The global mission of the NeuroCognition Lab is to provide a better understanding of the neuronal basis of cognition in normal adults and children. We are part of a relatively new field of inquiry known as Cognitive Neuroscience. To understand this discipline you have to know something about its two parent fields: Cognitive Psychology and Neuroscience. Typically, neuroscientists seek to understand the basic principles of the nervous systems of humans and other species and in most cases are interested in relatively low level mechanisms — for example, understanding the basic workings of neurons. Traditional cognitive psychology focuses on much higher level “mental” processes, seeking to understand the principles and properties of perception, attention, problem solving and language. Historically cognitive psychology has approached the understanding of mental phenomena without much of an emphasis on the specifics of how the brain is involved. Cognitive Neuroscience blends the goals of neuroscience and cognitive psychology asking specifically how the brain gives rise to a variety of cognition processes.
The primary question our lab is interested in is how language and other, possibly related, cognitive systems are organized and function in the human brain. This question turns out to be one of the most vexing questions in science both because language is such a complex skill, but also unlike most other cognitive systems (e.g., memory and attention), there are no animal models of language. Humans are the only species (we know of) that have evolved a complex, learned communication system with a rich set of structural rules. The lack of animal models has made it almost impossible to perform the kind of invasive controlled manipulation of the brain necessary to better understand how language works. Therefore, we have been forced to rely on less invasive procedures.
Over the last several decades a number of new and exciting non-invasive techniques have become available for directly examining brain structure, and more recently brain function. MRI, PET, fMRI, ERP and MEG are some of the new techniques that allow the experimenter to take a snap-shot of the awake and intact human brain. Using a computer, the experimenter can then construct a series of pictures of different regions/areas of the brain. While traditional MRI shows what the brain looks like structurally (i.e., it reveals the anatomy of the brain), PET, fMRI, MEG and ERP show areas of the brain that are active or functioning (i.e., they show the physiology of the brain).
PET, fMRI and MEG are very expensive — the equipment used to take these measures cost in the millions of dollars. Typically, these systems can only be afforded by large medical centers that use them for clinical procedures, although recently there has been a trend for more “research dedicated” scanning facilities. The advantage of these techniques is that they have relatively good spatial resolution. This means that they can tell with some accuracy where in the brain activity is occurring (within a few centimeters or even millimeters).
ERPs, which record the electrical activity of the brain, are within the budget of most psychological researchers, but they have suffered from inherently poor spatial resolution. This means that while they can measure different brain functions (i.e., activity in different cognitive systems) they cannot easily determine where the activity is coming from. However, recent advances in signal analysis and increases in the density of electrode arrays has improved the spatial resolution of ERPs — especially ERP recording is coupled with other techniques such as MRI. So, there is now some promise that this technique will be better able to determine which brain regions are active in different cognitive tasks.
One thing that has become very apparent in the study of human cognition is that time is of the essence. Although neurons operate at a relatively slow rate (the 1 to 10 ms range), most of the higher-level processes that neurons are responsible for take place on a time scale that is only slightly slower – on the order of less than a second. For example, readers can process, on average, about three to four words a second, which means that a word is perceived, recognized and understood in about 250 to 400 milliseconds! The rate for processing spoken words is more variable, but is on the same basic time scale. Therefore, it stands to reason that any technique used to reveal the brain processes involved in word processing will have to have sufficient temporal resolution to differentiate the relevant sub-components (e.g., perceiving, recognizing, understanding) involved. PET and fMRI, because they measure the dynamics of blood flowing in the brain, have temporal resolutions on the order of, at best, a few seconds. This is because it takes a few seconds after a change in brain state for it to show up in blood flow changes – which are what these techniques pick up on. Clearly, this is too slow to resolve the sub-processes involved in word comprehension or most other cognitive skills for that matter. ERPs (and MEG), because they directly monitor the electrical activity of the brain, have millisecond level resolution. This is sometimes referred to as on-line sensitivity. The bottom line is that ERPs reflect brain activity well within the range of the component processes of most cognitive tasks — including word comprehension.
A substantial body of research now exists supporting the view that ERPs are sensitive to a variety of the neural events involved in language processing. In the NeuroCognition Lab we use ERPs to study the neuronal basis of reading and listening to language and more recently language production (speaking). We also use ERPs to compare reading and listening to other cognitive skills such as picture processing. The primary interest in this case is whether the same or very similar brain systems are involved in processing different kinds or domains of information or whether the brain has uses different systems for dealing with different types of information. We are also interested in the developmental time course of language comprehension — especially reading. The process of learning to read is very complex and although it has been studied for many years it is still not well understood — especially with respect to the underlying brain systems. Currently we are engaged in several projects that seek to better understand some of the changes that occur in the brain as a child learns to read. And finally, a major goal of our research in recent years has been to provide a better understanding of the brain mechanisms involved in using and learning second languages. You can find out more about the specific questions we are studying by reading about our on-going projects.