Tag Archives: Brain

Crystal Goh: Inside My Brain

Crystal Goh looks at brains every day, as part of her work in a brain and sleep imaging lab in Berkeley. She wanted to know how her brain was different from other brains, in a quantitative way. In the video below, Crystal explains voxel-based morphometry, normalization and standard deviation calculations, and the scary, revealing things she has learned about herself by seeing her brain scan! (Filmed by the San Francisco QS meetup group.)

Crystal Goh – Inside My Brain from Gary Wolf on Vimeo.

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Ryota Kanai on Quantifying his Brain

Ryota Kanai does brain scans for a living. He can assess a person’s intelligence level, personality traits, and social proclivity from these scans. He even did a study correlating number of friends on Facebook with brain structure. In the video below, Ryota shows a 3-D scan of his brain, highlighted with colors to show where he has more or less brain than average. He also answers questions about changes in brain structure and how to get a brain scan on the cheap. (Filmed by the London QS Show&Tell meetup group.)

Quantify My Brain from Ken Snyder on Vimeo.

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Matt Keener on The Brain and Self-Quantification: A Bidirectional Relationship

I had to post one more breakout session description for next week’s conference, because this project is so fascinating to me! Check it out, from brain researcher Matt Keener:

Our brains sit at the apex of primate evolution, making it possible for us to think, feel and be self-aware, all made possible through the unique development of specific brain regions and systems over a period of 65 million years. Neuroscience now suggests the “self” as emerging from the integrated workings of three distinct brain systems (limbic, cortical midline, and lateral fronto-parietal). The brain creates the self. Each of these develop through biology, culture, and training; each come with their own varied ways of representing the self, and each can be assessed through different means of measurement.

In my research I study how these brain regions cooperate to create a coherent sense of self, mediate the regulation of our emotions and how this goes wrong in mood disorders like Bipolar Disorder. Bipolar Disorder is a characteristic example of how brain and self interact. It is characterized in part by limbic hyperactivity and medial prefrontal cortex abnormalities. Accordingly we see wide fluctuations in one’s anxiety/energy as well as one’s social role and “self”-introspection. The disease wreaks havoc on one’s personality and the self will vary according to illness state, ranging from worthlessness and social isolation to grandiosity and a deep sense of accomplishment and personal agency.

There are various ways to treat this disorder, and a recent study done by CureTogether showed that several interventions relying upon self-assesment and quantification were reported to be of significant benefit, in this sample even moreso than most psychiatric medications.  These modalities like meditation and sleep regulation are not only reported as being helpful, but also have been shown elsewhere to result in functional and structural changes in cortical midline regions as well as limbic areas (for instance the medial frontal cortex and amygdala respectively). The “Self” creates the brain. The function of these areas would then be measured in very different ways if examining the body’s physiology and behavior.

So the self is the product of a brain, that is itself shaped by the actions of the “self”. Through a better understanding of the different brain systems that generate this sense of self, we can now begin to deliver the next generation of integrated self-quantification that may tap into these key brain systems in a more targeted, meaningful manner.

In this session we’ll briefly discuss the three basic brain systems involved in self-processing and talk about some examples of QS paradigms that tap into each. Then we can all discuss the future of cognitive and affective QS tools that can enable us to quantify the entirety of the self in a rational fashion, and in doing so better organize our own brains toward a fuller and more meaningful concept of ‘self.’

(The above image is from Elevated Amygdala Activation to Happy Emotion in Bipolar Disorder. Keener et al., Psychological Medicine 2012.)

 

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Jim Keravala on Mind Mapping

At our June Bay Area Quantified Self Show&TellJim Keravala of Flaii gave us a brief tour of the mind map he developed using TheBrain. He spends 1-2 hours a day entering information into his virtual brain, and has recorded about 65,000 thoughts so far. He feels that the main benefit he gets from it is enhanced recall, which has given him an advantage in business situations. In the video below, he reveals that he has become very attached to the system he uses and doesn’t like to be away from it for more than a few hours at a time.

