This article was timely in that I wanted to present something about how entrainment influences neuroplasticity as a way to underscore the relevance of using specific QEEG-informed pulse frequencies in the delivery of tPBM. This paper is helpful specifically as it relates to visual processing efficiency, i.e., perceptual decision making. It is not much of an inference to extrapolate to other sensory processes and the likelihood that their functionality will be positively effected using the same methodology. The Neuradiant 1070+ technology integrated this principle by including pulse frequency control in 4 independent quadrants.
From the abstract:
Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual’s alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.
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