WaterCooler Neuroscience
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© 2019 watercoolerneuroscience
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A podcast that opens up brain science labs and teaches professional scientific techniques to everyone
99 Episodes
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This episode finalises the series of episodes where Jordana Adler interviews Wilf Nelson on his PhD, the thesis that was produced and the journey he had learned to conduct, design and analyse experiments.
Episode 4 brings you the first of Wilf's episodes that were designed from conception by himself. His work leads him to try to understand how inhibition works when we have multiple competing senses active but now we are going further. This episode explores how the brain uses inhibition when it both knows something is coming up and when it doesn't. Wilf's research lead him away from using EEG and fMRI but instead to using a machine called magnetoencephalography or MEG. Wilf talks about why he had to train with this machine and what new data this brought to his expanding collection of research.
The next episode in the series on Wilf Nelson's PhD thesis is brought to you like season 5 of WaterCooler Neuroscience. In this episode, Wilf talks about this first experiment that just didn't work the way he wanted. Jordana and Wilf talk about their experiences running EEG experiments and tests and what experiments that don't work can tell us in science. In fact, this experiment not working the way it was supposed to be even more interesting because it is the same experiment as chapter 2 but this time is done with an EEG cap instead of an fMRI machine.
In this episode of WaterCooler Neuroscience, we discuss Wilf's first experimental chapter of his thesis. This is when a scientist prepares an experiment and in their dissertation will write a chapter to explain and describe that experiment to other scientists. This experiment is looking at how the brain can decide to inhibit or 'turn off' regions that are competing with what we want to be doing. In reality, the brain can't turn anything off, it is more like putting a state where it is just ticking over but ready to go if it needs to. Wilf talks about his experience of designing the experiment while Jordana Adler is the host and brings her insight from the world of neurofeedback.
This episode is a special one because it is the first part of a five-episode series of WaterCooler Neuroscience on Wilf Nelson's, the host's, PhD. In this episode, Jordana Adler from BTAB is the host and interviewing Wilf on his PhD from starting through to all of the experimental chapters of his thesis. The first episode covers a lot of the questions that scientists get asked when they start their PhD and probes what it means to be trained as a scientist. Listen now to learn about Wilf Nelson going from Wilf Nelson to Wilf Nelson, PhD.
To finish off this series of WaterCooler Neuroscience we are talking about why AI probably shouldn't be a general intelligence. General intelligence is what humans have, we can turn our minds to anything we chose and learn new things with success based on how intelligent we are overall. AI does not work like this; an AI is trained to be good at one thing but fail. Look no further than asking a chess expert to make a cheese sandwich versus a chess AI, the chess AI can't even be spoken to. We talk about why many specific AI is probably the best route for the future rather than a general AI that tries to mimic human behaviour. If you aren't convinced consider your phone is already a collection of very specific AI instead of one general AI.
There are things our brains do that are so natural and obvious we don't even notice our brain does it. One of those things is the perception that we have a body, even if you feel pain or that something is slightly off with your body you always perceive that you have a body. In this episode, we are talking about how researchers are working to understand how our brain is constantly measuring our limbs to keep track of what they are and what state they are in and more importantly we are learning how AI can help us replicate those signals in amputees. If you want to see the future of brain-body research and prosthetics then tune in.
In Season 4 of WaterCooler Neuroscience, we have spoken a lot about the abstract ways to use AI to understand the brain. In this episode, we talk with Michael J Frank about a more grounded, clinical use of AI in understanding the study and uses of dopamine across the brain. What is dopamine? What do disorders of dopamine teach us and how can we better understand it in this modern age of neuroscience?
Computational Neuroscience is a toolbox for researchers to use on whatever they want. AI can mean using a basic analysis program all the way to programs that can simulate and create new faces or new models of information. In this episode, we talk with Thomas Carlson about how to build a modern computational neuroscience lab from the ground up.
