Publications by authors named "Jennifer L Ferris"

Objective: Mindfulness meditation training has been previously shown to enhance behavioral measures of executive control (e.g., attention, working memory, cognitive control), but the neural mechanisms underlying these improvements are largely unknown.

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Background: Mindfulness meditation training interventions have been shown to improve markers of health, but the underlying neurobiological mechanisms are not known. Building on initial cross-sectional research showing that mindfulness meditation may increase default mode network (DMN) resting-state functional connectivity (rsFC) with regions important in top-down executive control (dorsolateral prefrontal cortex [dlPFC]), here we test whether mindfulness meditation training increases DMN-dlPFC rsFC and whether these rsFC alterations prospectively explain improvements in interleukin (IL)-6 in a randomized controlled trial.

Methods: Stressed job-seeking unemployed community adults (n = 35) were randomized to either a 3-day intensive residential mindfulness meditation or relaxation training program.

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Recent studies indicate that mindfulness meditation training interventions reduce stress and improve stress-related health outcomes, but the neural pathways for these effects are unknown. The present research evaluates whether mindfulness meditation training alters resting state functional connectivity (rsFC) of the amygdala, a region known to coordinate stress processing and physiological stress responses. We show in an initial discovery study that higher perceived stress over the past month is associated with greater bilateral amygdala-subgenual anterior cingulate cortex (sgACC) rsFC in a sample of community adults (n = 130).

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This fMRI study examines how students extend their mathematical competence. Students solved a set of algebra-like problems. These problems included Regular Problems that have a known solution technique and Exception Problems that but did not have a known technique.

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Behavioral and function magnetic resonance imagery (fMRI) data were combined to infer the mental states of students as they interacted with an intelligent tutoring system. Sixteen children interacted with a computer tutor for solving linear equations over a six-day period (days 0-5), with days 1 and 5 occurring in an fMRI scanner. Hidden Markov model algorithms combined a model of student behavior with multi-voxel imaging pattern data to predict the mental states of students.

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Students were taught an algorithm for solving a new class of mathematical problems. Occasionally in the sequence of problems, they encountered exception problems that required that they extend the algorithm. Regular and exception problems were associated with different patterns of brain activation.

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Hemodynamic measures of brain activity can be used to interpret a student's mental state when they are interacting with an intelligent tutoring system. Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distribution of solution times from measures of problem complexity.

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Two studies used puzzles that required participants to find a word that satisfied a set of constraints. The first study used a remote-association task, where participants had to find a word that would form compound words with 3 other words. The second study required participants to complete a word fragment with an associate of another word.

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In a double-blind, placebo-controlled experiment that used midazolam, a benzodiazepine that creates temporary amnesia, we compared acquisition and retention of paired associates of different types. Some word pairs were studied before the injection of saline or midazolam, and two lists of word pairs were studied after the injection. Critical comparisons involved retention of pairs that were practiced on all three lists, pairs studied on only one list, and pairs that involved recombining cue and response terms from one list to the next, as a function of drug condition.

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