Speech Prosody Serves Temporal Prediction of Language via Contextual Entrainment.

Temporal prediction assists language comprehension. In a series of recent behavioral studies, we have shown that listeners specifically employ rhythmic modulations of prosody to estimate the duration of upcoming sentences, thereby speeding up comprehension. In the current human magnetoencephalography (MEG) study on participants of either sex, we show that the human brain achieves this function through a mechanism termed entrainment. Through entrainment, electrophysiological brain activity maintains and continues contextual rhythms beyond their offset. Our experiment combined exposure to repetitive prosodic contours with the subsequent presentation of visual sentences that either matched or mismatched the duration of the preceding contour. During exposure to prosodic contours, we observed MEG coherence with the contours, which was source-localized to right-hemispheric auditory areas. During the processing of the visual targets, activity at the frequency of the preceding contour was still detectable in the MEG; yet sources shifted to the (left) frontal cortex, in line with a functional inheritance of the rhythmic acoustic context for prediction. Strikingly, when the target sentence was shorter than expected from the preceding contour, an omission response appeared in the evoked potential record. We conclude that prosodic entrainment is a functional mechanism of temporal prediction in language comprehension. In general, acoustic rhythms appear to endow language for employing the brain's electrophysiological mechanisms of temporal prediction.

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.

Laminar neural dynamics of auditory evoked responses: Computational modeling of local field potentials in auditory cortex of non-human primates.

Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Modeling and simulations provide a way to integrate these different types of information to clarify underlying neural mechanisms. In this study, we aimed to shed light on the neural dynamics underlying auditory evoked responses by fitting a rate-based model to LFPs recorded via multi-contact electrodes which simultaneously sampled neural activity across cortical laminae. Recordings included neural population responses to best-frequency (BF) and non-BF tones at four representative sites in primary auditory cortex (A1) of awake monkeys. The model considered major neural populations of excitatory, parvalbumin-expressing (PV), and somatostatin-expressing (SOM) neurons across layers 2/3, 4, and 5/6. Unknown parameters, including the connection strength between the populations, were fitted to the data. Our results revealed similar population dynamics, fitted model parameters, predicted equivalent current dipoles (ECD), tuning curves, and lateral inhibition profiles across recording sites and animals, in spite of quite different extracellular current distributions. We found that PV firing rates were higher in BF than in non-BF responses, mainly due to different strengths of tonotopic thalamic input, whereas SOM firing rates were higher in non-BF than in BF responses due to lateral inhibition. In conclusion, we demonstrate the feasibility of the model-fitting approach in identifying the contributions of cell-type specific population activity to stimulus-evoked LFPs across cortical laminae, providing a foundation for further investigations into the dynamics of neural circuits underlying cortical sensory processing.

Neural entrainment via perceptual inferences.

Entrainment depends on sequential neural phase reset by regular stimulus onset, a temporal parameter. Entraining to sequences of identical stimuli also entails stimulus feature predictability, but this component is not readily separable from temporal regularity. To test if spectral regularities concur with temporal regularities in determining the strength of auditory entrainment, we devised sound sequences that varied in conditional perceptual inferences based on deviant sound repetition probability: strong inference (100% repetition probability: If a deviant appears, then it will repeat), weak inference (75% repetition probability) and no inference (50%: A deviant may or may not repeat with equal probability). We recorded EEG data from 15 young human participants pre-attentively listening to the experimental sound sequences delivered either isochronously or anisochronously (±20% jitter), at both delta (1.67 Hz) and theta (6.67 Hz) stimulation rates. Strong perceptual inferences significantly enhanced entrainment at either stimulation rate and determined positive correlations between precision in phase distribution at the onset of deviant trials and entrained power. We conclude that both spectral predictability and temporal regularity govern entrainment via neural phase control.

Orienting auditory attention in time: Lateralized alpha power reflects spatio-temporal filtering.