Jim Karavala – The Brain from Gary Wolf on Vimeo.

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Bay Area QS Show&Tell #14 – Recap

BayAreaQS14.jpgThis was the scene two days ago, when the lower floor of the Tech Museum of Innovation in San Jose was opened after hours to an energetic group of Quantified Self enthusiasts and interested spectators.

The first 90 minutes was filled with mingling, enjoying healthy munchies, and gathering around the various devices that people brought to show as part of the theme this time: “Gadgets for Gathering Data.”

Then the talks began – some prepared, some spontaneous, all of them interesting. Here’s a quick recap:

1. Bill Jarrold showed his
hot-off-the-command-line charts for how many UNIX commands he issues by
hour of the day. He found that 3 pm was his peak performance in terms
of number of commands. A second peak at at 10/11 pm
showed him that he was a night-owl.  He was surprised to see that by
this measure, his productivity at midnight was as good as his
productivity at 10 am.

2. Jim Keravala of Flaii gave us a brief tour of the mind map he developed
using TheBrain. He spends 1-2 hours a day inputting information
into his virtual brain, and has recorded about 65,000 thoughts so far. He felt that the main benefit
this gave him was enhanced recall, which has given him an advantage in
business situations. He said he has become very attached to the
system he uses and doesn’t like to be away from it for more than a few
hours at a time.
 
keravala.jpg
3.
Bharat Vasan demonstrated his PulseTracer heart rate monitor, which
betrayed his pulsetracer.pngnervousness at public speaking by flashing a heart rate of 120 bpm on his wrist. He
described how this single measure served as an indicator of the
stressfulness of situations he found himself in, and helped him remember
to take positive actions he might otherwise have forgotten in the heat
of the moment.
4. Alex Bangs talked about his experience with Philips DirectLife, and dove into some beautiful bar graphs. He found that using
DirectLife since last October has increased his activity level,
especially when he sees large gaps in activity from sitting at the
computer, and when he gets little “light show” rewards from the
DirectLife on days when he’s met his target. He was surprised to find that
even these very simple rewards were consistently motivating.

Giving Thanks and Looking Forward

A huge thanks to our sponsors who generously helped make this event possible: Ron Gutman thankyou.pngof HealthTap, which is setting up a “Quantified Self Room” at their soon-to-be-opened offices in Palo Alto; the Tech Museum, who is collecting ideas for health exhibits as part of their “participatory museum” philosophy (send ideas for to Alana Conner); and Zeo, the Personal Sleep Coach, who provided healthy food and videorecording.

And last, but very far from least, a standing ovation to Maren Connary for help with setting up, Loren Risker for taking the videos, Andrew Hessel for the picture at the top of this post, and Robin Barooah – for augmenting my memory of the talks and for his meditation tracking app that I have come to love.

The next Bay Area QS Show&Tell will be on August 5, at Institute for the Future, sponsored by HealthTap and Google Health. Any requests for a theme during the opening mingling? How about Apps, as in: “Self-tracking. There’s an app for that.”

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Steve Brown on Augmenting Your Brain

Complete notes and reference links from Monday night’s terrific QS Show&Tell will be up later in the week, with an assist from Mark Carranza’s amazing idea archive. In the meantime, Steve Brown has shared the slides from his rapid-fire talk about 3banana. Steve had the misfortune of going last during an incredible, crowded meeting, and I’ve asked him to come back next time and go first, so he can have some time for back and forth with everybody. He has being working in this area for a long time, and I know there will be lots of questions.

Steve is the founder of a company called 3banana. He talked about augmenting the brain through enhancing working memory. When he returns, some QS folks may also want to ask him about his last company, Health Hero, a pioneer of self-monitoring that was acquired last year by the Bosch Group.

Thanks again to everybody who showed up on Monday night! 

