In my first two years of study I have come across Cognitive Psychology, Neuropsychology and Neuroscience, but Cognitive Neuroscience is a term I was not familiar with — up until recently.
Past Thursday I was lucky enough to get to talk to Ivan Simpson-Kent, a PhD candidate at the Cambridge Cognition and Brain Sciences Unit. Ivan specializes in developmental cognitive neuroscience, researching how intelligence is produced via interaction of the brain and behavior. But let’s take a look at the discipline as such first.
What is Cognitive Neuroscience?
The field concerns itself with the study of the biological processes and aspects that lie beneath cognition. Cognition is broadly defined as understanding and/or the acquisition of knowledge via experience, sensory processing and thought. Some of the more commonly known aspects that cognition encompasses would be memory and decision making.
As mentioned, what Cognitive Neuroscience does is looking at said aspects from a biological perspective — which means looking at what happens in the brain on a neural level. This also means that there is overlap with other disciplines such as Physiological Psychology as well as theories from Neuroscience and Computational Neuroscience. Yes, I know, it all kind of sounds the same — but it isn’t. As Ivan explained to me, Cognition, or rather Cognitive Science, can be understood as the overarching field of Cognitive Neuroscience, making the latter one of its underlying fields. Analogous to that, marine biology is considered a subfield or branch of Oceanography, since the former specifically looks into the biological aspects of marine life, while Oceanography includes all other aspects (e.g. geophysics and geology) beyond that. With that said, let’s go over to what the research looks like!
Research in Cognitive Neuroscience
Several methods contribute to the discipline, including study of the effects of lesions on cognitive functions in humans and animals, study of neuronal activity during cognitive processes via single- and multielectrode recordings, study of human functional brain activity using non-invasive methods such as fMRI and PET, and use of computational models to formalize explicit hypotheses about the underlying mechanisms.
… is what the International Encyclopedia of the Social & Behavioral Sciences says. Professor Josh Tenenbaum from the Department of Brain and Cognitive Sciences at MIT manages to describe it in a (slightly…) more intriguing way:
My colleagues and I in the Computational Cognitive Science group want to understand that most elusive aspect of human intelligence: our ability to learn so much about the world, so rapidly and flexibly. I like to ask, “How do we humans get so much from so little?” and by that I mean how do we acquire our commonsense understanding of the world given what is clearly by today’s engineering standards so little data, so little time, and so little energy.
Much better! But what is the aim of such research? As with every other kind of research, I would say that the primary goal is to understand (in this case, that basically means understanding how we understand). With understanding then comes opportunity for optimization — in the case of artificial intelligence this could mean finding ways to replicate/produce intelligence or maybe even compensate for certain shortcomings. Better understanding also provides us with improved problem-solving concerning brain-related challenges, e.g. in treatment of brain lesions or diseases. It would also mean simply having a clearer and broader picture of why we act the way we do, which would already be pretty great, wouldn’t you agree?
On a closing note, I want to thank Ivan Simpson-Kent very much for taking the time out of his day to talk to me and teach me about this exciting area of research. At some point down the line, I’ll hopefully be able to properly review some of his important contributions over at Cambridge!
That’s all— see you next Sunday!