Area:
Decision Neuroscience
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High-probability grants
According to our matching algorithm, Baba Shiv is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2004 — 2009 |
Levin, Irwin [⬀] Shiv, Baba |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Interplay of Affect and Cognition in Decision Making: Comparing Emotionally Impaired Patients and Controls
We will study basic decision processes in a patient group known to suffer from the inability to integrate thoughts and feelings when considering the long-term consequences of their decisions. This dysfunction has been tied to lesions in a specific neural circuitry within the brain. This patient population is thus ideal for studying the operation and integration of cognition and emotion in decision making. The logic is as follows: if we can characterize these patients by their inability to integrate thoughts and feelings, and if we can show that these patients are less sensitive than controls to selected variables such as risk level, then we will better understand the factors that play a key role in integrating thoughts and feelings for informed decision making. Controls will include a group of non-patients and a group of patients with lesions in other parts of the brain.
Our interdisciplinary research team has the background and experience to work with the target patient group to determine the neurological underpinnings of their decision making deficits and to create controlled tasks for isolating variables and response systems that differentiate between "informed" and "uninformed" decision making. For example, if our new studies show that the target patients are less responsive to changing risk levels than are controls, then we can assert that distorted perceptions of risk level are a key marker of uninformed decision making. We believe that the broader impact of this work will include: (1) demonstrating to future researchers the usefulness of combining traditional behavioral decision theory approaches with analyses of neural circuitries in the brain; (2) developing a more complete description of factors that differentiate "normal" and "abnormal" decision making; and (3) finding ways to understand and counsel groups with demonstrated deficits in making decisions that serve their best interests.
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