Auditory facilitation in deterministic versus stochastic worlds

The brain learns statistical regularities in sensory sequences, enhancing behavioral performance for predictable stimuli while impairing behavioral performance for unpredictable stimuli. While previous research has shown that violations of non-informative regularities hinder task performance, it remains unclear whether predictable but task-irrelevant structures can facilitate performance. In a tone duration discrimination task, we manipulated the task-irrelevant pitch dimension by varying transition probabilities (TP) between successive tone frequencies. Participants judged duration, while pitch sequences were either deterministic (a rule-governed pitch pattern, TP = 1) or stochastic (no discernible pitch pattern, TP = 1/number of pitch levels). The tone pitch was task-irrelevant and it did not predict duration. Results showed that reaction times (RTs) were significantly faster for deterministic sequences, suggesting that predictability in a task-irrelevant dimension still facilitates task performance. RTs were also faster in two-tone sequences compared to eight-tone sequences, likely due to reduced memory load. These findings suggest that statistical learning benefits extend beyond task-relevant dimensions, supporting a predictive coding framework in which the brain integrates predictable sensory input to optimize cognitive processing.

Predicting the Irrelevant: Neural Effects of Distractor Predictability Depend on Load

Distraction is ubiquitous in human environments. Distracting input is often predictable, but we do not understand when or how humans can exploit this predictability. Here, we ask whether predictable distractors are able to reduce uncertainty in updating the internal predictive model. We show that utilising a predictable distractor identity is not fully automatic but in part depends on available resources. In an auditory spatial n-back task, listeners (n = 33) attended to spoken numbers presented to one ear and detected repeating items. Distracting numbers presented to the other ear either followed a predictable (i.e., repetitive) sequence or were unpredictable. We used electroencephalography (EEG) to uncover neural responses to predictable versus unpredictable auditory distractors, as well as their dependence on perceptual and cognitive load. Neurally, pairs of targets and unpredictable distractors induced a sign-reversed lateralisation of pre-stimulus alpha oscillations (~10 Hz) and larger amplitude of the stimulus-evoked P2 event-related potential component. Under low versus high memory load, distractor predictability increased the magnitude of the frontal negativity component. Behaviourally, predictable distractors under low task demands (i.e., good signal-to-noise ratio and low memory load) made participants adopt a less biased response strategy. We conclude that predictable distractors decrease uncertainty and reduce the need for updating the internal predictive model. In turn, unpredictable distractors might mislead proactive spatial attention orientation, elicit larger neural responses and put higher demand on memory.

Probing Beat Perception with Event-Related Potentials (ERPs) in Human Adults, Newborns, and Nonhuman Primates

The aim of this chapter is to give an overview of how the perception of rhythmic temporal regularity such as a regular beat in music can be studied in human adults, human newborns, and nonhuman primates using event-related brain potentials (ERPs). First, we discuss different aspects of temporal structure in general, and musical rhythm in particular, and we discuss the possible mechanisms underlying the perception of regularity (e.g., a beat) in rhythm. Additionally, we highlight the importance of dissociating beat perception from the perception of other types of structure in rhythm, such as predictable sequences of temporal intervals, ordinal structure, and rhythmic grouping. In the second section of the chapter, we start with a discussion of auditory ERPs elicited by infrequent and frequent sounds: ERP responses to regularity violations, such as mismatch negativity (MMN), N2b, and P3, as well as early sensory responses to sounds, such as P1 and N1, have been shown to be instrumental in probing beat perception. Subsequently, we discuss how beat perception can be probed by comparing ERP responses to sounds in regular and irregular sequences, and by comparing ERP responses to sounds in different metrical positions in a rhythm, such as on and off the beat or on strong and weak beats. Finally, we will discuss previous research that has used the aforementioned ERPs and paradigms to study beat perception in human adults, human newborns, and nonhuman primates. In doing so, we consider the possible pitfalls and prospects of the technique, as well as future perspectives.

Rhythmic temporal prediction enhances neural representations of movement intention for brain-computer interface

Objective.Detecting movement intention is a typical use of brain-computer interfaces (BCI). However, as an endogenous electroencephalography (EEG) feature, the neural representation of movement is insufficient for improving motor-based BCI. This study aimed to develop a new movement augmentation BCI encoding paradigm by incorporating the cognitive function of rhythmic temporal prediction, and test the feasibility of this new paradigm in optimizing detections of movement intention.Methods.A visual-motion synchronization task was designed with two movement intentions (left vs. right) and three rhythmic temporal prediction conditions (1000 ms vs. 1500 ms vs. no temporal prediction). Behavioural and EEG data of 24 healthy participants were recorded. Event-related potentials (ERPs), event-related spectral perturbation induced by left- and right-finger movements, the common spatial pattern (CSP) and support vector machine, Riemann tangent space algorithm and logistic regression were used and compared across the three temporal prediction conditions, aiming to test the impact of temporal prediction on movement detection.Results.Behavioural results showed significantly smaller deviation time for 1000 ms and 1500 ms conditions. ERP analyses revealed 1000 ms and 1500 ms conditions led to rhythmic oscillations with a time lag in contralateral and ipsilateral areas of movement. Compared with no temporal prediction, 1000 ms condition exhibited greater beta event-related desynchronization (ERD) lateralization in motor area (P< 0.001) and larger beta ERD in frontal area (P< 0.001). 1000 ms condition achieved an averaged left-right decoding accuracy of 89.71% using CSP and 97.30% using Riemann tangent space, both significantly higher than no temporal prediction. Moreover, movement and temporal information can be decoded simultaneously, achieving 88.51% four-classification accuracy.Significance.The results not only confirm the effectiveness of rhythmic temporal prediction in enhancing detection ability of motor-based BCI, but also highlight the dual encodings of movement and temporal information within a single BCI paradigm, which is promising to expand the range of intentions that can be decoded by the BCI.

