Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult lifespan.

Preserved communication abilities promote healthy ageing. To this end, the age-typical loss of sensory acuity might in part be compensated for by an individual's preserved attentional neural filtering. Is such a compensatory brain-behaviour link longitudinally stable? Can it predict individual change in listening behaviour? We here show that individual listening behaviour and neural filtering ability follow largely independent developmental trajectories modelling electroencephalographic and behavioural data of N = 105 ageing individuals (39-82 y). First, despite the expected decline in hearing-threshold-derived sensory acuity, listening-task performance proved stable over 2 y. Second, neural filtering and behaviour were correlated only within each separate measurement timepoint (T1, T2). Longitudinally, however, our results raise caution on attention-guided neural filtering metrics as predictors of individual trajectories in listening behaviour: neither neural filtering at T1 nor its 2-year change could predict individual 2-year behavioural change, under a combination of modelling strategies.

Humans are social animals. Communicating with other humans is vital for our social wellbeing, and having strong connections with others has been associated with healthier aging. For most humans, speech is an integral part of communication, but speech comprehension can be challenging in everyday social settings: imagine trying to follow a conversation in a crowded restaurant or decipher an announcement in a busy train station. Noisy environments are particularly difficult to navigate for older individuals, since age-related hearing loss can impact the ability to detect and distinguish speech sounds. Some aging individuals cope better than others with this problem, but the reason why, and how listening success can change over a lifetime, is poorly understood. One of the mechanisms involved in the segregation of speech from other sounds depends on the brain applying a 'neural filter' to auditory signals. The brain does this by aligning the activity of neurons in a part of the brain that deals with sounds, the auditory cortex, with fluctuations in the speech signal of interest. This neural 'speech tracking' can help the brain better encode the speech signals that a person is listening to. Tune and Obleser wanted to know whether the accuracy with which individuals can implement this filtering strategy represents a marker of listening success. Further, the researchers wanted to answer whether differences in the strength of the neural filtering observed between aging listeners could predict how their listening ability would develop, and determine whether these neural changes were connected with changes in people's behaviours. To answer these questions, Tune and Obleser used data collected from a group of healthy middle-aged and older listeners twice, two years apart. They then built mathematical models using these data to investigate how differences between individuals in the brain and in behaviours relate to each other. The researchers found that, across both timepoints, individuals with stronger neural filtering were better at distinguishing speech and listening. However, neural filtering strength measured at the first timepoint was not a good predictor of how well individuals would be able to listen two years later. Indeed, changes at the brain and the behavioural level occurred independently of each other. Tune and Obleser's findings will be relevant to neuroscientists, as well as to psychologists and audiologists whose goal is to understand differences between individuals in terms of listening success. The results suggest that neural filtering guided by attention to speech is an important readout of an individual's attention state. However, the results also caution against explaining listening performance based solely on neural factors, given that listening behaviours and neural filtering follow independent trajectories.

Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization.

The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult. Here, magnetoencephalography (MEG) data was obtained during a classic N400 paradigm where the semantic predictability of a fixed target noun was manipulated in simple German sentences. To estimate causality, we implemented a novel approach based on machine learning and temporal generalization to estimate the effect of inferior frontal gyrus (IFG) on temporal areas. In this method, a support vector machine (SVM) classifier is trained on each time point of the neural activity in IFG to classify less predicted (LP) and highly predicted (HP) nouns and then tested on all time points of superior/middle temporal sub-regions activity (and vice versa, to establish spatio-temporal evidence for or against causality). The decoding accuracy was significantly above chance level when the classifier was trained on IFG activity and tested on future activity in superior and middle temporal gyrus (STG/MTG). The results present new evidence for a model predictive speech comprehension where predictive IFG activity is fed back to shape subsequent activity in STG/MTG, implying a feedback mechanism in N400 generation. In combination with the also observed strong feedforward effect from left STG/MTG to IFG, our findings provide evidence of dynamic feedback and feedforward influences between IFG and temporal areas during N400 generation.

Trajectories and contributing factors of neural compensation in healthy and pathological aging.

