Infra-Low-Frequency Neurofeedback Alters EEG Network Efficiency: exploratory Evidence from Healthy Volunteers

Infra‐Low‐Frequency Neurofeedback (ILF‐NFB) combines classic frequency‐band (FB) and infra‐low‐frequency (ILF) EEG components in implicit training protocols and is increasingly applied in clinical contexts. Yet, the neurophysiological mechanisms underlying ILF‐NFB remain to be further elucidated. In this randomized, sham‐controlled and double‐blind study, we explored the online impact of a one‐session ILF‐NFB application on EEG correlates in healthy participants (39 analyzed datasets). Continuous 31‐channel EEG was recorded during verum and sham feedback in a double‐blind, randomized crossover design. In this exploratory analysis approach, functional connectivity was estimated using the debiased weighted phase‐lag index (dwPLI) and analyzed with graph‐theoretical measures. The results revealed higher global efficiency during verum compared to sham in the Beta1 band (12‐15 Hz), reaching significance in the primary comparison but not surviving Bonferroni correction across the five tested bands; block‐wise follow‐ups showed a significant verum‐sham difference in the first half of the neurofeedback session and a directionally consistent pattern in the second half. The Condition × Block interaction was not significant. No consistent differences were observed in other frequency bands, nor for betweenness centrality. While preliminary, these exploratory results point to possible network‐level effects during ILF‐NFB and motivate further confirmatory work in extended training protocols and clinical populations.