Functional near-infrared spectroscopy can detect low-frequency hemodynamic oscillations in the prefrontal cortex during steady-state visual evoked potential-inducing periodic facial expression stimuli presentation

Abstract

Brain oscillations are vital to cognitive functions, while disrupted oscillatory activity is linked to various brain disorders. Although high-frequency neural oscillations (> 1 Hz) have been extensively studied in cognition, the neural mechanisms underlying low-frequency hemodynamic oscillations (LFHO) < 1 Hz have not yet been fully explored. One way to examine oscillatory neural dynamics is to use a facial expression (FE) paradigm to induce steady-state visual evoked potentials (SSVEPs), which has been used in electroencephalography studies of high-frequency brain oscillation activity. In this study, LFHO during SSVEP-inducing periodic flickering stimuli presentation were inspected using functional near-infrared spectroscopy (fNIRS), in which hemodynamic responses in the prefrontal cortex were recorded while participants were passively viewing dynamic FEs flickering at 0.2 Hz. The fast Fourier analysis results demonstrated that the power exhibited monochronic peaks at 0.2 Hz across all channels, indicating that the periodic events successfully elicited LFHO in the prefrontal cortex. More importantly, measurement of LFHO can effectively distinguish the brain activation difference between different cognitive conditions, with happy FE presentation showing greater LFHO power than neutral FE presentation. These results demonstrate that stimuli flashing at a given frequency can induce LFHO in the prefrontal cortex, which provides new insights into the cognitive mechanisms involved in slow oscillation.

The Bergen Breakfast Scanning Club dataset: a deep brain imaging dataset

“…One of the main goals of neuroscience is to understand the human brain's complexity and underlying neuronal mechanisms. One common approach to achieve this goal for the last three decades was to compare two groups of people with distinct phenotypes, such as between groups (Lu et al, 2020;Lu et al, 2021;Wang, Zhang, Miao, Lin, & Yuan, 2020) or conditions (Wang, Yuan, Zhang, Xiang, & Yuan, 2020;Wang & Yuan, 2021). This group average comparison method can provide insights into the general (cross-subject) brain functional and structural organization; however, it fails to depict the intra-and inter-subject discrepancies which is essential for understanding the brain.…”

Editorial: Variability and reproducibility of brain imaging

“…The human brain processes a constant stream of sensory information, necessitating advanced filtering and cognitive processing for tasks like recognizing dynamic facial expressions (Wang and Yuan, 2021 ). Advances in noninvasive neuroimaging methods, such as electroencephalogram (EEG) (Wang et al, 2020a ), magnetic resonance imaging (MRI) (Lu et al, 2021 ), and near-infrared spectroscopy (NIRS) (Wang et al, 2020b ) have deepened our understanding of how the human brain works over the last decades (Finn et al, 2023 ). However, the reliability and reproducibility of the results have been recently questioned and exposed in the spotlight (Cognitive neuroscience at the crossroads, 2022 ), highlighting the need to address and clarify the integrity of the research field (Revisiting doubt in neuroimaging research, 2022 ).…”