Focal Suppression of Distractor Sounds by Selective Attention in Auditory Cortex

Schwartz, Zachary; David, Stephen V.

doi:10.1093/cercor/bhx288

Cited by 41 publications

(50 citation statements)

References 81 publications

(156 reference statements)

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“…An absence of similar changes in anaesthetized rats is consistent with anaesthesia-related partial blockade of top-down influences, as previously suggested by an absence of perceptual learning and cortical disconnectivity with anaesthesia (Aberg et al 2009;Jordan et al 2013;Mashour, 2014). These findings are in agreement with recent work showing context and experience-based predictions in humans and animals (Ostroff et al 2003;Fakhri et al 2012;Leung et al 2013;Skoe et al 2014;Sohoglu & Chait, 2016;Parras et al 2017;Schwartz & David, 2018). Furthermore, repetition-induced increases in speech understanding, as well as improvements in the visual recognition of degraded objects with repetition, provide evidence in support of our interpretation of an increased response to degraded predictable stimuli (Rivenez et al 2006;Muller et al 2013;Helfer et al 2018).…”

Section: Effects Of Ageing On Central Auditory System and Top-down Prsupporting

confidence: 91%

Top‐down or bottom up: decreased stimulus salience increases responses to predictable stimuli of auditory thalamic neurons

Kommajosyula

Cai

Bartlett

et al. 2019

The Journal of Physiology

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Key pointsr Temporal imprecision leads to deficits in the comprehension of signals in cluttered acoustic environments, and the elderly are shown to use cognitive resources to disambiguate these signals.r To mimic ageing in young rats, we delivered sound signals that are temporally degraded, which led to temporally imprecise neural codes.r Instead of adaptation to repeated stimuli, with degraded signals, there was a relative increase in firing rates, similar to that seen in aged rats.r We interpret this increase with repetition as a repair mechanism for strengthening the internal representations of degraded signals by the higher-order structures.Abstract To better understand speech in challenging environments, older adults increasingly use top-down cognitive and contextual resources. The medial geniculate body (MGB) integrates ascending inputs with descending predictions to dynamically gate auditory representations based on salience and context. A previous MGB single-unit study found an increased preference for predictable sinusoidal amplitude modulated (SAM) stimuli in aged rats relative to young rats. The results suggested that the age-degraded/jittered up-stream acoustic code may engender an increased preference for predictable/repeating acoustic signals, possibly reflecting increased use of top-down resources. In the present study, we recorded from units in young-adult MGB, comparing responses to standard SAM with those evoked by less salient SAM (degraded) stimuli. We hypothesized that degrading the SAM stimulus would simulate the degraded ascending acoustic code seen in the elderly, increasing the preference for predictable stimuli. Single units were recorded from clusters of advanceable tetrodes implanted above the MGB of young-adult awake rats. Less salient SAM significantly increased the preference for predictable stimuli, especially at Srinivasa P. Kommajosyula is a postdoctoral fellow at Southern Illinois University School of Medicine (SIU SOM) under the mentorship of Donald Caspary. His doctoral thesis on sudden death in epilepsy in audiogenic seizure models spurred his curiosity into maladaptive plasticity in networks witnessed in this model and central auditory system. His research interests include understanding the pathophysiological and compensatory changes in central auditory system with ageing and noise induced trauma. The present study highlights evidence of such changes in auditory thalamic coding of less salient stimuli that switch the preference of single unit to repeated stimuli. Rui Cai is a Research Instructor at SIU SOM. She obtained her PhD in East China Normal University where she studied the environmental effects on the plasticity of auditory function. She continues her work in auditory system in SIU, with an emphasis on the mechanisms of age-related hearing loss and tinnitus. * These authors contributed equally to this work. S. P. Kommajosyula and others J Physiol 597.10 higher modulation frequencies. Rather than adaptation, higher modulation frequencies elicited increased numbers of...

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Section: Effects Of Ageing On Central Auditory System and Top-down Prsupporting

confidence: 91%

Top‐down or bottom up: decreased stimulus salience increases responses to predictable stimuli of auditory thalamic neurons

Kommajosyula

Cai

Bartlett

et al. 2019

The Journal of Physiology

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“…Recent work suggests that mice are able to attend to explicitly cued visual 290 patterns (Wang and Krauzlis, 2018) or auditory streams (Chapuis and 291 Chadderton, 2018), indicating that mice may not lack a mechanism for top-down 292 attentional control. Both humans and carnivores (Schwartz and David, 2018) can 293 be cued implicitly using target probability -providing further evidence that the 294 effect of stimulus probability on perception may be due to sensory ecology rather 295 than taxonomy. While both primates and carnivores might use their auditory 296 senses to tune in and follow potential prey or conspecific communication signals, 297 tracking of the statistics in mice -a prey species -may predominantly serve to 298 detect sudden, potentially dangerous changes in the environment.…”

Section: Sensory Ecology 283mentioning

confidence: 98%

“…A possible explanation for 124 mice not taking advantage of tracking probabilities is that they are not able to focus 125 on a single frequency band in a continuous noise background with very sparse 126 tones appearing at random times. We reasoned that a more natural situation could 127 be the presence of multiple streams of tones that allow to attach selective attention 128 to one of these streams (Lakatos et al, 2013;Schwartz and David, 2018). We 129 therefore designed an experiment in which the animals had to detect a frequency 130 change in either one of two continuous streams of tone pips (Fig.…”

