Low-frequency cortical oscillations are modulated by temporal prediction and temporal error coding

Barne, Louise Catheryne; Claessens, Patricia; Reyes, Marcelo Bussotti; Caetano, Marcelo S.; Cravo, André M.

doi:10.1016/j.neuroimage.2016.11.028

Cited by 14 publications

(11 citation statements)

References 42 publications

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“…It is reasonable for timing prediction to induce positive delta waveform and beta-gamma ERSP suppression, especially in the central brain area. To be specific, delta oscillation in the central area is believed to be instrumental for reflecting many voluntary mental activities, including the perceptual judgement [ 20 , 30 , 31 ], difficulty assessment [ 30 ], target detection [ 31 ], perceptual learning [ 28 , 32 ], etc. In the current study, the ERP profiles started to go upwards shortly after the predicted moment, which worked as a reflection of perceptual judgement, indicating subjects have realized that time was up.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, the ‘what’ template was observed with the assistance of magnetoencephalogram (MEG) [ 21 ] or high-resolution functional magnetic resonance image (fMRI) [ 19 , 22 ], but no EEG evidence was found. While the ‘when’ template is usually embodied as the estimation of specific time interval and could trigger specific patterns of neural oscillations in both the MEG [ 23 , 24 , 25 , 26 ] and EEG [ 27 , 28 ] studies. On that basis, this study investigated the endogenous signatures of timing prediction and tested whether distinct temporal templates can induce separable EEG features for active brain–computer interfaces.…”

Section: Introductionmentioning

confidence: 99%

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Separable EEG Features Induced by Timing Prediction for Active Brain-Computer Interfaces

Meng

Wang

et al. 2020

Sensors

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Brain–computer interfaces (BCI) have witnessed a rapid development in recent years. However, the active BCI paradigm is still underdeveloped with a lack of variety. It is imperative to adapt more voluntary mental activities for the active BCI control, which can induce separable electroencephalography (EEG) features. This study aims to demonstrate the brain function of timing prediction, i.e., the expectation of upcoming time intervals, is accessible for BCIs. Eighteen subjects were selected for this study. They were trained to have a precise idea of two sub-second time intervals, i.e., 400 ms and 600 ms, and were asked to measure a time interval of either 400 ms or 600 ms in mind after a cue onset. The EEG features induced by timing prediction were analyzed and classified using the combined discriminative canonical pattern matching and common spatial pattern. It was found that the ERPs in low-frequency (0~4 Hz) and energy in high-frequency (20~60 Hz) were separable for distinct timing predictions. The accuracy reached the highest of 93.75% with an average of 76.45% for the classification of 400 vs. 600 ms timing. This study first demonstrates that the cognitive EEG features induced by timing prediction are detectable and separable, which is feasible to be used in active BCIs controls and can broaden the category of BCIs.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Separable EEG Features Induced by Timing Prediction for Active Brain-Computer Interfaces

Meng

Wang

et al. 2020

Sensors

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“…36 It is currently an open question to what extend entrained neural delta oscillations 37 are a signature of processing rhythmic input, or whether they pose a more parsimo- 38 nious mechanism of temporal prediction. Important evidence for an endogenous role 39 of delta oscillations in auditory temporal attention comes from two studies showing 40 that auditory processing fluctuates with the phase of spontaneously present delta 41 activity in auditory cortex, in absence of rhythmic stimulation [38,39]. 42 Furthermore, previous studies have shown that entrainment is subject to top- 43 down modulation, shown by enhanced phase coherence of slow oscillations in antici- 44 pation of temporally predictive input [11,16,35].…”

Section: Introductionmentioning

confidence: 99%

“…To our knowledge, only one study in the visual domain reported a role 49 of slow oscillations in single trial temporal predictions [5, theta band]. Furthermore, 50 a recent study [41] showed that delta phase in the target-onset time window reflects 51 adjustments to previously encountered violations of temporal predictions in an explicit 52 timing task. To date, to the best of our knowledge, no study has assessed whether 53 oscillations implement implicit temporal predictions for audition.…”

Section: Introductionmentioning

confidence: 99%

“…Due to computational constraints, we only specified a random 327 intercept, but no random slopes for the predictors. 328 To account for the circularity of the phase angles, we followed an approach 329 previously described by Wyart et al [55] (see also [16,41]) of using the sine and cosine 330 of the phase angles jointly as linear predictors in a regression. For both, the sin(ϕ) 331 and cos(ϕ), we specified an interaction with ∆pitch:…”

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confidence: 99%

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Implicit temporal predictability biases slow oscillatory phase in auditory cortex and enhances pitch discrimination sensitivity

Herbst

Obleser

2018

Preprint

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Can human listeners use implicit temporal contingencies in auditory input to form temporal predictions, and if so, how are these predictions represented endogenously? To assess this question, we manipulated foreperiods in an auditory pitch discrimination task: unbeknownst to participants, the pitch of the standard tone could either be deterministically predictive of the temporal onset of the target tone, or convey no predictive information. Predictive and non-predictive conditions were presented interleaved in one stream, and separated by variable inter-stimulus intervals such that there was no dominant stimulus rhythm throughout. Even though participants were unaware of the implicit temporal contingencies, pitch discrimination sensitivity (the slope of the psychometric function) increased when the onset of the target tone was predictable in time (N = 49, 28 female, 21 male). Concurrently recorded EEG data (N = 24) revealed that standard tones that conveyed temporal predictions evoked a more negative N1 component than non-predictive standards. We observed no significant differences in oscillatory power or phase coherence between conditions during the foreperiod. Importantly, the phase angle of delta oscillations (1-3 Hz) in auditory areas in the post-standard and pre-target time window predicted behavioral pitch discrimination sensitivity. This suggests that temporal predictions can be initiated by an optimized delta phase reset and are encoded in delta oscillatory phase during the foreperiod interval. In sum, we show that auditory perception benefits from implicit temporal contingencies, and provide evidence for a role of slow neural phase in the endogenous representation of temporal predictions, in absence of exogenously driven entrainment to rhythmic input. Acknowledgments: This research was supported by a DFG grant (HE 7520/1-1) to SKH.Auditory environments come with an inherent temporal structure, which human listeners can use to predict the timing of future inputs. Yet, how these regularities in sensory inputs are transformed into temporal predictions is not known. Here, we implicitly induced temporal predictability in the absence of a rhythmic input structure, to avoid exogenously driven entrainment of neural oscillations. Our results show that even implicit and non-rhythmic temporal predictions are extracted and used by human listeners, underlining the role of timing for auditory processing. Furthermore, our EEG results point towards an instrumental role of delta oscillations in initiating temporal predictions, possibly by an optimized phase reset in response to a temporally predictive cue.

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Timing the Brain to Time the Mind: Critical Contributions of Time-Resolved Neuroimaging for Temporal Cognition

Wassenhove

Herbst

Kononowicz

2019

Magnetoencephalography

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Low-frequency cortical oscillations are modulated by temporal prediction and temporal error coding

Cited by 14 publications

References 42 publications

Separable EEG Features Induced by Timing Prediction for Active Brain-Computer Interfaces

Separable EEG Features Induced by Timing Prediction for Active Brain-Computer Interfaces

Implicit temporal predictability biases slow oscillatory phase in auditory cortex and enhances pitch discrimination sensitivity

Timing the Brain to Time the Mind: Critical Contributions of Time-Resolved Neuroimaging for Temporal Cognition

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