Face to phase: pitfalls in time delay estimation from coherency phase.
Coherency phase is often interpreted as a time delay reflecting a transmission delay between spatially separated neural populations. However, time delays estimated from corticomuscular coherency are conflicting and often shorter than expected physiologically. Recent work suggests that corticomuscular coherence is influenced by afferent sensory feedback and bidirectional interactions. We investigated how bidirectional interaction affects time delay estimated from coherency, using a feedback model of the corticomuscular system. We also evaluated the effect of bidirectional interaction on two popular directed connectivity measures: directed transfer function (DTF) and partial directed coherence (PDC). The model is able to reproduce the range of time delays found experimentally from coherency phase by varying the strengths of the efferent and afferent pathways and the recording of sensory feedback in the cortical signal. Both coherency phase and DTF phase were affected by sensory feedback, resulting in an underestimation of the transmission delay. Coherency phase was altered by the recording of sensory feedback in the cortical signals and both measures were affected by the presence of a closed loop feedback system. Only PDC phase led to the correct estimation of efferent transmission delay in all simulated model configurations. Coherency and DTF phase should not be used to estimate transmission delays in neural networks as the estimated time delays are meaningless in the presence of sensory feedback and closed feedback loops.
Laboratory of Biomechanical Engineering, MIRA Institute of Biomedical Engineering and Technical Medicine, University of Twente, PO box 217, 7500 AE, Enschede, the Netherlands, s.f.campfens@utwente.nl.
S Floor
SF
Campfens
Herman
H
van der Kooij
Alfred C
AC
Schouten
D000344:Afferent Pathways / Q000502:physiology; D003198:Computer Simulation; D056228:Feedback, Sensory / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009044:Motor Cortex / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D016571:Neural Networks, Computer; D011930:Reaction Time / Q000502:physiology*