Neural Representation Of Sound Research Articles

Visuospatial attention revamps cortical processing of sound amid audiovisual uncertainty.

Selective attentional biases arising from one sensory modality manifest in others. The effects of visuospatial attention, important in visual object perception, are unclear in the auditory domain during audiovisual (AV) scene processing. We investigate temporal and spatial factors that underlie such transfer neurally. Auditory encoding of random tone pips in AV scenes was addressed via a temporal response function model (TRF) of participants' electroencephalogram (N = 30). The spatially uninformative pips were associated with spatially distributed visual contrast reversals ("flips"), through asynchronous probabilistic AV temporal onset distributions. Participants deployed visuospatial selection on these AV stimuli to perform a task. A late (~300 ms) cross-modal influence over the neural representation of pips was found in the original and a replication study (N = 21). Transfer depended on selected visual input being (i) presented during or shortly after a related sound, in relatively limited temporal distributions (<165 ms); (ii) positioned across limited (1:4) visual foreground to background ratios. Neural encoding of auditory input, as a function of visual input, was largest at visual foreground quadrant sectors and lowest at locations opposite to the target. The results indicate that ongoing neural representations of sounds incorporate visuospatial attributes for auditory stream segregation, as cross-modal transfer conveys information that specifies the identity of multisensory signals. A potential mechanism is by enhancing or recalibrating the tuning properties of the auditory populations that represent them as objects. The results account for the dynamic evolution under visual attention of multisensory integration, specifying critical latencies at which relevant cortical networks operate.

Stability of complex sound representations in the auditory midbrain across the lifespan despite age-related brainstem delays

The extent to which aging of the central auditory pathway impairs auditory perception in the elderly independent of peripheral cochlear decline is debated. To cause auditory deficits in normal hearing elderly, central aging needs to degrade neural sound representations at some point along the auditory pathway. However, inaccessible to psychophysical methods, the level of the auditory pathway at which aging starts to effectively degrade neural sound representations remains poorly differentiated. Here we tested how potential age-related changes in the auditory brainstem affect the stability of spatiotemporal multiunit complex speech-like sound representations in the auditory midbrain of old normal hearing CBA/J mice. Although brainstem conduction speed slowed down in old mice, the change was limited to the sub-millisecond range and only minimally affected temporal processing in the midbrain (i.e. gaps-in-noise sensitivity). Importantly, besides the small delay, multiunit complex temporal sound representations in the auditory midbrain did not differ between young and old mice. This shows that although small age-related neural effects in simple sound parameters in the lower brainstem may be present in aging they do not effectively deteriorate complex neural population representations at the level of the auditory midbrain when peripheral hearing remains normal. This result challenges the widespread belief of ‘pure’ central auditory decline as an automatic consequence of aging, at least up to the inferior colliculus. However, the stability of midbrain processing in aging emphasizes the role of undetected ‘hidden’ peripheral damage and accumulating effects in higher cortical auditory-cognitive processing explaining perception deficits in ‘normal hearing’ elderly.

Auditory detection learning is accompanied by plasticity in the auditory evoked potential

Auditory detection can improve with practice. These improvements are often assumed to arise from selective attention processes, but longer-term plasticity as a result of training may also play a role. Here, listeners were trained to detect either an 861-Hz or 1058-Hz tone (counterbalanced across participants) presented in noise at SNRs varying from -10 to -24 dB. On the following day, they were tasked with detecting 861-Hz and 1058-Hz tones at an SNR of -21 dB. In between blocks of this active task, EEG was recorded during passive presentation of trained and untrained frequency tones in quiet. Detection accuracy and confidence ratings were higher for trials at listeners’ trained, than untrained-frequency (i.e., learning occurred). During passive exposure to sounds, the P2 component of the auditory evoked potential (∼150 – 200 ms post tone onset) was larger in amplitude for the trained compared to the untrained frequency. An analysis of global field power similarly yielded a stronger response for trained tones in the P2 time window. These effects were obtained during passive exposure, suggesting that training induced improvements in detection are not solely related to changes in selective attention. Rather, there may be an important role for changes in the long-term neural representations of sounds.

