The influence of the global/local probability effect on the neural processing of cues and targets. A functional systems approach

The relative importance of local contingencies and global biases for statistical learning

Effective behavior requires adapting to the changing regularities evident in the world. Analogous to the global and local processing distinction for perception, these statistical regularities may be evident in global biases (i.e., some events are more likely) or local contingencies (i.e., subsequent events depend on preceding events). To explore whether mental model updating unfolds in distinct ways according to global and local statistical properties, we had healthy individuals perform two variations of an updating task in which both global and local statistical properties changed over time. Participants predicted whether the next triangle in a sequence of triangles would point up or down. The probability of pointing up or down was fixed for epochs of trials (i.e., global probability) and correlated with the colors of elements in the display. In addition, we made the triangle's apex direction on trial n+1 depend on the pointing direction of the prior trial (i.e., local probability). For both experiments, it was the local contingencies that dominated participant choices. When global and local statistical cues of equal magnitude are available, we conclude that healthy individuals are biased towards using the local statistical properties.

Late N1 and Post Imperative Negative Variation analysis depending on the previous trial history in paradigms of increasing auditory complexity

Predictive coding reflects the ability of the human brain to extract environmental patterns in order to reformulate previous expectations. The present report analyzes through the late N1 auditory component and the post imperative negative variation (PINV) the updating of predictions regarding the characteristics of a new trial, depending on the previous trial history, complexity, and type of trial (standard or deviant). Data were obtained from 31 healthy subjects recorded in a previous study, based on two paradigms composed of stimulus sequences of decreasing or increasing frequencies intermingled with the sporadic appearance of unexpected tone endings. Our results showed a higher amplitude for the most complex condition and deviant trials for both the late N1 and the PINV components. Additionally, the N1 and PINV presented a different amplitude response to the standard and deviant trials as a function of previous trial history, suggesting a continuous updating of trial categorization. The results suggest that the late N1 and PINV components are involved in the generation of an internal model about the rules of external auditory stimulation.

P300 response modulation reflects breaches of non-probabilistic expectations

In oddball paradigms, infrequent stimuli elicit larger P300 event related potentials (ERPs) than frequent ones. One hypothesis is that P300 modulations reflect the degree of “surprise” associated with unexpected stimuli. That is the P300 represents how unlikely the stimulus is and this signal is then used to update the observer’s expectations. It could be hypothesized that P300 is modulated by any factor affecting an observer’s expectations, not only target probability. Alternatively, the P300 may reflect an evaluative process engaged whenever a discrepancy between task context and sensory inputs arises, irrespective of the latter probability. In previous ERP studies, stimulus probability was often the only determinant of task set confounding the effects of stimulus probability and set stimulus discrepancy. In this study, we used a speeded luminance detection task. The target was preceded by a central cue that predicted its location. The probability that the target was valid, i.e. would appear at the cued location was manipulated by varying the reliability of the cue. Reaction times were modulated by probabilistic expectations based on cue reliability and target validity while P300 was affected by target validity only. We conclude that increased P300 amplitude reflects primarily breaches of non-probabilistic expectations, rather than target probability.

Tracking the Time Course of Bayesian Inference With Event-Related Potentials:A Study Using the Central Cue Posner Paradigm

In this study, we asked whether the event-related potentials associated to cue and target stimuli of a Central Cue Posner Paradigm (CCPP) may encode key parameters of Bayesian inference – prior expectation and surprise – on a trial-by-trial basis. Thirty-two EEG channel were recorded in a sample of 19 young adult subjects while performing a CCPP, in which a cue indicated (validly or invalidly) the position of an incoming auditory target. Three different types of blocks with validities of 50%, 64%, and 88%, respectively, were presented. Estimates of prior expectation and surprise were obtained on a trial-by-trial basis from participants’ responses, using a computational model implementing Bayesian learning. These two values were correlated on a trial-by-trial basis with the EEG values in all the electrodes and time bins. Therefore, a Spearman correlation metrics of the relationship between Bayesian parameters and the EEG was obtained. We report that the surprise parameter was able to classify the different validity blocks. Furthermore, the prior expectation parameter showed a significant correlation with the EEG in the cue-target period, in which the Contingent Negative Variation develops. Finally, in the post-target period the surprise parameter showed a significant correlation in the latencies and electrodes in which different event-related potentials are induced. Our results suggest that Bayesian parameters are coded in the EEG signals; and namely, the CNV would be related to prior expectation, while the post-target components P2a, P2, P3a, P3b, and SW would be related to surprise. This study thus provides novel support to the idea that human electrophysiological neural activity may implement a (Bayesian) predictive processing scheme.