Related Experiment Video
Updated: Sep 12, 2025

11:52
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
Published on: February 9, 2017
6.0K
ERP prediction error responses under temporal constraints
Álvaro Darriba1, Hamdi Habacha1, Yang Seok Cho2
1Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, F-75006 Paris, France.
Brain Research
|August 5, 2025
Summary
The brain prioritizes earlier cues when processing multiple predictions under time pressure. This suggests a bottleneck in integrating sequential predictions, impacting prediction error responses.
Area of Science:
- Cognitive Neuroscience
- Neuroscience
- Psychology
Background:
- Anticipating future events is crucial for adaptive behavior.
- Understanding how the brain handles multiple, concurrent predictions is essential.
Purpose of the Study:
- To investigate neural mechanisms of processing multiple predictions under temporal constraints using EEG.
- To examine event-related potential (ERP) responses to prediction errors (PEs).
Main Methods:
- Participants performed a task involving two auditory cues predicting visual stimulus features (tilt, spatial frequency).
- Cue-stimulus intervals were varied (200 ms and 1000 ms).
- EEG recorded event-related potentials (ERPs) to assess prediction error responses.
Main Results:
- Violations of the first cue's prediction reliably evoked N2b responses, irrespective of the second cue's accuracy.
- Violating both cues also resulted in strong N2b amplitudes.
- Isolated violations of the second cue did not significantly affect N2b responses.
- No significant differences were found between short and long cue intervals.
Conclusions:
- Sequential prediction integration faces a temporal bottleneck.
- Earlier predictive cues exert a dominant influence on prediction error-related EEG responses.
- Temporal intervals do not appear to modulate the processing of sequential predictions.
More Related Videos
Related Concept Videos
Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
Hindsight Biases
3.9K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
3.9K
Predicting Products: Substitution vs. Elimination
12.3K
When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
The following factors can influence the mechanisms competing against each other:
12.3K
Predicting Reaction Outcomes
8.6K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.6K
Detection of Gross Error: The Q Test
6.4K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.4K
Improving Translational Accuracy
11.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.9K

