Distinguishing Neural Adaptation and Predictive Coding Hypotheses in Auditory Change Detection

Abstract

The auditory mismatch negativity (MMN) component of event-related potentials (ERPs) has served as a neural index of auditory change detection. MMN is elicited by presentation of infrequent (deviant) sounds randomly interspersed among frequent (standard) sounds. Deviants elicit a larger negative deflection in the ERP waveform compared to the standard. There is considerable debate as to whether the neural mechanism of this change detection response is due to release from neural adaptation (neural adaptation hypothesis) or from a prediction error signal (predictive coding hypothesis). Previous studies have not been able to distinguish between these explanations because paradigms typically confound the two. The current study disambiguated effects of stimulus-specific adaptation from expectation violation using a unique stimulus design that compared expectation violation responses that did and did not involve stimulus change. The expectation violation response without the stimulus change differed in timing, scalp distribution, and attentional modulation from the more typical MMN response. There is insufficient evidence from the current study to suggest that the negative deflection elicited by the expectation violation alone includes the MMN. Thus, we offer a novel hypothesis that the expectation violation response reflects a fundamentally different neural substrate than that attributed to the canonical MMN.

Immediate stimulus repetition abolishes stimulus expectation and surprise effects in fast periodic visual oddball designs

“…What are the likely cortical sources of the visual mismatch responses we observed in Experiment 2? The topographies of the frequency domain ( Figure 6C Figure 7B) appears to reflect a posterior negativity to surprising stimuli, accompanied by the negative dipole of a frontal positivity to surprising stimuli (for similar results see Dambacher et al, 2009;Symonds et al, 2017). The later part of the response (~330ms in Figure 7B) appears to instead be generated from bilateral posterior sources.…”

“…Recent work has found that repetition effects are larger for surprising stimuli, due to large surprise-related signal increases for unrepeated stimuli (Amado & Kovacs, 2016;Larsson & Smith, 2012;Choi et al, 2017;Kovacs et al, 2012Kovacs et al, , 2013reviewed in Kovacs & Vogels, 2014). Similar interaction effects have also been found for ERPs/ERFs, with several studies showing that expectation violation responses can be reduced when stimuli are repeated (Todorovic & de Lange, 2012;Symonds et al, 2017;Wacongne et al, 2011). Demonstrating similar interactions in visual oddball designs is critical to extending existing models of novelty/change detection (e.g., Kremlacek et al, 2016) to incorporate interacting mechanisms driven by recent stimulus exposure (stimulus repetition) and longer-term stimulus appearance probabilities (expectation).…”

A Review of Auditory Prediction and Its Potential Role in Tinnitus Perception

“…Attention (broadly referring to the ability or power to concentrate mentally [Zenner et al, 2006;Fritz et al, 2007]) appears to serve the purpose of enhancing rather than generating predictive processes. Regularity formation and deviation detection can act independently of attention (Takegata et al, 2005;Winkler et al, 2005;Symonds et al, 2017). Chennu et al (2016) observed using electroencephalography (EEG) and magnetoencephalography (MEG) that attention modulates the strength and precision of prediction errors generated for omissions.…”

Brain signatures of surprise in EEG and MEG data

“…Similar surprise-related temporal components have been 94 reported in the studies of MEG (Magnetoencephalography) signals [34][35][36]. 95 An experiment specifically designed to account for the different brain reactions to 96 rare and frequent stimuli is the oddball task, in which a randomly composed 97 sequence of standard and deviant stimuli is presented to a subject [27,28,37]. 98 Previous surprise modeling studies mainly base their conclusions on a single 99 component extracted from the brain signals, with the MMN [27] or the P300 [12, 24, 100 25] or both [29] serving as the main such target components.…”