The deployment of neural alpha (8-12 Hz) lateralization in service of spatial attention is well-established: Alpha power increases in the cortical hemisphere ipsilateral to the attended hemifield, and decreases in the contralateral hemisphere, respectively. Much less is known about humans' ability to deploy such alpha lateralization in time, and to thus exploit alpha power as a spatio-temporal filter. Here we show that spatially lateralized alpha power does signify - beyond the direction of spatial attention - the distribution of attention in time and thereby qualifies as a spatio-temporal attentional filter. Participants (N = 20) selectively listened to spoken numbers presented on one side (left vs right), while competing numbers were presented on the other side. Key to our hypothesis, temporal foreknowledge was manipulated via a visual cue, which was either instructive and indicated the to-be-probed number position (70% valid) or neutral. Temporal foreknowledge did guide participants' attention, as they recognized numbers from the to-be-attended side more accurately following valid cues. In the magnetoencephalogram (MEG), spatial attention to the left versus right side induced lateralization of alpha power in all temporal cueing conditions. Modulation of alpha lateralization at the 0.8 Hz presentation rate of spoken numbers was stronger following instructive compared to neutral temporal cues. Critically, we found stronger modulation of lateralized alpha power specifically at the onsets of temporally cued numbers. These results suggest that the precisely timed hemispheric lateralization of alpha power qualifies as a spatio-temporal attentional filter mechanism susceptible to top-down behavioural goals.

Functional brain plasticity during L1 training on complex sentences: Changes in gamma-band oscillatory activity.

The adult human brain remains plastic even after puberty. However, whether first language (L1) training in adults can alter the language network is yet largely unknown. Thus, we conducted a longitudinal training experiment on syntactically complex German sentence comprehension. Sentence complexity was varied by the depth of the center embedded relative clauses (i.e., single or double embedded). Comprehension was tested after each sentence with a question on the thematic role assignment. Thirty adult, native German speakers were recruited for 4 days of training. Magnetoencephalography (MEG) data were recorded and subjected to spectral power analysis covering the classical frequency bands (i.e., theta, alpha, beta, low gamma, and gamma). Normalized spectral power, time-locked to the final closure of the relative clause, was subjected to a two-factor analysis ("sentence complexity" and "training days"). Results showed that for the more complex sentences, the interaction of sentence complexity and training days was observed in Brodmann area 44 (BA 44) as a decrease of gamma power with training. Moreover, in the gamma band (55-95 Hz) functional connectivity between BA 44 and other brain regions such as the inferior frontal sulcus and the inferior parietal cortex were correlated with behavioral performance increase due to training. These results show that even for native speakers, complex L1 sentence training improves language performance and alters neural activities of the left hemispheric language network. Training strengthens the use of the dorsal processing stream with working-memory-related brain regions for syntactically complex sentences, thereby demonstrating the brain's functional plasticity for L1 training.

Nonlinear interaction decomposition (NID): A method for separation of cross-frequency coupled sources in human brain.

Cross-frequency coupling (CFC) between neuronal oscillations reflects an integration of spatially and spectrally distributed information in the brain. Here, we propose a novel framework for detecting such interactions in Magneto- and Electroencephalography (MEG/EEG), which we refer to as Nonlinear Interaction Decomposition (NID). In contrast to all previous methods for separation of cross-frequency (CF) sources in the brain, we propose that the extraction of nonlinearly interacting oscillations can be based on the statistical properties of their linear mixtures. The main idea of NID is that nonlinearly coupled brain oscillations can be mixed in such a way that the resulting linear mixture has a non-Gaussian distribution. We evaluate this argument analytically for amplitude-modulated narrow-band oscillations which are either phase-phase or amplitude-amplitude CF coupled. We validated NID extensively with simulated EEG obtained with realistic head modelling. The method extracted nonlinearly interacting components reliably even at SNRs as small as -15 dB. Additionally, we applied NID to the resting-state EEG of 81 subjects to characterize CF phase-phase coupling between alpha and beta oscillations. The extracted sources were located in temporal, parietal and frontal areas, demonstrating the existence of diverse local and distant nonlinear interactions in resting-state EEG data. All codes are available publicly via GitHub.

Magnetoencephalography for epileptic focus localization in a series of 1000 cases.

