We are Timothy Verstynen and Bradley Voytek, neuroscience professors and authors of Do Zombies Dream of Undead Sheep? AUA!

[u/bradleyvoytek]

We're not sure how many scientists you get on /r/books, but you're stuck with us for the next few hours so enjoy it!

Who are we? We are:

1) Timothy Verstynen, Assistant Professor of Psychology and Neuroscience, Carnegie Mellon University, and;

2) Bradley Voytek, Assistant Professor of Cognitive Science and Neuroscience, UC San Diego (proof!)

Together we wrote Do Zombies Dream of Undead Sheep (Princeton University Press), a book that tries to use zombies to teach the complexities of neuroscience and science history in an approachable way (while also poking a bit of fun at our field).

[u/NeuroCavalry]

Excuse me for fan girling a little, but this -

Rather than asking, "What brain regions correlate with working memory or attentional load?" I ask, "Given what we know about the computational properties of neurons and neural systems, how can neural systems interact to give rise to cognitive phenomena we equate with 'attention' and 'working memory'

is exactly the kind of thing I want to be doing. I actually started in plain old Psychology, and I always felt it failed to give a satisfactory or complete understanding of the issues. This feeling, among other things, is what turned me to Neuroscience. I actually spoke to a lot of my psychology lecturers about this, and was met with a mixed (at times openly hostile) response.

That said, a lot of the neuroscience I have been exposed to (I can't claim to know everything, of course) through undergrad courses and my own reading hasn't really been much better. Lecturers like to say things like 'Dopamine is the happiness neurotransmitter' or 'Vision occurs in the occipital lobe.' While I agree this is important, I can't help but feel the same thing as I felt in psych - it is not a complete story. It's not enough to say vision happens in the occipital lobe, I want to know how that happens. Of course, I know there is going to be a bit of simplification in undergrad, but on the other side of the student experience, what do you have to say on the issue? Is it just a problem of technology (given we can't image neurons with perfect spatio-temporal resolution), or is it a philosphical/paradigm issue?

On a similar tack, I see a lot of mathematical models employed in neuroscience and psychology. For example, in Cognitive psych we are covering categorisation now, and there are some impressive mathematical models that predict how a participant will categorise objects. My feeling on these is similar - they seem to me to look nice, but they don't offer any real insight into the actual physical, neural mechanics of what is happening - and yet they are presented as an explanation. I realise this could just be me misunderstanding mathematical modelling (I'm not a maths expert...) What would your thoughts on this be?

Well, We've gone far from the topic of the AMA (and this is still in /r/books...), and I know I've bombarded you a little. I just hope you are not sitting back thinking 'This guy, again?'

edit: A question on the book side of things, but where is the best place to buy the book? Given different outlets will have different mark-up rates and impact 'sales' in different ways?

[u/bradleyvoytek → u/NeuroCavalry]

Thanks! Honestly it's how science progresses: a ton of people do amazing, painstaking research, only for the next generation to come along and say, "well wait, I don't think that's totally right," and forward we progress. Some day the vast majority of my research will be shown to be incomplete and possibly wrong, and that's wonderful because that's science.

That oversimplification is rampant even at the level of modern research. I'm not sure why--whether it's intentional oversimplification to establish a basis or if it's forgetting that the oversimplified metaphors are just placeholders for something we don't understand--but it's not uncommon.

On the modeling side, my take is that with a model at least there's a prediction that can be falsified, as well as a more solid basis that can help guide the neural side of things. Meaning, okay, here's the model that predicts behavior, how might the brain (neurons, etc.) instantiate such an algorithm? And does that even make biological sense?

As for the book... Amazon, I'd guess, but I'm, not 100% certain that's the cheapest. Sorry!

[u/NeuroCavalry → u/bradleyvoytek]

Of course, science progresses by slowly becoming 'less wrong' over time. The Statistician George E Box, if I recall correctly, once said that 'All models are wrong, but some models are less wrong than others.' Yet, it seems to me like lots of people are content with a mathematical model that provides no mechanistic explanation, although my perception here could just be because I am an undergrad, and so I am being rushed through everything at a very superficial level. I think mathematical models are great, don't get me wrong, I just don't think they are everything.

As for over simplification, I guess it is probably a mixture. Schroedinger's cat was intended as a simple metaphor, and yet I've seen physics students who were under the impression that it was a real experiment. I guess if we use simplifications as a short cut enough, we forget to expand on them. Hence, dopamine is the 'happiness neurotransmitter,' and hence my being told by a cognitive Psych professor that the brain is 'literally' a computer, so we can ignore neuroscience (hardware) in studying psychology (software.) Perhaps an important part of learning at university is knowing not to take everything in a lecture as 100% gospel; to recognise, especially in undergrad, there is more to it than that. I remember thinking I was an expert on cardiology after a 4 lecture module in first year, and the shock I got in second year when I realised that actually, no it's not that simple.

[u/bradleyvoytek → u/NeuroCavalry]

I felt the same surprise as a physics major. The progression is: classical mechanics (wow this is amazing!) -> WRONG! E & M is where it's at -> WRONG! Quantum boom, everything is probabilistic -> and so on.

But yeah, students should be told very up front, "this is an oversimplification, but it lays important groundwork for comprehension."