How I spent my winter break

Academia provides ample breaks (even though the work is never done).

I choose to spend this winter break "sharpening my saw" by improving my typing ability and learning a new computer language.

Improving typing is simple but not easy, any program or class will work. It is developing procedural expertise, you will get better if you receive immediate feedback and practice copiously.

The harder, more interesting project was learning Python. I have massive sunk cost in MATLAB programming. However given my move into web-based research, I need a language that is designed for where I am and where I want to go. Python appears to have the best return for minimal investment. "Learning Python the Hard Way" was the first step in my journey.

The magic was stopping the "doing" of work and pairing the two projects. Temporarily pausing other projects provided focused blocks of time to learn. Also, freely oscillating between cognitive and procedural challenges kept both fresh.

Biohacking lessons

I gave my final lecture for Sensation and Perception at Catholic University of America. The entire course was an amazing experience.

I ended the class by profiling "biohacking." Biohacking is a logical bookend, circling back to transduction and discussing a possible future direction for sensation and perception.

As a bonus, I was able to share an life-changing idea - Pick yourself to make the world a better, more interesting place. No one assigned the people in video biohacking as a requirement for a course. Independently, they leveraged the available resources to make a meaningful contribution to their own and others' lives. I hope the same can be said about my course.

Jerry Colonna on the "Good Life"

Excellent insights into modern work with a practical approach to manifesting them.

Why are you doing what you are doing?

I know my actions (including reading and responding to email) should be help me fulfill my life purpose - "Grow & Give." If I take too many actions that are not consistent with my purpose, it is time to calibrate. Sometimes I lack the awareness that I should recalibrate. Other times I lack a method to recalibrate. It is helpful to be reminded of the possibilities for both.

"Building Better Models in Cognitive Neuroscience" talks

Building better models in science is a personal passion. I think we live in a time of revolution. Our ability to understand the brain and, in turn, use those insights to understand cognition and behavior is growing at an exponential rate. Cognitive neuroscience models need to keep pace to leverage those insights. Additionally, we need to use more rigorous methods to build those models. I gave a series of talks about the approach I choose to use in "Building Better Models in Cognitive Neuroscience."

You can check out the slides for Part I here, based on Ashby and Héile, 2011.

You can check out the slides for Part II here, based on Ashby, Ennis, and Spiering, 2007.

The publication RSS water torture

Drip. Drip. Drip.

There is always something new to read inorder to keep current in a scientific field.

I could try to drink it drop-by-drop or I could let the glass fell up.

Part of my work is drawing connections between separate streams of research and design ground-breaking research, both of which require prespective. The latest and loudest of any field rarely includes prepective.

Supplemental Materials Made Easier

I am methods-based scientist. I initially seek a thorough understanding of a study's method. From that understanding, I can put the data and narrative in a context.

Journals are increasingly putting methodical materials in separate supplemental sections, but they do not make it frictionless to assess that material. Several high quality journals do not hyperlink directly to the supplemental materials for a paper. By direct hyperlink, I mean the specific figure or table hosted on its own page (not a zip file). Direct hyperlinking is straightforward for both the html and pdf versions of a paper.

Server space is cheap; Use it to reduce friction in science.

Publication: Implicit and explicit categorization- A tale of four species

I am proud to present my latest publication - "Implicit and explicit categorization: A tale of four species"

Abstract: Categorization is essential for survival, and it is a widely studied cognitive adaptation in humans and animals. An influential neuroscience perspective differentiates in humans an explicit, rule-based categorization system from an implicit system that slowly associates response outputs to different regions of perceptual space. This perspective is being extended to study categorization in other vertebrate species, using category tasks that have a one-dimensional, rule-based solution or a two-dimensional, information-integration solution. Humans, macaques, and capuchin monkeys strongly dimensionalize perceptual stimuli and learn rule-based tasks more quickly. In sharp contrast, pigeons learn these two tasks equally quickly. Pigeons represent a cognitive system in which the commitment to dimensional analysis and category rules was not strongly made. Their results may reveal the character of the ancestral vertebrate categorization system from which that of primates emerged. The primate results establish continuity with human cognition, suggesting that nonhuman primates share aspects of humans' capacity for explicit cognition. The emergence of dimensional analysis and rule learning could have been an important step in primates' cognitive evolution.

You can read more here.

Maryland Neuroimaging Retreat November 12

I will be attending the Maryland Neuroimaging Retreat in Baltimore on November 12 (Yes, that is a couple of months in the future, but I am a planner).

If you are attending and would like to meet up for coffee to discuss research, please send me an email.

