From statistical regularities in multisensory inputs to peripersonal space representation and body ownership: Insights from a neural network model,European Journal of Neuroscience

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From statistical regularities in multisensory inputs to peripersonal space representation and body ownership: Insights from a neural network model
European Journal of Neuroscience ( IF 2.7 ) Pub Date : 2020-09-23 , DOI: 10.1111/ejn.14981
Tommaso Bertoni ₁ , Elisa Magosso ₂ , Andrea Serino ₁

Affiliation

Peripersonal space (PPS), the interface between the self and the environment, is represented by a network of multisensory neurons with visual (or auditory) receptive fields anchored to specific body parts, and tactile receptive fields covering the same body parts. Neurophysiological and behavioural features of hand PPS representation have been previously modelled through a neural network constituted by one multisensory population integrating tactile inputs with visual/auditory external stimuli. Reference frame transformations were not explicitly modelled, as stimuli were encoded in pre‐computed hand‐centred coordinates. Here we present a novel model, aiming to overcome this limitation by including a proprioceptive population encoding hand position. We confirmed behaviourally the plausibility of the proposed architecture, showing that visuo‐proprioceptive information is integrated to enhance tactile processing on the hand. Moreover, the network's connectivity was spontaneously tuned through a Hebbian‐like mechanism, under two minimal assumptions. First, the plasticity rule was designed to learn the statistical regularities of visual, proprioceptive and tactile inputs. Second, such statistical regularities were simply those imposed by the body structure. The network learned to integrate proprioceptive and visual stimuli, and to compute their hand‐centred coordinates to predict tactile stimulation. Through the same mechanism, the network reproduced behavioural correlates of manipulations implicated in subjective body ownership: the invisible and the rubber hand illusion. We thus propose that PPS representation and body ownership may emerge through a unified neurocomputational process; the integration of multisensory information consistently with a model of the body in the environment, learned from the natural statistics of sensory inputs.

中文翻译：

从多感官输入的统计规律到个人周围空间表征和身体所有权：来自神经网络模型的见解

周围空间（PPS）是自我与环境之间的界面，由多感觉神经元网络表示，视觉（或听觉）感受野锚定到特定的身体部位，触觉感受野覆盖相同的身体部位。手部 PPS 表征的神经生理学和行为特征先前已通过神经网络进行建模，该神经网络由整合触觉输入与视觉/听觉外部刺激的多感官群体构成。参考系变换没有明确建模，因为刺激是在预先计算的以手为中心的坐标中编码的。在这里，我们提出了一种新颖的模型，旨在通过包含编码手部位置的本体感觉群体来克服这一限制。我们在行为上证实了所提出的架构的合理性，表明视觉本体感受信息被集成以增强手上的触觉处理。此外，在两个最小假设下，网络的连接性是通过类赫布机制自发调整的。首先，可塑性规则旨在学习视觉、本体感受和触觉输入的统计规律。其次，这种统计规律只是由身体结构强加的。该网络学会了整合本体感觉和视觉刺激，并计算它们以手为中心的坐标来预测触觉刺激。通过相同的机制，网络再现了与主观身体所有权有关的操纵的行为相关性：无形的和橡皮手的错觉。因此，我们建议 PPS 表示和身体所有权可能通过统一的神经计算过程出现；从感官输入的自然统计中学习到的多感官信息与环境中的身体模型一致的整合。

更新日期：2020-09-23

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