The test doesn’t give binary “yes or no” results; instead, it plots an individual’s cortical structure in its relative distance from an average non-autistic brain. As Neuroskeptic notes in an excellent summary of the study’s methodology, it might not help diagnosis in borderline cases. As with behavioral symptoms, the anatomical results come in shades of grey – and that still means drawing a diagnostic line somewhere.

The 90% statistic is also misleading, as it indicates the sensitivity of the test rather than the positive predictive value. If we’re asking, “If I have autism, will the brain scan find it?,” the answer is an encouraging 90% “yes.”  But if we change the question to “If the scan says I have autism, do I have the ASD?,” that number plummets to something like 5%.  In a sobering critique of the study’s hype, Carl Heneghan writes in the Guardian:

Let’s think of 10,000 children. Of these 100 (1%) will have autism, 90 of these 100 would have a positive test, 10 are missed as they have a negative test: there’s the 90% reported accuracy by the media.

But what about the 9,900 who don’t have the disease? 7,920 of these will test negative (the specificity in the Ecker paper is 80%). But, the real worry though, is the numbers without the disease who test positive. This will be substantial: 1,980 of the 9,900 without the disease. This is what happens at very low prevalences, the numbers falsely misdiagnosed rockets. Alarmingly, of the 2,070 with a positive test, only 90 will have the disease, which is roughly 4.5%.

This would seem to limit the research’s application to improving diagnosis of suspected individuals, rather than screening the population at large. Still, the research is exciting, even without the hype: it represents the first time that a neuroanatomical difference has been identified in ASD, and that’s an exciting step towards better understanding a baffling disorder. More work lies ahead: the study needs to be replicated in women, and it remains to be seen whether cortical differences can be distinguished in young (i.e. developing) brains.

The statistical issues raise some ethical questions about replacing the behavioral diagnosis with a brain scan. What if you were diagnosed with autism based entirely on the structure of your cortex, never having exhibited any of its behavioral symptoms? Even the study’s authors recognize the complexities involved, e.g. research supervisor Dr. Declan Murphey: “Clearly the ethical implications of scanning people who may not suspect they have autism needs to be handled carefully and sensitively as this technique becomes part of clinical practice.”  If you have the brain features, but not the behavioral ones, do you have autism?

These questions will problematize the upcoming DSM-5 and its proposed revisions to ASD’s definition. Upcoming studies will undoubtedly put these results to the test, and it remains to be seen what their diagnostic utility will be. But an anatomical element to ASD is exciting news indeed, and should breed a wave of new research into the implications of an identifiable autistic cortex. Hopefully that will pave the way to new treatments for a disorder affecting so many, and one so poorly understood.

[images: DrJerm.com]

Are we ready to explore our dreams?

In the upcoming movie Inception, Leonardo DiCaprio plays a criminal with the technology to project himself into the dreams of others. The circumstances of the film seem utter fantasy – amazing special effects are a big part of the movie. Yet the proposed technology may be rooted in real science being explored today. fMRIs, EEGs, and CT scans are all being used to ‘read’ and even influence the brain. In their current incarnations these technologies are ill-suited to achieving the infiltration of dreams, but the fundamental science they examine could be setting the stage for exactly that. Watch the two full length trailers below to see the film’s visually stunning take on the possibility of invading someone’s mind. While you’re marveling at the imagery ask yourself: is the technology of today putting us on a path towards the world of Inception?

The basic premise of Inception, that a device would allow you to connect to a virtual environment composed by someone’s dreams, relies on two fundamental (and as yet undeveloped) technologies: 1) a means of reading the images, emotions, and sounds creating by the brain, and 2) a means of inputing data into the brain in such a way as to have it appear in the subject’s thoughts. Using these two mythical technologies you could write and read someone’s dreams or connect multiple minds together (in or out of a dream state). Both are very difficult requirements to meet, but the first is much closer to reality than the latter.

We’ve seen many different ways in which scientists are able to use current brain-scanning technologies to explore human thoughts, emotions, and behaviors. If you’ll forgive the dumping of self-referential links, here is a quick summary of the research currently underway:

fMRI is perhaps the most extensively used tool in current efforts of exploring the brain. Researchers have found they can use fMRI to predict some changes in behavior, match images to what your eyes are looking at, and communicate with patients in a permanent vegetative state. There is further research into if fMRIs could provide insight into when someone is lying, and how to distinguish between individuals based on brain activity. EEG scanners are much more portable systems and are available commercially. They have been used to understand which parts of the brain are being used to process an image, and this information can help categorize what you are looking at. Electrodes wired directly into the brain, such as those seen with Braingate, can read neuron signals and translate these into action, or even give a better understanding of what part of the brain is used for different tasks (such as language processing). Direct electrode connections have even had some success in translating brain activity into spoken words.