Teaching Sensation and Perception Fall 2012

I am honored to be invited by the Department of Psychology at The Catholic University of America to teach Sensation and Perception for the Fall of 2012.

Sensation and perception is one of my favorite topics, sitting at the intercetion of cognitive psychology, neurosicence, cluture, and personal experience.

One of my goals for the class is reimagining the instruction of sensation and perception. Sensation and perception is a complex, inherently dynamic topic, and its instruction should reflect those properties. I am updating the curriculum and bridging the gap between the tradiational classroom and Khan Academy-style learning to best serve my students. Those aims are reflected in my syllabus. I am excited to leverage cutting-edge online resourses, such as the video below.

Asking a Better Question in Neuroscience

The mysteries of the brain are often taken for granted. The average person (and their billions of neurons) is amazing system that adapts to a complex world in quickly and effortlessly. We are still at the first stages of understanding the neurobiology of healthy systems.

However neuroscience chooses not to expolore those everyday mysteries, instead choosing to focus on disfunctions, disorders, and diseases. Those mysteries are no less interesting but have limited application. Successful breakthroughs in the neuroscience of disfunction, disorder, and disease could directly help hundreds (perhaps thousands). Succesful breakthoughs in basic neuroscience could directly help millions (perahaps billions).

That distinction makes my research choices easier.

Idea List & Hit List

For every project I have two running lists: an idea list and a hit list. I sperate thinking (idea list) from doing (hit list).

An idea list is an inbox for a specific project. It welcomes all, without critical evaluation.

A hit list are the next actions for a specific project. I take ephemeral elements from the idea list and transform them into the physical reality of action. Since a hit list is commitments (to myself), it stays short (with lots of critical evaluation).

Externalizing my thoughts and furture actions allows them to be more easily tweaked and changed.

The concepts are most important but there are tricks & tips - these lists are text files synced via Dropbox. That means I can work anywhere and anytime, not in the frantic workaholism but in a reckless joy.

Neuroscience as Frontier

Universally, the frontier is a place for explorers, pioneers, and settlers to change and be changed.

I put my money (and time and attention) on neuroscience as a science frontier of my lifetime.

I have been changed by my explorations of the neuroscience frontier. Given the pace of change in the field, I developed the ability to modify previously held beliefs. Given the range of topics that could influence a project, I developed a basic working knowledge in many academic fields (from neuroanatomy to applied mathematics). In order to ask the questions worth answering, I took the time to develop deep expertise in a narrow specialty.

Those abilities also enrich my life outside of science.

Advice to young scientists: E.O. Wilson on TED.com

This video rings true for me.

Even though I am trained as a computational cognitive neuroscientist, my math skills are not strong. I routinely apply linear algebra to solve problems but have flunked out of the formal class!

While training young scientists, I try to spark a curiosity for understanding the world, followed with rigorous, systematic investigation.

As I make my own transition from young scientist to young investigator, I am seeking a niche to make my a contribution. One possibility is the study of category learning via magnetoencephalography (MEG). It is a small field. There is only one other person conducting similar research (to the best of my knowledge). Despite its size, it is ripe with possibilities. The ability to study brain signals on the order of 100ms has the potential answer long-standing questions about this fundamental human capacity.

The Power (and Limit) of Networks

Metaphors matter - They shape the nature of inquiry by limiting the questions worth asking. If you choose a tree as your metaphor, you will look for simple, linear connections. If you choose a network as your metaphor, you will look for complex, but-still-linear connections.

Right now, the problems worth solving are nonlinear. We need nonlinear metaphors.

Builders & Testers

In athletic training, there are builders and there are testers. 26.2 miles is the tester for a marathon. Putting in the miles everyday is the builder.

In research, finished projects are the testers. Ideas (supported by emprical data) are put into the world. They are sometimes accepted, more often rejected.

At the begining, just completing projects builds towards better projects (i.e., testers and builders are the same). But then something more needs to happen to improve.

I am not sure what are the best builders for research. Could it be books, workshops, conferences, or having lunch with better researchers? I am trying all of them and will let you know when I find the right combination,

The Space for Magic in Science

Whiteboarding is cheap, almost free.

Yet experimenters rush new experiments from the whiteboard into data collection, only to thrash during analysis. "It would be groundbreaking if we did ________ analysis." But alas, the design does not support it.

Try letting an experiment linger unfinished on the whiteboard a little longer.

Something magically might happen in that space.

How to look inside the brain: Carl Schoonover on TED.com

It is amazing how far and fast neuroscience has developed in the last 100 years. This talk reaffirms my passion to explore one of the most important frontiers of human knowledge. We are in the golden age of neuroscience, and I strive to make my meager contribution everyday.