Optimal features for auditory categorization

Humans and vocal animals use vocalizations to communicate with members of their species. A necessary function of auditory perception is to generalize across the high variability inherent in vocalization production and classify them into behaviorally distinct categories (‘words’ or ‘call types’). Here, we demonstrate that detecting mid-level features in calls achieves production-invariant classification. Starting from randomly chosen marmoset call features, we use a greedy search algorithm to determine the most informative and least redundant features necessary for call classification. High classification performance is achieved using only 10–20 features per call type. Predictions of tuning properties of putative feature-selective neurons accurately match some observed auditory cortical responses. This feature-based approach also succeeds for call categorization in other species, and for other complex classification tasks such as caller identification. Our results suggest that high-level neural representations of sounds are based on task-dependent features optimized for specific computational goals.

Acoustic and higher-level representations of naturalistic auditory scenes in human auditory and frontal cortex

Often, in everyday life, we encounter auditory scenes comprising multiple simultaneous sounds and succeed to selectively attend to only one sound, typically the most relevant for ongoing behavior. Studies using basic sounds and two-talker stimuli have shown that auditory selective attention aids this by enhancing the neural representations of the attended sound in auditory cortex. It remains unknown, however, whether and how this selective attention mechanism operates on representations of auditory scenes containing natural sounds of different categories. In this high-field fMRI study we presented participants with simultaneous voices and musical instruments while manipulating their focus of attention. We found an attentional enhancement of neural sound representations in temporal cortex - as defined by spatial activation patterns - at locations that depended on the attended category (i.e., voices or instruments). In contrast, we found that in frontal cortex the site of enhancement was independent of the attended category and the same regions could flexibly represent any attended sound regardless of its category. These results are relevant to elucidate the interacting mechanisms of bottom-up and top-down processing when listening to real-life scenes comprised of multiple sound categories.

Reconstructing the spectrotemporal modulations of real-life sounds from fMRI response patterns

Ethological views of brain functioning suggest that sound representations and computations in the auditory neural system are optimized finely to process and discriminate behaviorally relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finches). Here, we show that modeling of neural sound representations in terms of frequency-specific spectrotemporal modulations enables accurate and specific reconstruction of real-life sounds from high-resolution functional magnetic resonance imaging (fMRI) response patterns in the human auditory cortex. Region-based analyses indicated that response patterns in separate portions of the auditory cortex are informative of distinctive sets of spectrotemporal modulations. Most relevantly, results revealed that in early auditory regions, and progressively more in surrounding regions, temporal modulations in a range relevant for speech analysis (∼2-4 Hz) were reconstructed more faithfully than other temporal modulations. In early auditory regions, this effect was frequency-dependent and only present for lower frequencies (<∼2 kHz), whereas for higher frequencies, reconstruction accuracy was higher for faster temporal modulations. Further analyses suggested that auditory cortical processing optimized for the fine-grained discrimination of speech and vocal sounds underlies this enhanced reconstruction accuracy. In sum, the present study introduces an approach to embed models of neural sound representations in the analysis of fMRI response patterns. Furthermore, it reveals that, in the human brain, even general purpose and fundamental neural processing mechanisms are shaped by the physical features of real-world stimuli that are most relevant for behavior (i.e., speech, voice).

How learning to abstract shapes neural sound representations.

The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques such as multivariate pattern analysis (MVPA) in studying categorical sound representations. With their increased sensitivity to distributed activation changes—even in absence of changes in overall signal level—these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations.

Non-isomorphism in efficient coding of complex sound properties

To the extent that sensorineural systems are efficient, stimulus redundancy should be captured in ways that optimize information transmission. Consistent with this principle, neural representations of sounds have been proposed to become "non-isomorphic," increasingly abstract and decreasingly resembling the original (redundant) input. Here, non-isomorphism is tested in perceptual learning using AXB discrimination of novel sounds with two highly correlated complex acoustic properties and a randomly varying third dimension. Discrimination of sounds obeying the correlation became superior to that of sounds violating it despite widely varying physical acoustic properties, suggesting non-isomorphic representation of stimulus redundancy.

