Event-related potentials data quality in young children: Standardized measurement error of ERN and Pe

Optimal filters for ERP research I: A general approach for selecting filter settings

Filtering plays an essential role in event-related potential (ERP) research, but filter settings are usually chosen on the basis of historical precedent, lab lore, or informal analyses. This reflects, in part, the lack of a well-reasoned, easily implemented method for identifying the optimal filter settings for a given type of ERP data. To fill this gap, we developed an approach that involves finding the filter settings that maximize the signal-to-noise ratio for a specific amplitude score (or minimizes the noise for a latency score) while minimizing waveform distortion. The signal is estimated by obtaining the amplitude score from the grand average ERP waveform (usually a difference waveform). The noise is estimated using the standardized measurement error of the single-subject scores. Waveform distortion is estimated by passing noise-free simulated data through the filters. This approach allows researchers to determine the most appropriate filter settings for their specific scoring methods, experimental designs, subject populations, recording setups, and scientific questions. We have provided a set of tools in ERPLAB Toolbox to make it easy for researchers to implement this approach with their own data.

Intergenerational transmission of cognitive control capacity among children at risk for depression

A maternal history of major depressive disorder (MDD) is a well-known risk factor for depression in offspring. However, the mechanism through which familial risk is transmitted remains unclear. Cognitive control alterations are common in MDD, and thus, the current study investigated whether altered control capacity is transmitted intergenerationally, and whether it then contributes to the developmental pathways through which depression is passed from mothers to children. We recruited children (N = 65) ages 4-10-years-old, of which 47.7 % (n = 31) reported a maternal history of MDD, and their biological mother (N = 65). Children performed a child-friendly Go/NoGo task while electroencephalography (EEG) data were recorded, and mothers performed a Flanker task. Children exhibited heightened sensitivity to error versus correct responses, which was characterized by an error-related negativity (ERN), error positivity (Pe) as well as prominent delta and frontal midline theta (FMT) oscillations. Interestingly, worse maternal performance on the Flanker task associated with an increased Go/NoGo error rate and a smaller ERN and Pe in children. However, there was no association between maternal or child control indices with child depression symptoms. Our results suggest a familial influence of cognitive control capacity in mother-child dyads, but it remains unclear whether this confers risk for depressive symptoms in children. Further research is necessary to determine whether alterations in cognitive control over time may influence symptom development in at-risk children.

Variations in ERP data quality across paradigms, participants, and scoring procedures

Although it is widely accepted that data quality for event-related potential (ERP) components varies considerably across studies and across participants within a study, ERP data quality has not received much systematic analysis. The present study used a recently developed metric of ERP data quality- the standardized measurement error (SME)-to examine how data quality varies across different ERP paradigms, across individual participants, and across different procedures for quantifying amplitude and latency values. The EEG recordings were taken from the ERP CORE, which includes data from 40 neurotypical college students for seven widely studied ERP components: P3b, N170, mismatch negativity, N400, error-related negativity, N2pc, and lateralized readiness potential. Large differences in data quality were observed across the different ERP components, and very large differences in data quality were observed across participants. Data quality also varied depending on the algorithm used to quantify the amplitude and especially the latency of a given ERP component. These results provide an initial set of benchmark values that can be used for comparison with previous and future ERP studies. They also provide useful information for predicting effect sizes and statistical power in future studies, even with different numbers of trials. More broadly, this study provides a general approach that could be used to determine which specific experimental designs, data collection procedures, and data processing algorithms lead to the best data quality.

The default-interventionist model underlies premise typicality weakening the premise diversity effect during category-based induction: Event-related potentials evidence

The diversity effect during category-based induction (CBI) means that the more diverse the evidence, the higher will be the conclusion's inductive strength. However, it is influenced by the premise typicality. Three competitive cognitive processing models account for this influence: (1) The pre-emptive conflict resolution model assumes that only premise typicality activates; (2) the parallel-competitive model assumes that premise typicality and diversity activate in parallel; and (3) the default-interventionist model assumes that a default response of premise diversity first activates and is subsequently followed by premise typicality, or premise typicality activates first, followed by premise diversity. The timing of premise typicality affecting the diversity effect during CBI was measured using event-related potentials to determine which cognitive model best explains this influence. Similar to previous studies, non-diverse premise inductive tasks involving two typical premise categories were compared with diverse premise inductive tasks involving a typical and an atypical category. The results showed that non-diverse conditions had higher "correct" response proportions, greater inductive strength, higher "definitely" response proportions, and shorter reaction times than diverse conditions, showing that premise typicality weakens the diversity effect. Moreover, the diverse premises elicited larger P2, smaller FN400, and greater frontal post-N400-positivity amplitudes than non-diverse premises, suggesting that premise diversity was facilitated during a relatively early time window and revised by premise typicality in a later window. These results support the default-interventionist in nature during thinking and reasoning.