Steady-state visual evoked potential (SSVEP) has been widely used in electroencephalogram (EEG)-based brain-computer interfaces (BCIs) due to its high information transfer rate (ITR) and short training time. Current methods usually measure SSVEP from electrodes on the scalp, which is an uncomfortable and time-consuming method. Furthermore, most research relies on expensive and non-portable EEG devices. To utilise BCIs in daily life, however, these are critical issues to address. Hence, a wearable EEG device for in-ear SSVEP detection is proposed. The system is 40 × 21 × 10.5 mm 3 and weighs 14.2 g, thus being light weight and wearable. Moreover, the system has a noise level of 0.11 µV rms , which is comparable with commercial EEG systems. Six subjects participated in an offline BCI experiment that consisted of six visual targets using the developed in-the-ear EEG system. The results showed a highest ITR of 11.03 ± 4.18 bits/min with an accuracy of 79.9 ± 13.1%, and the experiments demonstrated that the system can be utilised for unobtrusive monitoring of SSVEP in BCI applications.

Pupillometry, thanks to its strong relationship with cognitive factors and recent advancements in measuring techniques, has become popular among cognitive or neural scientists as a tool for studying the physiological processes involved in mental or neural processes. Despite this growing popularity of pupillometry, the methodological understanding of pupillometry is limited, especially regarding potential factors that may threaten pupillary measurements’ validity. Eye blinking can be a factor because it frequently occurs in a manner dependent on many cognitive components and induces a pulse-like pupillary change consisting of constriction and dilation with substantive magnitude and length. We set out to characterize the basic properties of this “blink-locked pupillary response (BPR),” including the shape and magnitude of BPR and their variability across subjects and blinks, as the first step of studying the confounding nature of eye blinking. Then, we demonstrated how the dependency of eye blinking on cognitive factors could confound, via BPR, the pupillary responses that are supposed to reflect the cognitive states of interest. By building a statistical model of how the confounding effects of eye blinking occur, we proposed a probabilistic-inference algorithm of de-confounding raw pupillary measurements and showed that the proposed algorithm selectively removed BPR and enhanced the statistical power of pupillometry experiments. Our findings call for attention to the presence and confounding nature of BPR in pupillometry. The algorithm we developed here can be used as an effective remedy for the confounding effects of BPR on pupillometry.

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Background: Although transcranial direct current stimulation (tDCS) is widely used to affect various kinds of human cognition, behavioral studies on humans have produced highly inconsistent results. This requires a clear understanding of how tDCS impacts the system-level neural activity, a prerequisite for the principled application of tDCS to human cognition. Objective: Here, we aim to gain such understanding by probing the spatial and temporal cortical activity of the human early visual cortex (EVC) in diverse aspects while controlling the polarity and presence of tDCS. We target EVC to capitalize on its well-established anatomical and functional architecture that is readily accessible with non-invasive quantitative neuroimaging methods. Methods: To create an electric field in EVC precisely and effectively, we tailored high-definition stimulation montages for 15 individual brains by running electric field simulations. We then conducted an fMRI (functional magnetic neuroimaging)-tDCS experiment on each brain with a sham-controlled crossover design over multiple days. We quantified tDCS effects with eight measures, tested their significance with mixed ANOVA, and further validated their robustness to across-voxel and across-subject variability. Results: The anodal application of tDCS gradually elevated baseline BOLD activity of EVC and sharpened its spatial tuning by augmenting surround suppression without affecting its evoked activity. Conclusions: Comparisons of our and previous findings suggest the fundamental differences in tDCS effects between the visual and motor cortices, inhibitory and excitatory effects predominant in the former and latter, respectively. This calls for considering the differences in the excitatory-inhibitory recurrent network between brain regions in predicting or interpreting tDCS effects.

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