Cognitive neuroscience emphasises the use of non-invasive neuroimaging methods to better understand the neural bases of behaviour, cognition, and emotion. Of the many techniques employed, functional magnetic resonance imaging (fMRI) has emerged as the most widely used within the field. Maybe because of its relatively high spatial resolution (which naturally fits with cognitive neuroscience's goal of functional localisation within the brain), or the highly intuitive and coloured visuals it produces, fMRI is a mainstay in cognitive neuroscience's methodological toolkit, with some even arguing that it has defined the field since its introduction in 1992.
How is fMRI data normally interpreted? Generally, fMRI produces coloured maps of the brain, with different colours representing different levels of 'activation' across brain regions. For a particular region, differences in activation between task conditions are interpreted as differences in neural activity, with higher activation levels corresponding to increased neural activity. For example, if two conditions produced different activation intensities in the visual cortex, it wouldn't be uncommon for scientists to conclude the conditions led to different levels of neural activity in the visual cortex. Some might even make the stronger claim that the visual cortex is responsible for whatever functional difference exists between the conditions!
But can we actually draw such conclusions and inferences from fMRI data? While the above example is admittedly crude, I believe there are simply too many constraints surrounding the use of fMRI to warrant the claims that a) increased activation means increased neural activity and b) fMRI allows us to identify functional specialisation in the brain. As a mental heuristic, I think of these constraints as belonging to three categories: physiological, statistical/analytical, and conceptual/philosophical. In this blog, I focus on the physiological constraints on fMRI interpretation, and aim to cover the latter two in future posts.