Reduced duration MMN and impaired temporal integration window in clinical populations

Event Abstract Back to Event Reduced duration MMN and impaired temporal integration window in clinical populations Hirooki Yabe1* 1 Department of Neuropsychiatry, Fukushima Medical University, Japan The acoustic brain has probably developed the defensive mechanism for survival in the primeval forest. With this mechanism as reflected by the mismatch negativity (MMN), we can detect abnormal sounds coming from the dangerous events even when doing something else. MMN has attracted many researchers' attention for years, because it is considered to reflect the memory-based processing (Näätänen, 1992). MMN should be generated by the comparison process between sound deviation and neural trace of preceding sounds stored in auditory sensory memory. A large amount of previous studies provided evidence for the memory-based interpretation of MMN, “memory trace theory”. Our previous findings of MMN being elicited by sound omission also strongly supported this theory, because no afferent neurons could be activated by physical absence, “omission”. In addition, those studies provided new evidence for the other brain mechanism termed Temporal Window of Integration (TWI). The brain is considered to integrate the closely (<200 ms) presented sounds into single information units. MMN to occasional omission in repetitive tones were elicited only with SOAs shorter than 160 ms, suggesting a temporal correspondence between the duration of the neural sound-representations in sensory memory and the TWI of 160-170 ms. What was represented as the standard event was not single stimulus but rather a compound stimulus. Furthermore, sound trace is considered to be represented as time-functional information of the auditory scene. On the other hand, MMN provides a useful measure for clinical populations, because MMN generation does not require any tasks. MMN can be elicited by various types of sound deviations. Most interestingly, MMN to duration deviation is exceptionally sensitive to many clinical populations such as coma, Alzheimer disease, schizophrenia, and so on. Michie et al. (2000) reported that only duration-MMN was reliably reduced in patients with schizophrenia. Todd and Michie et al. (2007) also reported that a clear reduction in early schizophrenia was evident in MMN to duration but not frequency deviants. By the way, we have reported that the detection sensitivity nonlinearly declines over time within TWI of 160-170-ms in sensory memory. Recently, we found that the declined sensitivity of later part was remarkable in schizophrenia. In summary, the reduced duration-MMN which was reported by Michie and Todd et al. might be caused by the dysfunction of TWI. Conference: MMN 09 Fifth Conference on Mismatch Negativity (MMN) and its Clinical and Scientific Applications, Budapest, Hungary, 4 Apr - 7 Apr, 2009. Presentation Type: Oral Presentation Topic: Review Talk Citation: Yabe H (2009). Reduced duration MMN and impaired temporal integration window in clinical populations. Conference Abstract: MMN 09 Fifth Conference on Mismatch Negativity (MMN) and its Clinical and Scientific Applications. doi: 10.3389/conf.neuro.09.2009.05.005 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Mar 2009; Published Online: 19 Mar 2009. * Correspondence: Hirooki Yabe, Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan, Japan.hyabe@fmu.ac.jp Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Hirooki Yabe Google Hirooki Yabe Google Scholar Hirooki Yabe PubMed Hirooki Yabe Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

The promises of change-related brain potentials in cognitive neuroscience of music.

Even when simultaneously performing a task unrelated to sounds, the human auditory cortex can precisely model the invariances of the acoustic environment. Data acquired in a mismatch negativity (MMN) paradigm have shown that temporally and spectrally complex sounds as well as their relations are automatically represented in the human auditory cortex. Furthermore, MMN data indicate that these neural sound representations are spatially distinct from phonetic and musical sounds within and between the cerebral hemispheres. Most MMN studies were conducted in pitch dimension, but temporal aspects of sound processing are also under increasing experimentation. To some extent, musical expertise is also reflected in sound representation accuracy as indexed by the MMN paradigm.