Temporal expectation and spectral expectation operate in distinct fashion on neuronal populations

Distinct brain dynamics and networks for processing short and long auditory time intervals

Psychophysical studies suggest that time intervals above and below 1.2 s are processed differently in the human brain. However, the neural underpinnings of this dissociation remain unclear. Here, we investigate whether distinct or common brain networks and dynamics support the passive perception of short (below 1.2 s) and long (above 1.2 s) empty time intervals. Twenty participants underwent an EEG recording during an auditory oddball paradigm with .8- and 1.6-s standard time intervals and deviant intervals either shorter (early) or longer (delayed) than the standard interval. We computed the auditory ERPs for each condition at the sensor and source levels. We then performed whole brain cluster-based permutation statistics for the CNV, N1 and P2, components, testing deviants against standards. A CNV was found only for above 1.2 s intervals (delayed deviants), with generators in temporo-parietal, SMA, and motor regions. Deviance detection of above 1.2 s intervals occurred during the N1 period over fronto-central sensors for delayed deviants only, with generators in parietal and motor regions. Deviance detection of below 1.2 s intervals occurred during the P2 period over fronto-central sensors for delayed deviants only, with generators in primary auditory cortex, SMA, IFG, cingulate and parietal cortex. We then identified deviance related changes in directed connectivity using bivariate Granger causality to highlight the networks dynamics associated with interval processing above and below 1.2. These results suggest that distinct brain dynamics and networks support the perception of time intervals above and below 1.2 s.

Null effects of temporal prediction on recognition memory but evidence for differential neural activity at encoding. A registered report

Previous research has demonstrated that rhythmic presentation of stimuli during encoding boosts subsequent recognition and is associated with distinct neural activity compared with when stimuli are presented in an arrhythmic manner. However, it is unclear whether the effect is driven by automatic entrainment to rhythm or non-rhythmic temporal prediction. This registered report presents an Electroencephalographic (EEG) study aimed at establishing the cognitive and neural mechanisms of the effect of temporal prediction on recognition. In a blocked design, stimulus onset during encoding was systematically manipulated in four conditions prior to recognition testing: rhythmic fixed (RF), rhythmic variable (RV), arrhythmic fixed (AF), and arrhythmic variable (AV). By orthogonally varying rhythm and temporal position we were able to assess their independent contributions to recognition enhancement. Our behavioural results did not replicate previous findings that show a difference in recognition memory based on temporal predictability at encoding. However, event-related potential (ERP) component analysis did show an early (N1) interaction effect of temporal position and rhythm, and later (N2 and Dm) effects driven by temporal position only. Taken together, we observed effects of temporal prediction at encoding, but these differences did not translate to later effects of memory, suggesting that effects of temporal prediction on recognition are less robust than previously thought.

"What" and "when" predictions modulate auditory processing in a mutually congruent manner

Introduction

Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli and their timing, both of which are known to interactively modulate sensory processing. In real-world stimulus streams such as music, regularities can occur at multiple levels, both in terms of contents (e.g., predictions relating to individual notes vs. their more complex groups) and timing (e.g., pertaining to timing between intervals vs. the overall beat of a musical phrase). However, it is unknown whether the brain integrates predictions in a manner that is mutually congruent (e.g., if "beat" timing predictions selectively interact with "what" predictions falling on pulses which define the beat), and whether integrating predictions in different timing conditions relies on dissociable neural correlates.

Methods

To address these questions, our study manipulated "what" and "when" predictions at different levels - (local) interval-defining and (global) beat-defining - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N = 20) performing a repetition detection task.

Results

Our results reveal that temporal predictions based on beat or interval timing modulated mismatch responses to violations of "what" predictions happening at the predicted time points, and that these modulations were shared between types of temporal predictions in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" predictions selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network.

Discussion

Taken together, these results suggest that the brain integrates different predictions with a high degree of mutual congruence, but in a shared and distributed cortical network. This finding contrasts with recent studies indicating separable mechanisms for beat-based and memory-based predictive processing.

The auditory brain in action: Intention determines predictive processing in the auditory system-A review of current paradigms and findings

According to the ideomotor theory, action may serve to produce desired sensory outcomes. Perception has been widely described in terms of sensory predictions arising due to top-down input from higher order cortical areas. Here, we demonstrate that the action intention results in reliable top-down predictions that modulate the auditory brain responses. We bring together several lines of research, including sensory attenuation, active oddball, and action-related omission studies: Together, the results suggest that the intention-based predictions modulate several steps in the sound processing hierarchy, from preattentive to evaluation-related processes, also when controlling for additional prediction sources (i.e., sound regularity). We propose an integrative theoretical framework—the extended auditory event representation system (AERS), a model compatible with the ideomotor theory, theory of event coding, and predictive coding. Initially introduced to describe regularity-based auditory predictions, we argue that the extended AERS explains the effects of action intention on auditory processing while additionally allowing studying the differences and commonalities between intention- and regularity-based predictions—we thus believe that this framework could guide future research on action and perception.

