Lab manager position in the UO SAN/DSN labs!

The Developmental and Social Affective Neuroscience Labs, under the supervision of Profs. Jennifer Pfeifer and Elliot Berkman in the Department of Psychology at the University of Oregon, are currently seeking a lab manager to support studies of motivation, self-regulation, self-evaluation and decision-making, to begin mid-Summer 2014 (exact dates flexible). The position requires a commitment of at least one year.

Our research uses a combination of fMRI, behavioral, and longitudinal methods with adolescents and adults. Responsibilities will include assisting with the coordination and testing of human subjects, acquiring and analyzing fMRI data, programming stimuli, web design, managing IRB submissions and protocols, and coordinating day-to-day lab administration. The ideal candidate would also be excited to make original, creative contributions to the laboratory’s research.

Candidates must have a bachelor’s degree in psychology, neuroscience, or a related field. Some experience with fMRI and computer programming (e.g., MATLAB, R, Python) is preferred but not a prerequisite; however, candidates who are not yet proficient with a programming language must feel comfortable learning technical aspects of programming and data analysis. Experience working with a range of populations including adolescents, high-risk individuals, and adult community samples – or a desire to learn about doing so – is also highly valued. Candidates must be highly motivated, organized, and have excellent interpersonal skills.

For more information about the labs, visit http://dsn.uoregon.edu (developmental side) and http://sanlab.uoregon.edu (social side). Please apply online (http://jobs.uoregon.edu/unclassified.php?id=4694) regarding posting number 140506 with a cover letter indicating interest in this specific position, a current resume, references, and a list of relevant courses completed. Also, please be sure to mention Drs. Pfeifer and Berkman in your cover letter.

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New paper from SAN lab members Will and Lauren!

Will and Lauren are authors on a new paper in the journal Social Cognitive and Affective Neuroscience about vmPFC activation during personal relevance and self-similarity judgments. Congrats, Will and Lauren (and Jenn)!

Moore, W. E., Merchant, J. S., Kahn, L. E., & Pfeifer, J. H. (2013). ‘Like me?’: Ventromedial prefrontal cortex is sensitive to both personal relevance and self-similarity during social comparisons. Social Cognitive and Affective Neuroscience, 9, 421-426.

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Meditation, Gratitude, and Endogenous Opioids

Congrats to Lisa May for receiving a Varela Award from the Mind & Life Institute! This award complements her Dissertation Research Award from the Greater Good Science Center to support her work on the neurobiological mechanisms of pain relief.

Lisa writes about the funded project:

The goal of this project is to explore how meditation and gratitude affect pain. Quite a few scientific studies have documented that people who have a regular habit of meditating often feel less pain or perceive pain differently than people who don’t meditate. And there are good reasons to think that gratitude might cause pain relief, too. People who live with chronic pain often report that cultivating gratitude helps them deal with pain. Also, feeling pleasure, feeling like you’ve received something of value, or feeling motivated can cause pain relief, and gratitude incorporates pleasure, perceived value, and motivation!

What’s less well understood is how meditation and gratitude cause pain relief. One possibility is that gratitude and or meditation cause the release of endogenous opioids in the brain, leading to pain relief in exactly the same way morphine does. Other mental processes such as beliefs and expectations can release endogenous opioids, so it’s plausible that meditation or gratitude might. This study will test this by giving people an opioid antagonist drug called Naloxone. If Naloxone makes people’s meditation or gratitude-induced pain relief go away, that will be evidence that meditation and/or gratitude cause pain relief by activating opioid receptors.

