神经行为状态假说。

IF 2 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2024-11-08 DOI:10.1016/j.biosystems.2024.105361
Luis Fernando Ontiveros-Araiza
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引用次数: 0

摘要

自 2000 多年前希腊哲学家试图了解大脑的早期尝试以来,神经科学的主要问题之一一直是大脑如何感知环境中的所有刺激并利用这些信息做出反应。最新的神经密码假说依赖于理想观察者的存在,无论是大脑皮层的特定区域,还是由皮层和皮层下元素组成的分布式网络。神经行为状态假说认为,由于神经元分子成分的动态相互作用,神经元处于准稳定状态。与二元活跃/不活跃状态相比,这进一步提高了神经元的计算能力和电生理行为。整个大脑的神经元群共同学习识别内部和外部刺激,并将其与行动和情绪联系起来。此外,这种关联可以通过神经元成分的调节存储为新的准稳定状态。在这一框架下,行为的产生是内部和外部刺激与先前建立的准稳定状态之间动态互动的结果,而这些准稳定状态划定了行为反应的范围。最后,"神经行为状态假说 "以大脑内部从分子到网络层面复杂动态的现有证据为坚实基础,提出大脑通过经验驱动的联想进行自我配置,从而避免了对中心观察者的需求。
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The Neurobehavioral State hypothesis
Since the early attempts to understand the brain made by Greek philosophers more than 2000 years ago, one of the main questions in neuroscience has been how the brain perceives all the stimuli in the environment and uses this information to implement a response. Recent hypotheses of the neural code rely on the existence of an ideal observer, whether on specific areas of the cerebral cortex or distributed network composed of cortical and subcortical elements. The Neurobehavioral State hypothesis stipulates that neurons are in a quasi-stable state due to the dynamic interaction of their molecular components. This increases their computational capabilities and electrophysiological behavior further than a binary active/inactive state. Together, neuronal populations across the brain learn to identify and associate internal and external stimuli with actions and emotions. Furthermore, such associations can be stored through the regulation of neuronal components as new quasi-stable states. Using this framework, behavior arises as the result of the dynamic interaction between internal and external stimuli together with previously established quasi-stable states that delineate the behavioral response. Finally, the Neurobehavioral State hypothesis is firmly grounded on present evidence of the complex dynamics within the brain, from the molecular to the network level, and avoids the need for a central observer by proposing the brain configures itself through experience-driven associations.
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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