Received: 28 July 2021 Revised: 24 April 2022 Accepted: 29 April 2022

DOI: 10.1002/wcs.1610

PERSPECTIVE

Defining attention from an auditory perspective

Abigail L. Noyce | Jasmine A. C. Kwasa | Barbara G. Shinn-Cunningham

Neuroscience Institute, Carnegie Mellon

University, Pittsburgh, Pennsylvania, USA
Abstract
Attention prioritizes certain information at the expense of other information
Correspondence
in ways that are similar across vision, audition, and other sensory modalities.
Barbara G. Shinn-Cunningham,
Neuroscience Institute, Carnegie Mellon It influences how—and even what—information is represented and processed,
University, Pittsburgh, PA, USA. affecting brain activity at every level. Much of the core research into cognitive
Email: bgsc@andrew.cmu.edu
and neural mechanisms of attention has used visual tasks. However, the same
Funding information top-down, object-based, and bottom-up attentional processes shape auditory
National Institute of Neurological perception, largely through the same underlying, cognitive networks.
Disorders and Stroke, Grant/Award
Number: NINDS F99 NS115331; National This article is categorized under:
Institute on Deafness and Other
Psychology > Attention
Communication Disorders, Grant/Award
Number: R01 DC013825; Office of Naval
KEYWORDS
Research, Grant/Award Number:
N00014-20-1-2709 auditory attention, cortical attention networks, endogenous attention, exogenous attention

Edited by: Anna Fisher, Editor

1 | INTRODUCTION

Attention is a set of processes that modulate what information gets represented in the brain. These processes act
similarly—and are even shared—across auditory and other sensory modalities.
In 1953, Colin Cherry ignited research on the cocktail party problem, describing how attention alters perception in a
crowded setting with multiple sound sources (Cherry, 1953). However, by the 1990s, many hearing researchers, driven
to optimize information preserved in telephone communication and to understand the impact of hearing loss, had
turned to developing quantitative, bottom-up models that assumed an ideal observer (Egan, 1971; Fletcher &
Galt, 1950; Henning, 1967; Siebert, 1970). This approach specifically ignores any role of central cognitive processes like
memory and attention. Ideal observer models account well for performance on simple psychoacoustic tasks, but not for
how we cope with the cacophony of sounds in daily life.
Because vision scientists dominated attention studies in the ensuing decade (Corbetta & Shulman, 2002; Hopfinger
et al., 2000; Posner & Petersen, 1990; Treisman, 2006; Yantis, 2008), many discussions of attention and its underlying
brain mechanisms focused on results, paradigms, and stimuli from visual research. For instance, many visual para-
digms present a static scene of competing objects that, to make tasks demanding, is flashed on only briefly. Auditory
information, however, is intrinsically temporal: information is primarily conveyed by changes in time-varying acoustic
signals, such as amplitude and frequency modulation. There is no meaning in a “snapshot” of auditory stimuli. The
dominance of visual studies led to an emphasis on how visual features such as spatial adjacency influence the deploy-
ment of attention. Conversely, there was little work examining how attention operates through time to track dynamic

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https://doi.org/10.1002/wcs.1610
2 of 11 NOYCE ET AL.

objects, an issue critical to how attention works to track an auditory source that extends through time (known as a
“stream”). Here, as auditory researchers, we argue that most attention effects identified by visual studies operate analo-
gously in auditory attention; in addition, however, there are key temporal phenomena critical to how attention governs
auditory attention that likely impact visual attention as well.
Another key issue is that attentional abilities differ across individuals. For instance, people with sensorineural hear-
ing deficits or who use cochlear implants often have trouble focusing auditory attention (Dai et al., 2018; Shinn-
Cunningham & Best, 2008). Certain neurological disorders can compromise top-down cognitive control important for
focusing attention, including those with post-traumatic stress disorder (Bressler et al., 2017; Leskin & White, 2007;
Vasterling et al., 1998), autism spectrum disorder (Schwartz et al., 2020), schizophrenia (Mathalon et al., 2004), and
attention deficit and hyperactivity disorder (Hasler et al., 2016). Understanding the mechanisms of attention, including
how attention operates through time, are thus important for developing treatments and interventions to help individ-
uals who have trouble deploying attention, whether in vision or audition.

