Tag Archives: emotion
“How can I define what makes me happy and what makes me sad, what is good for me?”
In 2012 Benjamin Bolland was finishing up his undergraduate degree and working on a new start-up. He found that his moods were constantly changing and wondered if there was something he could do to make sense of them as they moved “up and down.” He began tracking his mood with an simple self-designed Google Form. Each day at 11AM and 6PM he reported his mood on a 1-10 scale and wrote a quick descriptive note. After 1.5 years of doing this nearly every day he realized that he didn’t really know what was making him happy or sad so he decided to update his Google Form to include a variety of different categories that he thought might affect his mood including physical health, sport participation, and many others. In this talk, presented at the Berlin QS meetup group, Benjamin describes his process and how he’s used this mood tracking process to be more reflective and mindful during his daily life.
Cliff Atkinson is a consultant who helps people tell their stories and showcase their data in clear and understandable ways. It’s no surprise that when he became interested in understanding himself he turned to his experiences with visual storytelling. In 2012, at a New York QS meetup, Cliff spoke about how he’s embarked on a project to “quantify the “unconscious.”
What Did He Do?
Cliff began this project because he was noticed that there were “recurring patterns of procrastination and motivation” going on in his life. He began trying to understand them by turning to the large body of literature on human psychology. Then he asked himself, “Would it be possible to use some quantitative methods to track what was happening.” Using what he’d learned in his research and his experiences he decided to track his body, emotions, and mind.
How Did He Do It?
Cliff used his expertise and knowledge around visual storytelling to create an interesting system of visual diaries with which he could record information in his three areas of interest: the body, emotions, and the mind. Using Penultimate, and iPad app for sketching and notation, along with some clip art, he tracked physical, emotional, and cognitive events.
What Did He Learn?
The process of creating a space to reflect and record how he’s feeling across these three chosen domains has created a space for Cliff to better understand himself and how his mind works. This is still a work in progress and it sounds like Cliff is still exploring how to better understand the data he’s capturing over a longer period of time and even correlating it with other information such as his work and speaking engagements.
“One of the models for therapy is that somebody else helps you. I think with the quantified self and the things we’re doing we can take some of that power into our own hand and start to come to some personal understanding of what’s going on in our own lives.”
Matt Dobson is working on automatic affect recognition, which basically means quantifying emotions beyond self-reporting. In the video below, Matt walks through the current technologies available to passively detect emotions, helpfully explaining things like galvanic skin response, heart rate variability, and speech tone. He also gives some hints as to where the future of emotion tracking lies. Matt, if you’re reading this, we’d love to hear what you have personally learned from tracking your own emotions! (Filmed by the London QS Show&Tell meetup group.)
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.)
Julio Terra, a grad student in the Interactive Telecommunications program at NYU, built MoodyJulio after increasingly noticing the role emotions were playing in his life. He wanted to correlate his emotional responses with physiological metrics, activities, and people in his life. It’s like a work in progress to see his emotional landscape in HD. Watch as Julio explores questions like how much power we have over our own emotions. (Filmed by the NY Quantified Self Show&Tell #10 at Google.)
Crowdsourcing Your Future is a postcard that you send to your friends to have them predict your preferable and probable future timelines, so you can take action to follow or avoid certain futures that your friends see for you.
Personal Microtrends is a daily diary that asks provocative questions and suggests behavior changes for the next day to continue or alter trends depending on your goals. Jessica says,
What if you could create a self-reflective diary that made use of
our everyday thoughts to provoke us in such a way that you were able to
change your future actions?
The Microtrend Diary
is a mirror of your daily actions and emotions that reveals provocative
ways to alter your future actions.
This personalised diary is printed to order based on a set
of preliminary personality questions. As the owner makes a daily record
of their actions, a unique set of provocative aide memoirs are revealed
under a perforated flap that suggest changing your behaviour in certain
ways for the following day.
