Auditory-cortex short-term plasticity induced by selective attention

Pathological changes of brain oscillations following ischemic stroke

Brain oscillations recorded in the extracellular space are among the most important aspects of neurophysiology data reflecting the activity and function of neurons in a population or a network. The signal strength and patterns of brain oscillations can be powerful biomarkers used for disease detection and prediction of the recovery of function. Electrophysiological signals can also serve as an index for many cutting-edge technologies aiming to interface between the nervous system and neuroprosthetic devices and to monitor the efficacy of boosting neural activity. In this review, we provided an overview of the basic knowledge regarding local field potential, electro- or magneto- encephalography signals, and their biological relevance, followed by a summary of the findings reported in various clinical and experimental stroke studies. We reviewed evidence of stroke-induced changes in hippocampal oscillations and disruption of communication between brain networks as potential mechanisms underlying post-stroke cognitive dysfunction. We also discussed the promise of brain stimulation in promoting post stroke functional recovery via restoring neural activity and enhancing brain plasticity.

The Imbalanced Plasticity Hypothesis of Schizophrenia-Related Psychosis: A Predictive Perspective

A considerable number of studies have attempted to account for the psychotic aspects of schizophrenia in terms of the influential predictive coding (PC) hypothesis. We argue that the prediction-oriented perspective on schizophrenia-related psychosis may benefit from a mechanistic model that: 1) gives due weight to the extent to which alterations in short- and long-term synaptic plasticity determine the degree and the direction of the functional disruption that occurs in psychosis; and 2) addresses the distinction between the two central syndromes of psychosis in schizophrenia: disorganization and reality-distortion. To accomplish these goals, we propose the Imbalanced Plasticity Hypothesis - IPH, and demonstrate that it: 1) accounts for commonalities and differences between disorganization and reality distortion in terms of excessive (hyper) or insufficient (hypo) neuroplasticity, respectively; 2) provides distinct predictions in the cognitive and electrophysiological domains; and 3) is able to reconcile conflicting PC-oriented accounts of psychosis.

Defining the Role of Attention in Hierarchical Auditory Processing

Communication in noise is a complex process requiring efficient neural encoding throughout the entire auditory pathway as well as contributions from higher-order cognitive processes (i.e., attention) to extract speech cues for perception. Thus, identifying effective clinical interventions for individuals with speech-in-noise deficits relies on the disentanglement of bottom-up (sensory) and top-down (cognitive) factors to appropriately determine the area of deficit; yet, how attention may interact with early encoding of sensory inputs remains unclear. For decades, attentional theorists have attempted to address this question with cleverly designed behavioral studies, but the neural processes and interactions underlying attention's role in speech perception remain unresolved. While anatomical and electrophysiological studies have investigated the neurological structures contributing to attentional processes and revealed relevant brain-behavior relationships, recent electrophysiological techniques (i.e., simultaneous recording of brainstem and cortical responses) may provide novel insight regarding the relationship between early sensory processing and top-down attentional influences. In this article, we review relevant theories that guide our present understanding of attentional processes, discuss current electrophysiological evidence of attentional involvement in auditory processing across subcortical and cortical levels, and propose areas for future study that will inform the development of more targeted and effective clinical interventions for individuals with speech-in-noise deficits.

