信号检测理论对小鼠绝对视觉阈值的估计与决策偏差无关。

IF 2.7 3区 医学 Q3 NEUROSCIENCES
eNeuro Pub Date : 2024-10-09 Print Date: 2024-10-01 DOI:10.1523/ENEURO.0222-24.2024
Sam LaMagna, Yumiko Umino, Eduardo Solessio
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引用次数: 0

摘要

决策偏差会影响对绝对视觉阈值的估计。然而,大多数对小鼠绝对视觉阈值的心理物理估计都没有考虑到偏差。在此,我们开发了一种单选项强迫选择(1AFC)试验,通过信号检测理论来评估小鼠在绝对视觉阈值上的决策偏差,并将我们的方法与更传统的高阈值理论方法进行了比较。在 1AFC 试验中,对雌雄小鼠进行训练,让它们发出是否检测到闪光刺激的信号。我们直接测量了 "命中率 "和 "误报率",并以此估算出 d'。利用信号检测理论,我们从 d'心理测量函数中插值出 d' = 1 的强度,从而得到绝对阈值。这给出了与偏差无关的绝对视觉阈值估计值,其范围超过 6 倍,在 1,000 个杆(n = 7 只小鼠)中平均为 ∼1R*。为了从同一只小鼠身上获得绝对视觉阈值的高阈值理论估计值,我们从看到的频率曲线中估计了阈值强度,并对猜测进行了校正。这样得出的阈值与判定偏差密切相关,范围超过 13 倍,在 2,500 根杆中的平均值为 1 R*。我们的结论是,信号检测理论利用 "假警报 "来克服小鼠的决策偏差并缩小阈值估计的范围,为理解绝对视觉阈值附近的检测行为提供了有力的工具。这种模糊性会带来决策偏差,使观察者对光的敏感度出现增大或减小的情况,从而增大敏感度估计值的范围。我们发现,信号检测理论提供了一个框架,通过考虑小鼠的自发神经活动来处理这些偏差,从而在检测微弱、短暂的闪光时缩小灵敏度估计的范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Signal Detection Theoretic Estimates of the Murine Absolute Visual Threshold Are Independent of Decision Bias.

Decision bias influences estimates of the absolute visual threshold. However, most psychophysical estimates of the murine absolute visual threshold have not taken bias into account. Here we developed a one-alternative forced choice (1AFC) assay to assess the decision bias of mice at the absolute visual threshold via the theory of signal detection and compared our approach with the more conventional high-threshold theoretic approach. In the 1AFC assay, mice of both sexes were trained to signal whether they detected a flash stimulus. We directly measured both hit and false alarm rates, which were used to estimate d' Using the theory of signal detection, we obtained absolute thresholds by interpolating the intensity where d' = 1 from d'-psychometric functions. This gave bias-independent estimates of the absolute visual threshold which ranged over sixfold, averaging ∼1 R* in 1,000 rods (n = 7 mice). To obtain high-threshold theoretic estimates of the absolute visual threshold from the same mice, we estimated threshold intensities from the frequency of seeing curves, corrected for guessing. This gave us thresholds that were strongly correlated with decision bias, ranging over 13-fold and averaged ∼1 R* in 2,500 rods. We conclude that the theory of signal detection uses false alarms to overcome decision bias and narrow the range of threshold estimates in mice, providing a powerful tool for understanding detection behavior near absolute visual threshold.

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来源期刊
eNeuro
eNeuro Neuroscience-General Neuroscience
CiteScore
5.00
自引率
2.90%
发文量
486
审稿时长
16 weeks
期刊介绍: An open-access journal from the Society for Neuroscience, eNeuro publishes high-quality, broad-based, peer-reviewed research focused solely on the field of neuroscience. eNeuro embodies an emerging scientific vision that offers a new experience for authors and readers, all in support of the Society’s mission to advance understanding of the brain and nervous system.
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