2 | D E S C R I B I N G A T T EN T I O N

Attention prioritizes certain information at the expense of other information. It determines whether we notice the broc-
coli on our plate or the serving dish it came from, and whether we register the gravel under our feet as we walk in the
park. Attention depends not only on how well we focus volitionally (top-down attention), but also on automatic
responses to salient events (bottom-up attention). It can be used to prepare for an event, to follow an information source
over time, and to reorient after a distraction.
Attention allows us to cope with the fact that human cognition is capacity limited. We cannot fully process the bar-
rage of information reaching us; instead, our brains favor processing information that is “important.” In top-down
attention, the observer consciously decides what to process based on their goals, while in bottom-up attention, the brain
blithely ignores predictable, expected information while automatically prioritizing new and unexpected events (e.g., a
crash of thunder or flash of lightning). The schematic in Figure 1 shows examples of top-down, object-based, and
bottom-up attention in an auditory scene with several sources.
Mechanisms of attention are distributed across every stage of cognitive processing. Throughout the cortex,
feedforward and feedback connections increase the representation of attended stimuli and decrease the representation
of ignored stimuli (Yantis, 2008). Attention can be directed either externally, to sensory input, or internally, to a mem-
ory representation (Panichello & Buschman, 2021), and even modify what gets encoded into memory (Payne
et al., 2013; Payne & Sekuler, 2014).

3 | TOP-DOWN ATTENTION

Top-down attention allows us to consciously focus on upcoming events, select a specific feature in a scene, or search for
a target amongst distractors. It is top-down attention that, in a setting with competing for sensory inputs, allows us to
deliberately bias what is enhanced and what is suppressed. For instance, Figure 1a illustrates the process of a listener
preparing to attend to a source from a known (desired) location; once that stream begins, attention selects that stream
by focusing an “attentional spotlight.”
When people successfully focus attention on a target, the neural responses to that target are magnified, and those to
competing distractors are suppressed (Clark & Hillyard, 1996; Foster et al., 2020; Woldorff et al., 1993). For example,
when subjects are instructed to listen to one source amongst overlapping sounds, attention enhances the event-related
potential (ERP) evoked by the onsets of events in the attended source and reduces ERPs to events in the other sources
(Choi et al., 2014; Hillyard et al., 1973).
Figure 2a shows a typical paradigm for studying top-down attention in audition. A listener is cued to attend to one
spatial location. Then, three melodies of complex tones are presented from the listener's left, center, and right.
Figure 2b shows grand average ERPs recorded during such a task. Onset times of tones in the left and right melodies
are shown by the blue and red vertical lines, respectively. The traces show the average voltage over the course of a trial.
The negative peaks approximately 0.15 s after each tone's onset reflect sensory processing. When subjects attend to the
left melody (blue traces), the peaks elicited by the left tones (blue circles) are larger than when subjects attend to the
right stream (red traces); the converse is true for peaks elicited by the right (red) stream. Many studies with similar
NOYCE ET AL. 3 of 11

Attention spotlight in Sound sources

azimuth/feature space over time

Non-spatial features
Spa res (a) (b) (c) (d)
fea
tu
tial

Time

F I G U R E 1 Auditory stimuli can be considered in a multidimensional space, with axes including time, spatial features (such as
interaural differences and spectral location cues), and nonspatial features, such as pitch and timbre, here collapsed into a single dimension
for visualization. This figure shows examples of how attention might behave in an auditory scene with several sources, depicted as acoustic
waveforms. (a) A prestimulus cue, such as “Listen to the left stream”, can orient a listener to engage top-down attention (visualized as the
highlighted area on the plots) towards an upcoming stream with the desired spatial features. Once that stream (illustrated in red) is selected,
attention focuses down to also emphasize other, nonspatial features of that stream. (b) Object-based attention allows the listener to follow
the object across momentary silent gaps. (c) When two sound sources (illustrated in red and yellow) are near each other in feature space,
they can be confused: Attention may begin tracking the distractor instead of the target, especially at moments of ambiguity, such as an
instantaneous silence in the target. (d) The sudden appearance of a new stream (illustrated in purple) can capture attention involuntarily
(via bottom-up processes), regardless of its similarity to the previous attentional target.

