Auditory predictions and prediction errors in response to self-initiated vowels

Abstract

It has been suggested that speech production is accomplished by an internal forward model, reducing processing activity directed to self-produced speech in the auditory cortex. The current study uses an established N1-suppression paradigm comparing self-and externallyinitiated natural speech sounds to answer two questions:(1) Are forward predictions generated to process complex speech sounds, such as vowels, initiated via a button press?(2) Are prediction errors regarding self-initiated deviant vowels reflected in the corresponding ERP components?Results confirm an N1-suppression in response to self-initiated speech sounds.Furthermore, our results suggest that predictions leading to the N1-suppression effect are specific, as self-initiated deviant vowels do not elicit an N1-suppression effect. Rather, selfinitiated deviant vowels elicit an enhanced N2b and P3a compared to externally-generated deviants, externally-generated standard, or self-initiated standards, again confirming prediction specificity.Results show that prediction errors are salient in self-initiated auditory speech sounds, which may lead to more efficient error correction in speech production.

Event-related potential correlates of learning to produce novel foreign phonemes

“…In line with a large body of research Curio et al, 2000;Heinks-Maldonado et al, 2005;Houde et al, 2002;Knolle et al, 2019;Niziolek et al, 2013), we observed a strong SIS. Whereas we did not find any differences in SIS between foreign and native phonemes in the early or intermediate timewindows (i.e., N1-P2, 85-290 ms after phonation), activity in a later time-window (LSW, starting approximately 300 ms after vocalization onset) was modulated by the pronunciation of foreign phonemes.…”

“…Correctly performed actions and feedback on a successful performance are associated with a positive amplitude shift in frontal central locations-the reward positivity-often interpreted as a correlate of reinforcement signals (Carlson et al, 2011;Glazer et al, 2018;Holroyd & Coles, 2002;Hoy et al, 2021;Ullsperger et al, 2014). In addition, the positive amplitude shift in LSW also coincides with the timing and topography of the P3a wave, which reflects attentional capture of salient or motivationally relevant stimuli (Knolle et al, 2019;Polich, 2007). The P3a wave is elicited by sensory stimuli that require a behavioral response form the participants (e.g., participant needs to classify a stimulus and respond using a button press) (Pitts et al, 2012;Scheerer & Jones, 2018), which likely explains why a P3a wave was not observed in the present study.…”

The Prefrontal-Hippocampal Comparator: Volition and Episodic Memory

“…It requires, at least in part, volitional intention. Self-initiated behavior (navigation, thought, speech, imagination, memorization) may, in fact, make prediction error signals more salient (Knolle et al, 2019) allowing the strengthening of behavior when the predictive consequences of behavior are confirmed, or behavioral flexibility and memory updating when they are disconfirmed. My interest in volition and the hippocampal theta rhythm derived from the work of Vanderwolf (1971) showing the strong relationship between theta rhythm and voluntary movement in rats.…”

Temporally precise movement-based predictions in the mouse auditory cortex

“…Importantly, movement-related modulation in the cortex can reflect specific expectations. When a movement reliably produces a sound, suppression in the auditory cortex becomes stronger for self-generated sounds that match the expected frequency, and neurons respond more strongly when a movement produces an unexpected frequency [28][29][30][31][32] . Neurons in the mouse visual cortex also respond more strongly when a behavior is accompanied by unexpected visual consequences, further supporting the idea that prediction may be a fundamental component of cortical sensory processing 24,[33][34][35] .…”