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Neural networks distinguish between taste qualities based on receptor cell population responses

机译:神经网络根据受体细胞群反应区分味觉品质

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Response features of taste receptor cell action potentials were examined using an artificial neural network to determine whether they contain information about taste quality. Using the loose patch technique to record from hamster taste buds in vivo we recorded population responses oi single fungiform papillae to NaCl (100 mM), sucrose (200 mM) and the synthetic sweetener NC-00274-01 (NC-01) (200 muM). Features of each response describing both burst and inter-burst characteristics were then presented to an artificial neural network for pairwise classification of taste stimuli. Responses to NaCl could be distinguished from those to both NC-01 and sucrose with accuracies of up to 86%. In contrast, pairwise comparisons between sucrose and NC-01 were not successful, scoring at chance (50%). Also, comparisons between two different concentrations of NaCI, 0.01 and 0.005 M, scored at chance. Pairwise comparisons using only those features that relate to the inter-burst behavior of the response (i.e. bursting rate) did not hinder the performance of the neural network as both sweeteners versus NaCI received scores of 75-85%. Comparisons using features corresponding to each individual burst scored poorly, receiving scores only slightly above chance. We then compared the sweeteners with varying concentrations of NaCI (0.1, 0.01, 0.005 and 0.001 M) using only those features corresponding to bursting rate within a 1 s time window. The neural network was capable of distinguishing between NaCI and NC-01 at all concentrations tested; while comparisons between NaCI and sucrose received high scores at all concentrations except 0.001 M. These results show that two different taste qualities can be distinguished from each other based solely on the bursting rates of action potentials in single taste buds and that this distinction is independent of stimulation intensity down to 0.001 M NaCI. These data suggest that action potentials in taste receptor cells may play a role in taste quality coding. [References: 23]
机译:使用人工神经网络检查了味觉受体细胞动作电位的响应特征,以确定它们是否包含有关味觉质量的信息。使用宽松的贴片技术记录体内仓鼠的味蕾,我们记录了单个真菌状乳突对NaCl(100 mM),蔗糖(200 mM)和合成甜味剂NC-00274-01(NC-01)(200 muM)的种群响应)。然后将描述爆裂和爆裂间特征的每个响应的特征呈现给人工神经网络,以对味觉刺激进行成对分类。对NaCl的响应可以与对NC-01和蔗糖的响应区分开,精度最高可达86%。相反,蔗糖和NC-01之间的成对比较未成功,得分为偶然(50%)。同样,偶然地在两个不同浓度的NaCl(0.01和0.005 M)之间进行了比较。仅使用与响应的爆发间行为有关的那些特征(即爆发率)的成对比较不会妨碍神经网络的性能,因为甜味剂和NaCl均获得75-85%的评分。使用与每个单独爆发对应的特征进行的比较得分很低,仅获得了略高于机会的得分。然后,我们仅使用与1 s时间窗内爆破速率相对应的那些特征,比较了具有不同浓度的NaCl(0.1、0.01、0.005和0.001 M)的甜味剂。神经网络能够在所有测试浓度下区分NaCl和NC-01。 NaCl和蔗糖之间的比较在0.001 M以外的所有浓度下均获得高分。这些结果表明,仅基于单个味蕾中动作电位的爆发速率,就可以将两种不同的味觉品质彼此区分开,并且这种区分与刺激强度低至0.001 M NaCl。这些数据表明,味觉受体细胞中的动作电位可能在味觉质量编码中起作用。 [参考:23]

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