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Mathematical Physics
Mathematical Physics: the application of mathematics to problems in physics and the development of mathematical methods suitable for such applications and for the formulation of physical theories. It is a branch of applied mathematics, but deals with physical problems. Mathematical physics seeks to apply rigorous mathematical ideas to problems in physics, or problems inspired by physics. As such, it is a remarkably broad subject. Mathematics and Physics are traditionally very closely linked subjects.
C.E. CREDITS
Computational or mathematical modeling generally refers to a mechanism-based formalism that help us test hypotheses, expand our understanding of a system, or make mechanism-aware predictions...
C.E. CREDITS
Threshold-linear networks (TLNs) display a wide variety of nonlinear dynamics including multistability, limit cycles, quasiperiodic attractors, and chaos. Over the past few years, we have de...
C.E. CREDITS
Cortical circuits often receive multiple inputs from upstream populations with non-overlapping stimulus tuning. Both the feedforward and recurrent architectures of the receiving cortical lay...
C.E. CREDITS
We will show how to combine large scale neural recordings and mechanistic neural network models to advance our conceptual understanding of how neural circuits mediate cognitive functions lik...
C.E. CREDITS
Learning Objections: 1. To learn a new approach to understanding brain function by creating networks to perform tasks using machine learning. 2. To learn how how to probe these networks to d...
C.E. CREDITS
Learning Objectives: 1. Delineate the goals of studies of brain, computation and behavior and how they can be integrated. 2. Describe how neuromodulators such as oxytocin transform circuits...
APR 15, 2021
7:00 AM PDT
APR 15, 2021
7:00 AM PDT
Date: April 15, 2021 Time: 7:00am (PDT), 10:00am (EDT) In widefield fluorescence microscopy both the contrast and resolution of a captured image is corrupted by light collected from adjacent...
As ‘omics research advances, separations data such as chromatograms and nuclear magnetic resonance (NMR) spectra are being used as direct inputs to machine-learning algorithms ranging...
