Yi Fang Hsu

Both attention and prediction are necessary for adaptive neuronal tuning in sensory processing

The brain as a proactive system processes sensory information under the top-down influence of attention and prediction. However, the relation between attention and prediction remains undetermined given the conflation of these two mechanisms in the literature. To evaluate whether attention and prediction are dependent of each other, and if so, how these two top-down mechanisms may interact in sensory processing, we orthogonally manipulated attention and prediction in a target detection task. Participants were instructed to pay attention to one of two interleaved stimulus streams of predictable/unpredictable tone frequency. We found that attention and prediction interacted on the amplitude of the N1 ERP component. The N1 amplitude in the attended/predictable condition was larger than that in any of the other conditions. Dipole source localization analysis showed that the effect came from the activation in bilateral auditory areas. No significant effect was found in the P2 time window. Our results suggest that attention and prediction are dependent of each other. While attention might determine the overall cortical responsiveness to stimuli when prediction is involved, prediction might provide an anchor for the modulation of the synaptic input strengths which needs to be operated on the basis of attention.

Distinctive Representation of Mispredicted and Unpredicted Prediction Errors in Human Electroencephalography

The predictive coding model of perception proposes that neuronal responses are modulated by the amount of sensory input that the internal prediction cannot account for (i.e., prediction error). However, there is little consensus on what constitutes nonpredicted stimuli. Conceptually, whereas mispredicted stimuli may induce both prediction error generated by prediction that is not perceived and prediction error generated by sensory input that is not anticipated, unpredicted stimuli involves no top-down, only bottom-up, propagation of information in the system. Here, we examined the possibility that the processing of mispredicted and unpredicted stimuli are dissociable at the neurophysiological level using human electroencephalography. We presented participants with sets of five tones in which the frequency of the fifth tones was predicted, mispredicted, or unpredicted. Participants were required to press a key when they detected a softer fifth tone to maintain their attention. We found that mispredicted and unpredicted stimuli are associated with different amount of cortical activity, probably reflecting differences in prediction error. Moreover, relative to predicted stimuli, the mispredicted prediction error manifested as neuronal enhancement and the unpredicted prediction error manifested as neuronal attenuation on the N1 event-related potential component. These results highlight the importance of differentiating between the two nonpredicted stimuli in theoretical work on predictive coding. SIGNIFICANCE STATEMENT The current research seeks to dissociate the neurophysiological processing of two types of “nonpredicted” stimuli that have long been considered interchangeable: mispredicted and unpredicted stimuli. We found that mispredicted stimuli, which violate predictions, and unpredicted stimuli, which lack predictions, are represented distinctively in the brain. The results will influence the design of experiments on the predictive coding mechanism, in which the contrast between predicted and “nonpredicted” conditions should be specifically defined to reveal the prediction error proper. This is of general interest because it concerns the logic of research investigating all levels of processing (including perceptual, motor, and cognitive processing) in many neuroscientific domains.

The time course of symbolic number adaptation: oscillatory EEG activity and event-related potential analysis.

Several functional magnetic resonance imaging (fMRI) studies have used neural adaptation paradigms to detect anatomical locations of brain activity related to number processing. However, currently not much is known about the temporal structure of number adaptation. In the present study, we used electroencephalography (EEG) to elucidate the time course of neural events in symbolic number adaptation. The numerical distance of deviants relative to standards was manipulated. In order to avoid perceptual confounds, all levels of deviants consisted of perceptually identical stimuli. Multiple successive numerical distance effects were detected in event-related potentials (ERPs). Analysis of oscillatory activity further showed at least two distinct stages of neural processes involved in the automatic analysis of numerical magnitude, with the earlier effect emerging at around 200ms and the later effect appearing at around 400ms. The findings support for the hypothesis that numerical magnitude processing involves a succession of cognitive events.

Arithmetic mismatch negativity and numerical magnitude processing in number matching

BackgroundThis study examined the relationship of the arithmetic mismatch negativity (AMN) and the semantic evaluation of numerical magnitude. The first question was whether the AMN was sensitive to the incongruity in numerical information per se, or rather, to the violation of strategic expectations. The second question was whether the numerical distance effect could appear independently of the AMN. Event-related potentials (ERPs) were recorded while participants decided whether two digits were matching or non-matching in terms of physical similarity.ResultsThe AMN was enhanced in matching trials presented infrequently relative to non-matching trials presented frequently. The numerical distance effect was found over posterior sites during a 92 ms long interval (236-328 ms) but appeared independently of the AMN.ConclusionsIt was not the incongruity in numerical information per se, but rather, the violation of strategic expectations that elicited the AMN. The numerical distance effect might only temporally coincide with the AMN and did not form an inherent part of it.

Repetition priming results in sensitivity attenuation

Repetition priming refers to the change in the ability to perform a task on a stimulus as a consequence of a former encounter with that very same item. Usually, repetition results in faster and more accurate performance. In the present study, we used a contrast discrimination protocol to assess perceptual sensitivity and response bias of Gabor gratings that are either repeated (same orientation) or alternated (different orientation). We observed that contrast discrimination performance is worse, not better, for repeated than for alternated stimuli. In a second experiment, we varied the probability of stimulus repetition, thus testing whether the repetition effect is due to bottom-up or top-down factors. We found that it is top-down expectation that determines the effect. We discuss the implication of these findings for repetition priming and related phenomena as sensory attenuation. This article is part of a Special Issue entitled SI: Prediction and Attention.

The auditory N1 suppression rebounds as prediction persists over time.