Additionally, the beautiful, powerful images in this talk are examples of "Science as Art." I am off to track down more prints for my office.

Best Practices for Science

There are a plethora of best practices for business books.

I cannot find any best practices for science books.

Hmmm ...

The Assumptions of Academic Hierarchy

It is assumed someone who can:
• Achieve high grades can conduct novel research

• Conduct novel research can teach effectively

• Teach effectively can lead a research team

• Lead a research team will be skilled at administration

In my experience, those assumptions are violated more often than they hold.

A Critical Look at Presenting Science: Daniel Poppel

Daniel Poppel's talk is a tour de force of presenting science - equal parts wit, clarity, brevity, and humility.

A good example of presenting data can be seen at 9:12. On the top panel, he presents groups means with error bars and a best fit line. The x-axis is tone frequency in Hz, therefore assuming interval scaling is more likely to hold. On the bottom panel, he shows data for individual trials with error bars. Then he goes one step further by presenting individual participants' data with error bars. The audience can decide at which level the data should be averaged, if at all. Remember: not all data should be averaged.

Those three graphs provide the audience with the information needed to make their own informed decisions concerning the validity of his conclusions.

A Critical Look at Presenting Science: Patricia Kuhl

I had the privilege of attending the 2012 McGovern Institute Symposium "MEG: Applications to Cognitive Neuroscience." The symposium covered the breadth and depth of magnetoencephalography (MEG) research. The majority of the talks were brilliantly presented, well-done science. There was one talk, despite being well-received by the audience, which did not live up to rigorous scientific standards.

Patricia Kuhl's talk is rife with scientific peccadilloes. The figure presented at 24:19 is a one of the best examples. The complete absence of error bars is the greatest error of omission. Variance is a critical element in understanding mean differences, and the audience is not given that information and is unable to draw their own conclusions concerning the significance of the mean differences.

In addition to that error of omission, there is an error of commission. Dr. Kuhl drew a straight line between the groups in the graph. She is assuming, with no justification, interval scaling on the x-axis. Why can we assume distance between 6-8 months and 10-12 months is the same as the distance between 10-12 months and "adult"*? When in doubt, a scientist should assume the lowest scale of measurement. It is better to assume ordinal scale when comparing these groups, thus making a bar graph appropriate. Just because you can draw a line between data points does not mean you should.

There needs to be a high standard for the presentation of scientific findings in all contexts. It is the responsibility of fellow scientists to uphold that standard.

* It is unclear what "adult" means in this context. It is a chronological or developmental definition? How was it operationalized?

Best (but not right)

All models are inherently wrong.

They can never match reality. The distillation of reality is their power and their limitation.

Therefore the goal is not to find the right model but find the best model for a given context.

A Case Against Bayesian Neuroscience

Bayesian inference is a powerful methodology but can be over-extended. Above is an example of over-extending the Bayes framework to neuroscience. Given its power, Bayes inference can easily account for behavioral phenomena, but it does not provide a plausible neural mechanism. There are no Bayesian neurons or areas in the brain.

Starting with the underlying architecture of the brain (i.e., neurons, synapses, and neurotransmitters) puts  neuroscience on a path to develop more robust models. Models built from the underlying neural architecture of the brain would be more complex than the simple elegance of Bayesian models but provide the opportunity for deeper insights into real brain processes.

The Best Use of My Time

It is the common, easy path to let others govern minutes. Check-in with my boss for a quick task. Check email and shoot a quick response. Peruse a social media website. There will always be someone else available to dictate my next action.

Those minutes add up to the hours of the week (and months of the year).

At the end, I have to stand true for my time.

Like most aspects of life, it is better to the opposite of what is common and easy. I reverse engineer time management. What do I want true in one year? Then, how do I spend the next minute to get there?

Free Range Model Comparisons

Comparing models is fundamental to all science, for example, Newtonian vs. Einsteinian (Physics), Uniformitarianism vs. Catastrophism (Geology), and Specialized vs. Generalized brain areas (Neuroscience).

Model comparison implies your current patterns of thoughts (i.e., a paradigm) could be replaced with different patterns of thought that better fit the world-as-is (i.e., the data). Just opening the door to that possibility is powerful (and scary).

Imagine a world with that potential for openness in all aspects of life.

Design Patterns in Science

Design patterns are reusable solutions to commonly occurring problems within a given context. For example if I write a computer function to present a stimulus, I reuse that function in all future experiments.

The same heuristic can be applied to other recurring problems in science, ranging from lab maintenance (e.g., having a current consent form) to creating sustainable lab culture (e.g., training new researchers).

