MODELING OF NON LINEAR DYNAMICS OF RENAL AUTOREGULATION
肾脏自动调节的非线性动力学建模
基本信息
- 批准号:6611238
- 负责人:
- 金额:$ 15.58万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2002
- 资助国家:美国
- 起止时间:2002-09-01 至 2003-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
During this past year we have made major progress on developing
and applying several of the essential modeling methodologies for
input/output, or nonparametric, models of point-process input neural
systems such as the hippocampus. First, we have pursued development
and application of adaptive estimation procedures for decomposition
studies of the hippocampus. Using this approach, we have been able to
successfully estimate linear and nonlinear properties of negative
feedback elements (analogous to inhibitory interneurons) given
input/output data for only the feedthrough element in the presence and
absence of inhibition, i.e., without direct observations from the
feedback pathway. Second, we have developed a new means for
estimating input/output properties of neural elements using artificial
(feedforward) neural networks, which we have demonstrated is
particularly powerful for estimating higher order nonlinearities from
electrophysiological data. We are particularly excited about the
potential for expanding this approach for estimating higher order
cross-kernels for multiple-input conditions. Third, for the first
time we have applied our nonlinear systems approach at the level of
intracellularly recorded synaptic potentials. We have recently
modeled the closed- and open-loop AMPA and NMDA components of
glutamatergic synaptic input to hippocampal neurons, have derived a
representation of the dynamics of the positive feedback to the NMDA
receptor-channel, and can accurately predict control EPSPs to a wide
range of input patterns. In addition, the model can account for
differences between closed- and open-loop NMDA receptor-mediated
synaptic responses. These are two of the most widely studied receptor
subtypes, as the dynamics of their interaction determine the direction
and magnitude of activity-dependent synaptic plasticity in
hippocampus, neocortex, and other brain regions. Finally, we have
made considerable progress in developing highly efficient circuit
designs for analog VLSI implementation of kernel models of hippocampal
neurons, a direction that should provide the means for developing
massively parallel architectures for simulating global hippocampal
system properties.
在过去的一年里,我们在发展方面取得了重大进展
项目成果
期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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DONALD J MARSH其他文献
DONALD J MARSH的其他文献
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{{ truncateString('DONALD J MARSH', 18)}}的其他基金
MODELING OF NON LINEAR DYNAMICS OF RENAL AUTOREGULATION
肾脏自动调节的非线性动力学建模
- 批准号:
6480874 - 财政年份:2001
- 资助金额:
$ 15.58万 - 项目类别:
MODELING OF NON LINEAR DYNAMICS OF RENAL AUTOREGULATION
肾脏自动调节的非线性动力学建模
- 批准号:
6205814 - 财政年份:1999
- 资助金额:
$ 15.58万 - 项目类别:
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