Neural degeneration is a hallmark of healthy aging and can be associated with specific cognitive impairments. However, neural degeneration per se is not matched by unremitting declines in cognitive abilities. Instead, middle-aged and older adults typically maintain surprisingly high levels of cognitive functioning, suggesting that the human brain can adapt to structural degeneration by neural compensation. Here, we summarize prevailing theories and recent empirical studies on neural compensation with a focus on often neglected contributing factors, such as lifestyle, metabolism and neural plasticity. We suggest that these factors moderate the relationship between structural integrity and neural compensation, maintaining psychological well-being and behavioral functioning. Finally, we discuss that a breakdown in neural compensation may pose a tipping point that distinguishes the trajectories of healthy vs pathological aging, but conjoint support from psychology and cognitive neuroscience for this alluring view is still scarce. Therefore, future experiments that target the concomitant processes of neural compensation and associated behavior will foster a comprehensive understanding of both healthy and pathological aging.

Pupil Size Sensitivity to Listening Demand Depends on Motivational State.

Motivation plays a role when a listener needs to understand speech under acoustically demanding conditions. Previous work has demonstrated pupil-linked arousal being sensitive to both listening demands and motivational state during listening. It is less clear how motivational state affects the temporal evolution of the pupil size and its relation to subsequent behavior. We used an auditory gap detection task (N = 33) to study the joint impact of listening demand and motivational state on the pupil size response and examine its temporal evolution. Task difficulty and a listener's motivational state were orthogonally manipulated through changes in gap duration and monetary reward prospect. We show that participants' performance decreased with task difficulty, but that reward prospect enhanced performance under hard listening conditions. Pupil size increased with both increased task difficulty and higher reward prospect, and this reward prospect effect was largest under difficult listening conditions. Moreover, pupil size time courses differed between detected and missed gaps, suggesting that the pupil response indicates upcoming behavior. Larger pre-gap pupil size was further associated with faster response times on a trial-by-trial within-participant level. Our results reiterate the utility of pupil size as an objective and temporally sensitive measure in audiology. However, such assessments of cognitive resource recruitment need to consider the individual's motivational state.

Predictors of transition in patients with clinical high risk for psychosis: an umbrella review.

Diagnosis of a clinical high-risk (CHR) state enables timely treatment of individuals at risk for a psychotic disorder, thereby contributing to improving illness outcomes. However, only a minority of patients diagnosed with CHR will make the transition to overt psychosis. To identify patients most likely to benefit from early intervention, several studies have investigated characteristics that distinguish CHR patients who will later develop a psychotic disorder from those who will not. We aimed to summarize evidence from systematic reviews and meta-analyses on predictors of transition to psychosis in CHR patients, among characteristics and biomarkers assessed at baseline. A systematic search was conducted in Pubmed, Scopus, PsychInfo and Cochrane databases to identify reviews and meta-analyses of studies that investigated specific baseline predictors or biomarkers for transition to psychosis in CHR patients using a cross-sectional or longitudinal design. Non-peer-reviewed publications, gray literature, narrative reviews and publications not written in English were excluded from analyses. We provide a narrative synthesis of results from all included reviews and meta-analyses. For each included publication, we indicate the number of studies cited in each domain and its quality rating. A total of 40 publications (21 systematic reviews and 19 meta-analyses) that reviewed a total of 272 original studies qualified for inclusion. Baseline predictors most consistently associated with later transition included clinical characteristics such as attenuated psychotic and negative symptoms and functioning, verbal memory deficits and the electrophysiological marker of mismatch negativity. Few predictors reached a level of evidence sufficient to inform clinical practice, reflecting generalizability issues in a field characterized by studies with small, heterogeneous samples and relatively few transition events. Sample pooling and harmonization of methods across sites and projects are necessary to overcome these limitations.

Target enhancement but not distractor suppression in auditory neural tracking during continuous speech.