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Measuring My Brain Function: One-Finger Typing

Noticing that flaxseed oil improved my balance led me to measure its effects on other tests of brain function.
It also made me wonder what else in my life affected how well my brain
works. Eventually I measured the mental effects of flaxseed oil with
four tests, but each had problems:

  1. Balance. Time-consuming (15 minutes for one daily test), not portable.
  2. Memory search.  Anticipation errors, speed-accuracy tradeoff.
  3. Arithmetic. Speed-accuracy tradeoff.
  4. Digit span. Insensitive.

“Speed-accuracy tradeoff” means it was easy to go faster and make
more errors. It wasn’t easy to keep the error rate constant. If I got
faster, there were two possible explanations: (a) brain working better
or (b) shift on the speed-accuracy tradeoff function. The balance and
digit span tests had other weaknesses. Only the balance test was
enjoyable.

I’m still doing the arithmetic test, which has been highly
informative. However, I want to regularly do at least two tests to
provide a check on each other and to allow test comparison (which is
more sensitive?). I tried a test that involved typing random strings of
letters several times but as I got faster I started to make many
mistakes.

I have recently started doing a test that consists of one-fingered
typing of a five-letter string. There are 30 possible five-letter
strings. Each trial I see one of them and type it as fast as possible.
15 trials = one test. Takes three minutes.

I am doing one-finger rather than regular typing because I hope
one-finger typing will be more accurate, very close to 100%. With the
error rate always near zero, I won’t have to worry about speed-accuracy
tradeoff. Another reason is the need for skilled movement and hand-eye
coordination. Doing this sort of task can be enjoyable. One-finger typing (unlike regular typing) is skilled movement with hand-eye coordination; maybe it will be fun.

I restricted the number of possible letter strings to 30 to make
learning easier. Yet 30 is too large to cause the anticipation errors I
might make if there were only a few strings.

Here are early results.

2009-06-14 one-finger typing early results.jpeg

So far so good. Accuracy is high. On any trial, it isn’t easy to go faster, so speed-accuracy tradeoff is less of a problem. Even better, it’s vaguely enjoyable. Doing the task is a little like having a cup of tea. A pleasant break. There’s no need to do the test four times/day; I just want to.

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Hey, What Happened to My Brain?

For a few months, I’ve been measuring how well my brain is working
using arithmetic problems. Each test session includes 100 simple
problems (3+4, 7-0, 4*8) divided into 5 blocks of 20. I type the last
digit of the answer as quickly as possible. I got the idea from Tim Lundeen, who got better on a similar task when he increased his DHA intake. My performance on an earlier version of this task was improved by flaxseed oil.

I’ve blogged about this. The virtues of this test include: 1. Fast. Takes only a few minutes. 2. Portable. Requires only a laptop. 3. Many possible answers (1, 2, 3, etc.). This reduces anticipation errors. 4. Many numbers (reaction times) per test. 
This allows me to get a measure of variability for each session and can
correct for the difficulty of the problem. Aspects with room for
improvement include: 1. Speed/accuracy tradeoff. Accuracy isn’t fixed.
Depending on how accurate I want to be, I’ll go faster or slower. (I
aim for 95% correct.) 2. No complex actions. The most enjoyable games
have a motor-skill aspect that this task does
not.

Here’s the data so far.3336375181_952054f435_z.jpg

The big gap happened because I moved from Beijing to Berkeley. The most
fascinating result, of course, is the sudden drop on February 2. Here
is a close-up.
3337207892_8d58294701_z.jpg
The drop was easy to notice. All of a sudden I was faster (and only
slightly less accurate). How sharp the change: On February 2 at 8 am I took the test; my
scores were roughly the same as they had been the past month. At 2 pm
the same day, I took the test again and was about 50 msec faster. (In
reaction-time experiments, a surprising 50-msec effect is huge.) I
remained faster for at least several weeks.

