Cognitive loading via mental arithmetic modulates effects of blink‐related oscillations on precuneus and ventral attention network regions

Abstract

Blink‐related oscillations (BROs) have been linked with environmental monitoring processes associated with blinking, with cortical activations in the bilateral precuneus. Although BROs have been described under resting and passive fixation conditions, little is known about their characteristics under cognitive loading. To address this, we investigated BRO effects during both mental arithmetic (MA) and passive fixation (PF) tasks using magnetoencephalography (n =20), while maintaining the same sensory environment in both tasks. Our results confirmed the presence of BRO effects in both MA and PF tasks, with similar characteristics including blink‐related increase in global field power and blink‐related activation of the bilateral precuneus. In addition, cognitive loading due to MA also modulated BRO effects by decreasing BRO‐induced cortical activations in key brain regions including the bilateral anterior precuneus. Interestingly, blinking during MA—but not PF—activated regions of the ventral attention network (i.e., right supramarginal gyrus and inferior frontal gyrus), suggesting possible recruitment of these areas for blink processing under cognitive loading conditions. Time–frequency analysis revealed a consistent pattern of BRO‐related effects in the precuneus in both tasks, but with task‐related functional segregation within the anterior and posterior subregions. Based on these findings, we postulate a potential neurocognitive mechanism for blink processing in the precuneus. This study is the first investigation of BRO effects under cognitive loading, and our results provide compelling new evidence for the important cognitive implications of blink‐related processing in the human brain.

How the motor aspect of speaking influences the blink rate

“…This clearly indicates that the cognitive load was not particularly increased during normal vocalization. After this important step, we did not find a significant difference in blink rate between the easy and difficult task, but there is a tendency towards a higher blink rate during difficult tasks, which has been reported previously [5,23,33]. Our results further showed that an increase above baseline and a clearly visible modulation due to task difficulty was only observed when the task was performed with vocalization.…”

“…mental arithmetic, revealed contradictory outcomes. While some researchers showed a negative correlation between blink rate and cognitive load during mental arithmetic [24,25], other studies found an increase in blink rate for difficult arithmetic compared to rest or easy arithmetic [5,23]. The advantage of an arithmetic task, in comparison to our task, namely talking about a given topic, is that one can receive feedback as to the solution for such a task and easily control for the task fulfilment.…”

“…Humans blink approximately every 3-6 seconds, which is far more than needed to keep a constant tear film on the cornea [1]. Blink behavior is known to be affected by multiple factors, including external sensory [e.g., 2,3] and internal cognitive factors [e.g., 4,5]. During visually demanding tasks such as reading, the blink rate drops from approximately 17 blinks per minute during rest to approximately 4 to 5 blinks per minute.…”

“…Consequently, if other factors such as speaking increases blink rate in the same direction, this might lead to inaccurate medical examinations. In healthy humans, blink rate is often used as an indicator of cognitive load [e.g., 4,5,15]. A speech-related motor influence might therefore affect experimental outcomes using verbal responses.…”

Brain Vital Signs: Expanding From the Auditory to Visual Modality

“…Artifact rejection was done using gradients (maximal allowed voltage step: 10 uV/ms and maximal allowed difference of values in intervals: 100 uV), and visually reviewed for each subject. In line with prior work (Liu et al, 2017, 2018), independent component analysis (ICA) was performed for artifact correction (e.g., blinks, saccades, cardiac activity, muscle contractions, breathing) using the Infomax algorithm (Lee et al, 1999). Segments were baseline corrected (−100 to 0 ms), low-passed filtered at 20 Hz, and averaged based on experimental condition (Luck, 2014).…”