It worth spending time to create and maintain the infrastructure to solve a problem only once. As I create a deliverable, I also create a separate file of notes and steps that enabled me to solve the problem. My design element kit includes both the final product and production capacity elements.

The real art is applying the same design patterns across problems and projects.

My New Postdoctoral Fellowship

I am delighted to announce my new postdoctoral fellowship with Thomas Carlson at The University of Maryland.

He has assembled a dynamic team to conduct ground-breaking research in object recognition vision science. I look forward to contributing to it. The position is a great platform to continue my life mission - researching and sharing neuroscience. The first step is transitioning my previous category learning paradigms to a categorization paradigms, a distinction with a difference with regards to the questions worth asking. I will be expanding my neuroimaging toolbox to include magnetoencephalography (MEG).

If you are in the same neck of the woods (either physical location or research area), drop me a line.

When to hold fast and when to scuttle

There are two kinds of research mistakes: A mistake that scuttles a project and all the rest.

An inherent design confound could end a research project. In category learning research, participants respond to stimuli with motor movements. It is hard (but impossible) to get a response without a motor component. The category learning paradigm includes all the processes associated with motor responses. Any project that wants to look at category learning orthogonally to motor responses is dead in the water.

All other mistakes do not stop a project unless you let them. The worst case scenario is more pilot data than you intended to collect.

An example of a mistake that appears stops a project is discovering someone has published a similar study. Many people scuttle projects at this point. I do not. I now have the opportunity to be a artist and create something more interesting within already proven paradigm.

Pick the right fight the education revolution

While developing materials for my fall class, I am modeling other classes that have leveraged current technologies (e.g., ubiquitous and asynchronous access to information).

However, the world-as-it-is-now lacks many of the resources to easily and successfully bridge the gap between the predigital classroom and a classroom that maximizes current technologies.

It is the classic trade-off between production and production capacity. My primarily mission is producing a great class, regardless of digital integration. During the course of the process, I will increase my own technology production capacity and possibly do the same for future classes.

One example of raising the production capacity of university education is profiled here.

The Heart of Science

There is a cottage industry of popular press articles, blogs, and podcasts that rehash findings from scientific journal articles. While constructing those narratives, the ambiguity and nuisance of science is airbrushed. The wrinkles of low sample size are lessened. The birthmarks of confusing correlation and causation are removed.

The same happens within scientific journal articles. The introduction and discussion section construct a narrative around the facts and figures of the method and the results section. The rough edges of confounds and raw data are smoothed over.

The heart of science lies within the method and the results section.

When trying to understand the science of any topic, eat the raw heart first.

Improving at the Craft of Scientific Writing

On my continuing quest to improve my writing ability, I stumbled upon these nuggets.

Start with the second link first - "Techniques for Clear Scientific Writing and Editing." The six principles and pithy examples are my Elements of Style.

"Say it Simply: Tips for Clear Writing" shows complex original scientific sentences and the improved versions. Most vitally, it explains the rational for the improvements.

Book Suggestion: My Stoke of Insight

I just finished My Stroke of Insight by Jill Bolte Taylor. It is an informational and inspiring read for anyone interested in the brain and effects of stroke.

Jill gives the best basic introduction to brain anatomy and function I have read. She makes a complex topic as simple as possible, but never simplistic. She recognizes the separate features and functions of the two brain hemispheres to create our coherent conscious experience. She suggests methods to maximize each of them separately. That concept is also presented in this book - Pragmatic Thinking: Refactor Your Wetware.

The book is equally inspiring. She uses her traumatic event as a catalyst to change the meaning of her life. The books opens a door into alternative ways of the perceiving the world, without being dictating the precise path.

On a personal note, my mother had a stroke 10 years. The book provided me insights into what she went through during the event and on her recovery path.

I am so enthralled with the book I am assigning it as supplement reading for my fall course in Sensation and Perception.

The Story of Technology

is a monochromatic, "I'm not quite sure what it does, but it is new and shiny."

Technology is better used to help tell a story.

Teaching technical analysis of neuroimaging data is a story I frequently tell. A digital recording of a relevant talk is easy to share. The person I'm mentoring can watch it at their speed. I do not give the same foundational lecture again (and again).

Sometimes the ideas are better communicated in the journal article format. The digital version of journal article is far easier to share than the paper version.

Technology is better suited to facilitate the telling of already great story, rather than be the story itself.

Solving A Better Problem

I do not have to solve low-level problems (e.g., physical security, physical wants, or paying bills).

If I choose, I can try to solve high-level problems (e.g., enchanting everyone I meet, adding value to the communities I care about, and doing meaningful, creative work).

What Teaching Should Look Like ...

Teaching, at its best, should be a life-changing message delivered well.

