Electrical stimulus is one of the common stimulating methods, and Galvanic vestibular stimulation (GVS) is the oldest form as an electrical stimulation. Nevertheless, GVS is still considered as a secondary stimulating tool for the medical purposes. Even though some unarguable findings have made using GVS, its use has been limited because of its ambiguity as an input source. For better understanding, many previous studies mainly focused on its functional effects, like the ocular reflexes. However, its fundamental effects on the neural activities are still elusive, such as the dominant influences by different parameters of GVS. Here we compared the effects on the neuronal responses by applying two different parameters, strength and rate, of GVS. To assess the dominance on the neuronal responses to these parameters, we designed three independent stimuli. Those stimuli were multiply applied to obtain the responding slopes based on the mechanism of non-associative learning processes, and the effects on the neurons were calculated as an inner angle between two responding slopes. Out of 23 neurons, 15 (65.2%) units were affected more by the strength with a statistical significance (p = 0.047). The ranges of the inner angles also implied the strength (- 3.354°~2.063°) mainly modulated by the neuronal responses comparing with those by the rate (- 2.001°~1.975°). The dominance of the parameters was closely related with the neuronal sensitivity to stimulation (SE) (p = 0.018), while there were few relations with the neuronal regularity, directional preference (DP), and the physiological response (PR) (p > 0.059). Thus, the neural information related with the dominance was delivered by the irregular neurons, and these types of neurons should be the targets for the stimulation. Graphical abstract.

中文翻译：

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非关联学习过程的前庭电刺激的主要参数。

电刺激是常见的刺激方法之一，电前庭刺激（GVS）是最早的电刺激形式。尽管如此，出于医学目的，GVS仍被认为是辅助刺激工具。尽管使用GVS取得了一些无可辩驳的发现，但由于其作为输入源的歧义，其使用受到了限制。为了更好地理解，以前的许多研究主要集中在其功能效果上，例如眼反射。但是，它对神经活动的基本影响仍然难以捉摸，例如GVS不同参数的主要影响。在这里，我们通过应用GVS的两个不同参数（强度和速率）比较了对神经元反应的影响。为了评估在神经元对这些参数的反应中的优势，我们设计了三个独立的刺激。根据非关联学习过程的机制，将这些刺激多次应用于获得响应斜率，并将对神经元的影响计算为两个响应斜率之间的内角。在23个神经元中，有15个（65.2％）的单位受到强度的影响更大，具有统计学意义（p = 0.047）。内角的范围也暗示了强度（-3.354°〜2.063°）主要受神经元反应调节，而强度则由比率（-2.001°〜1.975°）所调节。参数的优势与神经元对刺激的敏感性（SE）密切相关（p = 0.018），而与神经元规律性，方向偏好（DP）和生理反应（PR）的关系则很少（p> 0.059） ）。从而，与优势有关的神经信息是由不规则神经元传递的，这些类型的神经元应该成为刺激的目标。图形概要。