(a) (b) Left onsets Right onsets

“Listen Left”
Evoked potential (μV)

−3

−6 “Listen Right”

F I G U R E 2 (a) Schematic of a typical top-down auditory attention task. A subject is cued to attend to one of three spatially separated
streams of sound and report its contents. (b) ERP traces (electrode Cz) while subjects attend to either a left-spatialized melody (onset times
shown by blue vertical lines) or a right-spatialized melody (red lines). The auditory cue telling subjects to listen to either the left or right
stream occurs at the time denoted by the vertical black line. When subjects attend to the left stream (blue traces), negative-going ERPs
elicited by notes in the left melody are enhanced (blue circles) and those elicited by notes from the right are suppressed, and vice versa. Data
from Choi et al. (2014)

results demonstrate that attention modulates neural responses, explicitly altering information's representation in the
brain. Note that the very first tone onset elicits equally strong responses regardless of the task instructions, an example
of bottom-up attentional capture (see below).
In vision studies, researchers distinguish between focusing attention to a particular location (e.g., 15 degrees left of
fixation) versus to some nonspatial attribute (e.g., a red object). In part, this reflects the fact that visual inputs at the
4 of 11 NOYCE ET AL.

retina are encoded according to where objects are relative to an observer's eyes (an organization that is topographically
preserved throughout the visual system), while other features must be centrally computed. In contrast, the auditory sys-
tem is not organized by spatial location. Sound location is itself a feature that must be computed from the signals
reaching the two ears. Still, listeners can focus attention to sounds based on either location or other features, such as
pitch, timbre, or talker identity. And, as we discuss below, even though both spatial and nonspatial acoustic features
must be centrally computed, spatial auditory attention recruits different brain networks than does nonspatial auditory
attention, paralleling functional differences between spatial and feature-based attention in vision.
Most headphone-based studies of auditory spatial attention use simplified spatialization cues (such as a pure time
delay between the signals at the two ears), ignoring the frequency-dependent differences in the levels and timing of the
signals that would reach the left and right ears in the real world. Many even use dichotic presentations, in which
entirely separate streams of information are presented to each ear (Hashimoto et al., 2000; Jäncke et al., 2003;
Kimura, 1967; Treisman, 1960). Listeners can successfully direct spatial attention even with such unnatural, degraded
spatialization (Baumgartner et al., 2017; Ross et al., 2010). Some dichotic studies find that people can follow the stream
in the right ear better than the left-ear stream, an effect that has been ascribed to left-lateralized language specialization
in the brain (Hiscock & Kinsbourne, 2011; Kimura, 1961). However, recent work suggests that the right-ear bias may
instead arise from increased powers of attention to the right hemifield (Payne et al., 2017; Tanaka et al., 2021). In addi-
tion, it is not clear whether such asymmetries arise with natural binaural spatial cues; at least one study has shown that
unrealistic spatial simulations do not fully engage the brain networks devoted to spatial auditory attention (Deng, Choi,
et al., 2019).

