Reverse engineering the cognitive brain.
作者信息
Cauwenberghs Gert
机构信息
Department of Bioengineering and Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093-0412.
出版信息
Proc Natl Acad Sci U S A. 2013 Sep 24;110(39):15512-3. doi: 10.1073/pnas.1313114110. Epub 2013 Sep 12.
Abstract
摘要
相似文献
1
Reverse engineering the cognitive brain.逆向工程认知大脑。
Proc Natl Acad Sci U S A. 2013 Sep 24;110(39):15512-3. doi: 10.1073/pnas.1313114110. Epub 2013 Sep 12.
2
Computational modeling of high-level cognition and brain function.高级认知与脑功能的计算建模
Hum Brain Mapp. 1999;8(2-3):128-36. doi: 10.1002/(SICI)1097-0193(1999)8:2/3<128::AID-HBM10>3.0.CO;2-G.
3
Towards predictive neural network dynamical theory: Comment on "The growth of cognition: Free energy minimization and the embryogenesis of cortical computation" by Wright and Bourke.迈向预测神经网络动力学理论：对赖特和伯克所著《认知的发展：自由能最小化与皮层计算的胚胎发生》的评论
Phys Life Rev. 2021 Mar;36:30-32. doi: 10.1016/j.plrev.2020.08.006. Epub 2020 Sep 3.
4
Topographical dynamics of brain connections for the design of asynchronous brain-computer interfaces.用于异步脑机接口设计的脑连接拓扑动力学
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:2520-3. doi: 10.1109/IEMBS.2007.4352841.
5
Construction and Supervised Learning of Long-Term Grey Cognitive Networks.长期灰色认知网络的构建与有监督学习。
IEEE Trans Cybern. 2021 Feb;51(2):686-695. doi: 10.1109/TCYB.2019.2913960. Epub 2021 Jan 15.
6
A Model for Structured Information Representation in Neural Networks of the Brain.大脑神经网络中的结构化信息表示模型。
eNeuro. 2020 May 29;7(3). doi: 10.1523/ENEURO.0533-19.2020. Print 2020 May/Jun.
7
Neural networks in the study of the brain.大脑研究中的神经网络。
Mol Chem Neuropathol. 1996 May-Aug;28(1-3):231-5. doi: 10.1007/BF02815227.
8
Emergence of cognitive priming and structure building from the hierarchical interaction of canonical microcircuit models.认知启动和结构构建从典型微电路模型的分层相互作用中浮现。
Biol Cybern. 2019 Jun;113(3):273-291. doi: 10.1007/s00422-019-00792-y. Epub 2019 Feb 14.
9
Operational principles of neurocognitive networks.神经认知网络的运作原理。
Int J Psychophysiol. 2006 May;60(2):139-48. doi: 10.1016/j.ijpsycho.2005.12.008. Epub 2006 Feb 21.
10
Community detection for directional neural networks inferred from EEG data.从脑电图（EEG）数据推断出的定向神经网络的社区检测
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:7155-8. doi: 10.1109/IEMBS.2011.6091808.
引用本文的文献
1
Artificial intelligence meets brain theory (again).人工智能（再次）邂逅大脑理论。
Biol Cybern. 2025 Jun 28;119(4-6):16. doi: 10.1007/s00422-025-01013-5.
2
Infant neuroscience: how to measure brain activity in the youngest minds.婴儿神经科学：如何测量最年轻的大脑的活动。
Trends Neurosci. 2024 May;47(5):338-354. doi: 10.1016/j.tins.2024.02.003. Epub 2024 Apr 3.
3
Emotions as Abstract Evaluation Criteria in Biological and Artificial Intelligences.情感作为生物智能和人工智能中的抽象评估标准
Front Comput Neurosci. 2021 Dec 14;15:726247. doi: 10.3389/fncom.2021.726247. eCollection 2021.
4
Markov Chain Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission for Neuromorphic Computing.用于神经形态计算的突触传递中电化学反应扩散的马尔可夫链抽象
Front Neurosci. 2021 Nov 29;15:698635. doi: 10.3389/fnins.2021.698635. eCollection 2021.