Selective attention modulates the neural tracking of speech in auditory cortical regions. It is unclear whether this attentional modulation is dominated by enhanced target tracking, or suppression of distraction. To settle this long-standing debate, we employed an augmented electroencephalography (EEG) speech-tracking paradigm with target, distractor, and neutral streams. Concurrent target speech and distractor (i.e., sometimes relevant) speech were juxtaposed with a third, never task-relevant speech stream serving as neutral baseline. Listeners had to detect short target repeats and committed more false alarms originating from the distractor than from the neutral stream. Speech tracking revealed target enhancement but no distractor suppression below the neutral baseline. Speech tracking of the target (not distractor or neutral speech) explained single-trial accuracy in repeat detection. In sum, the enhanced neural representation of target speech is specific to processes of attentional gain for behaviorally relevant target speech rather than neural suppression of distraction.

Neural α Oscillations and Pupil Size Differentially Index Cognitive Demand under Competing Audiovisual Task Conditions.

Cognitive demand is thought to modulate two often used, but rarely combined, measures: pupil size and neural α (8-12 Hz) oscillatory power. However, it is unclear whether these two measures capture cognitive demand in a similar way under complex audiovisual-task conditions. Here we recorded pupil size and neural α power (using electroencephalography), while human participants of both sexes concurrently performed a visual multiple object-tracking task and an auditory gap detection task. Difficulties of the two tasks were manipulated independent of each other. Participants' performance decreased in accuracy and speed with increasing cognitive demand. Pupil size increased with increasing difficulty for both the auditory and the visual task. In contrast, α power showed diverging neural dynamics: parietal α power decreased with increasing difficulty in the visual task, but not with increasing difficulty in the auditory task. Furthermore, independent of task difficulty, within-participant trial-by-trial fluctuations in pupil size were negatively correlated with α power. Difficulty-induced changes in pupil size and α power, however, did not correlate, which is consistent with their different cognitive-demand sensitivities. Overall, the current study demonstrates that the dynamics of the neurophysiological indices of cognitive demand and associated effort are multifaceted and potentially modality-dependent under complex audiovisual-task conditions.SIGNIFICANCE STATEMENT Pupil size and oscillatory α power are associated with cognitive demand and effort, but their relative sensitivity under complex audiovisual-task conditions is unclear, as is the extent to which they share underlying mechanisms. Using an audiovisual dual-task paradigm, we show that pupil size increases with increasing cognitive demands for both audition and vision. In contrast, changes in oscillatory α power depend on the respective task demands: parietal α power decreases with visual demand but not with auditory task demand. Hence, pupil size and α power show different sensitivity to cognitive demands, perhaps suggesting partly different underlying neural mechanisms.

Slow neural oscillations explain temporal fluctuations in distractibility.

Human environments comprise various sources of distraction, which often occur unexpectedly in time. The proneness to distraction (i.e., distractibility) is posited to be independent of attentional sampling of targets, but its temporal dynamics and neurobiological basis are largely unknown. Brain oscillations in the theta band (3 - 8 Hz) have been associated with fluctuating neural excitability, which is hypothesised here to explain rhythmic modulation of distractibility. In a pitch discrimination task (N = 30) with unexpected auditory distractors, we show that distractor-evoked neural responses in the electroencephalogram and perceptual susceptibility to distraction were co-modulated and cycled approximately 3 - 5 times per second. Pre-distractor neural phase in left inferior frontal and insular cortex regions explained fluctuating distractibility. Thus, human distractibility is not constant but fluctuates on a subsecond timescale. Furthermore, slow neural oscillations subserve the behavioural consequences of a hitherto largely unexplained but ever-increasing phenomenon in modern environments - distraction by unexpected sound.

Explaining flexible continuous speech comprehension from individual motor rhythms.

When speech is too fast, the tracking of the acoustic signal along the auditory pathway deteriorates, leading to suboptimal speech segmentation and decoding of speech information. Thus, speech comprehension is limited by the temporal constraints of the auditory system. Here we ask whether individual differences in auditory-motor coupling strength in part shape these temporal constraints. In two behavioural experiments, we characterize individual differences in the comprehension of naturalistic speech as function of the individual synchronization between the auditory and motor systems and the preferred frequencies of the systems. Obviously, speech comprehension declined at higher speech rates. Importantly, however, both higher auditory-motor synchronization and higher spontaneous speech motor production rates were predictive of better speech-comprehension performance. Furthermore, performance increased with higher working memory capacity (digit span) and higher linguistic, model-based sentence predictability-particularly so at higher speech rates and for individuals with high auditory-motor synchronization. The data provide evidence for a model of speech comprehension in which individual flexibility of not only the motor system but also auditory-motor synchronization may play a modulatory role.

