Paige has been working on cancer cells in Nitin Agrawal’s lab at the Krasnow Institute, and will continue her research this summer by looking at how cancer cells react to a low-oxygen environment. She plans to start another degree in the fall, majoring in Bioengineering at the Volgenau School.
You can learn more about Paige in this NBC4 News piece, as well as in the Washington Post.
The symposium is held annually to promote collaboration among the various subfields of neuroscience, to allow students and faculty to explore diverse research being conducted at Mason, and to foster relationships and collaboration among researchers. This year’s program featured a keynote by Dr. Hongkui Zeng (Allen Institute for Brain Science), and talks by Dr. Rebekah Evans (National Institutes of Health) and Dr. Eswar P.R. Iyer (Harvard Medical School), as well as a poster session and reception.]]>
The 4-VA collaborative was created in 2010 by the presidents of George Mason University, James Madison University, University of Virginia and Virginia Tech. One of its goals is to increase collaborative research among member institutions and expand opportunities for Virginians to complete their education. 4-VA is funded and supported by the state legislature.
Many of Krasnow’s research teams rely heavily on microscopy for their cutting-edge work on the mind, the brain, and complex adaptive systems. Advances in microscopy can push back the boundaries of our insight into human thought processes. Dr. Betzig’s ground-breaking work uses fluorescent molecules to circumvent previous limitations of optical microscopy.
In his lecture, Dr. Betzig gave an engaging overview of his lengthy collaborative project to develop new, super-resolution optical tools to answer the complex questions arising from our deepening understanding of biological systems. In addition, he sketched his own non-traditional career and life experiences. For more, you can read Michele McDonald’s article on Dr. Betzig’s visit here.
The Monday Seminars Series will resume on 2/16/2015 with a talk by Dr. Zayd Khaliq entitled Excitability and Synaptic Integration in Midbrain Dopamine Neurons.]]>
This seminar has been canceled due to inclement weather, but we hope to reschedule Dr. Khaliq for a later date.
The goal of our research is to understand the mechanism of synaptic integration and excitability of neurons located in the basal ganglia. Initial efforts in the lab have focused primarily on synaptic and dendritic properties of dopamine-releasing neurons located in the substantia nigra, which play a central role in reward and motor behaviors. In particular, our work focuses on how synaptic inputs interact with active ionic conductances present in the dendrites of dopamine neurons to produce reward-relevant firing patterns such as “burst firing” – high-frequency bursts of action potentials that result in a transient spike in the concentration of dopamine released in the striatum, a brain region critical for action selection and goal-directed behaviors. The presentation will cover our recent work that examines how background tonic activity shapes dendritic excitability and burst firing in dopamine neurons.]]>
We recently developed a free-propagator reweighting (FPR) algorithm that solves reaction-diffusion (RD) dynamics of systems at single particle resolution both accurately and efficiently. The full spatio-temporal resolution of this RD method allows us to model complex biological systems where details like spatial gradients or particle assembly render simple rate-based kinetics insufficient. The treatment of proteins at single-particle resolution also allows us to begin building in further molecular details into the physics of the binding interactions, such as multiple domains in proteins, rotational and orientational effects, and interaction potentials. We have recently used our method to quantify the effect of membrane recruitment in altering the equilibrium and time-scales of protein binding interactions relative to their behavior in solution, which has implications for understanding the mechanisms of clathrin-coat formation in the early stages of endocytosis. Finally, we have used our RD simulations and new theoretical results to characterize the limitations of modeling reactions dynamics in 2D using simple rate-based kinetics. The use of rate equations assumes a well-mixed system over the lengthscale of the (sub)volume being modeled, and additionally assumes a single rate-constant parameterizes association between binding partners. In 2D, however, the second assumption of a single characteristic rate constant is not generally true. Understanding when this approximation breaks down is critical both for accurate simulations and for robust parameterization of experimental binding data. We determine in what regimes a single rate is appropriate, and when additional parameterization is necessary. Because the use of rate equations provide an efficient and widely used tool for simulating reaction dynamics, we introduce a concentration dependent rate constant in 2D as an approximate representation of the more microscopic dynamics dependent on the multi-parameter model.]]>
Abstract. Neuromorphic engineering takes inspiration from biology to design brain-like systems that are extremely low-power, fault-tolerant, and capable of adaptation to complex environments. The field of neurorobotics has grown into an exciting area of research and engineering. The common goal is twofold: 1) Developing systems that demonstrate some level of cognitive ability could lead to a better understanding of the neural machinery that realizes cognitive function. 2) Deep theoretical understanding of cognition, neurobiology and behavior obtained by constructing physical systems could lead to a system that demonstrates capabilities commonly found in the animal kingdom, but rarely found in artificial systems. Because of limitations in computation, sensor technology, and robot platforms, combining large-scale neural models with robotics was difficult in the past. In a recent project, we used our GPU accelerated spiking neural network simulator to develop a large-scale model of the visual motion perception pathway in the mammalian cortex. I will present results in which we embody this model on an autonomous mobile robot that leverages smartphone technology. I will discuss the advantages of this approach and how it might lead to future neuromorphic applications.]]>