Long-Range Temporal Correlations in Alpha Oscillations Stabilize Perception of Ambiguous Visual Stimuli

Abstract

Ongoing brain dynamics have been proposed as a type of “neuronal noise” that can trigger perceptual switches when viewing an ambiguous, bistable stimulus. However, no prior study has directly quantified how such neuronal noise relates to the rate of percept reversals. Specifically, it has remained unknown whether individual differences in complexity of resting-state oscillations—as reflected in long-range temporal correlations (LRTC)—are associated with perceptual stability. We hypothesized that participants with stronger resting-state LRTC in the alpha band experience more stable percepts, and thereby fewer perceptual switches. Furthermore, we expected that participants who report less discontinuous thoughts during rest, experience less switches. To test this, we recorded electroencephalography (EEG) in 65 healthy volunteers during 5 min Eyes-Closed Rest (ECR), after which they filled in the Amsterdam Resting-State Questionnaire (ARSQ). This was followed by three conditions where participants attended an ambiguous structure-from-motion stimulus—Neutral (passively observe the stimulus), Hold (the percept for as long as possible), and Switch (as often as possible). LRTC of resting-state alpha oscillations predicted the number of switches only in the Hold condition, with stronger LRTC associated with less switches. Contrary to our expectations, there was no association between resting-state Discontinuity of Mind and percept stability. Participants were capable of controlling switching according to task goals, and this was accompanied by increased alpha power during Hold and decreased power during Switch. Fewer switches were associated with stronger task-related alpha LRTC in all conditions. Together, our data suggest that bistable visual perception is to some extent under voluntary control and influenced by LRTC of alpha oscillations.

Temporal Signatures of Criticality in Human Cortical Excitability as Probed by Early Somatosensory Responses

“…DFA was chosen since it requires less strict assumptions about the stationarity of the signal than the classical auto-correlation function or power spectral density (Linkenkaer-Hansen et al, 2001;Hardstone et al, 2012;Sangiuliano Intra et al, 2018), and its power-law exponent estimates are robust even when removing large portions of the data or when analyzing data that have been stitched together (Chen et al, 2002). Furthermore, the choice of DFA allowed direct comparisons with the existing literature on scale-free behavior in neuronal data.…”

Circadian Rhythms in Fractal Features of EEG Signals

“…It has been suggested that the temporal correlations of amplitude modulation of oscillations on time scales of seconds to tens of seconds may be important for the temporal integrity of cognition, since a reduction of scaling exponent is related to several neurological impairments and diseases (Hausdorff et al, 2001 ; Parish et al, 2004 ; Linkenkaer-Hansen et al, 2005 ; Montez et al, 2009 ). Moreover, a more whitened state, characterized by a lower scaling exponent, has been found to lead more often to percept destabilization (Sangiuliano Intra et al, 2018 ).…”

Long-range temporal correlation in Auditory Brainstem Responses to Spoken Syllable/da/

“…It has been exhibited that various time series extracted from biological systems, including electrocardiography (ECG) [21,22], electroencephalography (EEG) [23][24][25][26][27][28][29][30][31][32][33][34][35], signal neuron discharge [36] and human gait [37] behave as scale-invariant processes. The power-law scaling studies have shown the of the behaviors in the complex biological systems [38][39][40][41][42]. The indicates that there are properties for a large portion of systems which are independent of the dynamics of systems.…”