Even simple phones can tell if they are looking at a face or at least a photo of a face, and that is thanks to developments in teaching AI how to understand the makeup of a human face. This technology however originated in labs as researchers tried to use the enormous data processing capabilities of AI to understand how humans see faces. In this episode, we talk with Nikolaus Kriegeskorte about how his labs use AI to study the many different ways we see images. We also learn about how AI competition works, many AI can be made to do a task but we need to test and understand which is better to make better machines and programs in the future.
1Computational Neuroscience has had many massive claims in the future mostly around being able to disprove free will or use AI code to mindread what people are thinking in courtrooms and airports. In this episode, we bring you the neuroscientist who is the basis for many of these claims, and he never said any of those things. We delve into what we can really say using AI about how people make decisions and what they think about by talking with John about his illustrious career.
AI are always in the news and regularly credited with amazing advancements in the data processing. AI has become so capable of handling complex data the field of computational neuroscience is now flourishing around the world. This series will talk with experts on computational neuroscience to see how AI and brains are coming together. We start the series with a discussion with John Laird and while he is not a neuroscientist he does make AI from the ground up. John is an expert in making AI and he talks with us about what they can and can't do, what he uses them for in his lab and why he isn't worried about AI trying to kill us all.
This episode finishes the mini-series about Bethany Teachman's lab by interviewing Bethany Teachman herself to talk about her role in running a professional academic lab
This episode continues the series from December 2021 by talking with Jeremy Eberle about his experience working in Bethany Teachman's lab.
Emotions are a bit of a minefield when you run a science podcast. Emotions are constant for human beings so everyone knows what they are and can talk about their emotions all day but scientists have very precise ways to discuss emotions. This means you end up talking a lot about terms and techniques that seem to just be making an everyday thing needlessly complex. In this episode, we do a bit of myth-busting and talk about what all the terms from emotion and mood through to valence and affect mean. We also talk about how our guest studies emotion data from a sleep deprivation lab and the surprising findings we find what shows how we act and think doesn’t always match how we feel or say we feel.
Think Fast is continuing its deep dive into Prof. Teachman’s lab to better understand how multiple different research projects are run at the same time and give you a better look at what a proper academic lab is like. In this episode we are talking about some of the data analysis that goes on behind the scenes looks like. For any lab, the analysis of data is just as important as acquiring it but instead of having a set pipeline up and running data analysis can take many forms. We talk with one of the lab’s researchers to see what their day-to-day looks like and how they turn anonymised data into useable findings.
Think Fast is doing a deep dive into the lab of Professor Bethany Teachman who has been on the show before and we are talking about how her lab studies anxiety. Normally on Think Fast, we will talk about only one research project or one show but labs regularly work on multiple projects at a time once they are established. The next four episodes are going to be an expose on what Prof. Teachman’s lab is doing and how it is really very similar to a large commercial lab in its day-to-day running.
Today’s episode brings you more from the world of computational neuroscience or trying to recreate parts of the brain in a computer. Brains were once thought of as just as a pile of jelly and neurons were neurons, blood was blood and support cells were called glial (for glue). Modern neuroscience has a much more advanced understanding of how the brain is composed of many different types of neurons, glial and microglial as well as complex systems to provide oxygen and nutrients and remove waste. One question however does keep popping up, why do we have so many different types of neurons? Why isn’t one all-purpose neuron the way our brains evolved? In this episode, we talk about how computer models allow us to test tests that would take millions of years through evolution in the lab but a computer can do it in a few days.
Being in the zone is called a flow state in Psychology/Neuroscience, it is the state of focusing on one task to the point that information from the outside world can not even reach our conscious awareness. Team Flow is the very specific circumstance where we are in the zone or in a state of flow but we can specifically not ignore our teammates and integrate the information from other people while keeping that high level of focus. We also learn how professional video gamers are a perfect population for testing this phenomenon which is only a new field to academic study.
Inhibition is a fundamental function of the brain, our brain can't always be on. In this episode we talk with our guest, Dr Corette Wierenga, to better understand how our neurons can be activated in a way that starts to promote the growth of inhibitory connections. This is how our brains balance themselves, it is a method for the brain to work in real-time to alter the strength of different signals and ensure that no one signal gets too strong in the brain.
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