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Brain systems for controlling food cravings

Nicole Giuliani writes:

Many of us spend a great deal of time and effort managing our temptations to indulge in food we know isn’t good for us. One of the ways that we do this is by thinking differently about that food, for example, by saying to ourselves, “sure that donut looks delicious, but man there must be a lot of lard in there and I know how quickly those calories will add up.” This process of mental reframing, called reappraisal, has been studied extensively in the realm of negative emotions, but hardly at all as it applies to positive emotions such as food cravings. And science knows even less about how someone’s ability to reappraise relates to real-world measures of actual eating. My colleagues Elliot Berkman, Traci Mann, Janet Tomiyama and I recently published a study using neuroimaging to explore what happens in the brain when people use reappraisal to control their temptations to indulge in unhealthy foods. We found that reappraising food craving engages parts of the brain involved in other kinds of self-control and reappraisal of negative emotions. This result supports the idea that many forms of impulse can be regulated by one, “domain-general” brain system. Furthermore, brain activity was associated with body mass index (BMI) in several ways. More reward-related brain activity during unhealthy food viewing was related to higher BMI, more control-related brain activity during reappraisal was related to lower BMI, and greater regulation-related brain activity reduced the link between reactivity-related brain activity and BMI. This set of results is important because it indicates that there might be a common neural network underlying the ability to reappraise the emotional content of anything, and that your ability to see the bright side of a bad situation may be related to your weight. We will follow up on each of these possibilities in future research.

 

This study also investigated whether personal preferences play a role in reappraisal. We all know that resisting temptation can be harder when you particularly like the food in question. The upside is that people were just as successful if not moreso in reappraising their desires for unhealthy foods they really liked versus ones they din’t like as much. However, a comparison of the brain activity for reappraising cravings for these two types of foods revealed some interesting patterns. Not surprisingly, many of the brain areas involved in food craving reappraisal had to work a lot harder to reappraise the desire to eat the foods that participants especially liked compared to ones they didn’t. Interestingly, there were some additional brain regions that were active exclusively during reappraisal of personally desired foods, and not for reappraisal in general. This is important for both brain researchers and brain owners. For brain researchers, this result indicates that scientists need to take into account how personally relevant the experimental stimuli are when they analyze their data. For brain owners, our results demonstrate that there may be some special mental tricks for controlling those desires to indulge junk food temptations.

Citation info: Giuliani, N.R., Mann, T., Tomiyama, A.J., & Berkman, E.T. (in press). Neural systems underlying the reappraisal of personally-craved foods. Journal of Cognitive Neuroscience. [pdf]

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fMRI cannot detect lies

Elliot weighs in (and, naturally, gets misquoted) about the prospects of using fMRI as a lie detector in this interview. The target paper in Frontiers says it all: fMRI cannot now, and perhaps never, be used as a valid lie detection device.

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How does “brain training” to build self-control work, and why doesn’t it generalize?

The recent proliferation of commercial “brain-training” services that promise to enhance intelligence and cognitive functioning is understandable: Who wouldn’t want more working memory, attention, and inhibitory control? However, the effectiveness of these services has been questioned, particularly with respect to how well their training generalizes to the real world. My students Lauren Kahn and Junaid Merchant and I recently published a study using neuroimaging to explore what happens in the brain during a training to improve inhibitory control and to explain why that training might not transfer to new contexts. We found that training caused activity in parts of the brain network associated with inhibitory control to shift earlier in time, proactively engaging before control was needed. This shift improved performance on the training task itself because proactive control is more efficient than reactive control, but there’s a catch: with training, the brain activity became linked to specific cues that predicted when inhibitory control might be needed. This result is important because it explains how brain training improves performance on a given task and also why the performance boost doesn’t generalize beyond that task. Following replication of our result, a compelling next step is to develop an intervention that features cues from real environments where inhibitory control is desirable.

We trained inhibitory control using the stop-signal task, which models inhibitory control as a race between a “go” process and a “stop” process. A faster stop process (relative to the go process) indicates more efficient inhibitory control. In each of a series of trials, participants were given a “go” signal—an arrow pointing left or right. The instruction was simply to press a key corresponding to the direction of the arrow as quickly as possible, launching the go process. However, on a minority of trials, a beep sounded after the arrow appeared, signaling participants to try to withhold their button press, launching the stop process. On beep trials, we inferred that the go process won if participants pressed a button, and that the stop process won if they didn’t press one. By varying the time between the arrow and the beep, and then measuring the proportion of successful stops, we obtained a measure of inhibitory control performance for each participant at each training session.