Right now Jessica’s diary is just at the concept stage, but the idea of looking at microtrends in your daily life, based on whatever data you collect, could allow self-quantifiers to spot patterns and make any needed changes on a more granular basis. It’s like rapid prototyping for self-experimentation.
When I first wrote about my tracking
People thought I was narcissistic
What they didn’t see
The hatred behind the tracking
I had stopped trusting myself
Letting the numbers drown out
I was afraid
Of not being in control
Of becoming obese like my genetic predecessors
I was addicted
To my iPhone apps
To getting the right numbers
To beating myself up
My self-worth was tied to the data
One pound heavier this morning?
2 g too much fat ingested?
You’re out of control.
Skipped a day of running?
Didn’t help 10 people today?
It felt like being back in school
Less than 100% on an exam?
I’m starting to realize
That I need to
That I’m more than the numbers
That I’m beautiful, strong, and super smart
I don’t need data to tell me that
And I don’t need to punish myself anymore
Will I ever track again?
For a specific goal or experiment
Or to observe a pattern
I’ll try to keep an objective, non-judging eye
But then I’ll stop
When I’ve seen what I needed to see
And learned what I wanted to learn
Like any tool
Self-tracking can be used for benefit or harm
I won’t let it
Be an instrument of self-torture
How do you feel in different places? The precise correlation of location and emotional arousal is the topic of Christan Nold‘s long running biomapping project. The project used a simple galvanic skin response meter, which gives a reading of how excited you are.
A GSR device is simple. Here’s the Lego version.
These GSR readings are not very specific. They do not tell you whether you are disgusted, shocked, thrilled, or fascinated. But once Nold added GPS tracking, and invited people to annotate their readings, he could produce a map that correlates emotion with locations. This can be mashed up in Google Earth with contributions from others.
Nold’s device looks like this.
You can download a printable version of the San Francisco map (PDF). But, better yet, you can get the raw data (kmz) and load it onto Google Earth to browse. Right now this is an art project, a vision of the future, a hint of the utopian upside in surveillance and tracking.
Next step – getting my own version!
I want to become more rational. So do many people I know. But shouldn’t the quest for more rationality itself be conducted rationally, so that we can avoid damaging mistakes? We probably all know people whose Spock-like anti-emotionalism does not seem to correlate with very good decision making, people who show outward signs of being logical but who seem to miss important factors when calculating the probably outcome of events. That’s why I liked this recent paper (PDF) by Myeong-Gu Seo and Lisa Feldman Barrett, which shows how suppression of emotion correlates with poor performance in a simulated stock picking game. People who had a higher level of emotional intensity and who were able to report their negative emotions with greater precision performed better.
Why is this true? The authors theorize that, while emotions can bias decision making, the way to combat these biases is not to suppress emotion, but to notice it and regulate its influence. Something that is not consciously experienced cannot be consciously regulated.
So, an obvious question: how can we become more skilled and noticing and regulating the effect of emotion on our decisions? There are a range of instruments designed to put numbers on feelings. Many of them involve too much active self-assessment to integrate into daily life and real decision-making situations. But with the integration of self-assessment and automated assessment, the day is coming when we will have better reminders of how we feel.
“… the popular prescription for successful emotion regulation, “Ignore your emotions,” appears, in view of our results, not to be the right answer for effective regulation of feelings and their influence on decision making. Instead, the results suggest exactly the opposite: individuals who better understood what was going on with their feelings during decision making and thus reported them in a more specific and differentiated fashion were more successful in regulating the feelings’ influence on decision making and, as a result, achieved higher investment returns.”
“One additional finding in this study that also has an important theoretical implication is that people achieved the benefit of successful affective influence regulation from understanding and differentiating among their current negative feelings, but not from differentiating among positive feelings. This result was consistent with the finding in Barrett and her colleagues’ (2001) study that negative emotion differentiation, not positive emotion differentiation, led to greater self-regulation of emotions.”