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Showing posts from 2013

A guide to post publication peer review

Interesting things are happening in science publishing. In the recent months we witnessed how multiple post publication peer review platforms were born and gained popularity. In this post I will try to clarify what is post publication peer review, what are the differences between existing platforms and what those changes mean for the future of publishing. But before I begin let me say a few words about how most publishing works right now. We were always joking that we should start a new journal that would accept everything and use post publication peer review. To give it enough gravitas to compete with Nature and Science we decided to call it Truth. In the  picture (on the right) - a long time supporter of Truth -  +Jonathan Smallwood  . Peer review before the intertubes Say you are a scientist (if you are reading this it is very likely that you are, but let me try to make this topic understandable for people outside of academia). You have just discovered some exciting

What "Hitchhiker's Guide to the Galaxy" is really about

I was on holiday recently lying on a meadow somewhere near Furka pass in Switzerland. It was the middle of the night and the sky was cloudless. Far from any civilization I could see the night sky in all its glory - with all the tiny stars and the clear shape of the Milky Way. Truly stunning view! Coincidentally I was also reading Douglas Adams "Hitchhiker's Guide to the Galaxy". It's brilliant! Funny and smart. It struck me what it really is about. Let me give you a hint by quoting a paragraph: "Han Wavel is a world which consists largely of fabulous ultra-luxury hotels and casinos, all of which have been formed by the natural erosion of wind and rain. The chances of this happening are more or less one to infinity against. Little is known of how this came about because none of the geophysicists, probability statisticians, meteoranalysts or bizzarrologists who are so keen to research it can afford to stay there." Yes! It is basically saying that bec


I live in a culture of success. I'm being constantly told that if I put my mind to it I can achieve anything. "Yes we can!" It's great - it gives me motivation when I need it. When things get tough I am reminded that if I truly believe in my dream I can move mountains. I would not be where I am now without this push. It's awesome, but not for all dreams. I call those other dreams dreamitts. They are bad dreams, but unlike nightmares, they will not scare you away. Quite the opposite, they are like bright light that lures you in. It's a candle shining in the dark and you are the hopeless moth - when you get too close you will just burn. Dreamitts will make you suffer while trying to achieve them. You will fall. A lot. You will hear "You can do it!" stand up just to fall again. And since dreamitts are so unattainable they seem much more valuable than they really are . Our lives are short, our energy is limited. Some dreams are just not worth pursuin

You are your brain

It is a puzzling mental exercise to reflect upon the processes behind your own thoughts. Philosophers have been struggling with the problem of consciousness for ages and recently entered into dialog with neuroscientists to look for its neural correlates. The road to understanding how the human brain works is very long and we have only just started this journey. Despite efforts of many great minds, our knowledge of mechanisms underlying human activities such as  love, compassion, problem solving, speech, or even vision is still far from complete. Undeniably we have made some progress: we have learned how to map different brain areas to minimize damage during brain surgeries, treat depression and Parkinson’s disease by directly stimulating a particular part of the brain and develop drugs that alter chemicals in the brain and allow to manage some mental disorders. Despite the limitations of our knowledge one thing is certain: whoever we are, whatever we do, and whatever we feel o

The tempting illusion of simplicity

"Plurality is not to be posited without necessity" says one of the major rules of scientific thinking - The Occam's Razor . In other words when we have two explanations of the same evidence the one that is less complicated (or require fewer assumptions) is more likely to be true. Of course it is rarely the case that the models we are considering are explaining the data to the exact same extent, but modern statistical techniques have been developed deal with this (see BIC , AIC and Bayes factor ). In short, those methods combine evidence for each model (such as goodness of fit or likelihood) with complexity of the said model (for example the number of free parameters) in a way that penalizes overly complex solutions.  All of this should be nothing new to anyone dealing with models, data, and theories. There is, however, one additional aspect concerning the complexity of explanations - a social one. We intrinsically like simple stories. It's not only because it is

Making data sharing count

Consider a typical fMRI study:  Twenty participants scanned for an hour = 10000 USD. Research Assistant to run participants = 20000 USD. Postdoc to invent the study and write it up = 40000 USD. 70000 USD later science is richer by an eight page paper, peer reviewed and published in an academic journal. The authors might look at the data again some time later, maybe join it with some other of their dataset to improve power. Maybe. Or maybe they will not have time. We may never learn if there was anything more in the data (all 360 million datapoints of it) than what those eight pages described. Most scientists agree that sharing data makes sense and leads to better, more reproducible, transparent, and objective science. Funding agencies (the guys who turn your taxes into academic papers) understand how expensive data collection is and want to squeeze as much as possible out of existing data. But the perspective of an individual scientist is different. Sharing data does not co

"The Shallows: What the Internet is Doing to Our Brains" - Book Review

I'm impatient by nature. When I'm on the interner, however, I'm like Twitchy on coffee  (now imagine what happens when I'm browsing the web after having a cup of the dark brew). I don't stay on one website longer than five minutes, I struggle to finish watching a youtube video without checking something in the background, I catch myself mindlessly going to websites and asking myself "Why did I opened this tab?". It's bad. It's a constant crave for new information, new stimuli, something surprising, something funny. But it didn't use to be this way. I used to be able to finish reading a book in one sitting (even though it did not happen often). Now I struggle with one academic paper without a break. Something changed in me about how hard it is for me to focus on one task for an extended period of time. The obvious thing to blame was the Internet. And I know I'm not the only one. Why services like and are

On how we estimate value

A friend of mine once had a crush on a girl. The girl wasn't really interested, but valued him as a friend and was too polite to tell him he does not stand a chance (or maybe she just enjoyed the extra attention - who knows!). So the chase went on reaching pretty pathetic levels. At the same time another girl was basically throwing herself at him. Yet he wasn't paying attention to her and preferred to chase an illusion. It's not a single case. Even if you have not experienced it yourself (on which I congratulate you - I'll try to touch on individual differences later on), you must've heard similar stories from your friends. Actually if you look for most popular dating advice you will learn that the trick is to let go and maintain the magical balance of not caring and being interested (or as John Green would say in his witty way: "dumpees should fight the clingy urge" ). Speaking more general my friend was assessing a potential relationship mostly basing

A more probabilistic view on multiple comparisons problem

Even though this blog is not going to be only about multiple comparisons (I could not think of another name), I decided to write about an old problem in slightly new way. Multiple Comparisons Whenever we are testing many hypotheses and are trying to figure out which of them are true we stumble upon so called Multiple Comparisons problem. This is especially evident in fields where we do tens of thousands tests (such as neuroimaging or genetics). So what is the big deal? Imagine that you divide the brain into a buch of regions (voxels) and for each of them you will perform some statistical test (checking for example if this part of the brain is involved in perception of kittens). Some of the regions will yield high statistical values (suggesting relation to kittens) and some will not. Lets try to show this with a simple simullation. Let's assume for now that we will test 100 voxels and only 10 of them will be related to kittens. We will model both populations of voxels u