Seth Godin's idea in this video:
1) Know the successful strategies
2) Be great at the tactics
3) Care

What I Use: 15% Time

Stephen Covey makes a distinction between production and production capacity. In factory work, the former is cranking widgets today and the latter is greasing the gears to crank more widgets tomorrow.

Since I am a scientist, I have to operationalize the conceptional definitions I use. Enter - My 15% Time. I spend 85% of time "cranking widgets" (e.g., designing studies, running subjects, analyzing data, writing, and answering email). I spend 15% of the time improving my ability to do those tasks. For every six hours on a task, I will spend ~1 hour thinking and tinkering with methods to increase efficiency (do more in less time) or even better, increase effectiveness (do the work that matters). These activities include reading books, learning keyboard shortcuts, and going on coffee dates with people that I can learn from.

What makes this work for me is blocking out the time with a timer.

A Personal Reminder to Publish (or cast)

On a recent visit to National Gallery of Art, I was moved by Degas's "The Little dancer" sculpture.

Most of his scluputres were in wax, a material that does not last or display well. He choose to cast very few of them. Once a statute is cast it is no longer malleable. Degas did not readily commit to his sculptures.

That is an act of The Resistance. His job as an artist was to bring art into the world. Commit to the art.

The world is a poorer place due to that lack of commitment.

The Last Data Point

The last data point is an important data point.

You have all the emperical evidence for your case. Now is the time to synthesize and share.

Open-book/Open-note Environment

Section 70 - "Grammr and the decline of our civilization" of Stop Stealing Our Dreams has a deep resonance with me. It makes the case that the how of education is built on the why of education.

A teacher's job should be preparing students for the world-as-it-is-now. No one has a clue about the long-term future so it impossible to specifically prepare for it. The world-as-it-is-now is Open-book/Open-note. It is a contrivance to assume otherwise.

I am preparing to teach an undergraduate class in the fall on a topic I find fascinating but could be perceived (wink, wink) has a collection of obscure facts. I have hundreds of choices to make, including the content and format of the test. In the past, tests have accessed how well student memorized disjointed facts in the short-term. Instead, I am developing tests requiring the synthesize of given, or easily looked-up, facts. I have never written that style of test. It is frightening and necessary (for both me and the students).

Addressing Formal Instruction in Music and Language Research

There is a debate on whether music and language share common neural basis. In legal terms, the field is in the discovery phase. Experiments are being run, and the data is being collected. My intuition says the final story will be nuanced, it will be a matter of degree and definitions. I am motivated to contribute to the current conversation.

In order to have a productive conversation, there needs to be guidelines for fairness and civility. One of my conversational guidelines is reciprocity; whatever the standard, it should apply to all sides.

Music and language should be judged by the same standard. That is not frequently the case in the literature. For example in Functional Anatomy of Language and Music Perception: Temporal and Structural Factors Investigated Using Functional Magnetic Resonance Imaging by Corianne Rogalsky, Feng Rong, Kourosh Saberi, and Gregory Hickok, participants self-reported formal music education but not formal language instruction.

Almost everyone is an expert in their native language and music. That expertise is implicit for both. Most people receive formal, explicit language training. Some people receive formal, explicit musical training. The scientific literature should treat formal instruction as an equally confounding variable for both language and music.

Step Zero in Research Hiring

What do you look for in someone to fill an academic research position? Do you seek someone with deep domain knowledge, the same domain knowledge that will be obsolete in a couple of years. Do you seek someone with expertise in the technology you are currently using, the same technology that will be obsolete in a couple of years.

Or do you seek out someone that possess the meta-skills for the job? Primary academic research meta-skills being self-starting and project management (self and others). Then train for specific domain and technology knowledge.

It is a decision based on a belief in which skills are more difficult to acquire and more difficult to change.

The Hold Steady

There is a frequent lament that the next generation will not have an increased standard of living. I usually ignore that rhetoric as just another version of the narrative of decline, a unfortunately popular refrain in America. If that doesn't work, I remember people are not skilled at making specific predictions about the future. The world is a complex, nonlinear system thus making those type of predictions futile.

Let's assume the next generation will not have a higher standard living. Is that so bad?

We live the longest lives in the most abundant, peaceful time in human history. It ain't a bad time to possibly plateau.

The Neurobiology of Intuition

In this engaging talk, Daniel Kahneman outlines his main argument in Thinking, Fast and Slow.

The book and the talk are full of insights into the power and limitations of human thought. However, he misses an opportunity to make a stronger case by willfully ignoring neurobiology. Outlining the neurobiological mechanisms underlying human thought and behavior is not necessary; it is an additional, powerful class of evidence.

