When I first started studying neuroscience I found a scientific
paper that inspired and motivated me.
The paper demonstrated how
advances in science and technology enable further advances.
Advances in any area of science can potentially help any other area of science. Under the right conditions, science and technology can accelerate its own development. There is nothing you can learn that will be detrimental to your ability to learn.
Neuroscience in particular has been greatly aided be advances in chemistry, molecular biological, genetics, and microscopes. For example when NASA studies optical lenses for their telescopes, some of their advances find their way into optical microscopes, and neuroscientists use those microscopes to study the brain in ever increasing detail.
When I first started studying neuroscience in earnest I was surprised by the state-of-the-art methods. Scientists are studying the brain in unprecedented detail and collecting massive amounts of highly accurate data. Computers have become a necessity for sifting through these massive datasets. And at times it seems as though we've traded listlessly hypothesizing without the data needed to confirm or reject, for furiously measuring without a theory with which to understand the data.
Early on I found a scientific article using GCaMP calcium imaging. The article's scientific discoveries didn't seem important, but I was captivated by the methods they used to collect their data. The technique was roughly as follows:
Here is an example of what this looks like in action. The box in the lower-right corner of the video shows what's going on inside of the mouse's brain. The white dots that keep appearing and fading away are neurons with increased calcium-ions concentrations.
GCaMP imaging represents the confluence of decades of research and development across numerous fields of science and technology. We've genetically modified a mouse such that we can simply "read out" data directly from its brain. This method would have been unimaginable 30 years ago. With tools like this will we finally be able to understand the mysteries of the brain?
PS. I think that this was the paper I originally found describing their GCaMP experiments:
Cerebellar granule cells encode the expectation of reward
Mark J. Wagner, Tony Hyun Kim, Joan Savall, Mark J. Schnitzer & Liqun Luo (March 2017)
https://doi.org/10.1038/nature21726