Dr. Russ Poldrack, a renowned neuroscientist, is a self-proclaimed information junkie, who admits to spending hours at the computer screen and fidgeting with his cell phone in meetings as he checks for incoming messages.
Russ is not much different from many of us—except in how he spends his week. He heads the Imaging Research Center at the University of Texas at Austin, where he and his team use MRI scanners with the inordinate power to study the human brain, multitasking, learning ability, and the effects of information overload.
In Russ’s world, “the million dollar question" is whether today’s students, especially the avid multitaskers who text and IM with unfettered abandon, will eventually have brains that function differently from those of the adults of earlier generations.
We interviewed Russ in September 2011, as we finished up Project Information Literacy’s (PIL) newest study about how today’s college students manage technology while in the campus library during the final weeks of the term. We discussed new discoveries about the effects of multitasking on the human brain and the capacity for “deep learning.
PIL: In our latest PIL study about how students use technology during crunch time, we found that more than any other activity, 81% college students in our sample (n = 560) said they had checked for new messages—email, Facebook, IM, texts—while they had been in the library during the previous hour. Many of us (including myself) constantly seem to be checking for new messages on cell phones, laptops, and even the answering machine at home. Why do our brains function like this—even if we try to resist these temptations?
Russ: I think that perhaps the most important reason that these devices become so addictive is that they are continuously delivering a stream of new social information, but that we are never certain what will arrive and when it will arrive. One thing we know from neuroscience is that unexpected novel events cause a release of dopamine in the brain. People often think of dopamine as being related to pleasure, but some very nice research by Kent Berridge and his colleagues at the University of Michigan has shown that dopamine is actually more involved in the “wanting” of rewards than in the actual pleasure that is obtained from them. We also know that dopamine is intimately tied to learning of new habits and creation of new memories; if we are doing something when dopamine is released, then we are more likely to do that same thing in the future. We actually understand how this works at the molecular level, which involves dopamine changing the ability of brain cells to modify the connections between them. It is these connections that are the basis for new habits and memories.
When we put this all together, we see that jokes like referring to the Blackberry as “crackberry” are really reflective of a biological reality: The brain systems that drive us to habitually check our devices and crave new messages are exactly the same ones that drive drug abusers to wreck their lives in search of the next hit. In the case of both drugs and digital devices, our brains are faced with a degree of stimulation (chemical or informational, respectively) that is unprecedented throughout evolution, and our powers of self-control are simply too weak to overcome the urges that are created by these innovations.
PIL: In the past 10 years, advances in neuroscience and technology have given researchers such as yourself, phenomenal insights into the way that the brain functions. In a seminal 2006 research article you and your fellow researchers report findings from a study using “functional magnetic resonance imaging” that found “heavy striatal engagement” occurring during multitasking. What is “heavy striatal engagement”? What does your research tell us about the cost of task switching while trying to learn? At the same time, why do so many students believe in "the myth of multitasking"—that they can do many tasks at once and, in fact, perform far better under these circumstances?
Russ: “Heavy striatal engagement” is a lot less titillating than it sounds. The striatum is a part of what are called the brain’s “basal ganglia.” These are a set of brain areas located deep in the brain, which receive input from many parts of the cerebral cortex and then send information back to those same regions via a set of “loops,” which are really just connections between several brain areas that loop back on themselves. The basal ganglia are involved in nearly every aspect of thinking and behavior, but we think they play a particular role in selecting which of several actions one will perform in a given situation, and especially in developing new habits and routines.
In the study that you mention, we asked people to learn how to categorize set of cards that were presented on the screen; the subjects had to learn by trial and error, which sets of cards went with each category. In one part of the experiment, they were able to do this while focused on the task. In another part, they had to try to learn another categorization problem while also performing a secondary task, which involved keeping a running count of the number of times that a particular sound happened. This is a difficult multitasking situation! What we found was that people could learn the categorization task under either single-task or multitasking conditions, but that they learned it differently in the two cases. In the single task conditions, they used a part of the brain called the hippocampus, which is known to be important for creating rich and flexible memories of the past. Fitting with this, when we tested for their ability to generalize the knowledge that they had gained (e.g., by testing using a different kind of test), subjects were able to generalize the knowledge well.
