Neural decoding of bistable sounds reveals an effect of intention on perceptual organization

Abstract

Auditory signals arrive at the ear as a mixture that the brain must decompose into distinct sources, based to a large extent on acoustic properties of the sounds. An important question concerns whether listeners have voluntary control over how many sources they perceive. This has been studied using pure tones H and L presented in the repeating pattern HLH-HLH-, which can form a bistable percept, heard either as an integrated whole (HLH-) or as segregated into high (H-H-) and low (-L--) sequences. Although instructing listeners to try to integrate or segregate sounds affects reports of what they hear, this could reflect a response bias rather than a perceptual effect. We had human listeners (15 males, 12 females) continuously report their perception of such sequences and recorded neural activity using magnetoencephalography. During neutral listening, a classifier trained on patterns of neural activity distinguished between periods of integrated and segregated perception. In other conditions, participants tried to influence their perception by allocating attention either to the whole sequence, or to a subset of the sounds. They reported hearing the desired percept for a greater proportion of time than when listening neutrally. Critically, neural activity supported these reports; stimulus-locked brain responses in auditory cortex were more likely to resemble the signature of segregation when participants tried to hear segregation than when attempting to perceive integration. These results indicate that listeners can influence how many sound sources they perceive, as reflected in neural responses that track both the input and its perceptual organization. Significance StatementCan we consciously influence our perception of the external world? We address this question using sound sequences that can be heard either as coming from a single source, or as two distinct auditory streams. Listeners reported spontaneous changes in their perception between these two interpretations while we recorded neural activity to identify signatures of such integration and segregation. They also indicated that they could, to some extent, choose between these alternatives. This claim was supported by corresponding changes in responses in auditory cortex. By linking neural and behavioral correlates of perception we demonstrate that the number of objects we perceive can depend not only on the physical attributes of our environment, but also on how we intend to experience it.

Rhythmic Temporal Expectation Boosts Neural Activity by Increasing Neural Gain

“…On a methodological note, our study is the first to show robust M/EEG-based multivariate decoding of pure tone frequency across a broad range of frequencies. While recent studies have brought substantial advances in decoding auditory features, studies using discreet stimuli have focused on decoding complex features such as pitch/rate modulation based on spectral information in MEG signals (Herrmann et al, 2013b) or bistable percepts based on evoked MEG responses (Billig et al, 2018). In the domain of speech decoding, speech-evoked responses can be used to decode vowel categories (Yi et al, 2017), but typically a combination of complex spectral features is used to decode the speech envelope (Luo and Poeppel, 2007;Ng et al, 2013;de Cheveigné et al, 2018).…”

Decoding continuous variables from event-related potential (ERP) data with linear support vector regression (SVR) using the Decision Decoding Toolbox (DDTBOX)

“…DDTBOX uses a moving-window approach in which the trial data (usually containing a baseline period and epoched and truncated, depending on the individual research question) is analysed within an analysis time window, which is moved through the entire trial in small (overlapping or non-overlapping) steps, each time containing the next step's data. It is also possible to use a pre-defined time-period of interest instead (e.g., Billing et al, 2018), but we will focus on the moving-window approach in this paper. Each analysis step/window is treated as an independent analysis.…”

Slow rhythmic eye motion predicts periodic alternation of bistable perception

“…For example, it was observed that asking subjects intentionally to switch or hold their perceptual states can significantly bias their perceptual alternation rate of bistable perception 10,11,13,30 . While such behavioral changes stemming from various factors have been observed, the detailed mechanism by which these components mediate perceptual alternation frequency remains unknown 18,31 .…”