Individual variability in human brain

Principal Investigators: Hava Siegelmann, University of Massachusetts Amherst and Lilianne Mujica-Parodi, SUNY Stony Brook
Title: Individual variability in human brain connectivity, modeled using multi-scale dynamics under energy constraint
BRAIN Category: Individuality and Variation

Clinical neuroscience currently lacks the tools for probing how biological constraints imposed upon synapses impact functional connectivity patterns. Our long-range goal is to develop these tools, focusing first upon energy constraints across synaptic-hemodynamic scales.

Understanding individual differences in cognitive performance

Principal Investigator: Zhong-Lin Lu, Ohio State and Mark Steyvers, UC Irvine
Title: Understanding individual differences in cognitive performance: Joint hierarchical Bayesian modeling of behavioral and neuroimaging data
BRAIN Category: Individuality and Variation

This project explores a mathematical and computational framework for investigating a large-sample neuroimaging and behavioral dataset in order to improve our understanding of individual differences in cognitive performance

Recording and Stimulating Arm Nerves

Principal Investigator: David Warren, University of Utah
Title: Sensory-Motor Integration via Recording and Stimulating Arm Nerves
BRAIN Category: Individuality and Variation

This project's goal is to create movement and sensation abilities in individuals with amputation that are more similar to that in normally enabled individuals.

qEEG in freely behaving people

Principal Investigator: Jose Luis Contreras-Vidal, University of Houston
Title: Assaying neural individuality and variation in freely behaving people based on qEEG
BRAIN Category: Individuality and Variation

The goals of this research are to uncover neural signals associated with the passive and interactive perception/production of art and to assess the long-term stability of neural activity acquired via quantitative electroencephalography (or qEEG).

Noise in mental exploration for learning

Principal Investigator: Joshua Gold, Neuroscience @Penn
Title: The role of noise in mental exploration for learning
BRAIN Category: Individuality and Variation

In our unpredictable world, decision-makers face an inherent trade-off: higher certainty leads to more precise and accurate choices when the world is stable but an inability to adjust to change, whereas less certainty can lead to greater adaptability but also more variable and imprecise decisions. The investigators propose that this trade-off is regulated by interactions between arousal and cortical systems.

Neural Variability During Motor Learning

Principal Investigator: Steven Chase, CMU
Title: The Structure of Neural Variability During Motor Learning
BRAIN Category: Individuality and Variation

This study will investigate the neural correlates of motor variability and establish the connections between neural variability, behavioral performance, and learning.

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