This is part two of a series of a posts in which I provide background knowledge for evaluating neuroscience findings reported in the news. This post is rather basic, but it's important groundwork for my future posts on neuroscience and writing.
When evaluating experimental results, you have to understand the techniques used to get them. Here is a summary of three ways neuroscientists learn about the brain.
Lesions - Lesions are probably the earliest way people learned about the brain. Injuries to certain brain regions allowed scientists to draw conclusions about the region's function. Some fascinating case studies include Phineas Gage and HM.
1. Lesions make a strong case for arguing a causal relationship between a region and a function. For example, if you can't form new memories after the hippocampus gets destroyed, then the hippocampus was probably involved in memory formation.
1.Lack of control/precision: For obvious reasons, ethical scientists can't conduct lesion experiments in humans. We only learn from lesions when they occur by chance in a relevant region. Because lesions don't happen for the convenience of neuroscientists, they are often messy and cover multiple brain regions, making it hard to make precise conclusions.
Electroencephalography (EEG) - In this technique, electrodes are placed on a participant's scalp to measure the electric fields produced by neural activity as the he performs different tasks.
1. EEG is a direct measure of neural activity (as opposed to fMRI, described next).
2. EEG has very good temporal resolution (It can detect fast activity on the millisecond scale.)
3. EEG is non-invasive, so we can perform EEG experiments on volunteers without causing them harm.
1. Bad spatial resolution. While there are algorithms to compute the source of an EEG signal, it is mathematically impossible to calculate for certain what part of the brain a signal is coming from based only on readings from scalp electrodes. In other words, with EEG you can tell when something is happening in the brain, but have a very fuzzy idea of where.
2. EEG is a correlational measure, so it's harder to establish causality. For example, if you get a pattern of activity when someone is speaking, the activity might be due to speech processing. However, the activity could also be due to something else that is happening at the same time (listening to your own voice, for example).
Functional Magnetic Resonance Imaging (fMRI) - Most of the brain imaging techniques reported in the news, in which the brain "lights up", are fMRI studies. fMRI uses an MRI machine to measure blood flow to the brain as participants perform different tasks.
1. fMRI has pretty good spatial resolution. You can pinpoint things down to the millimeter range. This is currently the best we can do in humans without opening up the skull.
2. fMRI is noninvasive, like EEG. Also, unlike PET or CT scans, fMRI doesn't require radioactive substances.
1. fMRI is an indirect measure. This technique measures blood flow, not neural activity. We can use blood flow as an indicator of neural activity because neurons require more oxygen and glucose as they fire. The cardiovascular system therefore sends more blood to active brain regions. However, the exact nature of the connection between neural activity and blood flow is still an active area of investigation.
2. Like EEG, fMRI is a correlational measure.
3. fMRI has bad temporal resolution. Activation is averaged over windows of roughly 2 seconds. This is many orders of magnitude longer than the actual timescale of neurons. Thus, we lose a lot of information.
I hope this made sense. Please let me know if you have any questions, or if any of my jargon was not confusing. We will return to our regularly scheduled program in the next post.