The aim of epilepsy surgery in patients with focal, pharmacoresistant epilepsies is to remove the complete epileptogenic zone to achieve long-term seizure freedom. In addition to a spectrum of diagnostic methods, magnetoencephalography focus localization is used for planning of epilepsy surgery. We present results from a retrospective observational cohort study of 1000 patients, evaluated using magnetoencephalography at the University Hospital Erlangen over the time span of 28 years. One thousand consecutive cases were included in the study, evaluated at the University Hospital Erlangen between 1990 and 2018. All patients underwent magnetoencephalography as part of clinical workup for epilepsy surgery. Of these, 405 underwent epilepsy surgery after magnetoencephalography, with postsurgical follow-ups of up to 20 years. Sensitivity for interictal epileptic activity was evaluated, in addition to concordance of localization with the consensus of presurgical workup on a lobar level. We evaluate magnetoencephalography characteristics of patients who underwent epilepsy surgery versus patients who did not proceed to surgery. In operated patients, resection of magnetoencephalography localizations were related to postsurgical seizure outcomes, including long-term results after several years. In comparison, association of lesionectomy with seizure outcomes was analysed. Measures of diagnostic accuracy were calculated for magnetoencephalography resection and lesionectomy. Sensitivity for interictal epileptic activity was 72% with significant differences between temporal and extra-temporal lobe epilepsy. Magnetoencephalography was concordant with the presurgical consensus in 51% and showed additional or more focal involvement in an additional 32%. Patients who proceeded to surgery showed a significantly higher percentage of monofocal magnetoencephalography results. Complete magnetoencephalography resection was associated with significantly higher chances to achieve seizure freedom in the short and long-term. Diagnostic accuracy was significant in temporal and extra-temporal lobe cases, but was significantly higher in extra-temporal lobe epilepsy (diagnostic odds ratios of 4.4 and 41.6). Odds ratios were also higher in non-lesional versus lesional cases (42.0 versus 6.2). The results show that magnetoencephalography provides non-redundant information, which significantly contributes to patient selection, focus localization and ultimately long-term seizure freedom after epilepsy surgery. Specifically in extra-temporal lobe epilepsy and non-lesional cases, magnetoencephalography provides excellent accuracy.

Aging Affects Adaptation to Sound-Level Statistics in Human Auditory Cortex.

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; n = 19) and older (mean: 64 years; n = 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.SIGNIFICANCE STATEMENT 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.

Oscillatory dynamics of cortical functional connections in semantic prediction.

An event related potential, known as the N400, has been particularly useful in investigating language processing as it serves as a neural index for semantic prediction. There are numerous studies on the functional segregation of N400 neural sources; however, the oscillatory dynamics of functional connections among the relevant sources has remained elusive. In this study we acquired magnetoencephalography data during a classic N400 paradigm, where the semantic predictability of a fixed target noun was manipulated in simple German sentences. We conducted inter-regional functional connectivity (FC) and time-frequency analysis on known regions of the semantic network, encompassing bilateral temporal, and prefrontal cortices. Increased FC was found in less predicted (LP) nouns compared with highly predicted (HP) nouns in three connections: (a) right inferior frontal gyrus (IFG) and right middle temporal gyrus (MTG) from 0 to 300 ms mainly within the alpha band, (b) left lateral orbitofrontal (LOF) and right IFG around 400 ms within the beta band, and (c) left superior temporal gyrus (STG) and left LOF from 300 to 700 ms in the beta and low gamma bands. Furthermore, gamma spectral power (31-70 Hz) was stronger in HP nouns than in LP nouns in left anterior temporal cortices in earlier time windows (0-200 ms). Our findings support recent theories in language comprehension, suggesting fronto-temporal top-down connections are mainly mediated through beta oscillations while gamma band frequencies are involved in matching between prediction and input.

A generic deviance detection principle for cortical On/Off responses, omission response, and mismatch negativity.

