In the previous lesson we talked about the fields of psychology from the 20th century, now in the 21st century we have many fields of neuroscience, and we are going to explore what they are and what they aren't.
The first thing to say is no field of psychology really ever dies, it is a science, and while some things come in and out of favour I have had colleagues that only study learning and behaviour and could be called behaviourists, although they wouldn't call themselves that and experimental cognitive psychology is still the strongest and admittedly broadest field in psychology. What the 21st century brought was widespread neuroimaging, neuroscience became a field of psychology, and engineers and physicists found ways to take imaging devices out of the labs, into hospitals, and as hospitals needed MRIs and EEGs, so their price lowered so research institutes could afford them.
Modern psychology, if you look outside behaviour, cognitive and social psychology, is very heavily focused on two main things. First, using neuroimaging to see what the brain is doing. In earlier episodes, we talked about what EEG and fMRI are, what they can do, and what they can't do. That is called cognitive neuroscience; it is where you use machines to find out how the biology of the brain links up to what a person is doing or says they are thinking about. The other area is computational neuroscience; it has had a huge growth because it is linked to AI. AI from a science perspective isn't a conscious machine or a terminator, it is just a machine that can learn, and by learn I mean take data and alter how it runs. If your radiator had a program that always keeps the temperature at 25 celsius or 77 Fahrenheit and over the year that is ok in winter but in summer you turn it down, and it records all those numbers and then the next year it just repeats what you did last year as its guide for how hot it should be in February or May or June or November then that is an artificially intelligent machine. Despite human standards being as dumb as a rock. The media are saying AI and scientists are saying AI are very, very different terms.
So how does AI come into neuroscience? Well because of neuroimaging oddly enough. Let me explain. When you do a neuroimaging study you want to know how the brain is firing, in EEG you can see things on really small timescales but as my old lecturer used to say you can't tell where anything happened except down to a quarter of the scalp. That limits its use a lot, fMRI can tell you where things happen, even deep in the brain but it measures blood flow, and it is slow, like 15 to 30 seconds to know something happened kind of slow. This means we can either know when something happened down to the millisecond or where down to a couple of millimeters but not both. And on top of that, we can get thousands and thousands, even millions of data points back from just one study. That is why we need statistics, I know stats are scary, and we are breaking it down later in this course.
So AI comes into it because AI can handle a million data points and we tell it, these people responded like this in category one, these people responded like this in category two, and we can do that for really long experiments, and eventually, AI can figure it out. Now when I say AI can figure it out what do I mean? Well, computational neuroscience hasn't solved the brain, but when we want to know if brain signal A or brain signal B is caused by showing something on the screen that is something an AI can do, when we want to understand the whole brain at once, not just single slides, that is something AI can do, and when we want to make artificial models of the brain test what we found, that is something AI can do.
These two fields have been absorbed into the old fields very handily. Social neuroscience is an enormous field with studies every day using fMRI to get people to watch social scenes or interact with participants out of the scanner and see how brains respond when we are in social situations. Experimental cognitive psychologists that we spoke about in the last lesson were the ones making the experiments when neuroscience started, hand in hand with physicists who made the experiments and biologists telling psychologists what each area of the brain was doing. Now a modern neuroscientist like myself receives training in all these areas; we become one person bands with a lot of training. Traditional psychology experiments with people in cubicles in front of computers still go on, I have done them myself but the pull to neuroscience, to the scanners is stronger every day.
The final new amazing technology is OPM which is an EEG cap that uses magnetism so the skull doesn't get in the way of the data and you can move with it on. The old EEG caps don't work when you move, but OPM does, and that means we can now have people use them and start to understand how people's brains play table tennis in real-time, how they interact in social settings, and how the brain navigates in 3D space, something previously not possible when scientists like me were asking people to stay still the whole time.
I hope these lessons have let you understand better what the 20th century and 21st century are doing in the world of neuroscience and when people say they work in psychology, now you have a roadmap to understand them better.