Beat-based and Memory-based Temporal Expectations in Rhythm: Similar Perceptual Effects, Different Underlying Mechanisms

Predicting the timing of incoming information allows the brain to optimize information processing in dynamic environments. Behaviorally, temporal expectations have been shown to facilitate processing of events at expected time points, such as sounds that coincide with the beat in musical rhythm. Yet, temporal expectations can develop based on different forms of structure in the environment, not just the regularity afforded by a musical beat. Little is still known about how different types of temporal expectations are neurally implemented and affect performance. Here, we orthogonally manipulated the periodicity and predictability of rhythmic sequences to examine the mechanisms underlying beat-based and memory-based temporal expectations, respectively. Behaviorally and using EEG, we looked at the effects of beat-based and memory-based expectations on auditory processing when rhythms were task-relevant or task-irrelevant. At expected time points, both beat-based and memory-based expectations facilitated target detection and led to attenuation of P1 and N1 responses, even when expectations were task-irrelevant (unattended). For beat-based expectations, we additionally found reduced target detection and enhanced N1 responses for events at unexpected time points (e.g., off-beat), regardless of the presence of memory-based expectations or task relevance. This latter finding supports the notion that periodicity selectively induces rhythmic fluctuations in neural excitability and furthermore indicates that, although beat-based and memory-based expectations may similarly affect auditory processing of expected events, their underlying neural mechanisms may be different.

Dissociable neural effects of temporal expectations due to passage of time and contextual probability

The human brain is equipped with complex mechanisms to track the changing probability of events in time. While the passage of time itself usually leads to a mounting expectation, context can provide additional information about when events are likely to happen. In this study we dissociate these two sources of temporal expectation in terms of their neural correlates and underlying brain connectivity patterns. We analysed magnetoencephalographic (MEG) data acquired from N = 24 healthy participants listening to auditory stimuli. These stimuli could be presented at different temporal intervals but occurred most often at intermediate intervals, forming a contextual probability distribution. Evoked MEG response amplitude was sensitive to both passage of time (time elapsed since the cue) and contextual probability, albeit at different latencies: the effects of passage of time were observed earlier than the effects of context. The underlying sources of MEG activity were also different across the two types of temporal prediction: the effects of passage of time were localised to early auditory regions and superior temporal gyri, while context was additionally linked to activity in inferior parietal cortices. Finally, these differences were modelled using biophysical (dynamic causal) modelling: passage of time was explained in terms of widespread gain modulation and decreased prediction error signalling at lower levels of the hierarchy, while contextual expectation led to more localised gain modulation and decreased prediction error signalling at higher levels of the hierarchy. These results present a comprehensive account of how independent sources of temporal prediction may be differentially expressed in cortical circuits.

Organizational principles of multidimensional predictions in human auditory attention

Anticipating the future rests upon our ability to exploit contextual cues and to formulate valid internal models or predictions. It is currently unknown how multiple predictions combine to bias perceptual information processing, and in particular whether this is determined by physiological constraints, behavioral relevance (task demands), or past knowledge (perceptual expertise). In a series of behavioral auditory experiments involving musical experts and non-musicians, we investigated the respective and combined contribution of temporal and spectral predictions in multiple detection tasks. We show that temporal and spectral predictions alone systematically increase perceptual sensitivity, independently of task demands or expertise. When combined, however, spectral predictions benefit more to non-musicians and dominate over temporal ones, and the extent of the spectrotemporal synergistic interaction depends on task demands. This suggests that the hierarchy of dominance primarily reflects the tonotopic organization of the auditory system and that expertise or attention only have a secondary modulatory influence.

Not All Predictions Are Equal: "What" and "When" Predictions Modulate Activity in Auditory Cortex through Different Mechanisms

Using predictions based on environmental regularities is fundamental for adaptive behavior. While it is widely accepted that predictions across different stimulus attributes (e.g., time and content) facilitate sensory processing, it is unknown whether predictions across these attributes rely on the same neural mechanism. Here, to elucidate the neural mechanisms of predictions, we combine invasive electrophysiological recordings (human electrocorticography in 4 females and 2 males) with computational modeling while manipulating predictions about content ("what") and time ("when"). We found that "when" predictions increased evoked activity over motor and prefrontal regions both at early (∼180 ms) and late (430-450 ms) latencies. "What" predictability, however, increased evoked activity only over prefrontal areas late in time (420-460 ms). Beyond these dissociable influences, we found that "what" and "when" predictability interactively modulated the amplitude of early (165 ms) evoked responses in the superior temporal gyrus. We modeled the observed neural responses using biophysically realistic neural mass models, to better understand whether "what" and "when" predictions tap into similar or different neurophysiological mechanisms. Our modeling results suggest that "what" and "when" predictability rely on complementary neural processes: "what" predictions increased short-term plasticity in auditory areas, whereas "when" predictability increased synaptic gain in motor areas. Thus, content and temporal predictions engage complementary neural mechanisms in different regions, suggesting domain-specific prediction signaling along the cortical hierarchy. Encoding predictions through different mechanisms may endow the brain with the flexibility to efficiently signal different sources of predictions, weight them by their reliability, and allow for their encoding without mutual interference.SIGNIFICANCE STATEMENT Predictions of different stimulus features facilitate sensory processing. However, it is unclear whether predictions of different attributes rely on similar or different neural mechanisms. By combining invasive electrophysiological recordings of cortical activity with experimental manipulations of participants' predictions about content and time of acoustic events, we found that the two types of predictions had dissociable influences on cortical activity, both in terms of the regions involved and the timing of the observed effects. Further, our biophysical modeling analysis suggests that predictability of content and time rely on complementary neural processes: short-term plasticity in auditory areas and synaptic gain in motor areas, respectively. This suggests that predictions of different features are encoded with complementary neural mechanisms in different brain regions.