Circadian rhythms in auditory hallucinations and psychosis.

Circadian rhythms are imprinted in all organisms and influence virtually all aspects of physiology and behavior in adaptation to the 24-h day-night cycle. This recognition of a circadian timekeeping system permeating essentially all healthy functioning of body and mind quickly leads to the realization that, in turn, human ailments should be probed for the degree to which they are rooted in or marked by disruptions and dysregulations of circadian clock functions in the human body. In this review, we will focus on psychosis as a key mental illness and foremost one of its cardinal symptoms: auditory hallucinations. We will discuss recent empirical evidence and conceptual advances probing the potential role of circadian disruption in auditory hallucinations. Moreover, a dysbalance in excitation and inhibition within cortical networks, which in turn drive a disinhibition of dopaminergic signaling, will be highlighted as central physiological mechanism. Finally, we will propose two avenues for experimentally intervening on the circadian influences to potentially alleviate hallucinations in psychotic disorders.

Neural signatures of task-related fluctuations in auditory attention and age-related changes.

Listening in everyday life requires attention to be deployed dynamically - when listening is expected to be difficult and when relevant information is expected to occur - to conserve mental resources. Conserving mental resources may be particularly important for older adults who often experience difficulties understanding speech. In the current study, we use electro- and magnetoencephalography to investigate the neural and behavioral mechanics of attention regulation during listening and the effects that aging has on these. We first show in younger adults (17-31 years) that neural alpha oscillatory activity indicates when in time attention is deployed (Experiment 1) and that deployment depends on listening difficulty (Experiment 2). Experiment 3 investigated age-related changes in auditory attention regulation. Middle-aged and older adults (54-72 years) show successful attention regulation but appear to utilize timing information differently compared to younger adults (20-33 years). We show a notable age-group dissociation in recruited brain regions. In younger adults, superior parietal cortex underlies alpha power during attention regulation, whereas, in middle-aged and older adults, alpha power emerges from more ventro-lateral areas (posterior temporal cortex). This difference in the sources of alpha activity between age groups only occurred during task performance and was absent during rest (Experiment S1). In sum, our study suggests that middle-aged and older adults employ different neural control strategies compared to younger adults to regulate attention in time under listening challenges.

Age-related differences in the neural network interactions underlying the predictability gain.

Speech comprehension is often challenged by increased background noise, but can be facilitated via the semantic context of a sentence. This predictability gain relies on an interplay of language-specific semantic and domain-general brain regions. However, age-related differences in the interactions within and between semantic and domain-general networks remain poorly understood. Using functional neuroimaging, we investigated commonalities and differences in network interactions enabling processing of degraded speech in healthy young and old participants. Participants performed a sentence repetition task while listening to sentences with high and low predictable endings and varying intelligibility. Stimulus intelligibility was adjusted to individual hearing abilities. Older adults showed an undiminished behavioural predictability gain. Likewise, both groups recruited a similar set of semantic and cingulo-opercular brain regions. However, we observed age-related differences in effective connectivity for high predictable speech of increasing intelligibility. Young adults exhibited stronger connectivity between regions of the cingulo-opercular network and between left insula and the posterior middle temporal gyrus. Moreover, these interactions were excitatory in young adults but inhibitory in old adults. Finally, the degree of the inhibitory influence between cingulo-opercular regions was predictive of the behavioural sensitivity towards changes in intelligibility for high predictable sentences in older adults only. Our results demonstrate that the predictability gain is relatively preserved in older adults when stimulus intelligibility is individually adjusted. While young and old participants recruit similar brain regions, differences manifest in underlying network interactions. Together, these results suggest that ageing affects the network configuration rather than regional activity during successful speech comprehension under challenging listening conditions.

Implicit Versus Explicit Timing-Separate or Shared Mechanisms?