4 | OBJECT-BASED ATTENTION

When a person focuses on an object because it has a desired feature (such as location, pitch, etc.), top-down attention
tends to focus on the entire object. In other words, the natural unit of attention seems to be an object: a collection of
features that the brain believes came from the same external source (Duncan, 1984; Shinn-Cunningham, 2008).
Figure 1a illustrates this idea: attention focuses initially on one location; however, once a stream at that location
becomes the focus of attention, attentional focus narrows onto the nonspatial features of the attended source.
Relatedly, auditory objects extend across time, often even across silences. For instance, speech includes momentary
gaps, yet is perceived as one perceptual stream. Once we attend an element of a stream (e.g., a syllable in ongoing
speech), that stream tends to remain the focus of attention over time, automatically (Best et al., 2008, 2010; Billig &
Carlyon, 2016; Bressler et al., 2014; Woods & McDermott, 2015), and attention becomes more tightly focused to that
stream (Choi et al., 2014; Golumbic et al., 2013). Figure 1b illustrates this idea: attention remains focused to pick up the
next syllable from the ongoing stream even after a momentary gap.
When two streams are similar in spatial and other features, they can be confused across time. Figure 1c illustrates
this: a competing stream that is similar to the attended stream in high-dimensional feature space can be confused with
the attended stream, especially after a momentary silence in the attended stream. When a listener is asked to focus
attention on the speech from one location (e.g., “always report the words spoken from the left”) and the left talker sud-
denly switches locations with a competing talker, subjects often track the original talker rather than the original loca-
tion (Mehraei et al., 2018). That is, successful attention relies on object formation and segregation through time, and
object-based attention can even override volitional attention.
This critical role of attention as a mechanism for following an object through time is most evident in the auditory
system, where the temporal dynamics of scenes and stimuli cannot be ignored. However, this also affects vision and
other senses. One of the most challenging visual attention paradigms—multiple object tracking—requires subjects to
use attention to track moving objects among identical distractors (Alvarez & Cavanagh, 2004; Pylyshyn & Storm, 1988).
Similarly, everyday interactions with our surroundings require us to attend to objects over time: to catch a ball, to judge
whether it is safe to cross a street, or to fill a water glass without it overflowing.

5 | BOTTOM-UP ATTENTION

Attention can also be drawn by unusual or salient sensory inputs. For example, a plate smashing on the floor involun-
tarily captures attention. Automatic attentional capture occurs even for less dramatic events, such as the onset of a tone
NOYCE ET AL. 5 of 11

or appearance of an image, disrupting top-down and object-based attention (Bulger et al., 2020; Maryott et al., 2011;
Noyce & Sekuler, 2014a). Figure 1d shows an example of a new sound source's onset grabbing attention involuntarily,
away from the previously attended object.
In the audition, involuntary attentional capture interferes with top-down auditory attention regardless of the spatial
location of the interrupting event. Figure 3 illustrates this effect when a listener is attending a stream comprising three
speech syllables from one direction and ignoring a similar, competing stream from the opposite hemifield (taken from
Liang et al., 2022). Top-down attention allows the listener to select one stream, and object-based attention lets them fol-
low it over time. But when an unexpected sound (a cat “MEOW”) occurs just before the second target syllable, it cap-
tures attention, disrupting the ongoing processing and requiring the listener to reorient back to the intended target.
This interference is equally strong whether the MEOW comes from the same hemifield as the target or the opposite
hemifield.
Another interesting point demonstrated in Figure 3 is that salient interruptions interfere not only with attention per
se, but also with storing attended information in memory. In particular, the interrupting MEOW harms performance
on the first target syllable, which finishes playing before the MEOW even begins (Liang et al., 2022). Indeed, roughly
two-third of the 45 subjects tested in this study showed a significant decrease in their ability to recall the first syllable
due to the interrupting MEOW. Thus, attentional capture not only interferes with ongoing attention to a stream, but
with the memory encoding and storage of items that already occurred (see also Section 7).
Attention can also be disrupted, requiring subsequent reorienting, when the attended stream contains task-
irrelevant discontinuities. For instance, when subjects are instructed to attend to a source at a particular location,
changes in pitch impair performance; when subjects are attending to sources with a particular pitch, changes in location
impair performance (Maddox & Shinn-Cunningham, 2012). In both cases, the degree of disruption increases with the
magnitude of the task-irrelevant discontinuity. In some cases, this may be due to attention following a perceived object
in opposition to the task instructions (Mehraei et al., 2018), but disruptions of attention from stimulus discontinuity
can happen even if there is no competition for attention from other sources. For instance, if a listener is attending to

Syllable identification accuracy by serial position and interrupter location

No interrupter 100%

75%
Contralateral interrupter

50%

Ipsilateral interrupter

33% chance accuracy

25%
1st syllable 2nd syllable 3rd syllable

F I G U R E 3 (Left) Schematic of the spatial locations of two competing speech streams from the same talker, and, when present, an
interrupting cat “MEOW.” Subjects direct top-down spatial attention to follow either the left or right speech stream. The interrupting
MEOW, which happens randomly on one-fourth of trials, appears randomly from either the same or opposite hemifield as the target stream.
(Right) Syllable identification accuracy. The MEOW significantly affects the recall of not only the second and third, but also the first syllable.
Critically, contralateral and ipsilateral interrupters are equally disruptive
6 of 11 NOYCE ET AL.

