Attention plays a fundamental role in selectively processing stimuli in our environment despite distraction. Spatial attention induces increasing and decreasing power of neural alpha oscillations (8-12 Hz) in brain regions ipsilateral and contralateral to the locus of attention, respectively. This study tested whether the hemispheric lateralization of alpha power codes not just the spatial location but also the temporal structure of the stimulus. Participants attended to spoken digits presented to one ear and ignored tightly synchronized distracting digits presented to the other ear. In the magnetoencephalogram, spatial attention induced lateralization of alpha power in parietal, but notably also in auditory cortical regions. This alpha power lateralization was not maintained steadily but fluctuated in synchrony with the speech rate and lagged the time course of low-frequency (1-5 Hz) sensory synchronization. Higher amplitude of alpha power modulation at the speech rate was predictive of a listener's enhanced performance of stream-specific speech comprehension. Our findings demonstrate that alpha power lateralization is modulated in tune with the sensory input and acts as a spatiotemporal filter controlling the read-out of sensory content.attention | neural oscillations | alpha lateralization | synchronization | speech N eural oscillations are tenable biological substrates to instantiate attentional selection of sensory information from our environment (1-3). The power of alpha oscillations (8-12 Hz) is modulated by the degree of selective attention to a behaviorally relevant stimulus (4-6). Attentive focusing to one side in auditory, visual, or tactile space leads to a relative decrease in alpha power in contralateral compared with ipsilateral sensory brain regions (7-10) and governs success of selective attention, that is, of isolating one stimulus at a specific spatial location (11-13) in the context of other distracting stimuli. In speech, however, spatial selective attention alone does not suffice for successful speech comprehension given the multiple timescales (e.g., syllable and word rate) over which speech varies. Any attentional neural mechanism that respects the temporal structure of auditory sensory inputs must therefore be dynamic over time. Here, we tested the hypothesis that spatial attention to one of two concurrent speech streams induces a lateralization of alpha power that synchronizes with the speech rate over time and enhances speech comprehension.In addition to neural alpha oscillations and their role in selective attention, low-frequency neural oscillations (delta/theta band; 1-5 Hz) in sensory cortices synchronize with the temporal structure of acoustic stimuli (14, 15) such as human speech (16,17), and this synchronization supports perception (18). Furthermore, synchronization of low-frequency neural oscillations with speech is enhanced for speech streams to which participants attend (19,20). Critically, low-frequency oscillations are commonly specified as phase-locked activity (synchroni...

Speech comprehension in multitalker situations is a notorious real-life challenge, particularly for older listeners. Younger listeners exploit stimulus-inherent acoustic detail, but are they also actively predicting upcoming information? And further, how do older listeners deal with acoustic and predictive information? To understand the neural dynamics of listening difficulties and according listening strategies, we contrasted neural responses in the alpha-band (ϳ10 Hz) in younger (20 -30 years, n ϭ 18) and healthy older (60 -70 years, n ϭ 20) participants under changing task demands in a two-talker paradigm. Electroencephalograms were recorded while humans listened to two spoken digits against a distracting talker and decided whether the second digit was smaller or larger. Acoustic detail (temporal fine structure) and predictiveness (the degree to which the first digit predicted the second) varied orthogonally. Alpha power at widespread scalp sites decreased with increasing acoustic detail (during target digit presentation) but also with increasing predictiveness (in-between target digits). For older compared with younger listeners, acoustic detail had a stronger impact on task performance and alpha power modulation. This suggests that alpha dynamics plays an important role in the changes in listening behavior that occur with age. Last, alpha power variations resulting from stimulus manipulations (of acoustic detail and predictiveness) as well as task-independent overall alpha power were related to subjective listening effort. The present data show that alpha dynamics is a promising neural marker of individual difficulties as well as age-related changes in sensation, perception, and comprehension in complex communication situations.

