When writing about the experimental method, Claude Bernard stated:
We make an observation or an experiment. But once observations and experiments have been performed, we reason about them. This is when any type of explanation can be produced according to everyone’s way of thinking.
The observation is what it is, a fact, but its interpretation depends on the conceptual framework we are using. This framework is based on what we think we know at time t. Since our understanding of phenomena is constantly evolving, it is not surprising to find numerous examples in science when the most appropriate data interpretation had to wait years/decades following the initial observations. We all accept this, because this is how Science progresses. But there are more insidious traps in data interpretation, e.g., confounding factors that we are not aware of, or interpretations that we take for granted. Alerting on these experimental biases and common mistakes in data interpretation is also a goal of eNeuro, as we are here to serve the scientific community and believe highlighting these issues is an important step to avoiding these pitfalls. This editorial will hopefully spawn an ongoing series where we, scientists, will highlight these issues in the various Neuroscience subfields to the benefit of all. …