Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

Encoding under time pressure: stages and electrophysiological mechanisms in facial expression processing

Summarise with AI (MRCPsych/FRANZCP)

Neuroreport. 2026 Mar 4;37(4):145-154. doi: 10.1097/WNR.0000000000002249. Epub 2025 Feb 11.

ABSTRACT

OBJECTIVES: This study investigated the mechanisms by which shortened time constraints accelerate working memory encoding.

METHODS: Sixty-two participants completed a working memory task for facial emotions, with encoding durations manipulated between 250 and 1050 ms. Event-related potentials (ERPs) were recorded and analyzed in terms of component amplitude, latency, and their relationship to working memory performance. Time-frequency analyses were also conducted. Bayesian analyses were additionally conducted to validate null effects.

RESULTS: Behavioral and time-frequency results revealed a two-stage encoding process: an initial establishment stage that enabled reasonable accuracy within 250 ms, and a refinement stage that improved encoding quality with extended time. ERP results showed that shortened encoding time primarily affected amplitudes rather than latencies of the ERPs. Specifically, P1 and N170 latencies remained stable, whereas amplitudes associated with attentional functioning (P1-origin and P1), code establishment (N170), and refinement/storage (250-400 ms) were attenuated. Linear mixed-effects models further indicated that lower accuracy was consistently associated with reduced ERP amplitudes across nearly all these components.

CONCLUSION: Working memory encoding comprises establishment and refinement stages. Encoding acceleration under shortened time constraints is achieved by truncation of the refinement stage rather than acceleration of the establishment stage. Moreover, this acceleration compromises encoding quality by not only truncating the refinement stage, but also limiting the resource allocation to attentional capture, representation establishment, and storage. These findings have broader implications for understanding cognitive performance under time pressure.

PMID:41817453 | DOI:10.1097/WNR.0000000000002249

Document this CPD

AI Search

Share Evidence Blueprint

QR Code

Search Google Scholar

Save as PDF

close chatgpt icon
ChatGPT

Enter your request.

Psychiatry AI: Real-Time AI Scoping Review