I have made a contribution to this topic by co-proposing the SPEED Model. The SPEED Model describes the neurobiology of procedural learning and procedural expertise. Procedural behavioral can be considered a manifestation of intuition. In addition to explaining and predicting behavioral phenomenon, SPEED model propose a neurobiological mechanism linking learning and automatcity.

The First Data Point

The first data point is significant because it is the first foot strike on the empirical path.

Theorizing and planning are a helpful foundation of any endeavor, but higher value comes from the interaction of ideas with the world.

Thesis Residue

Writing a thesis is hard. If the act writing of a large body of independent research was not hard, the term ABD would not exist.

Thesis writing can be the time to sharpen writing attitudes and habits. The right attitudes and habits shape a successful career. More often, people create an attitude of fear and a habit of procrastination around creating large, meaningful deliverables.

Compared to the soon-to-be-out-of-date factual content of a thesis, writing attitudes and habits are a more valuable product of the thesis process.

Repost: Stop Stealing Dreams

Seth Godin released Stop Stealing Dreams today. His lastest manifesto directly addresses an issue I care deeply about - Education.

Education has transformed my life. It was my ticket from a lower class upbringing to my current "dream life." I choose to be a teacher to help others reach their dreams (and beyond). The power of education is limited by our current approach. Stop Stealing Dreams is an important step in the much needed full-scale renovation of education. Check it out here.

First Round Knockout

In college, I quickly picked up the "Study Hard, Test Easy" habit. I asked myself harder mock questions than a professor would ever ask on a test. It was much cheaper to fail in my dormroom than in the classroom.

I extended that habit to my science work. The most difficult round of peer review should be my lab group. The time, money, and energy cost of finding errors in the lab group phase is exponentially lower than cost of finding the same errors at the manuscript review phase.

Hire Me as Your Tutor

I am tutoring though WyzAnt.com in the subjects that I most love to teach. Currently, I am offering psychology, statistics, and SPSS. I'm available in-person in the Washington DC metro area or remotely. If you think I could help you, please check out my profile here.

A Better Approach to Methods Section

Today I visited the "Inventing a Better Mousetrap: Patent Models from the Rothschild Collection" exhibit at the American Art Museum. This american art was an artifact of the patent office. In the early days of the patent office, inventors were requited to submit scale models of proposed patents. The models helped patent examiners better understand the new idea. Physical models are easier to understand than words and drawings.

A similar direction would help modern journal-based science. A slideshow or video in the methods section of an experimental paper would help readers better understand the nature of the experiments. Given journals are electronic, a quick embedded video would be worth 10,000 words.

Science Wildcatting

Experimental permutations in science are straightforward. It is easy to run another set of experiments, just add another level to an establishing variable or cross two establishing variables. Experimental permutations guarantee small, limited returns by exploring the known space. It solves the interpolation problem by filling in current knowledge gaps.

The hard work of science is experimental extrapolation. Creating a new variable. Going into unknown space. Most results will be zero. However, the great work of science is there.

On Teaching Introduction to Psychology

How much time is an introduction to chemistry class expected to spend on alchemy? Most people say zero. It is an obsolete paradigm, which does not relate to current thinking in the field.

How much time is an introduction to psychology class expected to spend on Freud? I say zero. It is an obsolete paradigm, which does not relate to current thinking in the field.

In teaching the basics of any field, you either teach how we got where are or where we are. You can not do both well. Every moment you spend on history is one less moment available to spend on trying to understand the world as it is now. Covering the current field of psychology is out of scope for a single course, there is no need add the weight of history.

The history of a field has value. However that value belongs in the history class, not in the introduction class.

Thrashing, Process, & Productivity

How you do convince people to pay attention to their experiment development process?

Everyone makes mistakes. The art of productive science is making and catching mistakes at the right time and place, the best time is the design phase and the best place is on paper. Design time and paper are relatively cheap.

Thrashing on a paper during the design phase is not as exciting as collecting the first data or analyzing the data which supports a pet theory. I created a process which slows me down to catch mistakes of rushing forward. Part of that process is the drawer trick from Stephen King's On Writing.

When I am developing a new study, I design it from start-to-finish on paper from data collection to final analysis with mock figures. I print it out and put it in drawer. I completely forgot about it, that takes ~3 weeks for me. When I revisit the study, I have more detached viewpoint. I catch more mistakes that I care to admit but those are the cheap mistakes.

This process of early thrashing increases later productivity.

Peer Reviewing Gamification

Peer reviewing in scientific journals is a black box. There are known inputs and outputs but the process itself is mostly unknown. As a result, there are few incentives built into the current system to make peer reviewering both quick and high-quality.