All of these attempts at ‘reading’ someone’s mind are still in the very preliminary stages. The most reliable use of brain-scanning technology is probably the use of an EEG scan to allow people with decayed motor skills to type on a computer. That’s pretty basic stuff. In fact, spatial and temporal resolution for fMRI and EEGs suggest that these technologies (in their current form) simply won’t have the capabilities of reading the brain precisely and quickly enough to ever be used to successfully connect someone’s mind to a machine. Electrodes may be much faster and more precise in some cases, but there’s a practical limit in how many wires one can place inside the brain without causing widespread damage. At least for now.

Taken collectively, these projects show that science is very interested in exploring the brain, and will likely continue to develop new means of charting its activities. Even with just the devices available today there is much more of our thinking organ that we can understand. That insight is likely to lead to being able to read the mind of a subject, at least to some degree.

Of course, while scientists are still struggling to ‘read’ the mind they haven’t even really begun to ‘write’ on it. The most reliable means of influencing the brain is still through direct stimulation of the senses. Instead of machines that place images in your mind, we are likely to first have sophisticated means of placing images in your eyes. Virtual reality goggles, and headphones may be the better bet of influencing the brain in the short term. (In fact, looking at the trailers for Inception, it’s unclear how much of the workings of DiCaprio’s unnamed device may involve some sort of VR headgear.) There have been some cases of scientists inducing emotions in patients via electromagnetic stimulation (the so-called God Helmet is perhaps the most famous example) but we’re unlikely to perfect these until well after we better understand how to read activity in the brain.

So could Inception become a reality? We’re certainly working towards it. In addition to all the research I mentioned above, the XPrize foundation is considering a reward for the next generation of brain computer interfaces. The BlueBrain Project is working on creating a full scale simulation of a brain to be used as a pharmacological and neurological tool. In the next few decades we could have the means to understand, perhaps in rather detailed terms, what a person is thinking. Once that barrier is passed we may develop the means to influence what someone thinks by directly stimulating their brain. For now Inception is simply a cool looking bit of science fiction. We should remember, however, that while the mind is still a very mysterious place, it may not remain that way forever.

[image credit: WikiCommons]
[video credits: Warner Bros]
[source: Warner Bros]

Brian Dugan's attorney used fMRI evidence during his sentencing for the murder of Jeanine Nicarico (right).

Magnetic resonance imaging has been hailed as a possible means of creating the ultimate lie detector. Yet the first publicized fMRI evidence admitted into a US court was not used to separate fact from fiction, but to prove that a murderer was a real psychopath. Brian Dugan was already serving a life sentence for two murders when he was indicated in the 1983 rape and murder of a third, Jeanine Nicarico. In July of this year, Dugan pleaded guilty to killing the young girl. During the sentencing hearings that followed, Dugan’s lawyer, Steve Greenberg, introduced fMRI scans as evidence that his client suffered from a clear case of psychopathy. While Dugan was ultimately sentenced to death, the jury’s 5+ hour deliberation of the case may indicate that fMRI scans could become an important tool for defense attorneys in the US legal system.

Greenberg’s expert witness was Dr. Kent Kiehl, a researcher at the University of New Mexico. Kiehl regularly performs fMRI scans on prisoners as part of his studies in psychopathy and moral reasoning. According to Kiehl, Dugan has 37 out of 40 markers for the condition, placing him in the 99.5 percentile. Yet the prosecution argued, with the help of its own expert Jonathan Brodie of NYU, that a mental illness such as psychopathy does not mitigate the results of Dugan’s actions and that a scan in 2009 could not accurately reflect the state of mind of someone in 1983. The jury deliberated for five hours, notified the judge that they had reached a decision, but then asked for more time. Following a sequestered night, the jury met again before delivering the death sentence. The jury, before returning for further deliberation, was originally looking to give Dugan a life sentence, so Greenberg is seeking an appeal.