Auditory attentional filter in the absence of masking noise

Signals containing attended frequencies are facilitated while those with unexpected frequencies are suppressed by an auditory filtering process. The neurocognitive mechanism underlying the auditory attentional filter is, however, poorly understood. The olivocochlear bundle (OCB), a brainstem neural circuit that is part of the efferent system, has been suggested to be partly responsible for the filtering via its noise-dependent antimasking effect. The current study examined the role of the OCB in attentional filtering, particularly the validity of the antimasking hypothesis, by comparing attentional filters measured in quiet and in the presence of background noise in a group of normal-hearing listeners. Filters obtained in both conditions were comparable, suggesting that the presence of background noise is not crucial for attentional filter generation. In addition, comparison of frequency-specific changes of the cue-evoked enhancement component of filters in quiet and noise also did not reveal any major contribution of background noise to the cue effect. These findings argue against the involvement of an antimasking effect in the attentional process. Instead of the antimasking effect mediated via medial olivocochlear fibers, results from current and earlier studies can be explained by frequency-specific modulation of afferent spontaneous activity by lateral olivocochlear fibers. It is proposed that the activity of these lateral fibers could be driven by top-down cortical control via a noise-independent mechanism. SIGNIFICANCE: The neural basis for auditory attentional filter remains a fundamental but poorly understood area in auditory neuroscience. The efferent olivocochlear pathway that projects from the brainstem back to the cochlea has been suggested to mediate the attentional effect via its noise-dependent antimasking effect. The current study demonstrates that the filter generation is mostly independent of the background noise, and therefore is unlikely to be mediated by the olivocochlear brainstem reflex. It is proposed that the entire cortico-olivocochlear system might instead be used to alter the hearing sensitivity during focus attention via frequency-specific modulation of afferent spontaneous activity.

A Tutorial on Auditory Attention Identification Methods

Auditory attention identification methods attempt to identify the sound source of a listener's interest by analyzing measurements of electrophysiological data. We present a tutorial on the numerous techniques that have been developed in recent decades, and we present an overview of current trends in multivariate correlation-based and model-based learning frameworks. The focus is on the use of linear relations between electrophysiological and audio data. The way in which these relations are computed differs. For example, canonical correlation analysis (CCA) finds a linear subset of electrophysiological data that best correlates to audio data and a similar subset of audio data that best correlates to electrophysiological data. Model-based (encoding and decoding) approaches focus on either of these two sets. We investigate the similarities and differences between these linear model philosophies. We focus on (1) correlation-based approaches (CCA), (2) encoding/decoding models based on dense estimation, and (3) (adaptive) encoding/decoding models based on sparse estimation. The specific focus is on sparsity-driven adaptive encoding models and comparing the methodology in state-of-the-art models found in the auditory literature. Furthermore, we outline the main signal processing pipeline for how to identify the attended sound source in a cocktail party environment from the raw electrophysiological data with all the necessary steps, complemented with the necessary MATLAB code and the relevant references for each step. Our main aim is to compare the methodology of the available methods, and provide numerical illustrations to some of them to get a feeling for their potential. A thorough performance comparison is outside the scope of this tutorial.

Acoustical Enrichment during Early Development Improves Response Reliability in the Adult Auditory Cortex of the Rat

It is well known that auditory experience during early development shapes response properties of auditory cortex (AC) neurons, influencing, for example, tonotopical arrangement, response thresholds and strength, or frequency selectivity. Here, we show that rearing rat pups in a complex acoustically enriched environment leads to an increased reliability of responses of AC neurons, affecting both the rate and the temporal codes. For a repetitive stimulus, the neurons exhibit a lower spike count variance, indicating a more stable rate coding. At the level of individual spikes, the discharge patterns of individual neurons show a higher degree of similarity across stimulus repetitions. Furthermore, the neurons follow more precisely the temporal course of the stimulus, as manifested by improved phase-locking to temporally modulated sounds. The changes are persistent and present up to adulthood. The results document that besides basic alterations of receptive fields presented in our previous study, the acoustic environment during the critical period of postnatal development also leads to a decreased stochasticity and a higher reproducibility of neuronal spiking patterns.