Enhanced alpha power compared with a baseline can reflect states of increased cognitive load, for example, when listening to speech in noise. Can knowledge about "when" to listen (temporal expectations) potentially counteract cognitive load and concomitantly reduce alpha? The current magnetoencephalography (MEG) experiment induced cognitive load using an auditory delayed-matching-to-sample task with 2 syllables S1 and S2 presented in speech-shaped noise. Temporal expectation about the occurrence of S1 was manipulated in 3 different cue conditions: "Neutral" (uninformative about foreperiod), "early-cued" (short foreperiod), and "late-cued" (long foreperiod). Alpha power throughout the trial was highest when the cue was uninformative about the onset time of S1 (neutral) and lowest for the late-cued condition. This alpha-reducing effect of late compared with neutral cues was most evident during memory retention in noise and originated primarily in the right insula. Moreover, individual alpha effects during retention accounted best for observed individual performance differences between late-cued and neutral conditions, indicating a tradeoff between allocation of neural resources and the benefits drawn from temporal cues. Overall, the results indicate that temporal expectations can facilitate the encoding of speech in noise, and concomitantly reduce neural markers of cognitive load.

Behaviorally relevant environmental stimuli are often characterized by some degree of temporal regularity. Dynamic attending theory provides a framework for explaining how perception of stimulus events is affected by the temporal context within which they occur. However, the precise neural implementation of dynamic attending remains unclear. Here, we provide a suggestion for a potential neural implementation of dynamic attending by appealing to low-frequency neural oscillations. The current review will familiarize the reader with the basic theoretical tenets of dynamic attending theory, and review empirical work supporting predictions derived from the theory. The potential neural implementation of dynamic attending theory with respect to low-frequency neural oscillations will be outlined, covering stimulus processing in regular and irregular contexts. Finally, we will provide some more speculative connections between dynamic attending and neural oscillations, and suggest further avenues for future research.

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Optimal perception requires efficient and adaptive neural processing of sensory input. Neurons in nonhuman mammals adapt to the statistical properties of acoustic feature distributions such that they become sensitive to sounds that are most likely to occur in the environment. However, whether human auditory responses adapt to stimulus statistical distributions and how aging affects adaptation to stimulus statistics is unknown. We used MEG to study how exposure to different distributions of sound levels affects adaptation in auditory cortex of younger (mean: 25 years; = 19) and older (mean: 64 years; = 20) adults (male and female). Participants passively listened to two sound-level distributions with different modes (either 15 or 45 dB sensation level). In a control block with long interstimulus intervals, allowing neural populations to recover from adaptation, neural response magnitudes were similar between younger and older adults. Critically, both age groups demonstrated adaptation to sound-level stimulus statistics, but adaptation was altered for older compared with younger people: in the older group, neural responses continued to be sensitive to sound level under conditions in which responses were fully adapted in the younger group. The lack of full adaptation to the statistics of the sensory environment may be a physiological mechanism underlying the known difficulty that older adults have with filtering out irrelevant sensory information. Behavior requires efficient processing of acoustic stimulation. Animal work suggests that neurons accomplish efficient processing by adjusting their response sensitivity depending on statistical properties of the acoustic environment. Little is known about the extent to which this adaptation to stimulus statistics generalizes to humans, particularly to older humans. We used MEG to investigate how aging influences adaptation to sound-level statistics. Listeners were presented with sounds drawn from sound-level distributions with different modes (15 vs 45 dB). Auditory cortex neurons adapted to sound-level statistics in younger and older adults, but adaptation was incomplete in older people. The data suggest that the aging auditory system does not fully capitalize on the statistics available in sound environments to tune the perceptual system dynamically.

Hearing impairment in older adulthood puts people at risk of communication difficulties, disengagement from listening, and social withdrawal. Here, we develop a model of listening engagement (MoLE) that provides a conceptual foundation to understand when people engage in listening and why some people disengage. We use the term "listening engagement" to describe the recruitment of executive and other cognitive resources in the service of a valued communication goal. Listening engagement, listening motivation, and listening experiences are closely interconnected: motivation and other factors determine the degree to which resources are recruited during listening, which in turn influences subjective listening experiences such as enjoyment, effort, frustration, and boredom. We anticipate that this model will help researchers assess more accurately whether a person with hearing difficulties is at risk of disengagement and social withdrawal. It is further useful to more comprehensively characterize a person's listening experiences in laboratory settings when rich, engaging stimulus materials, such as spoken stories, are used. We hope this model will allow new questions in applied and basic hearing science and auditory cognitive neuroscience to be asked and answered.

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