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Quantifying rhythmicity in perceptual reports.

Tommaso Tosato1, Gustavo Rohenkohl2, Jarrod Robert Dowdall3

  • 1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, Germany.

Neuroimage
|August 16, 2022
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Summary
This summary is machine-generated.

This study compares methods for analyzing rhythmic cognitive processes. Single-trial analysis and the Max-Based approach for multiple comparisons showed superior sensitivity and specificity in simulated data.

Keywords:
Behavioral oscillationsGroup-level inferencePhase lockingPsychophysics methodsSingle-trial analysisSpectral analysis

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Psychology

Background:

  • Rhythmic processes in cognition are increasingly studied using diverse methods.
  • A lack of standardized methods hinders agreement on findings in perception and behavior.

Purpose of the Study:

  • To develop a quantitative framework for comparing methods analyzing cognitive rhythms.
  • To evaluate the performance of sine-wave fitting, discrete Fourier transform (DFT), and least square spectrum (LSS) methods.

Main Methods:

  • Simulated behavioral data from typical experiments.
  • Analysis using sine-wave fitting, DFT, and LSS on average accuracy and single trials.
  • Statistical inference using fixed-effects and random-effects models.
  • Multiple comparison correction with False Discovery Rate, Bonferroni, and Max-Based approaches.

Main Results:

  • Single-trial analysis methods demonstrated higher sensitivity and D-prime than average time-course methods.
  • Higher frequency rhythms and incorporating weighting factors (e.g., arousal) further improved performance.
  • The Max-Based and Bonferroni approaches offered the best specificity and D-prime for multiple comparisons.
  • Random-effects models showed higher D-prime with more participants, even with fewer trials per participant.

Conclusions:

  • Single-trial analysis is more sensitive for detecting cognitive rhythms, especially at higher frequencies.
  • The least square spectrum (LSS) method offers flexibility with weighting factors.
  • The Max-Based approach is recommended for multiple comparison correction.
  • Distributing trials across more participants enhances the reliability of random-effects analyses.