Participants practiced either the stop-signal task or a control task that didn’t involve inhibitory control every other day for three weeks. Performance improved more in the training group than in the control group. We also measured participants’ neural activity during the stop-signal task before and after using functional magnetic resonance imaging. Activity in the inferior frontal gyrus and the anterior cingulate cortex, which monitor for and trigger inhibitory control, decreased during inhibitory control but increased immediately before it in the training group more than in the control group. These data provide evidence that inhibitory control training causes a proactive shift, but we note that we focused exclusively on inhibitory control; we cannot tell whether these results extend to other kinds of executive function (e.g., working memory).

For further editorializing, see Elliot’s post on this paper on his blog at Psychology Today.

Citation info: Berkman, E.T., Kahn, L.E., & Merchant, J.S. (in press). Training-induced changes in inhibitory control network activity. Journal of Neuroscience. [pdf]

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What is the value of self-control?

Elliot’s latest blog post at Psychology Today about the possible connection between identity and self-control.

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How does motivation influence attention? It depends on the context

Rebecca Calcott writes:

Motivation is a powerful driving force behind goal pursuit in our daily lives. Two opposing motivational states that underlie much of our behavior are approach, the impulse to move towards, and avoidance, the impulse to move away. The type of motivation we feel can have a dramatic impact what we pay attention to, which in turn affects our decisions and actions. For instance, when we experience strong approach or avoidance motivation, we tend to pay attention to small details at the expense of the big picture. In this research, we expanded on the relationship between motivation and attention in two ways. First, we studied not only how motivation changes what we pay attention to, but also how it affects our ability to flexibly switch the target of our attention. For instance, while driving a car, motivation might affect how well we can shift our attention between the car ahead of us and the broader pattern of traffic. Second, we studied the role of the environmental context. In the previous example, perhaps the density of the traffic or the average speed of the cars on the road alters our ability to shift attention. Our general hunch going in was that different kinds of motivation would be beneficial in different contexts.

To study these questions, we had participants repeatedly shift their attention between global (big picture) and local (small detail) features of an image under varying contexts and motivational states. We changed context by altering the ratio of global to local targets, so that on some groups of trials there were more global or local targets, and on others there was an equal number of global and local targets. Motivation was varied by showing participants pictures of delicious versus disgusting things and by having them act out arm positions that are associated with approaching (e.g., pulling) versus avoiding (e.g., pushing). Faster switching between global and local features indicated how well our participants were able to shift their attention. When there were an equal number of global and local targets, avoidance motivation led to faster attention switching. On the other hand, when there were more global targets than local targets, approach motivation led to faster switching.

Our study shows that avoidance motivation may improve shifts in attention when those shifts are frequent or predictable, whereas approach may help responding to rare or unexpected events. This result is important because it demonstrates that, when considering the relationship between motivation and attention, it is also important to consider the context and situation. This finding also has implications for everyday life, because goals can usually be framed in either approach and avoidance terms. For example, driving to work can be motivated either by a desire to avoid being late or to get to an exciting meeting. Motivational framing, therefore, can be used to achieve more flexible or more focused attention depending on the environmental context.

Citation info: Calcott, R.D. & Berkman, E.T. (in press). Attentional flexibility during approach and avoidance motivational states: The role of context in shifts of attentional breadth. Journal of Experimental Psychology: General. [pdf]

 

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SAN Lab joins the Prevention Science Institute

We are pleased to announce the formation of the Prevention Science Institute (PSI). The translational aspects of our work will be connected with the Center for Translational Neuroscience which is part of the PSI. More details about the PSI can be found here.

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Jordan and Lauren receive NSF fellowships!

Lab members Jordan Livingston and Lauren Kahn are named 2013 NSF Graduate Research Fellows. Congratulations, Jordan and Lauren!

UPDATE [8/13/13]: Here is the Around-the-O story about them!

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