Time implicitly shapes cognition, but time is also explicitly represented, for instance, in the form of durations. Parsimoniously, the brain could use the same mechanisms for implicit and explicit timing. Yet, the evidence has been equivocal, revealing both joint versus separate signatures of timing. Here, we directly compared implicit and explicit timing using magnetoencephalography, whose temporal resolution allows investigating the different stages of the timing processes. Implicit temporal predictability was induced in an auditory paradigm by a manipulation of the foreperiod. Participants received two consecutive task instructions: discriminate pitch (indirect measure of implicit timing) or duration (direct measure of explicit timing). The results show that the human brain efficiently extracts implicit temporal statistics of sensory environments, to enhance the behavioral and neural responses to auditory stimuli, but that those temporal predictions did not improve explicit timing. In both tasks, attentional orienting in time during predictive foreperiods was indexed by an increase in alpha power over visual and parietal areas. Furthermore, pretarget induced beta power in sensorimotor and parietal areas increased during implicit compared to explicit timing, in line with the suggested role for beta oscillations in temporal prediction. Interestingly, no distinct neural dynamics emerged when participants explicitly paid attention to time, compared to implicit timing. Our work thus indicates that implicit timing shapes the behavioral and sensory response in an automatic way and is reflected in oscillatory neural dynamics, whereas the translation of implicit temporal statistics to explicit durations remains somewhat inconclusive, possibly because of the more abstract nature of this task.

Ten simple rules to study distractor suppression.

Distractor suppression refers to the ability to filter out distracting and task-irrelevant information. Distractor suppression is essential for survival and considered a key aspect of selective attention. Despite the recent and rapidly evolving literature on distractor suppression, we still know little about how the brain suppresses distracting information. What limits progress is that we lack mutually agreed upon principles of how to study the neural basis of distractor suppression and its manifestation in behavior. Here, we offer ten simple rules that we believe are fundamental when investigating distractor suppression. We provide guidelines on how to design conclusive experiments on distractor suppression (Rules 1-3), discuss different types of distractor suppression that need to be distinguished (Rules 4-6), and provide an overview of models of distractor suppression and considerations of how to evaluate distractor suppression statistically (Rules 7-10). Together, these rules provide a concise and comprehensive synopsis of promising advances in the field of distractor suppression. Following these rules will propel research on distractor suppression in important ways, not only by highlighting prominent issues to both new and more advanced researchers in the field, but also by facilitating communication between sub-disciplines.

Distributed networks for auditory memory differentially contribute to recall precision.

Re-directing attention to objects in working memory can enhance their representational fidelity. However, how this attentional enhancement of memory representations is implemented across distinct, sensory and cognitive-control brain network is unspecified. The present fMRI experiment leverages psychophysical modelling and multivariate auditory-pattern decoding as behavioral and neural proxies of mnemonic fidelity. Listeners performed an auditory syllable pitch-discrimination task and received retro-active cues to selectively attend to a to-be-probed syllable in memory. Accompanied by increased neural activation in fronto-parietal and cingulo-opercular networks, valid retro-cues yielded faster and more perceptually sensitive responses in recalling acoustic detail of memorized syllables. Information about the cued auditory object was decodable from hemodynamic response patterns in superior temporal sulcus (STS), fronto-parietal, and sensorimotor regions. However, among these regions retaining auditory memory objects, neural fidelity in the left STS and its enhancement through attention-to-memory best predicted individuals' gain in auditory memory recall precision. Our results demonstrate how functionally discrete brain regions differentially contribute to the attentional enhancement of memory representations.

Endogenous modulation of delta phase by expectation-A replication of Stefanics et al., 2010.

