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Updated: Jan 15, 2026

A Two-interval Forced-choice Task for Multisensory Comparisons
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Published on: November 9, 2018

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个体α频率与时间感知之间的关系:测试内部时钟与采样率假设的对比

Matteo Frisoni1, Luca Tarasi1, Sara Borgomaneri1

  • 1Center for Studies and Research in Cognitive Neuroscience, Department of Psychology "Renzo Canestrari", University of Bologna, Cesena Campus, Italy.

Cortex; a journal devoted to the study of the nervous system and behavior
|October 9, 2025
PubMed
概括

个人阿尔法频率 (IAF) 影响时间感知精度,而不是偏差. 更高的IAF与更好的时间灵敏度相关,支持α振荡采样机制,而不是传统的内部时钟心脏起器模型.

关键词:
阿尔法振荡是指阿尔法振荡.个别的α频率是个别的α频率.静止状态的EEG电力是一个静止状态.信号检测理论 信号检测理论时间感知时间感知.

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Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
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Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
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