Computation has fundamentally changed the way we study nature. Recentbreakthroughs in data collection technology, such as GPS and othermobile sensors, high definition cameras, satellite images, and genotyping, aregiving biologists access to data about wild populations, from genetic tosocial interactions, which are orders of magnitude richer than...
Creator:
Berger-Wolf, Tanya (University of Illinois, Chicago)
Created:
2012-02-27
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Work in collaboration with Evren Ozarslan of the National Institutes of Health and Baba Vemuri of the University of Florida.Magnetic resonance can be used to measure the rate and direction of molecular translational diffusion. Combining this diffusion measurement with magnetic resonance imaging methods allows the visualization of 3D motion of mo...
Creator:
Mareci, Thomas H. (University of Florida)
Created:
2006-01-10
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Inferring cause-effect relationships from observations is one of the fundamental challenges in natural sciences and beyond. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics has increased substantially, making scientists face this challenge in ...
Creator:
Davidsen, Jörn (University of Calgary)
Created:
2012-09-05
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
In this talk I will introduce the main mathematical questions arising in the modeling of large-scale neuronal networks involved at functional scales in the brain. Such networks are composed of multiple populations (different neuronal types), in which each neuron has a stochastic dynamics and operate in a random environment. Understanding the col...
Creator:
Touboul, Jonathan D (Collège de France)
Created:
2013-05-17
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
In this talk I will describe recent results on large populations of brain connectivity networks. We analyze sex and kinship relations and their effects in brain networks metrics and topologies. The reported results are obtained in collaboration between the team of Paul Thompson at UCLA and my team at the UofM, in particular Neda Jahanshad and Ju...
Creator:
Sapiro, Guillermo R. (University of Minnesota, Twin Cities)
Created:
2011-10-26
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Synaptic transmission is a central component of neural processing. Short term depression occurs when repeated driving of a synapse reduces its efficacy, a feature that is common across the nervous system. The mechanics of synaptic discharge are well characterized and involve both probabilistic release and uptake of neurotransmitter during activi...
Creator:
Doiron, Brent (University of Pittsburgh)
Created:
2013-05-14
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
With access to large datasets, deep neural networks (DNN) have achieved human-level accuracy in image and speech recognition tasks. However, in chemistry, data is inherently small and fragmented. In this work, we develop various approaches of using rule-based models and physics-based simulations to train ChemNet, a transferable and generalizable...
Creator:
Goh, Garrett (Pacific Northwest National Laboratory)
Created:
2018-03-08
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
This talk investigates the role of feedback in a network of amplifiers. We start by revisiting the theory of the individual feedback amplifier. Then, taking inspiration from neuronal behaviors, we present a simple architecture that makes the network amplification zoomable, allowing for a versatile modulation of the resolution of the network ampl...
Creator:
Sepulchre, Rodolphe (University of Cambridge)
Created:
2015-09-30
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.