The human brain efficiently extracts the temporal statistics of sensory environments and automatically generates expectations about future events. An influential Hypothesis holds that these expectations can find their implementation in neural oscillations, notably in the delta band (.5-3 Hz). Rhythmic fluctuations of cortical excitement are thought to align and match up in phase to the temporal structure of the sensory environment. This alignment is thought to result in the more excitable phase range of neural oscillations to overlap with the predicted onset of sensory events which in turn results in more efficient processing of sensory input, especially so in audition. An unresolved issue concerns whether such phase-aligned rhythmic brain activity is driven exclusively by the exogenous temporal structure of the input, or whether it also reflects phase re-alignment due to endogenous expectations based on stimulus probability and task relevance. In a seminal study, Stefanics et al. (2010) presented stimuli in a rhythmic stream and observed that delta phase consistency across trials was modulated by endogenous target onset expectations: delta phase consistency was higher prior to more probable (strongly expected) compared to less probable (weakly expected) target onsets. The present study replicates Experiment II of the original study, most importantly the modulation of delta phase consistency by endogenous expectations, and underlines a direct relationship between phase locking and behaviour. Our additional analyses locate the sources of the delta phase-alignment to motor, pre-motor, parietal, and temporal areas, and provide evidence for an ongoing delta oscillation, in line with the interpretation of oscillatory phase alignment rather than a transient evoked response. Importantly, this work shows that the phase of delta oscillations can be modulated by top-down control, and hence qualifies as a potential mechanism for the neural implementation of (rhythmic) temporal predictions.

Attentional sampling of visual and auditory objects is captured by theta-modulated neural activity.

Recent evidence suggests that visual attention alternately samples two behaviourally relevant objects at approximately 4 Hz, rhythmically shifting between the objects. Whether similar attentional rhythms exist in other sensory modalities, however, is not yet clear. We therefore adapted and extended an established paradigm to investigate visual and potential auditory attentional rhythms, as well as possible interactions, on both a behavioural (detection performance, N = 33) and a neural level (EEG, N = 18). The results during unimodal attention demonstrate that both visual- and auditory-target detection fluctuate at frequencies of approximately 4-8 Hz, confirming that attentional rhythms are not specific to visual processing. The EEG recordings provided evidence of oscillatory activity that underlies these behavioural effects. At right and left occipital EEG electrodes, we detected counter-phasic theta-band activity (4-8 Hz), mirroring behavioural evidence of alternating sampling between the objects presented right and left of central fixation, respectively. Similarly, alpha-band activity as a signature of relatively suppressed sensory encoding showed a theta-rhythmic, counter-phasic change in power. Moreover, these theta-rhythmic changes in alpha power were predictive of behavioural performance in both sensory modalities. Overall, the present findings provide a new perspective on the multimodal rhythmicity of attention.

Predicting speech from a cortical hierarchy of event-based time scales.

How do predictions in the brain incorporate the temporal unfolding of context in our natural environment? We here provide evidence for a neural coding scheme that sparsely updates contextual representations at the boundary of events. This yields a hierarchical, multilayered organization of predictive language comprehension. Training artificial neural networks to predict the next word in a story at five stacked time scales and then using model-based functional magnetic resonance imaging, we observe an event-based "surprisal hierarchy" evolving along a temporoparietal pathway. Along this hierarchy, surprisal at any given time scale gated bottom-up and top-down connectivity to neighboring time scales. In contrast, surprisal derived from continuously updated context influenced temporoparietal activity only at short time scales. Representing context in the form of increasingly coarse events constitutes a network architecture for making predictions that is both computationally efficient and contextually diverse.

Neural tracking in infants - An analytical tool for multisensory social processing in development.

Humans are born into a social environment and from early on possess a range of abilities to detect and respond to social cues. In the past decade, there has been a rapidly increasing interest in investigating the neural responses underlying such early social processes under naturalistic conditions. However, the investigation of neural responses to continuous dynamic input poses the challenge of how to link neural responses back to continuous sensory input. In the present tutorial, we provide a step-by-step introduction to one approach to tackle this issue, namely the use of linear models to investigate neural tracking responses in electroencephalographic (EEG) data. While neural tracking has gained increasing popularity in adult cognitive neuroscience over the past decade, its application to infant EEG is still rare and comes with its own challenges. After introducing the concept of neural tracking, we discuss and compare the use of forward vs. backward models and individual vs. generic models using an example data set of infant EEG data. Each section comprises a theoretical introduction as well as a concrete example using MATLAB code. We argue that neural tracking provides a promising way to investigate early (social) processing in an ecologically valid setting.