What we saw when subjects learned under multitasking conditions was quite different. Instead of using the hippocampus, subjects instead used the striatum to learn the task. Based on this, we suspected that the knowledge that they had gained would not be as flexible, and this is exactly what we found; unlike the problems that they learned under focused conditions, they were not able to generalize the knowledge that they had learned while multitasking when we tested them in a different way. It’s a fairly long stretch from this research to the classroom, but the results at least suggest that even if multitasking doesn’t prevent people from learning, it can change how they learn in ways that are not beneficial.
Why people believe in the “myth of multitasking” is a great question, and I don’t think we have a good answer. However, it’s consistent with the more general fact that people are often very mistaken about how their own minds work. In their book, The Invisible Gorilla (2011), Chris Chabris and Dan Simons do a great job of laying out many of these illusions that we have about our minds. Just as one example, think back to where you were when you found out about the 9/11 attacks. When emotional events like this happen, people often report what are called “flashbulb memories,” in which the memory seems like a vivid snapshot of the event. For many years psychologists assumed that these memories must be correct, but since the 1980’s a number of studies have shown that such memories can actually be highly inaccurate. A great example is a study published by Daniel Greenberg (2004) from Duke University that analyzed the transcripts of George Bush’s recollections after 9/11 and showed that Bush gave three different accounts of his memory for the events of that day, two of which had details were not plausible given what we know about the timeline of that morning. George Bush is not particularly special in this regard; in general, there is only a very loose relationship between the accuracy of our memories and how confident we are in them. And this is just one of the many domains in which we misunderstand how our own minds work.
PIL: What are the educational implications of your findings about multitasking for K-12 students, especially younger students who appear to be constantly multitasking while they also try to study and learn? Does your research suggest incoming freshmen a decade from now may be less adept at “deep learning” than were the freshmen starting college this year?
Russ: My major concern about the informational environment for today’s students is that the bombardment with such a great deal of information at every moment in their lives will reduce their ability to focus their attention on a single source of information. Just as sitting all day can cause muscular imbalances in our hips and butts, spending the entire day flipping between different informational streams without focusing is likely to reduce the strength of the “mental muscles” that allow us to focus when we need to. You can think of today’s world as a child-rearing experiment on a grand scale, since humans have never been raised in an environment like this before. Unfortunately, it’s not a controlled experiment so we can’t exactly test the effect of the intervention. The worst case scenario is that we will one day wake up and realize that we are living in a cognitive dystopia (think “Idiocracy”), but that like the metaphorical boiling frog, we won’t realize it until it’s too late.
How this relates to learning is still an open question, but I think that there is a good argument to be made that the cognitive effects of multitasking could be detrimental to richer forms of learning. The research on media multitasking by Ophir, Nass, and Wagner (2009) has shown that people who are heavy media multitaskers process information in a different way that light multitaskers, in that they are more “breadth-biased”: that is, they pay attention broadly, skimming larger amounts of information rather than focusing on particular bits of content. In particular, they showed that heavy multitaskers were more likely to be distracted by irrelevant information during a working memory task; that is, they had a harder time focusing only on the information that was relevant to the task. Because the creation of rich memories requires processing information deeply, it is likely that this kind of distractability would reduce the ability to form such memories, though I don’t think that idea has been directly tested yet.
Another interesting side note here is that this ability to resist interference from irrelevant information is one of the brain functions that is known to decline as we age, as has been shown in an elegant set of experiments by Adam Gazzaley and his colleagues at UCSF. Thus, we might expect that as today’s children age, they could experience a double whammy: after being driven to a “breadth-based” mind through years of multitasking, they would then find that their ability to focus is made even worse by aging. However, at this point, there are more questions than answers. In particular, we don’t know the direction of causality: Does multitasking cause changes in the breadth of attention, or do people become multitaskers because they have broad attention? Likewise, although we know that mental function can be drastically changed by experience and training, we don’t yet know exactly how experience with electronic media changes cognition and how those changes might be averted.
PIL: In our latest PIL study, we found that 85% of the students in our sample were what we called “light technology users.” We observed these respondents using one or two IT devices to support one or two primary activities (e.g., coursework and/or communication) at the time of the interviews. Most respondents described taking a “less is more” approach to managing technology and to what they were doing with their devices in the library during the final weeks of the term. Would you say this approach—intentional "light technology use"—could actually increase students’ ability to learn, (depending on, of course, what students were actually doing with those devices)? Do you know of any research about what happens to the brain and to the ability to learn when IT devices is intentionally "dialed down"—not eliminated entirely, but decreased?
