Table 1.

Definition of Main Terms in the Predictive Coding Framework.

Predictive coding	Neurobiologically informed theory of general brain function based on a generative mechanism of Bayesian hierarchical inference. Based on a model of the current stimulation, predictive coding posits that higher order processing stations send predictions to lower hierarchical levels to aid the suppression of any ascending neuronal activity evoked by sensory events that can be anticipated. These lower stations also forward prediction errors to the higher hierarchical levels whenever their current predictions fail, to prioritize the processing of those inputs and update the perceptual model. Hence, perception emerges from a dynamic interaction between top-down expectations and bottom-up prediction errors.
Rule or regularity	Logical principle that organizes the relationships between successive stimuli featuring in an experimental sequence used to study the effects of predictive coding on perceptual processing. In the oddball paradigm, where two tones are presented successively with an uneven probability of appearance (usually 90% vs. 10%), that regularity would be generated by the repetition of the common tone. More complex (or even abstract) rules can be implemented in experimental sequences to analyze the effects of identifying a particular regularity (e.g., two-tone alternation paradigm). Furthermore, multiple rules could be simultaneously at play in a given sequence (e.g., in the local/global paradigm).
Regularity encoding	The ability of a processing network to extract regular interstimulus relationships and adjust them to a perceptual model accounting for the organization of the flow of incoming sensory inputs. Thereby, it generates an internal representation from which perception and predictions or expectations about upcoming events emerge.
Standard condition	A sensory event that fits in the experimental rule or regularity. In other words, a sensory input that can be predicted by the perceptual model encoded in a certain processing network. In the oddball paradigm, the standard condition would be the commonly repeating stimulus.
Deviant condition	A sensory event that represents a punctual violation of the experimental rule or regularity. In other words, a sensory input that cannot be predicted by the perceptual model encoded in a certain processing network. The absence of that sensory input, that is, an omission, can also constitute a deviant condition. In the oddball paradigm, the deviant condition would be the random rare stimulus.
Deviance detection	Response evoked by a stimulus that violates a regularity encoded in the processing system, when compared with the response evoked by that same stimulus when it fitted in the internal representation of that regularity. In other words, the response contrasts to a certain stimulus when it was predictable and when it could not be predicted by the perceptual model. In the oddball paradigm, its index corresponds to the difference wave (for LFPs and ERPs, like MMN) or the contrast in firing rate (for cellular recordings, like SSA) between the rare tone (deviant condition) and the common tone (standard condition).
Expectation suppression	Decrease in the response evoked by a stimulus that was predictable, based on the perceptual model held on a certain processing network. In other words, the attenuating effect that an encoded representation has on the response to a sensory input that is coherent with it.
Repetition suppression	Decrease in the evoked response of a stimulus due to its reoccurrence. It is the simplest form of expectation suppression and the result of assuming that the upcoming input will be similar to the previous one represented. In the oddball paradigm, its index corresponds to the component of deviance detection between the control and the standard conditions.
Prediction error	Increase in the response evoked by a stimulus (or its omission) that could not be predicted by the perceptual model established on a certain processing network. In other words, the enhancement of the response to a sensory input (or the absence of it) that violates an encoded regularity. It constitutes an effort to mobilize processing resources at higher level networks, to update the internal representation of the ongoing stimulation and better account for the incoming input. In the oddball paradigm, its index corresponds to the component of deviance detection between the deviant and the control conditions.
Mismatch negativity	Scalp-recorded ERP biomarker of deviance detection, usually peaking at 150 to 250 ms from deviance onset in humans. MMN-like or mismatch signals are also detectable in animal models.
Stimulus-specific adaptation	Index of change in the firing rate of a single neuron or a localized neuronal population in response to a rare (deviant) tone randomly presented as part of an oddball sequence with another commonly repeating (standard) tone. Index of deviance detection for the oddball paradigm most commonly used in animal models.

Note. Most of the concept descriptions are illustrated taking as example the oddball paradigm, for its simplicity and popularity. Nevertheless, these terms are applicable to any experimental design in the study of deviance detection. ERP = event-related potential; LFPs = local field potentials; MMN = mismatch negativity; SSA = stimulus-specific adaptation.