Neural responses to sudden changes can be observed in many parts of the sensory pathways at different organizational levels. For example, deviants that violate regularity at various levels of abstraction can be observed as simple On/Off responses of individual neurons or as cumulative responses of neural populations. The cortical deviance-related responses supporting different functionalities (e.g., gap detection, chunking, etc.) seem unlikely to arise from different function-specific neural circuits, given the relatively uniform and self-similar wiring patterns across cortical areas and spatial scales. Additionally, reciprocal wiring patterns (with heterogeneous combinations of excitatory and inhibitory connections) in the cortex naturally speak in favor of a generic deviance detection principle. Based on this concept, we propose a network model consisting of reciprocally coupled neural masses as a blueprint of a universal change detector. Simulation examples reproduce properties of cortical deviance-related responses including the On/Off responses, the omitted-stimulus response (OSR), and the mismatch negativity (MMN). We propose that the emergence of change detectors relies on the involvement of disinhibition. An analysis of network connection settings further suggests a supportive effect of synaptic adaptation and a destructive effect of N-methyl-D-aspartate receptor (NMDA-r) antagonists on change detection. We conclude that the nature of cortical reciprocal wiring gives rise to a whole range of local change detectors supporting the notion of a generic deviance detection principle. Several testable predictions are provided based on the network model. Notably, we predict that the NMDA-r antagonists would generally dampen the cortical Off response, the cortical OSR, and the MMN.

Spatiotemporal dynamics of auditory attention synchronize with speech.

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.

Cingulate and cerebellar beta oscillations are engaged in the acquisition of auditory-motor sequences.

Singing, music performance, and speech rely on the retrieval of complex sounds, which are generated by the corresponding actions and are organized into sequences. It is crucial in these forms of behavior that the serial organization (i.e., order) of both the actions and associated sounds be monitored and learned. To investigate the neural processes involved in the monitoring of serial order during the initial learning of sensorimotor sequences, we performed magnetoencephalographic recordings while participants explicitly learned short piano sequences under the effect of occasional alterations of auditory feedback (AAF). The main result was a prominent and selective modulation of beta (13-30 Hz) oscillations in cingulate and cerebellar regions during the processing of AAF that simulated serial order errors. Furthermore, the AAF-induced modulation of beta oscillations was associated with higher error rates, reflecting compensatory changes in sequence planning. This suggests that cingulate and cerebellar beta oscillations play a role in tracking serial order during initial sensorimotor learning and in updating the mapping of the sensorimotor representations. The findings support the notion that the modulation of beta oscillations is a candidate mechanism for the integration of sequential motor and auditory information during an early stage of skill acquisition in music performance. This has potential implications for singing and speech. Hum Brain Mapp 38:5161-5179, 2017. © 2017 Wiley Periodicals, Inc.

Alpha Oscillatory Dynamics Index Temporal Expectation Benefits in Working Memory.

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.

Voice identity recognition: functional division of the right STS and its behavioral relevance.

The human voice is the primary carrier of speech but also a fingerprint for person identity. Previous neuroimaging studies have revealed that speech and identity recognition is accomplished by partially different neural pathways, despite the perceptual unity of the vocal sound. Importantly, the right STS has been implicated in voice processing, with different contributions of its posterior and anterior parts. However, the time point at which vocal and speech processing diverge is currently unknown. Also, the exact role of the right STS during voice processing is so far unclear because its behavioral relevance has not yet been established. Here, we used the high temporal resolution of magnetoencephalography and a speech task control to pinpoint transient behavioral correlates: we found, at 200 msec after stimulus onset, that activity in right anterior STS predicted behavioral voice recognition performance. At the same time point, the posterior right STS showed increased activity during voice identity recognition in contrast to speech recognition whereas the left mid STS showed the reverse pattern. In contrast to the highly speech-sensitive left STS, the current results highlight the right STS as a key area for voice identity recognition and show that its anatomical-functional division emerges around 200 msec after stimulus onset. We suggest that this time point marks the speech-independent processing of vocal sounds in the posterior STS and their successful mapping to vocal identities in the anterior STS.

Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models.

A BEM (boundary element method) based approach is developed to accurately solve an EEG/MEG forward problem for a modern high-resolution head model in approximately 60 seconds using a common workstation. The method utilizes a charge-based BEM with fast multipole acceleration (BEM-FMM) and a "smart" mesh pre-refinement (called b-refinement) close to the singular source(s). No costly matrix-filling or direct solution steps typical for the standard BEM are required; the method generates on-skin voltages as well as MEG magnetic fields for high-resolution head models in approximately 60 seconds after initial model assembly. The method is verified both theoretically and experimentally.

