中国神经再生研究(英文版) ›› 2026, Vol. 21 ›› Issue (3): 1124-1125.doi: 10.4103/NRR.NRR-D-24-01244

• 观点:脑损伤修复保护与再生 • 上一篇    下一篇

聚合组件:一种假定大脑功能和大脑连接的构建模块

  

  • 出版日期:2026-03-15 发布日期:2025-07-04

Converging assemblies: A putative building block for brain function and for interfacing with the brain

Eran Stark* , Lidor Spivak   

  1. Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel (Stark E) Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY, USA (Spivak L)
  • Online:2026-03-15 Published:2025-07-04
  • Contact: Eran Stark, MD, PhD, eranstark@sci.haifa.ac.il.
  • Supported by:
    We thank Amir Levi (UCSF, USA) for productive discussions. This work was supported in part by the Rosetrees Trust (#CF-2023-I-2_113) and by the Israel Ministry of Innovation, Science, and Technology (#7393) (to ES).

摘要: https://orcid.org/0000-0002-2446-9140 (Eran Stark)

Abstract: The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems. These networks are characterized by two key properties. First, they exhibit dense interconnectivity (Braitenburg and Schüz, 1998; Campagnola et al., 2022). The strength and probability of connectivity depend on cell type, inter-neuronal distance, and species. Still, every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons. Second, communication between neurons occurs primarily via chemical or electrical synapses. The transmission of information is mediated mainly during presynaptic spiking events that generate postsynaptic inward currents and intracellular depolarization, which in turn induce postsynaptic spikes. However, these two properties alone cannot explain the complex mechanisms of information processing in neuronal networks.