Area:
computation & theory
We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Mark S. Goldman is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2006 — 2009 |
Goldman, Mark S |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Neural Integration With Active Dendrites and Inhibition @ University of California Davis
[unreadable] DESCRIPTION (provided by applicant): Persistent neural activity has been observed in a wide range of brain regions and has been implicated in functions ranging from information storage and processing to motor control. Deficits in persistent neural activity in working memory areas of the brain have been suggested as a core feature of schizophrenia. The proposed work seeks to reveal the neural mechanisms underlying persistent neural activity by computational modeling of a model system exhibiting persistent neural activity, the goldfish oculomotor neural integrator. The oculomotor neural integrator receives velocity-coded eye movement commands and converts these into signals that control the position of the eyes. In the absence of velocity commands, neurons in the integrator maintain a steady rate of firing for tens of seconds. Patients with impaired neural integrators are unable to maintain a steady gaze and have deficits in eye tracking behavior and ocular reflexes. Previous models of the oculomotor system have neglected important features that have made them unable to be tested explicitly by experiment. Using a novel framework that allows data to be directly incorporated, an experimentally constrained and verifiable model of the goldfish oculomotor neural integrator will be constructed. The model will be used to analyze network and cellular contributions to persistent neural activity. The contributions of synaptic excitation, synaptic inhibition, and intrinsic neuronal excitability will be assessed by modeling recent anatomical and pharmacological manipulations of persistent neural activity in the system. Preliminary modeling at the network level suggests that recurrent interactions between cells are mediated by a bistable dendritic process that is hypothesized to be a dendritic plateau potential. A network model with dendritic branching structures and voltage-sensitive synaptic and intrinsic conductances will be constructed to test the hypothesis that voltage-dependent dendritic properties increase the robustness of the network to perturbations. The model will be constrained by intracellular recordings in slice and in vivo and will be compared to dendritic imaging experiments currently being conducted in the consultants' laboratories. By producing an experimentally constrained and verifiable model in a well-characterized system, this work promises to reveal core mechanisms by which persistent neural activity is generated. [unreadable] [unreadable] [unreadable]
|
1 |
2012 — 2016 |
Goldman, Mark Aksay, Emre |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Crcns: Collaborative Research: the Role of Dendritic Processing in Persistent Neural Activity @ University of California-Davis
Memories on the time scale of seconds to tens of seconds are stored as patterns of neural activity that persist long after the offset of a stimulus. This persistent neural activity is believed to be critical for processing new information and forming cognitive perceptions. Recent studies suggest that purely circuit-based mechanisms are insufficient to explain the robustness of persistent activity to biological noise and perturbation. This proposal will test the hypothesis that persistent activity is maintained by a hybrid cellular/circuit mechanism in which circuit level feedback mediates the activation of memory processes in a neuron's dendrites known as plateau potentials. To quantitatively understand how active dendritic properties contribute to persistent activity, a new modeling framework will be developed to directly and simultaneously fit a memory network to data from a diverse set of experiments characterizing intrinsic excitability, anatomical connectivity, neural coding, and response to perturbations. These models will be used to predict the patterns of dendritic activity that can be seen with fluorescence calcium imaging. To test these predictions, the zebrafish preparation will be used to directly measure dendritic activity during eye movement behavior from cells storing a memory of desired eye position. Two-photon imaging of calcium indicators will be used to measure spatiotemporal patterns of activity in the dendritic neuropil, and separately in individual dendritic branchlets, to determine the presence of plateau potentials. Together, these computational and experimental results will help determine how cellular and circuit properties work in concert to generate one of the most important brain dynamics, persistent neural activity.
|
0.915 |
2012 — 2015 |
Goldman, Mark Mulloney, Brian [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Encoding Information That Coordinates Distributed Neural Microcircuits @ University of California-Davis
A major goal of neuroscience is to understand the dynamics of neural circuits. In most cases, ignorance of intrinsic neural properties and the synaptic organization of circuits limit our ability to understand a circuit's function or to cure disorders of the nervous system caused by its malfunction. Modulation by transmitters and hormones can change the properties of neurons and synapses in these circuits dramatically, but leave some features of the circuit's performance strangely unmodified. This project exploits new discoveries of the synaptic organization of a circuit in the crayfish central nervous system (CNS) that coordinates limb movements during locomotion. This coordinating circuit links four pairs of modular local circuits distributed in different parts of the CNS that control individual limbs and are active during locomotion. Periodic motor output from these local circuits is synchronized, but occurs with a stable difference in phase between neighboring circuits. The goal of this research is to understand and explain in cellular terms the encoding of information needed to coordinate these distributed circuits. Electrophysiological experiments and computational analyses will be used to study and model encoding of information by the circuit's key coordinating neurons.
How stable phase differences are maintained in the face of neuromodulation is a deep problem. For example, cholinergic modulation of this system changes the period and strength of its motor output, but does not affect the phase differences between neighboring circuits. Electrophysiological and pharmacological experiments will be used to analyze how cholinergic modulation tunes encoding so that phase remains constant when period changes. This research will generate insights and analytical methods that can be applied to similar systems in the brain stem and spinal cord, and to rhythmic neural circuits in the brain. Student participants will be involved in all aspects of the project. The results will also be directly applicable to the development of flexible and adaptive robotic devices.
|
0.915 |