an isolated stream of speech, but the talker suddenly changes, attention to the stream is disrupted and must be
re-established (Lim et al., 2019; Mullennix & Pisoni, 1990; Nusbaum & Morin, 1992). Both electroencephalography
(EEG) and pupillometry show strong responses to task-irrelevant stimulus discontinuities, supporting the idea that such
discontinuities trigger bottom-up attention that requires re-orienting within the scene (Lim et al., 2021; Mehraei
et al., 2018).

6 | B R A I N NE T W O R K S C O N T R O L L I N G A T T E N T I O N

The most common framework for understanding the brain regions that participate in attention posits two anti-
correlated networks, one for top-down attentional control, and one for bottom-up attentional capture (Corbetta &
Shulman, 2002; Fox et al., 2005; Power et al., 2011; Yeo et al., 2011). However, evidence for these two networks comes
primarily from visual attention studies, in part due to the challenges of auditory studies in fMRI (Peelle, 2014). (See Lee
et al., 2014 for a review of auditory exceptions.)
We find that there are at least two similar, but differently specialized networks recruited for top-down attention
(Figure 4). One, the well-established frontoparietal network, is specialized for visual and spatial attention. However, a
second auditory-biased attention network includes distinct regions in lateral frontal cortex that interleave anatomically
with the frontoparietal network (Braga et al., 2013; Michalka et al., 2015; Noyce et al., 2017; Tobyne et al., 2018). These
complementary networks extend broadly throughout frontal cortex (Noyce et al., 2021; Tobyne et al., 2017).
The complementary affinities of vision for spatial information and audition for timing information play out in how
tasks recruit sensory-biased cortical networks. A rhythm memory task with purely visual stimuli recruits not only the
visual-biased frontal network, but also the auditory-biased network (Michalka et al., 2015). A spatial memory task with
purely auditory stimuli recruits the auditory-biased network, as well as visual-biased regions of both lateral frontal cor-
tex (Michalka et al., 2015) and anterior parietal cortex (Michalka et al., 2016). Magnetoencephalography (MEG) and
EEG reveal further evidence of parietal recruitment for spatial—but not nonspatial—auditory attention (Lee
et al., 2012). Contralateral alpha-band (8–14 Hz) oscillations over parietal cortex, long associated with visual–spatial
attention (Klimesch et al., 1999; Worden et al., 2000), also occur during auditory spatial attention, even tracking syllabic
events over time (Bonacci et al., 2019, 2020; Deng et al., 2020; Wöstmann et al., 2021). Contralateral transcranial alter-
nating current stimulation (tACS) in the alpha frequency disrupts spatial but not nonspatial auditory attention (Deng,
Reinhart, et al., 2019; Wöstmann et al., 2018).
Regardless of whether spatial or nonspatial attention guides auditory selective attention, the net result is similar:
information about the attended objects is represented more robustly in the brain. This is seen as a relative enhancement
of ERPs elicited by attended objects compared to those elicited by unattended objects (as illustrated in Figure 2),
stronger neural entrainment to the envelope of an attended vs. an unattended stream (Golumbic et al., 2013;

F I G U R E 4 Maps of bilateral visual-biased and auditory-biased regions in frontal cortex. Three visual-biased regions and five auditory-
biased regions control attention and working memory tasks. Adapted from Noyce et al. (2021)
NOYCE ET AL. 7 of 11

F I G U R E 5 Memory performance (d0 ) for short sequences, when cued to track either the locations (left) or timing (right, orange) of
events in a sequence. Subjects are better at encoding locations from a visual than an auditory sequence, but better at encoding timing in an
auditory than visual sequence. Adapted from Noyce et al. (2016)

Mesgarani & Chang, 2012), and increased success in decoding neural activity to reconstruct an attended versus an
unattended stimulus (Bednar & Lalor, 2020; Mesgarani & Chang, 2012).
Bottom-up attention has been ascribed to a ventral attention network, which includes nodes in cingulate,
temporoparietal, and opercular cortex, but this work has almost entirely been done in visual paradigms (Corbetta &
Shulman, 2002; Devaney et al., 2019; Dosenbach et al., 2007; Seeley et al., 2007). While few studies have investigated
brain networks controlling attentional reorienting to unexpected auditory events, at least one MEG study hints that the
“visual” ventral network is multisensory: auditory attention switching engages a region within this canonical bottom-
up attention network (Larson & Lee, 2013).