Effects of temporally regular versus irregular distractors on goal-directed cognition and behavior

Human environments comprise plenty of task-irrelevant sensory inputs, which are potentially distracting. Auditory distractors often possess an inherent temporal structure. However, it is largely unknown whether and how the temporal regularity of distractors interferes with goal-directed cognitive processes, such as working memory. Here, we tested a total sample of N = 90 participants across four working memory tasks with sequences of temporally regular versus irregular distractors. Temporal irregularity was operationalized by a final tone onset time that violated an otherwise regular tone sequence (Experiment 1), by a sequence of tones with irregular onset-to-onset delays (Experiment 2), and by sequences of speech items with irregular onset-to-onset delays (Experiments 3 and 4). Across all experiments, temporal regularity of distractors did not modulate participants’ primary performance metric, that is, accuracy in recalling items from working memory. Instead, temporal regularity of distractors modulated secondary performance metrics: for regular versus irregular distractors, recall of the first item from memory was faster (Experiment 3) and the response bias was more conservative (Experiment 4). Taken together, the present results provide evidence that the temporal regularity of task-irrelevant input does not inevitably affect the precision of memory representations (reflected in the primary performance metric accuracy) but rather the response behavior (reflected in secondary performance metrics like response speed and bias). Our findings emphasize that a comprehensive understanding of auditory distraction requires that existing models of attention include often-neglected secondary performance metrics to understand how different features of auditory distraction reach awareness and impact cognition and behavior.

Distractor probability influences suppression in auditory selective attention

Auditory selective attention is thought to facilitate listening to the sound of interest (e.g., voice or music) in a noisy environment. One mechanism thought to underlie this ability is suppression of distracting stimuli. However, little is known about its operation or characteristics. We tested whether suppression in auditory selective attention capitalizes on statistical regularities in the environment to facilitate attention. Participants listened to seven-second scenes consisting of several voices speaking sequences of numbers and a distractor, which occurred more (70%) or less (30%) frequently across trials. Participants had to find the voice that was a gender singleton and report whether it was saying even or odd numbers. If suppression is an active component of auditory selective attention, task performance was expected to be better when the more frequent distractor was present. Results across the experiment and three replications revealed significantly shorter RTs when the high-probability distractor was in the scene relative to the low-probability distractor. Results are suggestive of a suppression mechanism that mitigates the detrimental influence of a frequently occurring distracting sound.

Sustained Pupil Responses Are Modulated by Predictability of Auditory Sequences

The brain is highly sensitive to auditory regularities and exploits the predictable order of sounds in many situations, from parsing complex auditory scenes, to the acquisition of language. To understand the impact of stimulus predictability on perception, it is important to determine how the detection of predictable structure influences processing and attention. Here, we use pupillometry to gain insight into the effect of sensory regularity on arousal. Pupillometry is a commonly used measure of salience and processing effort, with more perceptually salient or perceptually demanding stimuli consistently associated with larger pupil diameters. In two experiments we tracked human listeners' pupil dynamics while they listened to sequences of 50-ms tone pips of different frequencies. The order of the tone pips was either random, contained deterministic (fully predictable) regularities (experiment 1, n = 18, 11 female) or had a probabilistic regularity structure (experiment 2, n = 20, 17 female). The sequences were rapid, preventing conscious tracking of sequence structure thus allowing us to focus on the automatic extraction of different types of regularities. We hypothesized that if regularity facilitates processing by reducing processing demands, a smaller pupil diameter would be seen in response to regular relative to random patterns. Conversely, if regularity is associated with heightened arousal and attention (i.e., engages processing resources) the opposite pattern would be expected. In both experiments we observed a smaller sustained (tonic) pupil diameter for regular compared with random sequences, consistent with the former hypothesis and confirming that predictability facilitates sequence processing.SIGNIFICANCE STATEMENT The brain is highly sensitive to auditory regularities. To appreciate the impact that the presence of predictability has on perception, we need to better understand how a predictable structure influences processing and attention. We recorded listeners' pupil responses to sequences of tones that followed either a predictable or unpredictable pattern, as the pupil can be used to implicitly tap into these different cognitive processes. We found that the pupil showed a smaller sustained diameter to predictable sequences, indicating that predictability eased processing rather than boosted attention. The findings suggest that the pupil response can be used to study the automatic extraction of regularities, and that the effects are most consistent with predictability helping the listener to efficiently process upcoming sounds.

Linguistic processing of task-irrelevant speech at a cocktail party

Paying attention to one speaker in a noisy place can be extremely difficult, because to-be-attended and task-irrelevant speech compete for processing resources. We tested whether this competition is restricted to acoustic-phonetic interference or if it extends to competition for linguistic processing as well. Neural activity was recorded using Magnetoencephalography as human participants were instructed to attend to natural speech presented to one ear, and task-irrelevant stimuli were presented to the other. Task-irrelevant stimuli consisted either of random sequences of syllables, or syllables structured to form coherent sentences, using hierarchical frequency-tagging. We find that the phrasal structure of structured task-irrelevant stimuli was represented in the neural response in left inferior frontal and posterior parietal regions, indicating that selective attention does not fully eliminate linguistic processing of task-irrelevant speech. Additionally, neural tracking of to-be-attended speech in left inferior frontal regions was enhanced when competing with structured task-irrelevant stimuli, suggesting inherent competition between them for linguistic processing.