Illusory Jitter Perceived at the Frequency of Alpha Oscillations

Abstract

Neural oscillations, such as alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-100 Hz), are widespread across cortical areas, and their possible functional roles include feature binding [1], neuronal communication [2, 3], and memory [1, 4]. The most prominent signal among these neural oscillations is the alpha oscillation. Although accumulating evidence suggests that alpha oscillations correlate with various aspects of visual processing [5-18], the number of studies proving their causal contribution in visual perception is limited [11, 16-18]. Here we report that illusory visual vibrations are consciously experienced at the frequency of intrinsic alpha oscillations. We employed an illusory jitter perception termed the motion-induced spatial conflict [19] that originates from the cyclic interaction between motion and shape processing. Comparison between the perceived frequency of illusory jitter and the peak alpha frequency (PAF) measured using magnetoencephalography (MEG) revealed that the inter- and intra-participant variations of the PAF are mirrored by an illusory jitter perception. More crucially, psychophysical and MEG measurements during amplitude-modulated current stimulation [20] showed that the PAF can be artificially manipulated, which results in a corresponding change in the perceived jitter frequency. These results suggest the causal contribution of neural oscillations at the alpha frequency in creating temporal characteristics of visual perception. Our results suggest that cortical areas, dorsal and ventral visual areas in this case, are interacting at the frequency of alpha oscillations [2, 3, 21-27].

Steady-state responses in the somatosensory system interact with endogenous beta activity

“…They showed 72 that the EEG response to the stimulation depends on both the stimulation intensity and the distance 73 between the flicker frequency and the participants' individual alpha frequency (IAF; Notbohm et al, 74 2016). Other studies found similar effects for tACS over occipital cortex which either increases EEG 75 power at participants' visual alpha frequency (Helfrich et al, 2014;Zaehle, Rach, & Herrmann, 2010), 76 or biases ongoing alpha oscillations in visual cortex towards the exogenous stimulation frequency 77 (Minami & Amano, 2017). Most previous studies have tested entrainment in visual cortex targeting 78 the alpha rhythm.…”

Non-linear transfer characteristics of stimulation and recording hardware account for spurious low-frequency artifacts during amplitude modulated transcranial alternating current stimulation (AM-tACS)

“…Interestingly, the DAC itself 321 exhibited comparatively weak artifacts, while the more complex setups showed stronger 322 artifacts at the modulation frequency and several harmonics. This might indicate that the effect 323 is driven by non-linearities of the stimulator or recording hardware rather than the DAC as 324 suggested by previous authors (Minami and Amano, 2017). 325…”

“…Consequently, the tACS artifact would be shifted into higher frequencies, elegantly 81 avoiding spectral overlap with the targeted brain oscillation. However, more recently low-fre-82 quency artifacts at have been reported in sensor-level MEG recordings during AM-tACS 83 (Minami and Amano, 2017). These artifacts required the application of advanced artifact sup-84 pression algorithms (Minami and Amano, 2017).…”

“…However, more recently low-fre-82 quency artifacts at have been reported in sensor-level MEG recordings during AM-tACS 83 (Minami and Amano, 2017). These artifacts required the application of advanced artifact sup-84 pression algorithms (Minami and Amano, 2017). Although the authors of that study explained 85 these artifacts by non-linear characteristics of the digital-analog conversion, a detailed inves-86 tigation into these low-frequency artifacts arising during AM-tACS and how these emerge has 87 not yet been provided.…”

“…336Given that the low-frequency AM-tACS artifacts are several orders of magnitude smaller than 337 the artifact arising during classical tACS (or at the carrier frequency), they are potentially easier 338 to correct/suppress i.e. by applying beamforming(Chander et al, 2016; Witkowski et al, 2016) 339 or temporal signal space separation(Minami and Amano, 2017; Taulu et al, 2005) in the MEG 340 and independent or principal component analysis (ICA/PCA) in the EEG(Helfrich et al, 2014). 341However, the efficiency of these methods in the context of AM-tACS needs to be systematically 342 investigated in future studies.…”