While PET scans, and brain abnormalities have been used in cases before, this is the first time that a fMRI scan has been admitted as evidence of a defendant’s mental or moral state. Of course, sentencing hearings in the US are less strict than trials in the admission of evidence. We are a long way away from knowing if fMRIs can be accepted as proof that a defendant (or witness) is lying about an event.

[photo credit: Sun Times]

A researcher, Adam Wilson, sent a tweet using BCI2000 software and an EEG.

Usually wearing a silly hat and staring at the computer doesn’t do anything besides make you lonely, but now with BCI 2000, that’s going to change. You’ve probably seen some of the really great videos of researchers playing pong, typing words, and controlling robots using just their thoughts. But did you know that they all relied upon the same software program to work? Brain Computer Interface 2000 is a software tool that facilitates reading brain signals in real time. That means EEGs and ECoGs can work better and faster. Why do you care? BCI 2000  lets you control computers with your mind. Someone even posted a tweet using BCI2000 and an EEG! Check out all the cool vids after the break.

Based out of New York and the University of Tubingen in Germany, BCI 2000 is helping make progress in a variety of institutions. The cool videos we have here all show how their software can be used to facilitate controlling computers, but the technology has a little more depth than that. Scientists can use BCI2000 to improve the clarity in their biosignal processing, and make rapid strides in their research. In fact, BCI 2000 has an open license so that those in academia or research centers can utilize it free of charge. Of course, generosity, as cool as it may be, isn’t quite as entertaining as watching someone play Spaced Invaders with their cerebral cortex.

You’ll notice that in each of these videos the controls have been simplified considerably. Typically the user is only required to control a single icon on the screen, and never in more than two dimensions. It’s also unclear what kinds of thought the test subjects are thinking. EEG and ECoG scans can focus on a wide range of neural activity: upper level thinking as well as motor neurons. There’s no guarantee then, that BCI 2000 let’s you control a robotic hand the same way as you control your own hand.

Compare this to the Braingate interface we’ve discussed before, which directly reads motor neuron signals, and is intuitive enough for use by monkeys. Of course, Braingate requires major surgery to install a chip on your brain, while BCI 2000 just requires you to wear a surface scan array. The less invasive procedure would certainly be more popular if it could provide the same level of resolution. We’ll let you know more about how these two techniques stack up to each as we learn more.

Part of the problem with evaluating BCI2000 is that it’s not tied to any single research. There have been many successful uses that simply involved better data analysis. Then again, it’s helped guide a robot dog (see below). More than 35 scientific papers were published last year that involved using BCI 2000 in some form or another. In the end, however, BCI 2000 isn’t thought-control technology, it’s just thought-analysis technology that’s occasionally been put to that use.

Which is still pretty cool. There’s only so many times I can watch people move cursors with their thoughts before I get a serious case of envy. I can’t wait until BCI 2000, or some other software tool, becomes sophisticated enough to allow three dimensional control and direct one to one mapping between thoughts and actions. Guiding a cursor to help direct a robot dog is neat, but there will come a day when the robot could follow your thoughts just like your hands or fingers do. Brain computer interfacing is developing rapidly, so go ahead and find yourself a silly hat. It will come in handy soon.

How could they actually read your brain? What kind of patterns would they use to authenticate your identity? Yeah, that haven’t quite figured that out yet. HUMABIO is still definitely in the “pre-commercial” and “proof of concept” phase. They do have a nice ethics manual to read, and they’ve actually written some “stories” that illustrate the uses of their various works in progress, but they haven’t produced a fieldable instrument yet. In fact, this aspect of the STREP (Specific Targeted Research Project) would hardly be remarkable if we didn’t know more about the available technology from other sources.

Singularity Hub has been keeping at the forefront of brain scanning news. From fMRIs being used as lie detectors and mind readers, to robots being controlled by thoughts, we’ve seen a lot of new tech that could be adapted to provide biometric data. Each method relies on scanning the brain and monitoring electrical signals or blood flow to “read” someone’s mind. Each brain has its own unique patterns, as well as common signals. Monitor a brain enough, and you should be able to distinguish it from other brains using a scan. The big question is, is this technology really going to be the final frontier in security checks?

Ok, but what I am thinking now?

There are a lot of competing technologies out there (including reading your ear). Many of which are also being pursued by HUMABIO. For its part, the UK’s Foreign Office is seeking to spend more than £15 million on facial, fingerprint, iris, and vein-palm recognition to help secure its embassies around the world. The FO has also said such technology would be used to enhance “surveillance” and “data collection” for various purposes. Am I the only one who wants governments just to drop the euphemisms and say “spying”? I’d be satisfied with “intelligence gathering”.

