Bayesian estimation of orientation and direction tuning captures parameter uncertainty.

IF 3 3区 医学 Q2 NEUROSCIENCES
Frontiers in Neural Circuits Pub Date : 2025-07-21 eCollection Date: 2025-01-01 DOI:10.3389/fncir.2025.1542332
Zongting Wu, Stephen D Van Hooser
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引用次数: 0

Abstract

This study explores the efficacy of Bayesian estimation in modeling the orientation and direction selectivity of neurons in the primary visual cortex (V1). Unlike traditional methods such as least squares, Bayesian estimation adeptly handles the probabilistic nature of neuronal responses, offering robust analysis even with limited data and weak selectivity. Through the analysis of both simulated and experimental data, we demonstrate that Bayesian estimation not only accurately fits the neuronal tuning curves but also effectively captures parameter certainty or uncertainty of both strongly and weakly selective neurons. Our results affirm the complex interdependencies among response parameters and highlight the variability in neuronal behavior under varied stimulus conditions. Our findings provide guidance as to how many response samples are necessary for Bayesian parameter estimation to achieve reliable fitting, making it particularly suitable for studies with constraints on data availability.

Abstract Image

Abstract Image

Abstract Image

贝叶斯估计的方向和方向调谐捕获参数的不确定性。
本研究探讨了贝叶斯估计在初级视觉皮层(V1)神经元定向和方向选择性建模中的有效性。与最小二乘等传统方法不同,贝叶斯估计熟练地处理神经元反应的概率性质,即使在有限的数据和弱选择性下也能提供稳健的分析。通过对仿真数据和实验数据的分析,我们证明贝叶斯估计不仅可以准确地拟合神经元的调谐曲线,而且可以有效地捕获强选择性和弱选择性神经元的参数确定性或不确定性。我们的研究结果证实了反应参数之间复杂的相互依赖关系,并强调了不同刺激条件下神经元行为的可变性。我们的研究结果为贝叶斯参数估计需要多少响应样本才能实现可靠拟合提供了指导,使其特别适用于数据可用性受限的研究。
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来源期刊
CiteScore
6.00
自引率
5.70%
发文量
135
审稿时长
4-8 weeks
期刊介绍: Frontiers in Neural Circuits publishes rigorously peer-reviewed research on the emergent properties of neural circuits - the elementary modules of the brain. Specialty Chief Editors Takao K. Hensch and Edward Ruthazer at Harvard University and McGill University respectively, are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Frontiers in Neural Circuits launched in 2011 with great success and remains a "central watering hole" for research in neural circuits, serving the community worldwide to share data, ideas and inspiration. Articles revealing the anatomy, physiology, development or function of any neural circuitry in any species (from sponges to humans) are welcome. Our common thread seeks the computational strategies used by different circuits to link their structure with function (perceptual, motor, or internal), the general rules by which they operate, and how their particular designs lead to the emergence of complex properties and behaviors. Submissions focused on synaptic, cellular and connectivity principles in neural microcircuits using multidisciplinary approaches, especially newer molecular, developmental and genetic tools, are encouraged. Studies with an evolutionary perspective to better understand how circuit design and capabilities evolved to produce progressively more complex properties and behaviors are especially welcome. The journal is further interested in research revealing how plasticity shapes the structural and functional architecture of neural circuits.
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