What might have caused this? The first test with better performance took
place while my landlady, who lives upstairs, was practicing piano.
Usually it’s quiet when I test myself. My first thought was that the
music had caused the improvement. But it persisted so long after the
music had stopped that the music couldn’t be the cause.

I moved to Beijing in October. Eventually I ran out of the Spectrum Organic flaxseed oil I’d brought with me and started drinking a Beijing brand called Joyful Organic.
When I returned to Berkeley I brought a few bottles of it with me and
continued to drink it. In late January I ran out; the evening of
January 29 I started drinking Spectrum Organic again. Four days later
my arithmetic scores sharply improved.

It’s really plausible that the improvement was due to the change in
flaxseed oils. Flaxseed oil had made a difference (versus nothing) with a very similar task.
A few weeks before the shift, a friend had asked how I knew if my
Chinese flaxseed oil was good; I’d said I’d find out when I switched
back to Spectrum Organic.

But why was the improvement delayed four days? I started studying
flaxseed oil because one evening I took several capsules and the next
morning noticed my balance was better. And if the improvement is going
to take that long, why would it happen so sharply after the delay? I
can’t even begin to answer these questions.

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Exercise for the Brain

[BrainExercise.jpg ](http://www.nytimes.com/2007/11/08/opinion/08aamodt.html?em&ex=1194670800&en=87671c1cea6447e9&ei=5087%0A)Brain training games are fun for every fan of self-optimization. We don’t like to play them, we like to point out how unconvincing the evidence is that they really help your brain. Today in the New York Times, two neuroscientists take aim at brain training. They guess that the effectiveness of puzzles and mazes in improving the mental function of laboratory animals may have something to do with the impoverished environment of the lab. “Animal enrichment research may be telling us something important not about the positive effects of stimulation, but about reversing the negative effects of deprivation.”

Sandra Aamodt, the editor in chief of Nature Neuroscience, and Sam Wang, a professor of molecular biology at Princeton, do discuss one type of exercise proven to improve cognitive performance: physical exercise. Aamodt and Wang run down some of the reasons physical exercise is recommended for people concerned to improve (or maintain) their intelligence: exercise is associated with reduced risk of dementia, and a slowing of age-related shrinkage in the frontal cortex; in rodents, exercise has been shown to increase capillary formation in the brain, and exercise is thought to stimulate the growth of neurons in the hippocampus.

But the best general source on exercise and the brain is this review article for the Journal of Applied Physiology, published last year. In it, Arthur F. Kramer,  Kirk I. Erickson, and  Stanley J. Colcombe review both human and animal studies. They begin their review with this paragraph:

MUCH AS BEEN WRITTEN OVER the ages about the benefits of exercise and physical activity. For example, Marcus Tullius Cicero stated, in 65 BC, that “It is exercise alone that supports the spirits, and keeps the mind in vigor” (41). Somewhat more recently, in the mid-1760s, John Adams, the second president of the United States, suggested that “Exercise invigorates, and enlivens all the faculties of body and of mind . . . It spreads a gladness and satisfaction over our minds and qualifies us for every sort of business, and every sort of pleasure” (14). Clearly, however, not all opinions from politicians, philosophers, writers and others concerning exercise and physical activity have been positive. For example, Mark Twain, a literary giant of the 19th century, expressed his disdain for exercise in the statement “I take my only exercise acting as Pallbearer at the funerals of my friends who exercise regularly” (36). Similarly, Henry Ford, the early 20th century industrialist and automotive designer, stated that “Exercise is bunk. If you are healthy, you don’t need it.”

The authors look at the whole scope of available research. They conclude that Cicero and John Adams were right; Mark Twain and Henry Ford were wrong.

In summary, the research reviewed in this paper highlights the positive effects that exercise has on the aging brain in clinical populations, nonpathological populations, and nonhuman animals. Although more intervention research is needed to further address questions related to the benefits of exercise, it appears to be the case that the benefits of physical exercise or physical activities promotes brain and cognitive vitality well into older adulthood.