Section: Experiments 2: Frequency Change Detection In Streams 122mentioning

confidence: 99%

Mice tune out not in: Violation of prediction drives auditory saliency

Rogalla¹,

Rauser²,

Schulze³

et al. 2019

Preprint

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1Successful navigation in complex acoustic scenes requires focusing on relevant 2 sounds while ignoring irrelevant distractors. It has been argued that the ability to 3 track stimulus statistics and generate predictions supports the choice what to 4 attend and what to ignore. However, the role of these predictions about future 5 auditory events in drafting decisions remains elusive. While most psychophysical 6 studies in humans indicate that expected stimuli serve as implicit cues attracting 7 attention, most work studying physiological auditory processing in animals 8 highlights the detection of unexpected, surprising stimuli. Here, we tested whether 9 in the mouse, target probability is used as an implicit cue attracting attention or 10 whether detection is biased towards low-probability deviants using an auditory 11 detection task. We implemented a probabilistic choice model to investigate 12 whether a possible dependence on stimulus statistics arises from short term serial 13 correlations or from integration over longer periods. Our results demonstrate that 14 adapt their behavior according to the stimulus statistics (Bargones and Werner, 39 1994a; Gordon Z. Greenberg and Larkin, 1968). This form of selective auditory 40 attention does not require awareness of the subject and is driven by unconscious 41 expectations (Wolmetz and Elhilali, 2016). Within this framework, the 42 improvement of detectability is based on the expectation as an implicit cue and 43 serves as an internal reward-maximizing strategy that drives the attention towards 44 the expectation (Girshick et al., 2011). 45 While most psychophysical studies indicate that expected stimuli serve as implicit 46 cues attracting attention, most work studying the physiology of auditory 47 processing highlights the detection of unexpected, surprising stimuli. Stimuli are 48 more salient when presented rarely to the auditory system and thus might be 49 easier to detect due to pre-attentive mechanisms (Malmierca et al., 2015; Pérez-50 González et al., 2005; Tiitinen et al., 1994). Within this framework, the evaluation 51 of stimulus statistics serves to detect novelty, emphasizing changes in the auditory 52 scene rather than enabling tracking of task relevant information. 53 Thus, tracking of stimulus probability influences auditory processing in two 54 contrary ways: on the physiological level, low-probability sounds elicit maximal 55 responses, but during listening tasks, relevant high-probability sounds appear to 56 attract attention, improving their detectability. While physiological evidence for 57 deviant detection spans all the way from animal models to humans (Heilbron and 58 Chait, 2017; Khouri and Nelken, 2015), behavioral assessment of the effects of 59 target probability is largely restricted to humans. In order to understand the neural 60 mechanisms underlying predictive coding, animal models such as rodents in 61 which both physiology and behavior can be studied are needed. 62 Although rodents serve as widely used animal models to study audi...

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“…active conditions and between attend-toward vs. attend-away conditions (Niwa et al, 2012b;Schwartz and David, 2017;von Trapp et al, 2016).…”

Section: Average A1 Neurons' Feature Sensitivity Is Constant Across Amentioning

confidence: 99%

An emergent population code in primary auditory cortex supports selective attention to spectral and temporal sound features

Downer¹,

Verhein

Rapone³

et al. 2020

Preprint

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Textbook descriptions of primary sensory cortex (PSC) revolve around single neurons' representation of low-dimensional sensory features, such as visual object orientation in V1, location of somatic touch in S1, and sound frequency in A1. Typically, studies of PSC measure neurons' responses along few (1 or 2) stimulus and/or behavioral dimensions. However, real-world stimuli usually vary along many feature dimensions and behavioral demands change constantly. In order to illuminate how A1 supports flexible perception in rich acoustic environments, we recorded from A1 neurons while rhesus macaques performed a feature-selective attention task. We presented sounds that varied along spectral and temporal feature dimensions (carrier bandwidth and temporal envelope, respectively). Within a block, subjects attended to one feature of the sound in a selective change detection task. We find that single neurons tend to be highdimensional, in that they exhibit substantial mixed selectivity for both sound features, as well as task context. Contrary to common findings in many previous experiments, attention does not enhance the single-neuron representation of attended features in our data. However, a population-level analysis reveals that ensembles of neurons exhibit enhanced encoding of attended sound features, and this population code tracks subjects' performance. Importantly, surrogate neural populations with intact singleneuron tuning but shuffled higher-order correlations among neurons failed to yield attention-related effects observed in the intact data. These results suggest that an emergent population code not measurable at the single-neuron level might constitute the functional unit of sensory representation in PSC. SIGNIFICANCE STATEMENTThe ability to adapt to a dynamic sensory environment promotes a range of important natural behaviors. We recorded from single neurons in monkey primary auditory cortex while subjects attended to either the spectral or temporal features of complex sounds.Surprisingly, we find no average increase in responsiveness to, or encoding of, the attended feature across single neurons. However, when we pool the activity of the sampled neurons via targeted dimensionality reduction, we find enhanced populationlevel representation of the attended feature and suppression of the distractor feature.This dissociation of the effects of attention at the level of single neurons vs. the population highlights the synergistic nature of cortical sound encoding and enriches our understanding of sensory cortical function.

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Focal Suppression of Distractor Sounds by Selective Attention in Auditory Cortex

Cited by 41 publications

References 81 publications

Top‐down or bottom up: decreased stimulus salience increases responses to predictable stimuli of auditory thalamic neurons

Top‐down or bottom up: decreased stimulus salience increases responses to predictable stimuli of auditory thalamic neurons

Mice tune out not in: Violation of prediction drives auditory saliency

An emergent population code in primary auditory cortex supports selective attention to spectral and temporal sound features

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