Perceptual Plasticity for Auditory Object Recognition

In our auditory environment, we rarely experience the exact acoustic waveform twice. This is especially true for communicative signals that have meaning for listeners. In speech and music, the acoustic signal changes as a function of the talker (or instrument), speaking (or playing) rate, and room acoustics, to name a few factors. Yet, despite this acoustic variability, we are able to recognize a sentence or melody as the same across various kinds of acoustic inputs and determine meaning based on listening goals, expectations, context, and experience. The recognition process relates acoustic signals to prior experience despite variability in signal-relevant and signal-irrelevant acoustic properties, some of which could be considered as "noise" in service of a recognition goal. However, some acoustic variability, if systematic, is lawful and can be exploited by listeners to aid in recognition. Perceivable changes in systematic variability can herald a need for listeners to reorganize perception and reorient their attention to more immediately signal-relevant cues. This view is not incorporated currently in many extant theories of auditory perception, which traditionally reduce psychological or neural representations of perceptual objects and the processes that act on them to static entities. While this reduction is likely done for the sake of empirical tractability, such a reduction may seriously distort the perceptual process to be modeled. We argue that perceptual representations, as well as the processes underlying perception, are dynamically determined by an interaction between the uncertainty of the auditory signal and constraints of context. This suggests that the process of auditory recognition is highly context-dependent in that the identity of a given auditory object may be intrinsically tied to its preceding context. To argue for the flexible neural and psychological updating of sound-to-meaning mappings across speech and music, we draw upon examples of perceptual categories that are thought to be highly stable. This framework suggests that the process of auditory recognition cannot be divorced from the short-term context in which an auditory object is presented. Implications for auditory category acquisition and extant models of auditory perception, both cognitive and neural, are discussed.

Modelling auditory attention

Sounds in everyday life seldom appear in isolation. Both humans and machines are constantly flooded with a cacophony of sounds that need to be sorted through and scoured for relevant information-a phenomenon referred to as the 'cocktail party problem'. A key component in parsing acoustic scenes is the role of attention, which mediates perception and behaviour by focusing both sensory and cognitive resources on pertinent information in the stimulus space. The current article provides a review of modelling studies of auditory attention. The review highlights how the term attention refers to a multitude of behavioural and cognitive processes that can shape sensory processing. Attention can be modulated by 'bottom-up' sensory-driven factors, as well as 'top-down' task-specific goals, expectations and learned schemas. Essentially, it acts as a selection process or processes that focus both sensory and cognitive resources on the most relevant events in the soundscape; with relevance being dictated by the stimulus itself (e.g. a loud explosion) or by a task at hand (e.g. listen to announcements in a busy airport). Recent computational models of auditory attention provide key insights into its role in facilitating perception in cluttered auditory scenes.This article is part of the themed issue 'Auditory and visual scene analysis'.

Modulatory Effects of Attention on Lateral Inhibition in the Human Auditory Cortex

Reduced neural processing of a tone is observed when it is presented after a sound whose spectral range closely frames the frequency of the tone. This observation might be explained by the mechanism of lateral inhibition (LI) due to inhibitory interneurons in the auditory system. So far, several characteristics of bottom up influences on LI have been identified, while the influence of top-down processes such as directed attention on LI has not been investigated. Hence, the study at hand aims at investigating the modulatory effects of focused attention on LI in the human auditory cortex. In the magnetoencephalograph, we present two types of masking sounds (white noise vs. withe noise passing through a notch filter centered at a specific frequency), followed by a test tone with a frequency corresponding to the center-frequency of the notch filter. Simultaneously, subjects were presented with visual input on a screen. To modulate the focus of attention, subjects were instructed to concentrate either on the auditory input or the visual stimuli. More specific, on one half of the trials, subjects were instructed to detect small deviations in loudness in the masking sounds while on the other half of the trials subjects were asked to detect target stimuli on the screen. The results revealed a reduction in neural activation due to LI, which was larger during auditory compared to visual focused attention. Attentional modulations of LI were observed in two post-N1m time intervals. These findings underline the robustness of reduced neural activation due to LI in the auditory cortex and point towards the important role of attention on the modulation of this mechanism in more evaluative processing stages.

