Topics:
Cognitive control and oscillatory neural activity
Back to topThe following PDFs are extracts from my dissertation (click here for the PDF).
Fundamentals of neuroscience. In this chapter, I try to show that there are three fundamental concepts every neuroscientist needs to understand - mathematically - and apply to build theories that can explain behaviour: information, control and stability.
Task switching. One of the clearest examples of what cognitive neuroscience needs to explain about behavior and the brain is the ability to task-switch. Task-switching means voluntarily and flexibly - at the time scale of seconds or below - changing what response will be given to physically identical stimuli. This makes clear that the brain controls itself, to some extent: the stimulus alone can't always predict the response.
The coordination of brain activity. Somehow, our nervous system can generate such flexible, goal-directed behavior. The focus of this text is to argue that regions over the whole brain work together flexibly to generate coherent behaviour. I think that this process of coordinating activity is where voluntary action resides.
Oscillations in brain activity seem to play an important role in flexible coordination. Furthermore, different frequency bands are consistently related to different (coordinating) functions. The theta-band is used for the long- and short-term encoding of relationships. Alpha-band activity is involved in inhibitory mechanisms. Actions and their planning and imaging are coded in beta-band neural activity.
Statistics
Back to topI keep coming across heated criticisms of statistical testing using P-values. I argue that there's nothing wrong with that, but you need to view the p-value from the perspective of the scientific process more than statistical models.
Some informal musings on what degrees of freedom are.
fMRI
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I'm not a physicist but I've been trying to get some kind of real understanding of the basics of MRI physics. The most useful things I've found in various sources are summarized in this guide to MRI. The section on K-space is probably the most worthwhile part. I was really missing a few visuals from the sources on K-space I'd found, that I've now made some hopefully clear (and correct) plots for.
EEG
Back to topSome doodlings on calculating instantaneous amplitude using wavelet filtering.