Peer-reviewing could be improved by gamification, explicitly defining the rules and what winning looks like. Reviewers/players could be tracked on a public or private scoreboard. Reviewers would earn points for completing their reviews early. They move up to more prestigious journals/leagues by the quality of their reviews. Submitters or editors could then pick reviewers based on objective metrics of their work. It would also provide another data point for merit-based academic promotions.

What I Use: The Two Minute Rule

The Two Minute Rule from Getting Things Done revolutionized how I check process email. I complete every action, that takes less than two minutes, associated with the current email before moving onto the next email. The most common actions are adding events in my calendar, tracking specific next actions, and replying with canned responses, via TextExpander.

Keyboard shortcuts are the engine that drives that machine. I avoid switching costs by not touching the mouse. As my muscle memory develops, I can complete more actions into that same block of time.

The small stuff is off my plate, and my mind, before I enjoy the entrée of the day.

The new face of scientific publishing

I am part of the scientific journal publishing machine.

I have written published papers. Currently, I am peer-reviewing journal articles. I am on the cusp of submitting another paper for review. I truly enjoy that aspect of my science work. However, there is unnecessary friction in the current system, if the goal is to have the best science in the world as quickly as possible for people to read and use.

The paywall issue is a canary in the coal mine for this industry. The journal publishing industry is predicated on a false sense of scarcity. One example is the notion of finite space. This is true for printed journals. That limit no longer exists since journals are now primarily electronic.

I am not ready to completely jump off the sinking ship of conventional journal publishing, but I am willing to work for a system better suited to the digital age.

What counts as evidence in your world?

Is it a story, an individual data point, a single data set, or a meta-analysis?

The hard work of science

A theory can be proved by experiment;

but no path leads from experiment to the birth of a theory.

- Manfred Eigen

Proposing new theories is the hard work of science. It requires insights and guts. The theory you propose will be proved wrong, since all theories are wrong. It is far easier to run another experiment. Experiments are usually a series of technical problems (e.g., How do we find subjects? How do we analysis the data?). It feels safe to correctly solve technical problems. It is harder to create the time and space to develop a new theory.

The importance of trivia

Given the almost constant access to the facts of the world, what is the function of knowing trivia?

One element of creativity is combining two or more different ideas (e.g., someone was the first person to put peanut butter and chocolate together for the eternal betterment of the world). The free recall of facts and figures is grist for that creative mill.

Trivia can be the start but is never the finish.

How much data is enough?

How do you know when you have collected enough data for a project?

Do you collect data until ...

you pass a criteria set before the start?

you pass an arbitrary statistical significance test?

you find something interesting?

you find something meaningful?

you run out of resources (i.e., money, time, or subject pool)?

you satisfy every reviewer?

you get published?

What I Use: Wolfram|Alpha Computational Knowledge Engine

Wolfram|Alpha Computational Knowledge Engine is a sleeping giant. It is a different service than the typical search engine by organizing the knowledge it provides. That basic synthesis helps make sense of the Internet's informational fire-hose tendency.

Wolfram|Alpha is an intergal part of my workflow as a trusted source for specific knowledge. That knowledge is more important to my work than just facts. One specific example to Matlab programming is finding the precise RGB values by simply typing in the common name. It also provides fact-based context, either to generate ideas or frame conversations. It is a great service that is getting better. I have seen the consistent and continuous improvements in the both breath and depth of the service during the time I have used it.

A good place to start is the examples page.

Tufte makes curry

Yesterday at a big box supermarket, I stumbled on this:

These two coconut milks appear to be nearly identical products. Given they were representing themselves as commodities, I was solely making my choice based on price. However, the store didn't make my choice simple or easy.

The can on the left retails for $1.39. The can on the right retails for $3.00 for 5. Furthermore, the prices are listed in different font sizes. Why isn't the price listed for an individual can, even though the cans differ in size by 0.5 oz? I was drawn to the red box, which reads "$1.65 per pound" for the left one and "the price is "$3.95 per quart" for the right one! The store chooses different metrics for the same goods, thus making a meaningful comparison very difficult. Imagine one gas station selling gas by the gallon and another station selling it by the pound. Because those stickers are unnecessarily different on multiple levels, the don't serve their function as more objective sources of information.

There is both a science and art in creating meaningful information. A foundation in basic science is a good place to start.

Real Problems

Problems worth solving are not always the same as:

• the easiest to solve problem

• the most apparent problem

• the first problem

• the latest problem

• the loudest problem

• the most popular problem

• other people's problems

The Neurobiology of Enchantment

One key tenant of enchantment is applying the power of unexpected positive surprises. Everyone likes unexpected positive surprises. There is a biological reason for it, like all human properties.