Closely Spaced MEG Source Localization and Functional Connectivity Analysis Using a New Prewhitening Invariance of Noise Space Algorithm

This paper proposed a prewhitening invariance of noise space (PW-INN) as a new magnetoencephalography (MEG) source analysis method, which is particularly suitable for localizing closely spaced and highly correlated cortical sources under real MEG noise. Conventional source localization methods, such as sLORETA and beamformer, cannot distinguish closely spaced cortical sources, especially under strong intersource correlation. Our previous work proposed an invariance of noise space (INN) method to resolve closely spaced sources, but its performance is seriously degraded under correlated noise between MEG sensors. The proposed PW-INN method largely mitigates the adverse influence of correlated MEG noise by projecting MEG data to a new space defined by the orthogonal complement of dominant eigenvectors of correlated MEG noise. Simulation results showed that PW-INN is superior to INN, sLORETA, and beamformer in terms of localization accuracy for closely spaced and highly correlated sources. Lastly, source connectivity between closely spaced sources can be satisfactorily constructed from source time courses estimated by PW-INN but not from results of other conventional methods. Therefore, the proposed PW-INN method is a promising MEG source analysis to provide a high spatial-temporal characterization of cortical activity and connectivity, which is crucial for basic and clinical research of neural plasticity.

Auditory conflict resolution correlates with medial-lateral frontal theta/alpha phase synchrony

When multiple persons speak simultaneously, it may be difficult for the listener to direct attention to correct sound objects among conflicting ones. This could occur, for example, in an emergency situation in which one hears conflicting instructions and the loudest, instead of the wisest, voice prevails. Here, we used cortically-constrained oscillatory MEG/EEG estimates to examine how different brain regions, including caudal anterior cingulate (cACC) and dorsolateral prefrontal cortices (DLPFC), work together to resolve these kinds of auditory conflicts. During an auditory flanker interference task, subjects were presented with sound patterns consisting of three different voices, from three different directions (45° left, straight ahead, 45° right), sounding out either the letters “A” or “O”. They were asked to discriminate which sound was presented centrally and ignore the flanking distracters that were phonetically either congruent (50%) or incongruent (50%) with the target. Our cortical MEG/EEG oscillatory estimates demonstrated a direct relationship between performance and brain activity, showing that efficient conflict resolution, as measured with reduced conflict-induced RT lags, is predicted by theta/alpha phase coupling between cACC and right lateral frontal cortex regions intersecting the right frontal eye fields (FEF) and DLPFC, as well as by increased pre-stimulus gamma (60–110 Hz) power in the left inferior fontal cortex. Notably, cACC connectivity patterns that correlated with behavioral conflict-resolution measures were found during both the pre-stimulus and the pre-response periods. Our data provide evidence that, instead of being only transiently activated upon conflict detection, cACC is involved in sustained engagement of attentional resources required for effective sound object selection performance.

Enhanced neural synchrony between left auditory and premotor cortex is associated with successful phonetic categorization

The cortical dorsal auditory stream has been proposed to mediate mapping between auditory and articulatory-motor representations in speech processing. Whether this sensorimotor integration contributes to speech perception remains an open question. Here, magnetoencephalography was used to examine connectivity between auditory and motor areas while subjects were performing a sensorimotor task involving speech sound identification and overt repetition. Functional connectivity was estimated with inter-areal phase synchrony of electromagnetic oscillations. Structural equation modeling was applied to determine the direction of information flow. Compared to passive listening, engagement in the sensorimotor task enhanced connectivity within 200 ms after sound onset bilaterally between the temporoparietal junction (TPJ) and ventral premotor cortex (vPMC), with the left-hemisphere connection showing directionality from vPMC to TPJ. Passive listening to noisy speech elicited stronger connectivity than clear speech between left auditory cortex (AC) and vPMC at ~100 ms, and between left TPJ and dorsal premotor cortex (dPMC) at ~200 ms. Information flow was estimated from AC to vPMC and from dPMC to TPJ. Connectivity strength among the left AC, vPMC, and TPJ correlated positively with the identification of speech sounds within 150 ms after sound onset, with information flowing from AC to TPJ, from AC to vPMC, and from vPMC to TPJ. Taken together, these findings suggest that sensorimotor integration mediates the categorization of incoming speech sounds through reciprocal auditory-to-motor and motor-to-auditory projections.