Attention to sound

Visual selective attention is thought to facilitate performance both through enhancement and inhibition of sensory processing of goal-relevant and irrelevant (or distracting) information. While much insight has been gained over the past few decades into the neural mechanisms underlying facilitatory effects of attention, much less is known about inhibitory mechanisms in visual attention. In particular, it is still unclear as to whether target facilitation and distractor inhibition are simply different sides of the same coin or whether they are controlled by distinct neural mechanisms. Moreover, recent work indicates that suppression of visual distractors only emerges when information about the distractor can be derived directly from experience, consistent with a predictive coding model of expectation suppression. This also raises the question as to how visual attention and expectation interact to bias information processing. In this talk, Professor Slagter will discuss recent findings from several behavioural and EEG studies that examined how expectations about upcoming target or distractor locations and/or features influence facilitatory and inhibitory effects of attention on visual information processing and representation using ERPs, multivariate decoding analyses, and inverted encoding models. Collectively, these confirm an important role for alpha oscillatory activity in town-down biasing of visual attention to, and sharpening of representations of target locations. Yet, they also show that target facilitation and distractor suppression are differentially influenced by expectation, and rely at least in part on different neural mechanisms, with distractor suppression selectively occurring after stimulus presentation. This latter finding raises the question as to whether voluntary preparatory inhibition is possible at all.

In a crowded visual scene, attention must be efficiently and flexibly distributed over time and space to accommodate different task contexts. In this talk, Professor Luo would like to present several works in the lab investigating the temporal structure of visual attention. First, by using a time-resolved behavioral measurement, the group demonstrates that attentional behavioural performance contains temporal fluctuations (theta-band, alpha-band, etc), supporting that neuronal oscillatory profile might be directly revealed at behavioural level. These behavioural oscillations display a temporal alternating relationship between locations, suggesting that attention samples multiple items in a time-based rhythmic manner. Second, by employing EEG recordings in combination with a TRF approach, the group extracted object-specific neuronal impulse responses during multi-object selective attention. The results show that attention rhythmically switches among visual objects every ~200 ms, and the spatiotemporal sampling profile adaptively changes in various task contexts. Finally, by using MEG recordings in combination with a decoding approach, the group demonstrates that attention fluctuates between attended orientation features in a theta-band rhythm, suggesting that feature-based attention is mediated by rhythmic sampling similar to that for spatial attention. In summary, attention is not stationary but dynamically samples multiple visual objects in a periodic or serial-like way. This work advocates a generally central role of temporal organisation in attention by flexibly and efficiently organising resources in time dimension.

Load Theory of attention and cognitive control offers a hybrid model that combines capacity limits in perception with automaticity of processing. The model proposes that perception has limited capacity but proceeds automatically and involuntarily in parallel on all stimuli within capacity: relevant as well as irrelevant. Much evidence accumulated to support load theory in vision research so far. However the cross modal effects of perceptual load across the senses are less clear. In her talk, Professor Lavie will present recent work on the effects of visual perceptual load on auditory perception and the related neural activity as assessed with magnetoencephalography. The results showed that the level of unattended auditory perception and the related neural signal critically depends on the level of perceptual processing load in the visual attention task. Task conditions of high perceptual load that takes up all capacity with attended task processing, lead to reduced processing of unattended stimuli. In contrast in conditions of low perceptual load that leave spare capacity ignored task-irrelevant stimuli are nevertheless perceived, and elicit neural response. These findings demonstrate the value of understanding the role of attention in auditory processing within the framework of Load Theory.

Neuroimaging with fMRI shows that there are distinct networks biased towards the processing of visual and auditory information. These networks include inter-digitated areas in frontal cortex as well as corresponding primary and secondary sensory regions. In Professor Shinn-Cunningham's studies, she sees these distinct frontal regions consistently in individual subjects across multiple studies spanning years; however, the inter-digitated structural organization of the 'visual' and 'auditory' regions in frontal cortex is not clear using standard methods for co-registering and averaging fMRI results across subjects. Although the networks that include these inter-digitated frontal control regions are 'sensory biased', they are also recruited to process information in the other sensory modality as needed. Specifically, areas that are always engaged by auditory attention are recruited when visual tasks require processing of temporal structure, but not when the same visual inputs are accessed for tasks requiring processing of spatial information. Conversely, processing of auditory spatial information preferentially engages the visually biased brain network – a network that is traditionally associated with spatial visual attention. This visuo-spatial network includes retinotopically organised spatial maps in parietal cortex. Recent EEG results from Professor Shinn-Cunningham's lab confirm that auditory spatial attention makes use of the parietal maps in the 'visual spatial attention' network. Together, these results reveal that visual networks for attention are a shared resource used by the auditory system.

