对海马CA1金字塔神经元和内神经元的适应性通用泄漏整合与火模式
Addolorata Marasco1,2, Emiliano Spera3, Vittorio De Falco4,5
1Department of Mathematics and Applications, University of Naples Federico II, Via Cintia ed. 5A, 80126, Naples, Italy. marasco@unina.it.
Bulletin of mathematical biology
|October 4, 2023
概括
这项研究引入了一种适应性神经元模型,可以准确地捕捉海马神经元中复杂的发射模式. 这项创新增强了计算神经科学模型,以实现更现实的in-silico实验和数字大脑双胞胎.
科学领域:
- 计算神经科学是一种神经科学.
- 生物物理学的生物物理.
- 系统神经科学 系统神经科学
背景情况:
- 现实的神经网络模型对于in-silico实验和数字大脑双胞胎至关重要.
- 当前简化的神经元模型,如通用泄漏的整合和发射,缺乏复制海马体等区域复杂的发射动态的准确性.
- 超级计算的技术限制需要高效但准确的神经元模型.
研究的目的:
- 开发一种可适应的通用漏洞整合和发射模型,能够复制海马CA1神经元和内神经元的复杂发射动态.
- 为了提高模拟海马神经活动的计算模型的准确性.
- 为了创建一个更高效的计算效率,但在生物物理上更现实的神经元模型.
主要方法:
- 提出了一个可适应的通用漏洞整合和发射模型,使用线性普通微分方程与非线性初始和更新条件.
- 运用对平衡稳定性和膜潜在单调性的数学分析来导出模型约束.
- 通过使用各种刺激协议,对85个海马神经元和内神经元的实验数据进行模型验证.
主要成果:
- 适应模型成功地复制了海马神经元和内神经元的非线性发射动态.
- 数学分析提供了限制,降低了参数优化计算成本.
- 该模型量化地复制并预测各种刺激协议的实验痕迹.
- 产生了无法统计区分的合成神经元副本,反映了实验变异性.
结论:
- 拟议的自适应神经元模型比模拟海马功能的现有模型提供了显著的改进.
- 这种方法可以创建大规模的,现实的神经网络模拟,具有受控的发射特性.
- 促进了对认知功能的更准确的in-silico调查和数字大脑双胞胎的发展.
更多相关视频
14:27Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording
Published on: August 11, 2019
12.6K
14:37Whole-cell Patch-clamp Recordings from Morphologically- and Neurochemically-identified Hippocampal Interneurons
Published on: September 30, 2014
24.6K
相关概念视频
01:19The Role of Ion Channels in Neuronal Computation
3.2K
A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
3.2K
01:28Integration of Synaptic Events
1.6K
Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
1.6K