Criticality and universality in neuronal cultures during “up” and “down” states

IF 3.4 3区 医学 Q2 NEUROSCIENCES
Mohammad Yaghoubi, Javier G. Orlandi, Michael A. Colicos, Jörn Davidsen
{"title":"Criticality and universality in neuronal cultures during “up” and “down” states","authors":"Mohammad Yaghoubi, Javier G. Orlandi, Michael A. Colicos, Jörn Davidsen","doi":"10.3389/fncir.2024.1456558","DOIUrl":null,"url":null,"abstract":"The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow. Another phenomenon observed during sleep, under anesthesia, and in <jats:italic>in vitro</jats:italic> cultures, is that cortical and hippocampal neuronal networks alternate between “up” and “down” states characterized by very distinct firing rates. Previous theoretical work has been able to relate these two concepts and proposed that only up states are critical whereas down states are subcritical, also indicating that the brain spontaneously transitions between the two. Using high-speed high-resolution calcium imaging recordings of neuronal cultures, we test this hypothesis here by analyzing the neuronal avalanche statistics in populations of thousands of neurons during “up” and “down” states separately. We find that both “up” and “down” states can exhibit scale-free behavior when taking into account their intrinsic time scales. In particular, the statistical signature of “down” states is indistinguishable from those observed previously in cultures without “up” states. We show that such behavior can not be explained by network models of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression, even when realistic noise levels, spatial network embeddings, and heterogeneous populations are taken into account, which instead exhibits behavior consistent with previous theoretical models. Similar differences were also observed when taking into consideration finite-size scaling effects, suggesting that the intrinsic dynamics and self-organization mechanisms of these cultures might be more complex than previously thought. In particular, our findings point to the existence of different mechanisms of neuronal communication, with different time scales, acting during either high-activity or low-activity states, potentially requiring different plasticity mechanisms.","PeriodicalId":12498,"journal":{"name":"Frontiers in Neural Circuits","volume":"28 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Neural Circuits","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fncir.2024.1456558","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow. Another phenomenon observed during sleep, under anesthesia, and in in vitro cultures, is that cortical and hippocampal neuronal networks alternate between “up” and “down” states characterized by very distinct firing rates. Previous theoretical work has been able to relate these two concepts and proposed that only up states are critical whereas down states are subcritical, also indicating that the brain spontaneously transitions between the two. Using high-speed high-resolution calcium imaging recordings of neuronal cultures, we test this hypothesis here by analyzing the neuronal avalanche statistics in populations of thousands of neurons during “up” and “down” states separately. We find that both “up” and “down” states can exhibit scale-free behavior when taking into account their intrinsic time scales. In particular, the statistical signature of “down” states is indistinguishable from those observed previously in cultures without “up” states. We show that such behavior can not be explained by network models of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression, even when realistic noise levels, spatial network embeddings, and heterogeneous populations are taken into account, which instead exhibits behavior consistent with previous theoretical models. Similar differences were also observed when taking into consideration finite-size scaling effects, suggesting that the intrinsic dynamics and self-organization mechanisms of these cultures might be more complex than previously thought. In particular, our findings point to the existence of different mechanisms of neuronal communication, with different time scales, acting during either high-activity or low-activity states, potentially requiring different plasticity mechanisms.
神经元培养在 "上升 "和 "下降 "状态下的临界性和普遍性
大脑可以被视为一个自组织的动态系统,它能优化信息处理和存储能力。从小型神经元集合到整个大脑的跨尺度研究都证明了这一点,在这些研究中,神经元活动表现出与统计物理学中的相变相关的典型特征。这种临界状态的特征是无尺度统计的出现,例如,信息流级联过程所对应的活动雪崩的大小和持续时间。在睡眠、麻醉和体外培养过程中观察到的另一个现象是,大脑皮层和海马神经元网络会在 "上升 "和 "下降 "状态之间交替,这两种状态的特点是发射率截然不同。以前的理论研究能够将这两个概念联系起来,并提出只有 "上升 "状态才是临界状态,而 "下降 "状态则是亚临界状态,这也表明大脑会自发地在这两种状态之间转换。利用对神经元培养物的高速高分辨率钙成像记录,我们分别分析了数千个神经元群体在 "上升 "和 "下降 "状态下的神经元雪崩统计,从而验证了这一假设。我们发现,如果考虑到其内在时间尺度,"上升 "和 "下降 "状态都可以表现出无标度行为。特别是,"下行 "状态的统计特征与之前在没有 "上行 "状态的培养物中观察到的特征没有区别。我们的研究表明,即使考虑到现实的噪声水平、空间网络嵌入和异质种群,这种行为也无法用具有短期突触抑制的非保守性漏整合-发射神经元网络模型来解释,而表现出与以前的理论模型一致的行为。当考虑到有限尺寸缩放效应时,也观察到了类似的差异,这表明这些培养物的内在动力学和自组织机制可能比以前认为的更为复杂。特别是,我们的研究结果表明,在高活性或低活性状态下,存在不同时间尺度的神经元交流机制,可能需要不同的可塑性机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
6.00
自引率
5.70%
发文量
135
审稿时长
4-8 weeks
期刊介绍: Frontiers in Neural Circuits publishes rigorously peer-reviewed research on the emergent properties of neural circuits - the elementary modules of the brain. Specialty Chief Editors Takao K. Hensch and Edward Ruthazer at Harvard University and McGill University respectively, are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Frontiers in Neural Circuits launched in 2011 with great success and remains a "central watering hole" for research in neural circuits, serving the community worldwide to share data, ideas and inspiration. Articles revealing the anatomy, physiology, development or function of any neural circuitry in any species (from sponges to humans) are welcome. Our common thread seeks the computational strategies used by different circuits to link their structure with function (perceptual, motor, or internal), the general rules by which they operate, and how their particular designs lead to the emergence of complex properties and behaviors. Submissions focused on synaptic, cellular and connectivity principles in neural microcircuits using multidisciplinary approaches, especially newer molecular, developmental and genetic tools, are encouraged. Studies with an evolutionary perspective to better understand how circuit design and capabilities evolved to produce progressively more complex properties and behaviors are especially welcome. The journal is further interested in research revealing how plasticity shapes the structural and functional architecture of neural circuits.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信