[My answer to a recent Quora question.]
There are two major problems with neuroscience:
- Weak philosophical foundations when dealing with mental concepts
- Questionable statistical analyses of experimental results
1. Neuroscience needs a bit of philosophy
Many neuroscientific results are presented without sufficiently nuanced philosophical knowledge. This can lead to cartoonish and potentially harmful conceptions of the brain, and by extension, of human behavior, psychology, and culture. Concepts related to the mind are among the hardest to pin down, and yet some neuroscientists give the impression that there are no issues that require philosophical reflection.
Because of a certain disdain for philosophy (and sometimes even psychology!), some neuroscientists end up drawing inappropriate inferences from their research, or distorting the meaning of their results.
One particularly egregious example is the “double subject fallacy”, which was recently discussed in an important paper:
Here’s the abstract of the paper:
Our intuitive concept of the relations between brain and mind is increasingly challenged by the scientific world view. Yet, although few neuroscientists openly endorse Cartesian dualism, careful reading reveals dualistic intuitions in prominent neuroscientific texts. Here, we present the “double-subject fallacy”: treating the brain and the entire person as two independent subjects who can simultaneously occupy divergent psychological states and even have complex interactions with each other-as in “my brain knew before I did.” Although at first, such writing may appear like harmless, or even cute, shorthand, a closer look suggests that it can be seriously misleading. Surprisingly, this confused writing appears in various cognitive-neuroscience texts, from prominent peer-reviewed articles to books intended for lay audience. Far from being merely metaphorical or figurative, this type of writing demonstrates that dualistic intuitions are still deeply rooted in contemporary thought, affecting even the most rigorous practitioners of the neuroscientific method. We discuss the origins of such writing and its effects on the scientific arena as well as demonstrate its relevance to the debate on legal and moral responsibility.
[My answer to the earlier question raises related issues:]
2. Neuroscience needs higher data analysis standards
On a more practical level, neuroscience is besieged by problems related to bad statistics. The data in neuroscience (and all “complex system” science) are extremely noisy, so increasingly sophisticated statistical techniques are deployed to extract meaning from them. This sophistication means that fewer and fewer neuroscientists actually understand the math behind the statistical methods they employ. This can create a variety of problems, including incorrect inferences. Scientists looking for “sexy” results can use poorly understood methods to show ‘significant’ effects where there really is only a random fluke. (The more methods you use, the more chances you create for finding a random “statistically significant” effect. This kind of thing has been called “torturing the data until it confesses”.)
Chance effects are unreproducible, and this is a major problem for many branches of science. Replication is central to good science, so when it frequently fails to occur, then we know there are problems with research and with how it is reviewed and published. Many times there is a “flash in the pan” at a laboratory that turns out to be fool’s gold.
See these article for more: