This being my first blog entry, I'm inclined to make it more of an introductory note. Specifically, who am I, where did I come from, and where am I going?
I am calling myself a Cognitive Neuroscientist these days, but this is more of where I wish to go than where I've been. Assigning titles in this field is not a straightforward proposition. I am officially a Psychologist — having studied Behavioural Neuroscience — but have focused in recent years on methodological and clinical topics which are far removed from what is traditionally considered Psychology. While the goal is to find better ways to properly investigate cognitive processes using neuroimaging techniques, for the most part I have been concerning myself in recent times with methodological issues I have run into in this pursuit. It's a slippery slope, I've found. You delve into specific topics as a Ph.D. student or postdoc, and you suddenly find yourself being defined by these topics, regardless of your original motivation.
I have no desire to be known as a "methods guy". In the pursuit of better methods, I have developed computational and statistical skills, and am a prolific programmer in many languages; but I have no desire to be known as a "computational guy" either. For one thing, there are hard-core trained "computational guys" in neuroscience who do things for which I am lucky if I comprehend the abstract. At the same time, I am never happy with just reusing other people's methods unless I am completely satisfied with them (and I rarely am).
This dilemma highlights, for me, a growing trend in academia; which is to treat the academic as hired talent — a means to an end defined by some committee or (worse) political appointee. There are many forces at play which have an impact on academic behaviour, the discussion of which I should save for further blog entries. The only point I wanted to make here is: given the pressure to narrowly focus one's research, and thus narrowly define oneself, there is the risk of discouraging critical thought and a deeper interpretation of scientific findings, in favour of generating output flows and neat, packaged research lines. In some cases, this can certainly act as a useful incentive and lead to decent research; but it can also be stifling. Academia was never meant to be an industry (insofar as it was "meant" to be anything).
In any case, if I have to define myself, I prefer it to be with the field which best motivates me, and this is the field which seeks to understand how neural phenomena, such as network organization and functional activation under given task conditions, are related to cognitive processes. My ultimate goal (and I am happy to announce that I am taking large steps in this direction with my latest research) is to characterize the predictive relationships between the many lines of evidence we have access to through human neuroimaging techniques (MRI, MEG, EEG, PET, and so on). Critical to this goal is an integration with other lines of evidence, such as those only available through invasive animal models of brain function. I will clarify these goals in future posts (and hopefully a new line of research articles).
That's all for now.