7 | ATTENTION AND MEMORY

Attention, especially top-down attention, and working memory (the ability to hold and manipulate information) are
intricately linked (Bettencourt et al., 2011; Panichello & Buschman, 2021). Working memory requires attention to be
directed to an internal representation that is maintained after sensory inputs are gone (Lim et al., 2015), and if attention
is disrupted the memory representation degrades (Payne et al., 2013; Unsworth & Robison, 2016). Attentional limits
likely restrict working memory capacity.
Attention also affects how objects are encoded into memory. Attended objects tend to be remembered (Maryott
et al., 2011; Noyce & Sekuler, 2014b); relatedly, events that disrupt attention also impair recall of events surrounding
the disruption (Lim et al., 2019). Even when an object is attended, not all of its features will get into memory: attended
features are encoded more robustly (e.g., Noyce et al., 2016).
Figure 5 shows discrimination performance when subjects are asked to attend to either the locations or time inter-
vals of a short sequence, which is composed of either visual or auditory events; they then must compare their stored
representation of the sequence to a subsequent, similar sequence of events in the other sensory modality. Performance
shows a significant interaction between sensory modality and the feature to be recalled. As we discussed above, atten-
tion co-opts the specialized neural circuitry for visual cognition when performing spatial tasks, and for auditory cogni-
tion when performing temporal tasks (Michalka et al., 2015, 2016). Consistent with this, it is easier to attend to and
stores spatial information from visual inputs, and easier to attend to and store timing information from auditory signals
(Noyce et al., 2016), as supported by better performance in conditions relying on these “natural” memory
representations.

8 | C ON C L U S I ON

Attention performs essential pre-processing for the rest of human cognition. It is a tug of war between our desires and
our distractions, in a finely tuned and complex interplay between top-down, bottom-up, and object-based attention.
8 of 11 NOYCE ET AL.

This allows us to select, to focus, to remember… while not getting eaten by a bear or hit by a taxi. After attention filters
important information from the barrage of neural events, the brain can analyze those important events in detail, letting
us understand speech, appreciate a sunset, or merely cross a busy intersection unscathed.

A U T H O R C ON T R I B U T I O NS
Abigail Noyce: Conceptualization (equal); investigation (equal); supervision (supporting); visualization (equal); writ-
ing – original draft (lead); writing – review and editing (equal). Jasmine Kwasa: Conceptualization (supporting);
investigation (equal); visualization (equal); writing – review and editing (supporting). Barbara Shinn-Cunningham:
Conceptualization (supporting); funding acquisition (lead); investigation (equal); project administration (lead); supervi-
sion (lead); visualization (equal); writing – original draft (supporting); writing – review and editing (lead).

FUNDING INFORMATION
This work was supported by NIDCD R01 DC013825 (to Barbara G. Shinn-Cunningham), ONR project
N00014-20-1-2709 (to Barbara G. Shinn-Cunningham), and NINDS F99 NS115331 (to Jasmine A. C. Kwasa).

CONFLICT OF INTEREST
The authors have declared no conflicts of interest for this article.

DATA AVAILABILITY STATEMENT

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

ORCID
Abigail L. Noyce https://orcid.org/0000-0002-4339-4113
Jasmine A. C. Kwasa https://orcid.org/0000-0001-5537-6054
Barbara G. Shinn-Cunningham https://orcid.org/0000-0002-5096-5914

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How to cite this article: Noyce, A. L., Kwasa, J. A. C., & Shinn-Cunningham, B. G. (2022). Defining attention
from an auditory perspective. WIREs Cognitive Science, e1610. https://doi.org/10.1002/wcs.1610