If you want to explore the chain of research cited, here is a handy citation map.

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Nueromodulation: brain tuning in the lab

9V Batter.jpg
This [interesting blog](http://brainmagnets.blogspot.com/) by Dr. Topher Stephenson tracks the use of “neuromodulation” techniques, including electrical and magnetic stimulation of specific brain regions to produce desired changes in mood and behavior. This seemingly far-out technology is a major topic of applied research today, with new discoveries coming almost too fast to track.
In [this post ](http://brainmagnets.blogspot.com/2007/09/9v-battery-for-depression.html), for instance, Dr. Stephenson reports on a small, double blind [study](http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=1044804) of “transcranial direct current stimulation” of 40 depressed patients that showed significant results.
Among the most interesting things about these techniques is that they use weak electrical current. “All with a nine volt battery,” is Dr. Stephenson’s wry comment. “Maybe I should regress back to being a young kid and start licking batteries more often???????”
The possibility of altering brain states using weak electrical current raises the possibility of – eventually – self-modulation. This is not to say that the knowledge exists to drive our brains the way we pilot a little remote control car; only that the increased precision and decreased power demands of neuromodulation reduces risk tremendously, and makes it ever more likely that these tools will eventually leave the lab.
Among the many interesting links from the NueroMod Blog is one to [this piece](http://www.technologyreview.com/blog/boyden/) by [Ed Boyden](http://edboyden.org/) in MIT’s technology review. Boyden points out that even fairly precise stimulation of specific brain regions can produce a range of different effects, not all of which may be equally desirable. Boydon is among the researchers attempting to sort out these different effects, and identify what types of interventions can work under different circumstances. He is a thoughtful, interesting writer.
Excerpts:
>
> Consider the question of how you might augment cognition and mood by stimulating selected neural circuits. You’d probably want maximum flexibility — the ability to tune mood, decision-making, judgment, and so on, independent of one another. Researchers have attempted to alter cognitive functions by noninvasive stimulation of cortical brain regions, each a few cubic centimeters in volume. It’s become clear, however, that these brain regions are not the most elementary of brain circuit elements. For example, manipulation of one specific brain region can change many cognitive and emotional functions, in parallel. Consider the concrete example of [transcranial magnetic stimulation](http://en.wikipedia.org/wiki/Transcranial_magnetic_stimulation) (TMS) of the right prefrontal cortex. In the last few years, studies have shown that TMS of this brain region with a standard protocol (one pulse per second for 10 to 30 minutes) can [alter decision-making in the face of unfairness](http://www.sciencemag.org/cgi/content/abstract/1129156), [improve the symptoms of depression](http://archpsyc.ama-assn.org/cgi/content/abstract/56/4/315), and [increase risk-taking behavior.](http://www.jneurosci.org/cgi/content/full/26/24/6469) Thus, it may be difficult to induce a specific, desired brain state, without inducing other (perhaps undesired) brain states, when the primitives under consideration are all “brain regions.” Clearly, this convenient abstraction layer, which has been prominent across centuries of neuroscience, will need to be refined in order to develop a fully flexible architecture for cognitive augmentation.
>
> (snip)
>
> In our lab, we have begun to assemble a toolbox of methods for precisely controlling specific neural-circuit primitives. We are now using these tools to learn how to control behavioral outputs, with great precision and power. Hopefully, in this way we will learn what the neurobiological primitives are for engineering the brain and develop design rules for the optimal control of neural-circuit output, especially in disease states. We’re at an early stage. The synthetic biologists started off with the strong hypothesis that genes were the right abstraction layer. After all, the genome is fundamental, and DNA is easy to generate, manipulate, and read. But for neural computation, we don’t know what the DNA equivalent is. Are the primitives dendritic elements? Single neurons? Synaptic connections? Cell types? Small networks? Large networks? And at what nervous-system scales should we be reading? Writing?
>

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