Measuring Brain Activity: Design, Acquisition, and Analysis of fMRI data

Functional Magnetic Resonance Imaging (fMRI) is the most advanced and commonly used non-invasive methodology for exploring the human brain while performing activities and experiencing mental states, including sensation, perception, attention, learning, memory, reasoning, decision making and so on, making it a crucial tool in investigating the relation between psychological processes and brain function (Poldrack, 2011). Differently from Magnetic Resonance Imaging (MRI), which only shows the brain in one given moment, fMRI allows researchers to acquire multiple images in a sequence obtained over time and can show how brain functions can change over time. fMRI is a great tool for enhancing studies about the human brain and the mind, especially when different disciplines such as neuroscience, medicine, sociology, anthropology, and psychology, among others, collaborate with each other. Using fMRI techniques is a very complex process that includes the careful design of experiments (directed by a certain research goal) followed by data acquisition, analysis and inference. Each of these phases represent an elaborate process in which physical, biological and mathematical knowledge, as well as statistical analysis are fundamental. This is why fMRI research should be carried out by a multidisciplinary team.

fMRI scans measure the consequences (or haemodynamic response) of the electrical impulses of neural activity. Neural communication – which involves the work of action potentials (electric impulses) and synapses releasing neurotransmitters to communicate with other synapses – produces the so called ‘phenomena of mind’. As neural activity is accompanied by changes in local blood flow, the observation of the presence of oxygenated blood in certain areas of the brain (blood-oxygen-level-dependent or BOLD response) is a crucial part of the fMRI technique. This is because when neurons are active, blood is needed to fuel them, consequently increasing the supply of oxygen. Trying to understand how the electric processes occurring at the level of the brain are linked to the human experience of emotions, thoughts and feelings is the main challenge of fMRI.

However, this link is not simple and the haemodynamic response can often be linked to synaptic events rather than action potentials (Stokes 2015). This is what Bennet, Miller and Wolford (2019) showed in a satirical, yet eye-opening, experiment, showing the brain responses of a dead salmon to which they displayed pictures of people in various social and emotional states. The fact that the dead salmon responded with brain activity to the images can be understood by looking at the second aspect of how fMRI works. The scan is a machine conventionally dividing the brain into 40,000 cubic units that can be seen in tridimensional resolution in a computer interface. Since each of these 2-3 mm cubes, called voxels (volumetric pixels), contains around six-hundred thousand neurons, some are likely to be activated even when not responding to an external stimulus. The experiment by Bennet et al., (2019), pointed out the “multiple comparisons problem”, meaning that when a large number of statistical tests is conducted, some results might occur that are misleading. These issues reveal the danger of applying fMRI techniques to detecting lies in a legal setting or communicating with people who are unable to communicate (Stix, 2008). However, important advancements have still been made by fMRI studies regarding general aspects of human thought (Ouellette, 2020; Cohen, 2020).

It is widely known that the mature brain has many specialized areas of function, and neurons that differ in structure and connections. The hippocampus, for example, which is a brain region that plays an important role in memory and spatial navigation, alone has at least 27 different types of neurons

What is not widely known is that the incredible diversity of neurons in the brain results from regulated neurogenesis during embryonic development. During the process, neural stem cells differentiate that is, they become any one of a number of specialized cell types, at specific times and regions in the brain Stem cells can divide indefinitely to produce more stem cells, or differentiate to give rise to more specialized cells, such as neural progenitor cells. These progenitor cells themselves differentiate into specific types of neurons.

In 1928, Santiago Ramón y Cajal, the father of modern neuroscience, proclaimed that the brains of adult humans never make new neurons. “Once development was ended,” he wrote, “the founts of growth and regeneration … dried up irrevocably. In the adult centers the nerve paths are something fixed, ended and immutable. Everything must die, nothing may be regenerated.”

But from the 1980s onward, this dogma started to falter. Researchers showed that neurogenesis does occur in the brains of various adult animals, and eventually found signs of newly formed neurons in the adult human brain. Hundreds of these cells are supposedly added every day to the hippocampus—a comma-shaped structure involved in learning and memory. The concept of adult neurogenesis is now so widely accepted that you can find diets and exercise regimens that purportedly boost it.