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podcasting science advocacy science communication Science for Progress tutorial

This is how you can subscribe to my podcast!

I am running a podcast for Science for Progress, and there I am talking about how to improve academia, and how science/academia interacts with society. I interview people who are, for example, working on better metrics for research(er) evaluation, people who work on topics relevant to society (such as GMO food, and animal welfare), or someone who can tell us a bit about Science Communication, or the PhD experience.

Interested? Well, you should subscribe to the podcast, then!

Here is how:

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podcasting science communication tutorial

Being a Guest on a Podcast Part 1 and 2

When you are going to be interviewed for a podcast, you should remember that the episode may be downloaded hundreds or thousands of times. And you don’t want your listeners to turn it off after a few minutes because your sound is awful.

Sure, the podcaster can do a couple of things in post-production to rescue a bad recording. But you want to make sure that you did everything you could (in that moment) to help improve the quality of your sound.

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science communication

Neuroscientists, where did you come from?

I have often been curious about where neuroscientists come from in an academic career / interests sense. Meaning: what kind of interests did they first start with, when they were young and innocent ;). So, after someone on Twitter brought this topic up again, I made a quick survey using SurveyMonkey and posted it on Twitter and Facebook. Here I want to share the results.

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neuroscience general opinions science communication

Why I think neurons are computers and why it matters.

The question about whether neurons perform computations came around several times on twitter, lately and there were at least two spin-off blog posts that came from these discussions:
Is the idea that neurons perform ‘computations’ in any way meaningful? from Adam Calhoun (@neuroecology) and then
The Diversity of Computation
by @mnxmnkmnd

So far so good. It appears that basically there is little discussion about whether neurons compute things. However, a new conversation between me and @mnxmnkmnd came up as I realized that for him it appears to be close to irrelevant whether you call a neuron a computer or not and you don’t learn more from emulating the computational function of a neuron than from simulating the thing the same way you would from simulating fluid dynamics or a pendulum.

So, here is my new attempt to explain, why I think it is important and meaningful to think of neurons as computing agents rather than simply physical phenomena.

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science communication science editing tutorial

Barplot Madness

Maybe it is because of the change in fields and scientific environment, but I increasingly doubt data presented in talks, posters, and articles. Mostly because I find myself wondering whether the choice of statistical description of the data makes any sense. I am not speaking of advanced statistics at all, just the simplest descriptive techniques and the choice of the right plot for it.

figure 1. X represents spike rates, categories cell types A and B respectively. Whisker indicates standard deviation.
figure 1. X represents spike rates, categories cell types A and B respectively. Whisker indicates standard deviation.

Bar plot as sketched in figure 1 raise my doubts. What looks like a rather okay representation of data actually does not really give you an intuitive idea of how the data are distributed.

A barplot is most useful to represent counts in histograms or percentages. The bar is supposed to indicate that there would be data points spanning the whole range from the top of the bar down to the x-axis (figure 2). Standard deviations on a barplot would indicate that one measured the whole thing several times and there is some wiggle at the overall sum of each measurement. For example, if you counted the number of labeled neurons in the same brain area of several animals and you want to show the cell count numbers. Here, the relation of the sizes of the bars directly translates into the relationship between count numbers.