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Research Spending & Results

Award Detail

Doing Business As Name:Vanderbilt University
  • Christos Constantinidis
  • (336) 716-7424
Award Date:09/19/2021
Estimated Total Award Amount: $ 670,680
Funds Obligated to Date: $ 670,680
  • FY 2020=$670,680
Start Date:01/01/2021
End Date:12/31/2023
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CRCNS US-Spain Research Proposal: Serial dependence in working memory
Federal Award ID Number:2127748
DUNS ID:965717143
Parent DUNS ID:004413456
Program:CRCNS-Computation Neuroscience
Program Officer:
  • Jonathan Fritz
  • (703) 292-7923

Awardee Location

Street:Sponsored Programs Administratio
Awardee Cong. District:05

Primary Place of Performance

Organization Name:Vanderbilt University
Street:PMB 407749 2301 Vanderbilt Place
Cong. District:05

Abstract at Time of Award

Working memory, the ability to retain and manipulate information over a period of seconds, represents a core component of higher cognitive functions, including language, problem solving, reasoning, and abstract thought. Working memory capacity accounts for a great proportion of individual variability in academic performance, and it is impaired in clinical conditions including schizophrenia, stroke, traumatic brain injury, and ADHD. Understanding the neural basis of working memory has been a question in the forefront of scientific research over the past few years. This project relies on an “imperfection” of working memory, serial dependence: the contents of memory in a previous trial often affect what is being recalled in a following one, even though this is no longer useful. Serial dependences can provide insight into cellular mechanisms and neurotransmitter systems. Patients with genetic conditions such as schizophrenia, autism, and encephalitis exhibit different patterns of serial dependence. This project forms a collaborative experimental and theoretical approach to understand the role of different neurotransmitter systems and brain areas in serial dependence, which will reveal fundamental properties of the circuits that mediate working memory. Beyond the immediate goals of the experiments, understanding the neural basis of working memory and developing mechanistic models that capture its properties is expected to have broader impacts on a number of scientific fields, including neuroscience, psychology, cognitive science, computer science, and machine learning. The combined experimental-modeling approach has also direct relevance to understanding and treating these clinical conditions. The approach opens new avenues of model-guided research in neuropsychiatric conditions and enhances the reach of computational psychiatry. Working memory has been linked to the prefrontal cortex, an area central to cognitive processing, with unique anatomical and cellular organization. NMDA receptors, which are abundant in the prefrontal cortex, are suspected to play a critical role for the maintenance of information in working memory, by virtue of their ability to maintain neurons at an excited state for an extended period of time, and to induce plasticity of synaptic connections. Direct evidence linking their cellular role to working memory behavior has been scant, however. This project will address the circuit mechanisms by which NMDA receptors support working memory function. We will rely on a novel approach, by investigating the mechanisms of history biases, as a manifestation of long-lasting NMDAR-dependent mechanisms in working memory. Serial dependencies are systematically affected in patients with schizophrenia and anti-NMDAR encephalitis, suggesting an underlying NMDAR-dependent mechanism. Experiments will train non-human primates to perform spatial working memory tasks; obtain single neuron neurophysiological recordings and local field potentials from dorsolateral prefrontal and posterior parietal cortex; administer NMDAR antagonists systemically; and use optogenetic cortical stimulation to test behavioral and physiological predictions of a computational model of serial biases. Analysis of neural data and computational modeling will integrate the results of the experiments in a fronto-parietal network model. This will shed light on the role of prefrontal NMDA receptors in shaping history-dependent biases, and the importance of local-circuit (intrinsic) connections and long-range connections. Specifying subunit-specific NMDAR mechanisms, and the role of the fronto-parietal network, will inform a new computational framework with biophysical detail and enhanced predictive power for subsequent experimentation. The project is expected to advance understanding of cognitive processes and the neural networks mediating them. A companion project is being funded by the National Institute of Health Carlos III, Spain (ISCIII). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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