Auditory attention is a fascinating feat. For example, it is most astonishing how our brain 'does away' with considerable differences in sound pressure between a behaviourally relevant sound source and other interferences. Meanwhile, auditory attention has remained this elusive phenomenon: do we really understand enough just yet of auditory attention to build machines that attend, or machines that help us attend? Illustrated by behavioural, electrophysiological, and functional imaging data from his own lab and others, Professor Obleser will take stock of the evidence: are top-down selective-attention abilities indeed a stable, trait-like feature of the individual listener, with predictable decline in older adults? And, what are we really getting from our current go-to neural measures of auditory attention, speech tracking aka 'neural entrainment' versus alpha-power fluctuations? Luckily, Professor Obleser will probably be out of time as the talk reaches the main question: what are we measuring when we measure auditory attention?

A fundamental assumption in attention research is that, since processing resources are limited, the core function of attention is to manage these resources and allocate them among concurrent stimuli or tasks, according to current behavioural goals and environmental needs. However, despite decades of research, we still do not have a full characterisation of the nature these processing limitations, or ‘bottlenecks’ – ie what processes can be in performed in parallel and where the need for attentional selection kicks in. This question is particularly pertinent in the auditory system, which has been studied far less extensively than the visual system, and is proposed to have a wider capacity for parallel processing of incoming stimuli.

In this talk Dr Golumbic will discuss a series of experiments studying the depth of processing applied to task-irrelevant sounds and their neural encoding in auditory cortex. She will look at how this is affected by the acoustic properties, temporal structure, and linguistic structure of unattended sounds, as well as by overall acoustic load and task demands, in attempt to understand what levels suffer most from processing bottlenecks. In addition, she will discuss what we can learn about the capacity of parallel processing of auditory stimuli from pushing the system to its limits and requiring the division of attention among multiple concurrent inputs.

Auditory attention is a crucial component of real-life listening and is required, for instance, to enhance a particularly relevant aspect of a sound or to separate a sound of interest from noisy backgrounds. When listening to simple tones, attending to a certain frequency range induces a rapid and specific adaptation of neuronal tuning, which ultimately results in enhanced processing of that frequency range and suppression of the other frequencies. But which are the neural mechanisms enabling attentive selection and enhancement when listening to complex real-life sounds and scenes? At which levels of neural sound representation does attention operate? And how do these mechanisms depend on the specific behavioural requirements? High-resolution fMRI and computational modelling of sound representations both provide a relevant contribution to address these questions. Sub-millimetre fMRI enables distinguishing the activity and connectivity of neuronal populations across cortical layers non-invasively in humans (laminar fMRI). This is required for disentangling feedforward/feedback processing in primary and non-primary auditory areas and the communication between auditory and other areas (eg frontal areas). Modelling of sound representations allows formulating well-defined hypotheses on the nature of simple and complex features processed in the network of auditory areas and how the neural sensitivity for these features is affected by attention and behavioural task demands. The combination of laminar fMRI and sound representation models is thus ideally positioned to unravel the neural circuitry and the computational architecture of auditory attention in naturalistic listening scenarios.

Professor Johnsrude and colleagues have previously demonstrated that, whereas the pattern of brain (fMRI) activity elicited by clearly spoken sentences does not seem to depend on attention, patterns are markedly different when attending or not to highly intelligible but degraded (6-band noise vocoded) sentences (Wild et al, J Neurosci, 2012). They have replicated and extended this work to sentences that, although slightly degraded (12-band noise vocoded), can be reported word-for-word with 100% accuracy. Even for these very intelligible materials, a marked dissociatation was observed in patterns of brain activity when people attended to these compared to when they were performing a multiple object tracking task. Furthermore, in both of these experiments, memory for degraded items was enhanced by attention, whereas memory for clear sentences was not, suggesting that even perfectly intelligible but degraded sentences are processed in a qualitatively different, attentionally gated, way, compared to clear sentences. Supported by a Canadian Institutes of Health Research operating grant (MOP 133450) and Canadian Natural Sciences and Engineering Research Council Discovery grant (3274292012).