Reward Prediction Error (RPE) theory predicts that unexpected positive surprises are more rewarding than expected positive events. Think about wining the lottery vs. last week's paycheck, even if they are same monetary value. The underlying mechanism of this effect is the unique biology of dopamine. Dopamine is the stuff of addiction (e.g., casinos and the *caines). That addiction can be positive or negative.

Dopamine and enchantment are powerful stuff. Use them wisely.

By the way, Enchantment is Guy Kawakisi 's latest book. Check it out. I did from my local library.

What I Use: Keyboard Shortcuts

It should not come as huge surprise I'm addicted to keyboard shortcuts, given my love of TextMate* and my fully-loaded 17'' MacBook Pro. Together we take on the world. Keyboard shortcuts let me fly through the busy work and allow me to focus on creating great stuff. You can find THE list of mac keyboard shortcuts here and a good textmate keyboard shortcut cheat sheet here.

Those are just the raw tools. Most people try to start by memorizing the first one that catches their eye. They try to remember, by sheer force of will, it and hope to recall it during their usual workflow. It could sit unused in their "psyche buffer" for 1 second or 1 day. That is the hard and inefficient path towards becoming a knowledge worker ninja. Additionally, it is easy to become overwhelmed with almost never ending list of keyboard shortcuts.

I have an experimental cognitive psychology twist on learning keyboard shortcuts.

It is the "glue game." Every time you sit down at your computer, your hands are "glued" to the keyboard. You lose the current round in the game when you touch the mouse (the trackpad counts, too). Your score is how much work you can do without touching the mouse. After you lose the current round by touching the mouse, you look up the specific keyboard shortcut for that action. You back up a couple of actions steps and use the shortcut. The next round of the game starts after you get up and sit back down. Each round should last a little longer and you should learn a single specific meaningful shortcut.

It is the easiest and quickest way to learn the actual keyboard shortcuts you use. It is called chaining in the business.

One of my favorite chains is:

⌘tab, repeat until textmate is selected

⌘N

⌘S

Five tabs

Up and down arrows into Dropbox

Return

That chain puts me in textmate, opens a new file, and saves to it to my dropbox folder, which lives in my sidebar. I can capture and, more importantly, never lose every idea, brilliant or not, I have. I started by learning ⌘tab link and then I added the ⌘N link. I added one link at a time until I created that complete chain.

Leave a comment with your single favorite keyboard shortcut chain.

*Do not comment or ask me about textmate 2!

Science by proxy

I value primary data and theories over science by proxy. Science by proxy (e.g., popular press articles, podcasts, and blogs) are the warmed-over rehashings of primary science. Frequently, it reposting without analysis. Primary data and theories are difficult. They require domain knowledge and a deep reading to gain understanding. Science by proxy on the other hand is addictively easy to produce and consume.

Science by proxy points to actual science but is not actual science. In a similar way, google is links to the web (not the actual web), wikipedia is facts about the world (not the actual world), and facebook is information about your friends (not your actual friends)*.

* I read that keen observation somewhere but am unable to cite it.

n of 1 always beats n of 0

An anecdote can be a first data point.

And data trumps speculation.

A Cheat Sheet for MATLAB

I love MATLAB.* It is a seamless workflow environment from experimental design to manuscript-ready figures, including data collection, high-level analysis, and computational modeling. As a result, my work is faster, easier, and higher quality by remaining within a single computer application.

However, MATLAB has a steep learning curve. I have been using it for so long I forget how difficult it is to initially learn. MATLAB is literally a foreign language with its own vocabulary, syntax, and thought patterns. Over the years, I have developed a method to teach Matlab with minimal time and pain. The complete method is beyond the scope of a blog post, but I can share a quick tactic. After the initial ramp-up, I hand my mentee "MATLAB for the Faint Hearted". It is the one-stop shop cheat sheet for MATLAB, my mentee no longer has to consult the multi-volume(!) Matlab manual to answer a simple question.

I wish I could give credit to the originator of "MATLAB for the Faint Hearted," but the exact origins of the document are lost in the mists of history. I have updated and expanded it over the years. Now I have decided to share it:

"MATLAB for the Faint Hearted."

PDF version

Quick Tip - If you ever get really frustrated with Matlab, type "Why" in the Command Window!

* Do you have to shout it every time you say it?

Looking past the fringe

The fringe of science gets the most attention. The new and weird of science is overrepresented in most media. The central tenants, or core, of science is not "news," by definition. However, a stronger understanding of them in a chosen field will provide a better long-term return on investment for your limited time and attention.