Russ: Your result is really interesting because it suggests that the myth of multitasking might not be as powerful as we think. I don’t know of any research that has specifically looked at the effects of dialing down technology use, but it’s pretty clear from all of the cognitive psychology research on multitasking that less is likely to be better, but it will depend critically on the organization of the activity. The effects of multitasking are due to the frequency of switching between different tasks, rather than the number of tasks being done per se. Thus, if you only have two devices but are switching between them every 10 seconds, you will be worse off than if you have 4 devices but only switch between them every 10 minutes. It’s also important to distinguish devices from the activities being used to perform them; most electronic devices can support many different types of activities, and using a single device to switch between four different programs is likely to be no better than switching between four different devices.
PIL: Overall, in our ongoing research at PIL, we have found college students struggling with information overload, especially sorting through irrelevant information from online searches. What happens to the brain when someone experiences information overload? Why is information overload disorienting and frankly, so frustrating for information seekers? Is there anything that someone else—a librarian, an instructor, or a friend—can do to alleviate someone else’s reaction to information overload?
Russ: “Information overload” can mean many different things, so let’s first define what we are talking about. When a person goes online to find information, they are presumably trying to actively hold onto some amount of information in memory; psychologists refer to this as “working memory.” When I talk about “information overload,” I am specifically referring to what happens when the amount of information that we are trying to hold in working memory becomes too large, such that it can’t all be held onto. We actually know quite a bit about how working memory is implemented in the brain, much of which comes from recordings of neurons in the brains of monkeys while they hold information in mind. What has been shown is that when a monkey holds information in mind for a short period, individual brain cells in the prefrontal cortex turn on and remain active as long as the information needs to be held in mind, then they turn off. In humans, we can see this with functional MRI; areas of the prefrontal cortex become active whenever we have to hold information in mind, and especially if we have to work with that information (such as doing mental arithmetic).
The important question is what happens when we hit our limit, and this is not as well understood. In some parts of the brain, it seems that activity increases until we hit our memory limit and then stays constant. Research by Ed Vogel and his colleagues at the University of Oregon has shown that this is related to each individual’s memory capacity, such that people with greater visual memory capacity show greater increases in brain activity as the amount of information to remember increases. In other parts of the brain, however, it seems that information overload can actually cause activity to go down. This has been seen particularly in the prefrontal cortex, where some studies have found an “inverted-U” relation between working memory load and brain activity. That is, activity goes up until memory starts to get overloaded, and then it starts going down. However, this is still an ongoing area of research, and not all studies have found this kind of a decrease with memory overload.
We know that information overload can be stressful, but another thing that neuroscience has shown is that stress can actually make information overload worse. Research by Amy Arnsten and her colleagues at Yale has worked out how this happens at the chemical level. They have found that as the amount of adrenaline in the brain increases (as it does when we are stressed), the ability of individual brain cells to hold onto information starts to break down due to the activity of a particular kind of receptor in the prefrontal cortex. This research suggests that information overload may be a vicious cycle – information overload causes us to be stressed, and the stress then further reduces our ability to deal with more information. One lesson to take away from this is that anything that can help reduce stress (such as relaxation, meditation, or yoga) may help improve our ability to deal with information overload.
It’s also worth noting the parallels between the specific complaint that you mentioned (“sorting through irrelevant information from online searches”) and the issues with filtering of irrelevant information that I mentioned above. Without more research it’s hard to say for sure, but it may well be the case that the breadth-based cognitive style that is associated with heavy multitasking makes it even more difficult to deal with all of the irrelevant information that one encounters when searching the Internet.
Russ frequently publishes the results of his research in scholarly journals. He is an occasional blogger for The Huffington Post, where he writes about the brain, multitasking, and learning, in addition to his personal blog at http://www.russpoldrack.org.
Smart Talks are informal conversations with leading thinkers about the challenges of finding and using information, conducting research, and managing technology in the digital age.
Smart Talks is an occasional series, produced by Project Information Literacy (PIL). PIL is an ongoing research study, based in the University of Washington’s Information School and supported with contributing funds from the Berkman Center for Internet & Society (Harvard University), Cable in the Classroom, and Cengage Learning.
Smart Talks interviews are open source. No permission for use is required from PIL, though we ask that this source be cited as Project Information Literacy Smart Talk, no. 9, Russell Poldrack: “May I Have your Attention? The Brain, Multitasking, and Information Overload.”
The Smart Talk interview with Russell Poldrack was conducted over email with Alison Head, Co-Director and Co-Principal Investigator at PIL during September 16 – October 3, 2011.