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.

NSF 2015 BRAIN Initiative awards

To support potentially transformative research in neural and cognitive systems, the National Science Foundation (NSF) has awarded 16 grants to multidisciplinary teams from across the United States.

Each award brings together scientists and engineers from diverse fields to investigate brain-related mysteries. The awards fall within two themes: neuroengineering and brain-inspired concepts and designs, and individuality and variation. Each provides up to $1 million over two to four years.

Decoding and Modulation of Human Language

Principal Investigators: Behnaam Aazhang, PhD – Rice and Nitin Tandon, MD - UT Health
Title: Micro-scale Real-time Decoding and Closed-loop Modulation of Human Language
BRAIN Category: Neuroengineering and Brain-inspired concepts and design

The engineering objective is to develop biocompatible microchips to vastly enhance our insight into language and other cognitive processes and learning.

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.

Nanomagnetic Stimulation Capability

Principal Investigators: Sydney Cash, MD/PhD – Mass General and Nian X. Sun, PhD – Northeastern
Title: Nanomagnetic Stimulation Capability for Neural Investigation and Control
BRAIN Category: Neuroengineering and Brain-inspired concepts and design

Abstract not yet available.

Integrating neural interfaces & machine intelligence for prosthetics

Principal Investigators: Charles Liu, PhD - USC; Kapil Katyal, PhD - JHU; Richard Andersen, PhD - Caltech
Title: Integrating neural interfaces and machine intelligence for advanced neural prosthetics
BRAIN Category: Neuroengineering and Brain-inspired concepts and design

This collaborative project will decode high-level cognitive actions from neural signals recorded in the parietal cortex of a tetraplegic human, then carry out those intents using a smart robotic prosthesis. Experimental results will be used to construct BMI control algorithms optimized to decode these cognitive signals.

Identifying Design Principles of Neural Cells

Principal Investigator: Amina Qutub, Rice University
Title: Identifying Design Principles of Neural Cells
BRAIN Category: Neuroengineering and Brain-inspired concepts and design (#1533708)

This proposal seeks to develop a robust theory of how single neural cells form electrically active networks. The project integrates emerging methods in computer science, systems biology, neuroengineering and developmental biology to offer insight into the brain's organization.

A circuit theory of cortical function

Principal Investigator: Charles Gilbert, Rockefeller Unviersity
Title: A circuit theory of cortical function
BRAIN Category: Neuroengineering and Brain-inspired concepts and design (#1532591)

This project aims to develop and test a new conceptual framework for understanding brain function, and informing biologically based artificial intelligence systems. The underlying theory holds that the properties of any neuron and any cortical area are not fixed but undergo state changes with changing perceptual task, expectation and attention.

Imaging synaptic activity using super-resolution cannula microscopy

Principal Investigator: Rajesh Menon - Utah Neuroscience
Title: "Imaging synaptic activity deep in the brain using super-resolution cannula microscopy"
BRAIN Category: Neuroengineering and Brain-inspired concepts and design (#1532591)

This project will develop a tool for high-resolution (<100-nm) imaging of synapses in freely moving animals for neuronal studies. It will accomplish this goal by the development and integration of compact and lightweight cannula microscopy with in vitro fluorescence imaging with accompanying technology and methodologies for imaging synapses.

Neural representation of visual memory

Principal Investigator: Aude Oliva - MIT
Title: Algorithmically explicit neural representation of visual memorability
BRAIN Category: Neuroengineering and brain-inspired concepts and design (#1532591)

We propose to combine three technologies to predict what makes an image memorable or forgettable: neuro-imaging technologies recording where encoding happens in the human brain (spatial scale), when it happens (temporal scale), and what types of computation are performed at the different stages of storage (computational scale.

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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