2009 — 2010 |
Middlebrooks, Paul G |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
The Neural Basis of Metacognition @ University of Pittsburgh At Pittsburgh
DESCRIPTION (provided by applicant): Humans possess the useful ability to monitor and control our own cognition, a phenomenon known as metacognition. This ability is essential to our sense of volition, confidence, and self-awareness, giving metacognition a broad clinical relevance. Functional magnetic resonance imaging (fMRI) and lesion studies suggest which particular brain regions may contribute to metacognitive processes, but the neural basis of metacognition remains to be explored. The primary goal of this proposal is to elucidate neuronal mechanisms underlying metacognition. To do this, existing metacognition behavioral paradigms will be adapted into a visual oculomotor task suitable for neurophysiology. The first specific aim is to test the hypothesis that the new metacognition task elicits metacognitive behavior. An operational definition of metacognitive behavior will be established, and psychophysical results will be analyzed to determine whether they meet the established criteria. The second specific aim is to test the hypothesis that metacognitive processes can be characterized at the single cell level. Single neuron activity will be recorded from specific cortical sites during performance of the metacognition task. Based on cortical regions previously established as important for visual, oculomotor, and higher cognitive functioning, and guided by metacognition fMRI studies, single neurons will be recorded from frontal eye field (FEF), dorsolateral prefrontal cortex (DLPFC), and supplementary eye field (SEF). Predictions will be tested regarding the types of responses likely to arise in each of these cortical regions. The third specific aim is to establish the functional roles of each of the cortical areas using reversible inactivation during performance of the metacognition task. This researched proposed herein will begin to elucidate the neural basis of metacognition, and will provide a foundation for future metacognition research. PUBLIC HEALTH RELEVANCE: The research proposed herein will begin to elucidate the neural basis of metacognition, and will provide a foundation for future metacognition research. Metacognitive deficits have been implicated in a range of pathologies, such as schizophrenia, Parkinson's disease, and Alzheimer's disease. Understanding the neural basis of metacogntion will help understand how to treat patients with such disorders. Currently, metacognition-based therapies are also being used as a tool to treat obsessive-compulsive disorder, post-traumatic stress disorder, and to improve learning in mentally disabled individuals.
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1 |
2014 — 2016 |
Middlebrooks, Paul G |
F32Activity Code Description: To provide postdoctoral research training to individuals to broaden their scientific background and extend their potential for research in specified health-related areas. |
Neuronal Mechanisms of Response Inhibition During Decision Making
DESCRIPTION (provided by applicant): Decades of research have been devoted to our ability to control whether we act and which action to make, but no neuroscience research has tested how these two vital cognitive functions work together. This study will be the first to specifically and thoroughly test this, from behavior to brain. The overall hypothesis is that distinct pools of neurons independently implement the two processes. Response inhibition is a form of executive control, exercised when an imminent action needs to be canceled. It has been extensively studied using the stop signal paradigm, and is now diagnostic for many psychiatric and neurological disorders. The task typically requires responding to a choice stimulus, but inhibiting the response when an infrequent stop signal is presented. The difficulty of canceling a response varies with the delay between the choice stimulus and subsequent stop signal, the stop signal delay (SSD). Inhibition is easier for shorter SSDs. The race model explains performance of the task as a race between stochastic GO and STOP processes. If the GO process finishes before the STOP process, a response is made, but if the STOP process finishes first the response is withheld. The model accounts for correct and error response times (RTs) and provides ways to estimate the duration of the covert stopping process. A saccade stop task with rhesus macaques found neuronal correlates of the GO and STOP processes in the frontal eye field (FEF). These neural data refined the race model from a cognitive process model into a brain mechanism model. However, the model and the associated behavior and single neuron data in monkeys addressed saccades to single targets. Nearly all stop signal studies in humans have used choice RT tasks, in which subjects discriminate a choice stimulus to respond. Both cognitive and neural race models lack an account of the categorical decision required by choice RT tasks. The neuronal basis of categorical decision-making has been explored extensively but has made little contact with the neuronal basis of response inhibition. Decision-making studies typically use a two-alternative forced choice task. Drift diffusion models explain decisions as a diffusion process between choice boundaries. Neuronal correlates of the diffusion have been found in FEF. The major research goal of this proposal is to integrate behavioral and neural decision making into the race model of response inhibition. The aims are (1) to explore neuronal mechanisms underlying response inhibition and decision making by recording neural activity in FEF of macaque monkeys performing a choice RT stop signal task, and (2) to develop a model that integrates response inhibition and decision-making and accounts for behavior and neurophysiology. The first major training goal of this proposal is to expand the applicant's neurophysiological skill set, building on previous experience. The second major training goal is to acquire expertise in cognitive modeling with stochastic accumulators. This research training coupled with professional development activities will build the foundation for the applicant's long-term goal of becoming an independent researcher in visual neuroscience.
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0.948 |