5
Materials for emergent silicon-integrated optical computing.用于应急硅集成光学计算的材料。
J Appl Phys. 2021 Aug 21;130(7):070907. doi: 10.1063/5.0056441. Epub 2021 Aug 19.
6
Novel hardware and concepts for unconventional computing.新型硬件和非常规计算概念。
Sci Rep. 2020 Jul 16;10(1):11843. doi: 10.1038/s41598-020-68834-1.
7
Sparse Coding Using the Locally Competitive Algorithm on the TrueNorth Neurosynaptic System.在TrueNorth神经突触系统上使用局部竞争算法的稀疏编码
Front Neurosci. 2019 Jul 23;13:754. doi: 10.3389/fnins.2019.00754. eCollection 2019.
8
Brain-inspired automated visual object discovery and detection.脑启发式自动化视觉目标发现与检测。
Proc Natl Acad Sci U S A. 2019 Jan 2;116(1):96-105. doi: 10.1073/pnas.1802103115. Epub 2018 Dec 17.
9
Data and Power Efficient Intelligence with Neuromorphic Learning Machines.基于神经形态学习机器的数据与功率高效智能
iScience. 2018 Jul 27;5:52-68. doi: 10.1016/j.isci.2018.06.010. Epub 2018 Jul 3.
10
Connecting the Brain to Itself through an Emulation.通过模拟实现大脑自身的连接。
Front Neurosci. 2017 Jun 30;11:373. doi: 10.3389/fnins.2017.00373. eCollection 2017.
本文引用的文献
1
Synthesizing cognition in neuromorphic electronic systems.神经形态电子系统中的认知综合。
Proc Natl Acad Sci U S A. 2013 Sep 10;110(37):E3468-76. doi: 10.1073/pnas.1212083110. Epub 2013 Jul 22.
2
Nanotools for neuroscience and brain activity mapping.用于神经科学和大脑活动测绘的纳米工具。
ACS Nano. 2013 Mar 26;7(3):1850-66. doi: 10.1021/nn4012847. Epub 2013 Mar 20.
3
An efficient learning procedure for deep Boltzmann machines.一种深度玻尔兹曼机的有效学习过程。
Neural Comput. 2012 Aug;24(8):1967-2006. doi: 10.1162/NECO_a_00311. Epub 2012 Apr 17.
4
Neuromorphic silicon neuron circuits.神经形态硅神经元电路。
Front Neurosci. 2011 May 31;5:73. doi: 10.3389/fnins.2011.00073. eCollection 2011.
5
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing.基于相变材料的纳米电子可编程突触用于类脑计算。
Nano Lett. 2012 May 9;12(5):2179-86. doi: 10.1021/nl201040y. Epub 2011 Jun 14.
6
Neuromorphic sensory systems.神经形态感觉系统。
Curr Opin Neurobiol. 2010 Jun;20(3):288-95. doi: 10.1016/j.conb.2010.03.007. Epub 2010 May 20.
7
CAVIAR: a 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing- learning-actuating system for high-speed visual object recognition and tracking.CAVIAR：一个用于高速视觉目标识别与跟踪的拥有4.5万个神经元、500万个突触、每秒120亿次连接的气动神经硬件传感-处理-学习-驱动系统。
IEEE Trans Neural Netw. 2009 Sep;20(9):1417-38. doi: 10.1109/TNN.2009.2023653. Epub 2009 Jul 24.
8
Simple substrates for complex cognition.复杂认知的简单底物。
Front Neurosci. 2008 Dec 15;2(2):255-63. doi: 10.3389/neuro.01.031.2008. eCollection 2008 Dec.
9
Transient cognitive dynamics, metastability, and decision making.瞬态认知动力学、亚稳定性与决策
PLoS Comput Biol. 2008 May 2;4(5):e1000072. doi: 10.1371/journal.pcbi.1000072.
Zotero 插件