When a scientific article is published, ideally the data behind the reported results should be made available. Anyone should be able to scrutinize the basis of scientific claims. While this has long been the ideal, it has rarely been practiced. But this has been changing, and momentum is building to actually require the posting of data in circumstances where it’s feasible.

I have argued before that scientists must do more to make available the original data behind their articles. Any scientific claim should ideally be verifiable, via scrutiny of the original evidence. Currently, the vast majority of scientists never share their data.

A new version of my 100-minute interactive neural network lesson is available. The lesson webpages guide university-level students through learning and directed play with a connectionist simulator. The outcome is that students gain a sense of how neuron-like processing units can mediate adaptive behavior and memory.

If you don’t understand the title of this post, you almost certainly will regret reading further. We’re doing an experiment in which one target is presented along with m distracters.

Scientific theories are alive. They are debated and actively questioned. Scientists have differing views, strong and informed ones. However, the system of science tends to mask the debate. In the scientific literature, differences are aired, but rarely in a way that most people would recognize as a debate. ‘Debate’ evokes a vision of two parties concisely articulating their positions, disputing points, and rebutting each other.

How do you get on top of the literature associated with a controversial scientific topic? For many empirical issues, the science gives a conflicted picture. Like the role of sleep in memory consolidation, the effect of caffeine on cognitive function, or the best theory of a particular visual illusion. To form your own opinion, you’ll need to become familiar with many studies in the area.

More and more researchers agree that more access is needed to the original data behind published research articles. Of course, the more general point is that not just the original data, but all materials needed to scrutinize the claims of a manuscript should be available.

First were the Climategate emails. There, Lack of transparency in climate data analyses and climate models contributed to the doubts of skeptics regarding climate change, and made it easier for the skeptics to convince the public that there is good reason for skepticism. Now, the Marc Hauser affair has cast a shadow across another sub-area of science. How can we prevent these scientific fiascos from occurring in the future?

To what extent should we have confidence in the average published scientific result? The news that Professor Marc Hauser of Harvard University may have been involved in scientific misconduct, yielding irreproducible results, prompts us to reflect on whether irreproducible results are usually caught, or not.

Most people are confused about temporal resolution. That includes my students. So I created this diagram to communicate the basic concept, with the example of human visual processing, using a water-works metaphor. Why water-works? I’m trying to explain an unfamiliar concept in terms that everyone can understand intuitively.

The BBC has produced a wonderful series called Richard Hammond’s Invisible Worlds. It’s visually stunning and it’ll wow you with a lot of cool science. The first episode is called Speed Limits. Because I study speed limits on perception, I was very excited.  To introduce the topic, Richard Hammond explains that vision is too slow to see many interesting things, things which can be revealed by high-speed imaging techniques.