Tag Archives: neuroscience

Ahnjili Zhuparris: Menstrual Cycles, 50 Cent, and Right Swipes


“I love reading random papers about the human body.”

Ahnjili Zhuparris came across a study on the menstrual cycle’s influence on cognition and emotion and was curious to see how hormonal changes may affect her day-to-day behavior. She figured her internet use may be a convenient and easy data set to assemble and examine for this effect. Using a few chrome plugins, Ahnjili was able to see not only where she spent her time online, but how she interacted with sites like Facebook and Youtube.

Her analysis yielded some interesting patterns. She found the most distinctive behaviors occurred during the fertile window, a span of about six days in the menstrual cycle when the body is most ready for conception. Looking at her shopping data from a clothing website:

 ”I found that there was no change in the amount of money I spent or the amount of time I shopped online… but while I was most fertile, I bought more red items. In fact, it was the only time I bought red items.”

In this talk, Ahnjili shows the differences in how she browsed Facebook, swiped in Tinder, and listened to music on YouTube.

Here are a few of the tools and papers that Ahnjili cites in her talk:

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What We Are Reading

We hope you enjoy these links, articles and other bits of interestingness we’ve found around the web over the last few weeks.

Taking the Guesswork out of Designing for Walkability by Xiongbing Jin & Fanis Grammenos: How should we design urban environments? In this article, the authors explore using agent-based modeling to test (a priori) what urban designs positively influence walking in a community.

The Quantified Brain of a Self-Tracking Neuroscientist by Susan Young: Russell Poldrack is a neuroscientist and imaging expert at the University of Texas. He’s currently in the middle of a massive self-tracking project which includes bi-weekly brain scans (MRI).

Blood Glucose Monitor Data Pushed to Smart Watch by Mike Szczys: This short post on the excellent Hackaday site introduces us to Don, an enterprising hardware hacker and diabetic. He’s spending some time attempting to send his blood glucose monitor data to his smartwatch and writing about it here.

Photo Lifelogging: Why I’m Skeptical by Peter Lewis: We’re moving quickly into a word with millions of wearable cameras. Peter, a QS meetup organizer, expounds on this trend and what what might happen when we’re all  able “ to censor — sorry, “curate” — [our] own photo streams.”

Home Tweet Home: A House with it’s own Voice on Twitter by Rachel Metz: The Internet of Things isn’t the future, it’s already here. Read about how Tom Coates has “wired” his home for constant data tracking and communication.

Personalized Medicine vs Guideline-based Medicine by Jeffrey Goldberger & Alfred Buxton: A short, but very interesting article that begins to explain the competing ideas behind the design and implementation of personalized vs guideline-based medicine.

Blood and Stories: How Genomics is Rewriting Race, Medicine, and Human History [pdf] by Priscilla Wald: “[If] we understand the power of the stories we can better understand the debates surrounding race and genomic medicine, which, in turn, can help us make better ethical and policy decisions and be useful in the practices of science and medicine.” (submitted by Whitney Erin Boesel)

(If you’re interested in more academic papers related to self-tracking and Quantified Self please join our Mendeley Group).

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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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Marcin Kowrygo on the Neuroscience of Ideation

Here’s another awesome breakout preview for the upcoming QS conference. Marcin Kowrygo, organizer of QS Poland, describes his session “Your Blue Room: The Neuroscience of Ideation”:


There is no more important meta-idea than knowing where every idea comes from. - Jonah Lehrer

Creativity is a vague term describing a complex phenomenon belonging to the group of humanity’s ultimate riddles. And just like with the terms consciousness and happiness, we may encounter two dominant groups looking at creativity: those satisfied with the true but not very enriching remark of “it’s the result of the brain’s activity” and those pointing towards a Bill O’Reilly-themed phrase “you can’t explain that”.

While modern neuroscience and bioinformatics are making a serious attempt to decypher the mysteries of our exceptional ability to connect X with Y in novel and useful ways, our self-tracking community can make inroads by testing the abundance of mental strategies, environmental changes, supplements, and brain stimulation techniques and quantifying the results.

During my session, I would like to present you a synthetic, integrative summary of various approaches in studying the neuronal and psychological mechanisms engaged in creativity. All in all, generating breaktrough ideas may be the single best thing we can do with our minds in the conceptual age. After that, I will be happy to share some of my concepts, and I look forward to a fruitful and productive discussion that would enable us to measure higher cognitive skills without being too simplistic.

Feel free to contact me, make suggestions and share your views. Failing big and upgrading “stolen” concepts is the key!

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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.
> 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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