The predictive coding model of perception proposes that neuronal responses reflect prediction errors. Repeated as well as predicted stimuli trigger suppressed neuronal responses because they are associated with reduced prediction errors. However, many predictable events in our environment are not isolated but sequential, yet there is little empirical evidence documenting how suppressed neuronal responses reflecting reduced prediction errors change in the course of a predictable sequence of events. Here we conceived an auditory electroencephalography (EEG) experiment where prediction persists over series of four tones to allow for the delineation of the dynamics of the suppressed neuronal responses. It is possible that neuronal responses might decrease for the initial predictable stimuli and stay at the same level across the rest of the sequence, suggesting that they reflect the predictability of the stimuli in terms of mere probability. Alternatively, neuronal responses might decrease for the initial predictable stimuli and gradually recover across the rest of the sequence, suggesting that factors other than mere probability have to be considered in order to account for the way prediction is implemented in the brain. We found that initial presentation of the predictable stimuli was associated with suppression of the auditory N1. Further presentation of the predictable stimuli was associated with a rebound of the components amplitude. Moreover, such pattern was independent of attention. The findings suggest that auditory N1 suppression reflecting reduced prediction errors is a transient phenomenon that can be modulated by multiple factors.

Temporal expectancies driven by self- and externally generated rhythms

&NA; The dynamic attending theory proposes that rhythms entrain periodic fluctuations of attention which modulate the gain of sensory input. However, temporal expectancies can also be driven by the mere passage of time (foreperiod effect). It is currently unknown how these two types of temporal expectancy relate to each other, i.e. whether they work in parallel and have distinguishable neural signatures. The current research addresses this issue. Participants either tapped a 1 Hz rhythm (active task) or were passively presented with the same rhythm using tactile stimulators (passive task). Based on this rhythm an auditory target was then presented early, in synchrony, or late. Behavioural results were in line with the dynamic attending theory as RTs were faster for in‐ compared to out‐of‐synchrony targets. Electrophysiological results suggested self‐generated and externally induced rhythms to entrain neural oscillations in the delta frequency band. Auditory ERPs showed evidence of two distinct temporal expectancy processes. Both tasks demonstrated a pattern which followed a linear foreperiod effect. In the active task, however, we also observed an ERP effect consistent with the dynamic attending theory. This study shows that temporal expectancies generated by a rhythm and expectancy generated by the mere passage of time can work in parallel and sheds light on how these mechanisms are implemented in the brain. HighlightsTemporal expectancies can be driven by rhythms or by the mere passage of time.We conceived a paradigm using EEG that tests for both these forms of expectancy.We compared self‐generated and externally generated rhythms.We found evidence for both expectancy processes working in parallel.

Category-specific features and valence in action-effect prediction: An EEG study

Despite extensive research on action-effect anticipation, little attention has been paid to the anticipation of different attributes of an event. An action-effect is not only a sensory event; it is often also an event of emotional value which can be pleasant or aversive. This latter attribute of action-effect prediction is similar to anticipation of reward versus punishment. To date the neural systems controlling sensory and reward anticipation have not been systematically compared. To this end, we designed an experiment to manipulate the sensory content and the emotional valence of the stimuli in an orthogonal fashion. We recorded and compared event-related potentials (ERPs) to the presentation of stimuli instantiating expected or unexpected features. Our results suggest (1) that both features are processed altogether and (2) that the prediction error resulting from the manipulation is reflected in an enhanced N400 component.

Prior precision modulates the minimisation of prediction error in human auditory cortex

The predictive coding model of perception proposes that successful representation of the perceptual world depends upon cancelling out the discrepancy between prediction and sensory input (i.e., prediction error). Recent studies further suggest a distinction between prediction error associated with non-predicted stimuli of different prior precision (i.e., inverse variance). However, it is not fully understood how prediction error from different precision levels is minimised in the predictive process. The current research used magnetoencephalography (MEG) to examine whether prior precision modulates the cortical dynamics of the making of perceptual inferences. We presented participants with cycles of repeated tone quartets which consisted of three prime tones and one probe tone. Within each cycle, the three prime tones remained identical while the probe tones changed at some random point (e.g., from repetition of 123X to repetition of 123Y). Therefore, the repetition of probe tones can reveal the development of perceptual inferences in low and high precision contexts depending on its position within the cycle. We found that the two conditions resemble each other in terms of N1m modulation (as both were associated with N1m suppression) but differ in terms of N2m modulation. While repeated probe tones in low precision context did not exhibit any modulatory effect, repeated probe tones in high precision context elicited a suppression and rebound of the N2m source power. The differentiation suggested that the minimisation of prediction error in low and high precision contexts likely involves distinct mechanisms.

Human susceptibility to social influence and its neural correlates are related to perceived vulnerability to extrinsic morbidity risks

Humans considerably vary in the degree to which they rely on their peers to make decisions. Why? Theoretical models predict that environmental risks shift the cost-benefit trade-off associated with the exploitation of others’ behaviours (public information), yet this idea has received little empirical support. Using computational analyses of behaviour and multivariate decoding of electroencephalographic activity, we test the hypothesis that perceived vulnerability to extrinsic morbidity risks impacts susceptibility to social influence, and investigate whether and how this covariation is reflected in the brain. Data collected from 261 participants tested online revealed that perceived vulnerability to extrinsic morbidity risks is positively associated with susceptibility to follow peers’ opinion in the context of a standard face evaluation task. We found similar results on 17 participants tested in the laboratory, and showed that the sensitivity of EEG signals to public information correlates with the participants’ degree of vulnerability. We further demonstrated that the combination of perceived vulnerability to extrinsic morbidity with decoding sensitivities better predicted social influence scores than each variable taken in isolation. These findings suggest that susceptibility to social influence is partly calibrated by perceived environmental risks, possibly via a tuning of neural mechanisms involved in the processing of public information.