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.

Accuracy of dipole source reconstruction in the 3-layer BEM model against the 5-layer BEM-FMM model.

Objective: To compare cortical dipole fitting spatial accuracy between the widely used yet highly simplified 3-layer and modern more realistic 5-layer BEM-FMM models with and without adaptive mesh refinement (AMR) methods. Methods: We generate simulated noiseless 256-channel EEG data from 5-layer (7-compartment) meshes of 15 subjects from the Connectome Young Adult dataset. For each subject, we test four dipole positions, three sets of conductivity values, and two types of head segmentation. We use the boundary element method (BEM) with fast multipole method (FMM) acceleration, with or without (AMR), for forward modeling. Dipole fitting is carried out with the FieldTrip MATLAB toolbox. Results: The average position error (across all tested dipoles, subjects, and models) is ~4 mm, with a standard deviation of ~2 mm. The orientation error is ~20° on average, with a standard deviation of ~15°. Without AMR, the numerical inaccuracies produce a larger disagreement between the 3- and 5-layer models, with an average position error of ~8 mm (6 mm standard deviation), and an orientation error of 28° (28° standard deviation). Conclusions: The low-resolution 3-layer models provide excellent accuracy in dipole localization. On the other hand, dipole orientation is retrieved less accurately. Therefore, certain applications may require more realistic models for practical source reconstruction. AMR is a critical component for improving the accuracy of forward EEG computations using a high-resolution 5-layer volume conduction model. Significance: Improving EEG source reconstruction accuracy is important for several clinical applications, including epilepsy and other seizure-inducing conditions.

Adverse listening conditions and memory load drive a common α oscillatory network.

How does acoustic degradation affect the neural mechanisms of working memory? Enhanced alpha oscillations (8-13 Hz) during retention of items in working memory are often interpreted to reflect increased demands on storage and inhibition. We hypothesized that auditory signal degradation poses an additional challenge to human listeners partly because it draws on the same neural mechanisms. In an adapted Sternberg paradigm, auditory memory load and acoustic degradation were parametrically varied and the magnetoencephalographic response was analyzed in the time-frequency domain. Notably, during the stimulus-free delay interval, alpha power monotonically increased at central-parietal sensors as functions of memory load (higher alpha power with more memory load) and of acoustic degradation (also higher alpha power with more severe acoustic degradation). This alpha effect was superadditive when highest load was combined with most severe degradation. Moreover, alpha oscillatory dynamics during stimulus-free delay were predictive of response times to the probe item. Source localization of alpha power during stimulus-free delay indicated that alpha generators in right parietal, cingulate, supramarginal, and superior temporal cortex were sensitive to combined memory load and acoustic degradation. In summary, both challenges of memory load and acoustic degradation increase activity in a common alpha-frequency network. The results set the stage for future studies on how chronic or acute degradations of sensory input affect mechanisms of executive control.

Early visual and auditory processing rely on modality-specific attentional resources.

Many everyday situations require focusing on visual or auditory information while ignoring the other modality. Previous findings suggest an attentional mechanism that operates between sensory modalities and governs such states. To date, evidence is equivocal as to whether this 'intermodal' attention relies on a distribution of resources either common or specific to sensory modalities. We provide new insights by investigating consequences of a shift from simultaneous ('bimodal') attention to vision and audition to unimodal selective attention. Concurrently presented visual and auditory stimulus streams were frequency-tagged to elicit steady-state responses (SSRs) recorded simultaneously in electro- and magnetoencephalograms (EEG/MEG). After the shift, decreased amplitudes of the SSR corresponding to the unattended sensory stream indicated reduced processing. We did not observe an amplitude increase of the SSR corresponding to the attended sensory stream. These findings are incompatible with a common-resources account. A redistribution of attentional resources between vision and audition would result in simultaneous processing gain in the attended sensory modality and reduction in the unattended sensory modality. Our results favor a modality-specific-resources account, which allows for independent modulation of early cortical processing in each sensory modality.