The influence of action-effect anticipation on bistable perception: differences between onset rivalry and ambiguous motion

Perception is strongly shaped by the actions we perform. According to the theory of event coding, and forward models of motor control, goal-directed action preparation activates representations of desired effects. These expectations about the precise stimulus identity of one's action-outcomes (i.e. identity predictions) are thought to selectively influence perceptual processing of action-contingent effects. However, the existing evidence for such identity-prediction effects is scarce and mixed. Here, we developed a new paradigm to capture such effects and examined whether action-outcome predictions can bias the perception of binocular onset rivalry (Experiments 1a and 1b) and bistable motion (Experiment 2). Participants performed learning tasks in which they were exposed to action-outcome associations. On test trials, actions were followed by bistable stimuli that could be perceived as being either congruent or incongruent with the aforementioned associations (i.e. rivalrous oriented gratings in Experiments 1a and 1b and spheres with ambiguous rotation directions in Experiment 2). Across three experiments, we show that, whilst exposure to action-effect associations can bias the apparent motion direction of ambiguous spheres, it fails to influence perceptual selection of grating orientations in binocular onset rivalry. This pattern of results extends previous work on ambiguous motion by demonstrating that action-induced modulations do not generalize to all types of bistable percepts.

Does emotion change auditory prediction and deviance detection?

In the last decades, a growing number of studies provided compelling evidence supporting the interplay of cognitive and affective processes. However, it remains to be clarified whether and how an emotional context affects the prediction and detection of change in unattended sensory events. In an event-related potential (ERP) study, we probed the modulatory role of pleasant, unpleasant and neutral visual contexts on the brain response to automatic detection of change in spectral (intensity) vs. temporal (duration) sound features. Twenty participants performed a passive auditory oddball task. Additionally, we tested the relationship between ERPs and self-reported mood. Participants reported more negative mood after the negative block. The P2 amplitude elicited by standards was increased in a positive context. Mismatch Negativity (MMN) amplitude was decreased in the negative relative to the neutral and positive contexts, and was associated with self-reported mood. These findings suggest that the detection of regularities in the auditory stream was facilitated in a positive context, whereas a negative visual context interfered with prediction error elicitation, through associated mood changes. Both ERP and behavioral effects highlight the intricate links between emotion, perception and cognitive processes.

Timing in Predictive Coding: The Roles of Task Relevance and Global Probability

Predictive coding models of attention propose that attention and prediction operate synergistically to optimize perception, as reflected in interactive effects on early sensory neural responses. It is yet unclear whether attention and prediction based on the temporal attributes of expected events operate in a similar fashion. We investigated how attention and prediction based on timing interact by manipulating the task relevance and a priori probability of auditory stimulus onset timing within a go/no-go task while recording EEG. Preparatory activity, as indexed via the contingent negative variation, reflected temporally specific anticipation as a function of both attention and prediction. Higher stimulus probability led to significant predictive N1 suppression; however, we failed to find an effect of task relevance on N1 amplitude and an interaction of task relevance with prediction. We suggest the predictability of sensory timing is the predominant influence on early sensory responses where a priori probabilities allow for strong prior beliefs. When this is the case, we find that the effects of temporal prediction on early sensory responses are independent of the task relevance of sensory stimuli. Our findings contribute to the expansion of predictive coding frameworks to include the role of timing in sensory processing.

Context-specific temporal learning with non-conflict stimuli: proof-of-principle for a learning account of context-specific proportion congruent effects

The conflict adaptation account proposes that participants adjust attention to target and distracting stimuli in response to conflict. This is argued to explain the proportion congruent effect, wherein the congruency effect decreases as the proportion of conflicting incongruent trials increases. Some reports further argue that this conflict adaptation process can be context-specific. This paper presents a proof-of-principle for a competing account. It is suggested that such context-specific effects might be driven by very basic temporal learning processes. In the reported experiment, we manipulated stimulus contrast in place of congruency. In one location, stimulus letters were mostly easy to identify (high stimulus contrast). In the other location, letters were mostly hard to identify (low stimulus contrast). Participants produced a larger contrast effect in the mostly easy context. Along with supplemental analyses investigating the role of context switching and previous trial response times, the results are consistent with the notion that different rhythms of responding are learned for an easy versus hard location context. These results suggest that context-specific proportion congruency effects might result, in whole or in part, from temporal learning. Conflict adaptation may or may not play an additional role.