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the claim

A single-trial analysis in neuroscience evaluates neural data from one individual stimulus presentation without averaging.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
5 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that a single-trial analysis in neuroscience evaluates neural data from one individual stimulus presentation without averaging?

Yes. Multiple neuroscience studies demonstrate that modern analysis techniques successfully evaluate and decode neural data from individual stimulus presentations without trial averaging.

Verdict: SUPPORTED · 5 sources for, 0 against · Last checked

The analysis

The retrieved papers consistently provide evidence demonstrating the use of single-trial analysis methods in neuroscience, ranging from fMRI and EEG decoding to behavioral modeling. No papers refute the claim.

Evidence for · 5
Decoding Articulatory Features from fMRI Responses in Dorsal Speech Regions
2015
The study uses multivariate decoding of single-trial fMRI responses to investigate speech perception without averaging across trials.
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Correia, J., Jansma, B., & Bonte, M. (2015). Decoding Articulatory Features from fMRI Responses in Dorsal Speech Regions. doi.org. https://doi.org/10.1523/JNEUROSCI.0977-15.2015

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More for · 4
Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex
2018
The study applies decoding models to analyse spatially distributed patterns of neural activity from multiple single-trial measurements of speech production.
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Livezey, J., Bouchard, K. E., & Chang, E. (2018). Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex. doi.org. https://doi.org/10.1371/journal.pcbi.1007091

Decoding covert motivations of free riding and cooperation from multi-feature pattern analysis of EEG signals.
2015
The research identifies neural features from single-trial event-related spectral perturbations to predict upcoming behavioral decisions.
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Chung, D., Yun, K., & Jeong, J. (2015). Decoding covert motivations of free riding and cooperation from multi-feature pattern analysis of EEG signals.. doi.org. https://doi.org/10.1093/scan/nsv006

Decoding mouse behavior to explain single-trial decisions and their relationship with neural activity
2019
The study develops decoding models that provide an accurate account of single-trial behavior and its relationship with neural activity.
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Weissenberger, Y., King, A. J., & Dahmen, J. C. (2019). Decoding mouse behavior to explain single-trial decisions and their relationship with neural activity. doi.org. https://doi.org/10.1101/567479

Distinct oscillatory signatures of emotional reactivity and cognitive reappraisal revealed through multiclass EEG decoding.
2026
The proof-of-concept study demonstrates that oscillatory EEG features can discriminate affective and regulatory states at the single-trial level.
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M, D. & C, C. (2026). Distinct oscillatory signatures of emotional reactivity and cognitive reappraisal revealed through multiclass EEG decoding.. doi.org. https://doi.org/10.3758/s13415-026-01462-w

What does the evidence say?

The retrieved papers consistently provide evidence demonstrating the use of single-trial analysis methods in neuroscience, ranging from fMRI and EEG decoding to behavioral modeling. No papers refute the claim.

Receipt History
first checked05 Aug 2026
judged → SUPPORTED · 8805 Aug 2026
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