生物可信的可重新配置的尖端神经元用于神经形态计算
Yu Xiao1, Yize Liu2,3, Bihua Zhang1
1College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Science advances
|February 5, 2025
概括
这项研究介绍了一种使用电化学记忆 (ECRAM) 进行神经形态计算的新型生物可信的神经元模型. 这种设计能够实现多样化的尖端行为,提高神经网络的分类准确性.
科学领域:
- 神经科学是一个神经科学.
- 材料科学 材料科学 材料科学
- 计算机工程 计算机工程
背景情况:
- 生物神经元表现出复杂的尖端模式,对于神经计算至关重要.
- 当前的神经形态系统经常使用简化的模型,限制了它们的生物可信性和功能.
- 在硬件中模拟复杂的生物尖峰模式在计算上是昂贵的.
研究的目的:
- 开发一个紧的,可重新配置的神经元设计,以模拟生物可信的尖端动态.
- 为了利用基于NbO2的尖端单元和电化学记忆 (ECRAM) 的内在特性,用于神经元建模.
- 在神经形态环境中展示射击模式和适应性行为的灵活重新配置.
主要方法:
- 提出了一种新的神经元设计,将一个基于NbO2的尖端单元与ECRAM集成在一起.
- 利用ECRAM的可调节电阻来控制膜潜力的时间动态.
- 实施了各种生物可信的发射模式,包括相位和爆发式.
- 构建了采用开发的生物可信神经元模型的尖端神经网络 (SNN).
主要成果:
- 成功模拟了生物神经元特征的快慢动态.
- 实现了发射模式 (相位,爆发) 的灵活重新配置和自适应性尖端.
- 与简化模型相比,在使用爆发神经元的SNN中证明了更好的分类准确性.
- 展示了更多生物可信的神经形态计算系统的潜力.
结论:
- 拟议的基于ECRAM的神经元设计为模拟复杂的生物神经元动态提供了具有成本效益的解决方案.
- 这种方法可以实现灵活和适应性的尖端行为,增强神经形态系统的能力.
- 开发的模型显示了促进生物可信的神经形态计算和人工智能的重大前景.
相关概念视频
01:01Neuroplasticity
272
Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
272
01:28Neuronal Communication
760
Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
760
01:25Neural Circuits
1.0K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.0K
01:19The Role of Ion Channels in Neuronal Computation
3.1K
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....
3.1K