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超越感觉的学习:梦境如何组织神经元的表征。

Learning beyond sensations: How dreams organize neuronal representations.

机构信息

Department of Physiology, University of Bern, Bern, Switzerland.

Department of Physiology, University of Bern, Bern, Switzerland.

出版信息

Neurosci Biobehav Rev. 2024 Feb;157:105508. doi: 10.1016/j.neubiorev.2023.105508. Epub 2023 Dec 12.

Abstract

Semantic representations in higher sensory cortices form the basis for robust, yet flexible behavior. These representations are acquired over the course of development in an unsupervised fashion and continuously maintained over an organism's lifespan. Predictive processing theories propose that these representations emerge from predicting or reconstructing sensory inputs. However, brains are known to generate virtual experiences, such as during imagination and dreaming, that go beyond previously experienced inputs. Here, we suggest that virtual experiences may be just as relevant as actual sensory inputs in shaping cortical representations. In particular, we discuss two complementary learning principles that organize representations through the generation of virtual experiences. First, "adversarial dreaming" proposes that creative dreams support a cortical implementation of adversarial learning in which feedback and feedforward pathways engage in a productive game of trying to fool each other. Second, "contrastive dreaming" proposes that the invariance of neuronal representations to irrelevant factors of variation is acquired by trying to map similar virtual experiences together via a contrastive learning process. These principles are compatible with known cortical structure and dynamics and the phenomenology of sleep thus providing promising directions to explain cortical learning beyond the classical predictive processing paradigm.

摘要

高级感觉皮层中的语义表示为稳健而灵活的行为提供了基础。这些表示是在无监督的方式下在发育过程中获得的,并在生物体的整个生命周期内持续维持。预测处理理论提出,这些表示源于对感觉输入的预测或重构。然而,众所周知,大脑会产生虚拟体验,例如在想象和做梦期间,这些体验超出了以前经历过的输入。在这里,我们认为虚拟体验在塑造皮层表示方面可能与实际感觉输入同样重要。具体来说,我们讨论了两种互补的学习原则,它们通过生成虚拟体验来组织表示。首先,“对抗性做梦”提出创造性的梦境支持皮层中对抗性学习的实现,其中反馈和前馈通路通过试图相互愚弄来进行富有成效的博弈。其次,“对比性做梦”提出,通过对比学习过程尝试将相似的虚拟体验映射在一起,可以获得神经元表示对无关变异因素的不变性。这些原则与已知的皮层结构和动力学以及睡眠的现象学兼容,从而为解释超越经典预测处理范例的皮层学习提供了有前途的方向。

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