The truth is, every government agency in charge of security is really fighting two fights: identifying/verifying its own people, and cataloging/marking likely threats. The technology used for one is readily adapted to serve in the other. More so when that technology is passive and unobtrusive as so many of these security check projects hope to become. The U.S. Intelligence Advanced Research Projects Authority (IARPA doesn’t have the same ring as HUMABIO) is seeking to ramp up its non-contact security checks with greater funding and new research.

Non-contact is one leg of the tripod of biometrics, the other two being 100% reliability and user acceptability. The big problem is that no one check (brain scan, iris scan, fingerprint, etc) is going to be 100% reliable or acceptable. Most of the relevant agencies (especially HUMABIO) are seeking a multi-tiered approach.

Could you find a way to fool a fingerprint scan? Sure, just watch Mythbusters to see how. Iris scan and voice scan defeats are probably on their way as well. But defeating a voice scan and an iris scan while simultaneously passing a brain scan? Much more difficult. And that’s a large part of what HUMABIO is attempting: layering biometric checks, hopefully in a way such that defeating one makes you more vulnerable to being detected by another.

Despite the lack of a commercially available system, HUMABIO has managed to run three successful tests of combined biometric security checks. A freight truck simulator used EEG (brain scan on scalp) and ECG (heart rhythm) monitoring, face recognition cameras, voice checking microphones and a sensing seat to verify the driver’s identity. A pilot security check used gait monitoring (they actually can identify you by the way you walk - the Bee Gees were right!) as well as face and voice recognition. The laboratory trial identified scientists using EEG, ECG, face and voice recognition. All three trials were shown to be effective and, just as importantly, were acceptable to the users. Even truck drivers didn’t find the security checks to be overly annoying.

Big Brother or Oh, Brother

For biometric tests to be successful you need to understand when they stop working. Voice recognition probably won’t work on someone weeping. Most gait measurements require you to walk at a steady pace. HUMABIO is aiming to understand these thresholds much better so that they can clue in one test to take over when another is unlikely to work.

And this is where I think the technology gets scary. The research that leads to us understanding when someone is too emotional or too stressed to pass an ID check will also enable us to identify those emotions on their own. That is, the same scanner that is trying to identify your face may soon be able to say “that guy looks upset” or “that guy looks like he’s going to kill someone.” HUMABIO is actively focusing on these ‘dynamic definitions’ of the test’s thresholds. The brain scan that is simply there to identify you, or the voice recognition that is supposed to give you access to your computer, may also be recording how you seem to be feeling. Which would be very useful when stopping terrorists from bombing an airport, but is a little intimidating for the general public.

This gate at Manchester Airport scans faces to make sure they match new UK passports.

That general public, however, is getting younger and more used to invasions into its personal life. In fact, the age of facebook and twitter actively encourages us to make our private lives public as a way of controlling the decline in privacy. As biometric security checks become more advanced, they will be able to learn more about us in a few seconds than people could learn on their own in years. That trend has started and will continue to grow even in the face of the public’s discomfort.

UK’s Home Office is already ramping up its biometric security checks. They plan on having ten more face-recognizing gates in the UK airports by August. Right now, the newest British passport holders traveling through Manchester or Stansted are being face-checked. As we seek to have a more secure society, the biometric tests are going to become much more common. When brain scans become reliable biometric tests, we will all experience them as we travel. While those machines read the blood flow and electrical pulses in our head, it’s important for us to remember our IDs are also our thoughts. Is the temporary loss of privacy going to be worth the benefits of security? The question may take a philosopher to answer.

For those without the time or interest in watching the entire video, a short summary:

1.  Put someone’s head in an fMRI machine and we can tell with increasing accuracy:

• the object they are thinking of (hammer, window, etc.)
• determine whether a person has seen a location before (such as a crime scene) by showing them a picture of the scene and monitoring them under fMRI
• extract certain macro thoughts such as lying, love, etc

2.  Court cases seem soon to come in which the legality of mind reading for lie detection and other uses will be confronted

3.  They’re trying to develop now a beam of light that would be projected onto your forehead. It would go a couple of millimeters into your frontal cortex, and then receptors would get the reflection of that light. And there’s some studies that suggest that we could use that as a lie detection device, or perhaps even thought detection device without you even knowing it was happening.