Brain Activity During Strategic Planning
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|ClinicalTrials.gov Identifier: NCT00728741|
Recruitment Status : Completed
First Posted : August 6, 2008
Last Update Posted : July 2, 2017
|First Submitted Date||August 5, 2008|
|First Posted Date||August 6, 2008|
|Last Update Posted Date||July 2, 2017|
|Study Start Date||August 1, 2008|
|Primary Completion Date||Not Provided|
|Current Primary Outcome Measures||Not Provided|
|Original Primary Outcome Measures||Not Provided|
|Change History||Complete list of historical versions of study NCT00728741 on ClinicalTrials.gov Archive Site|
|Current Secondary Outcome Measures||Not Provided|
|Original Secondary Outcome Measures||Not Provided|
|Current Other Outcome Measures||Not Provided|
|Original Other Outcome Measures||Not Provided|
|Brief Title||Brain Activity During Strategic Planning|
|Official Title||Functional Neuro-Imaging of Strategy Use During Human Behavior|
This study will locate areas in the brain that help people devise action plans to carry out complex tasks requiring use of strategy. The ability to plan strategically is impaired in patients who have had a stroke affecting the front parts of the brain. This study will use functional magnetic resonance imaging (fMRI) to examine the activity of different areas of the brain during the formulation and execution of plans.
Right-handed healthy volunteers between 18 and 60 years of age may be eligible for this study. Participants come to the NIH Clinical Center four to five times to complete the following procedures:
Visit 1 - Screening
Visit 2 - MRI brain scan (if one has not been done within the past year)
MRI - This test uses a strong magnetic field and radio waves to obtain images of the brain. The scanner is a metal cylinder surrounded by a magnetic field. The subject lies on a table that can slide in and out of the scanner, wearing earplugs to muffle loud noises that occur during the scanning.
Visits 3 to 5 - Task training sessions and two fMRI scans
Functional MRI involves taking MRI scans while the subject performs a task in order to learn about changes in brain regions that are involved in the performance of the task. Subjects are trained in two tasks (see below) and then perform the tasks while in the MRI scanner.
Efficient behavior requires the ability to generalize from previous experiences. This can be achieved by behavioral strategies. We use many behavioral strategies; some strategies have strict S-R associations -stop at the RED light-; others are modifiable -balancing skills of a ballerina that becomes very useful during rock climbing- and serve as abstract strategies that enable solving problems.
Strategy use is common in our behavioral repertoire. A strategy can be defined as a set of computations associated with the act of planning and directing overall operations and movements involved in a task. A behavioral strategy that conscious behaving primates spontaneously adopted in order to maximize their rewards have been well characterized in the literature. These are called "Repeat-Stay"/"Change-Shift" strategy, and were shown to be associated with prefrontal neuronal activity during multi-unit intra-cortical recordings, clearly indicating a special role played by the prefrontal cortex in computing strategy use. It is important to understand how the human brain computes and processes strategies. This study aims at understanding the activation patterns, and neuronal connectivity in the human brain when engaged in tasks that require strategies. We hypothesize that application of strategies to solve tasks would show specifically and significantly increase Blood Oxygenation Dependant (BOLD) signal, particularly the fronto-polar cortex (PFp), ventral and orbitofrontal prefrontal cortex (PFV+o) in the human brains.
The two experiments described in this protocol may recruit up to 61 (6 for the pilot study) adult healthy volunteers.
The study will consist of functional Magnetic Resonance Imaging (fMRI). The fMRI will consist of two separate experiments: (1) the strategy experiment and (2) the memory control experiment. Data will be analyzed separately for each part of the experiment: Responses to tasks will be collected and this data (response times, accuracy rates) will be searched for statistically significant differences using linear contrasts in an ANOVA model.
The imaging fMRI data will be analyzed for statistically significant functional activations by using an implementation of the General Linear Model (GLM) (R. Turner et al., 1998; K. J. Friston et al., 2005) in Statistical Parametric Mapping (SPM).
We propose to acquire response data (response times, error rates), and functional brain activation data using fMRI. Therefore, we would have two outcome measures.
From the response data we will evaluate statistically significant differences in response times, error rates, learning curves.
From the BOLD fMRI data, the main outcome would be task specific neural activations that would regress with the behavioral tasks in a General Linear Model.
These measures will further our understanding about how the human brains use strategies during complex task performance. This will lay the foundation to our understanding for how we are capable of generalizing our experiences from specific instances. Such knowledge will also improve our understanding of various aspects of movement genesis, and is likely to eventually shed light on various movement disorders including psychogenic movement disorders and chorea among others.
|Study Design||Time Perspective: Prospective|
|Target Follow-Up Duration||Not Provided|
|Sampling Method||Not Provided|
|Study Population||Not Provided|
|Study Groups/Cohorts||Not Provided|
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Study Completion Date||May 26, 2010|
|Primary Completion Date||Not Provided|
|Ages||18 Years to 60 Years (Adult)|
|Accepts Healthy Volunteers||Yes|
|Contacts||Contact information is only displayed when the study is recruiting subjects|
|Listed Location Countries||United States|
|Removed Location Countries|
|Other Study ID Numbers||080192
|Has Data Monitoring Committee||Not Provided|
|U.S. FDA-regulated Product||Not Provided|
|IPD Sharing Statement||Not Provided|
|Responsible Party||Not Provided|
|Study Sponsor||National Institute of Neurological Disorders and Stroke (NINDS)|
|PRS Account||National Institutes of Health Clinical Center (CC)|
|Verification Date||May 26, 2010|