Entrainment of visual steady-state responses is modulated by global spatial statistics

Abstract

The rhythmic delivery of visual stimuli evokes large-scale neuronal entrainment in the form of steady-state oscillatory field potentials. The spatiotemporal properties of stimulus drive appear to constrain the relative degrees of neuronal entrainment. Specific frequency ranges, for example, are uniquely suited for enhancing the strength of stimulus-driven brain oscillations. When it comes to the nature of the visual stimulus itself, studies have used a plethora of inputs ranging from spatially unstructured empty fields to simple contrast patterns (checkerboards, gratings, stripes) and complex arrays (human faces, houses, natural scenes). At present, little is known about how the global spatial statistics of the input stimulus influence entrainment of scalp-recorded electrophysiological signals. In this study, we used rhythmic entrainment source separation of scalp EEG to compare stimulus-driven phase alignment for distinct classes of visual inputs, including broadband spatial noise ensembles with varying second-order statistics, natural scenes, and narrowband sine-wave gratings delivered at a constant flicker frequency. The relative magnitude of visual entrainment was modulated by the global properties of the driving stimulus. Entrainment was strongest for pseudo-naturalistic broadband visual noise patterns in which luminance contrast is greatest at low spatial frequencies (a power spectrum slope characterized by 1/ƒ). Rhythmically modulated visual stimuli entrain the activity of neuronal populations, but the effect of global stimulus statistics on this entrainment is unknown. We assessed entrainment evoked by ) visual noise ensembles with different spectral slopes,) complex natural scenes, and ) narrowband sinusoidal gratings. Entrainment was most effective for broadband noise with naturalistic luminance contrast. This reveals some global properties shaping stimulus-driven brain oscillations in the human visual system.

LncRNA-AK131850 Sponges MiR-93-5p in Newborn and Mature Osteoclasts to Enhance the Secretion of Vascular Endothelial Growth Factor a Promoting Vasculogenesis of Endothelial Progenitor Cells

“…Similarly, our results also predicted the putative miR-93-5p binding sites with 3′-UTR of VEGFa and luciferase reporter assay further confirmed that miR-95-5p directly targeted VEGFa. Additionally, a novel post-transcriptional regulatory mechanism of RNAs has been reported in which lncRNAs crosstalk with miRNAs through competing, functioning as competing endogenous RNAs and thus modulating the derepression of miRNAs on their targets [55]. For instance, Xiao et al demonstrate that LncRNA MALAT1 may function as a competing endogenous RNAs to up-regulate Smad4 expression by sponging miR-204, promoting osteoblast differentiation of human aortic valve interstitial cells [28].…”

Phase Entrainment by Periodic Stimuli In Silico: A Quantitative Study

“…The signal amplitudes are trivial here as they do not affect the phases. Thus, the phase relation can be mapped on the unit circle in the complex plane, see (7). The Phase Locking Value (PLV) is defined as the mean of the instantaneous phase differences [55,56]:…”

“…There are different ways to measure neuronal synchrony. Our focus in this work is on phase synchronisation that is observed in steady state visually evoked potentials (SSVEP) -electroencephalogram (EEG) signals picked up by the scalp electrodes over the occipital and parietal lobes when a subject looks at a flickering light source [6,7]. SSVEP signals have stable spectrum and high signal-to-noise ratio, which makes them popular in clinical neuroscience for studying neurological conditions such as schizophrenia, migraine and epilepsy [8].…”

Towards a state-space geometry of neural responses to natural scenes: A steady-state approach

“…Exactly how the early visual system enables unique neural representations from this onslaught of visual information is a long-standing question in systems neuroscience. The last two decades have provided novel insights into the early visual encoding of real world stimulus images ("natural scenes") in non-human vertebrates at levels of analysis ranging from single-units [1][2][3][4][5][6][7][8][9] to local population measures [10][11][12], and in humans using macro-scale measures such as EEG or fMRI [13][14][15][16][17][18] and psychophysics [19][20][21][22][23][24].…”