N Barascud

Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns

Significance We reveal the temporal dynamics and underlying neural sources of the process by which the brain discovers complex temporal patterns in rapidly unfolding sound sequences. We demonstrate that the auditory system, supported by a network of auditory cortical, hippocampal, and frontal sources, continually scans the environment, efficiently represents complex stimulus statistics, and rapidly (close to the bounds implied by an ideal observer model) responds to emergence of regular patterns, even when these are not behaviorally relevant. Neuronal activity correlated with the predictability of ongoing auditory input, both in terms of deterministic structure and the entropy of random sequences, providing clear neurophysiological evidence of the brains capacity to automatically encode high-order statistics in sensory input. We use behavioral methods, magnetoencephalography, and functional MRI to investigate how human listeners discover temporal patterns and statistical regularities in complex sound sequences. Sensitivity to patterns is fundamental to sensory processing, in particular in the auditory system, because most auditory signals only have meaning as successions over time. Previous evidence suggests that the brain is tuned to the statistics of sensory stimulation. However, the process through which this arises has been elusive. We demonstrate that listeners are remarkably sensitive to the emergence of complex patterns within rapidly evolving sound sequences, performing on par with an ideal observer model. Brain responses reveal online processes of evidence accumulation—dynamic changes in tonic activity precisely correlate with the expected precision or predictability of ongoing auditory input—both in terms of deterministic (first-order) structure and the entropy of random sequences. Source analysis demonstrates an interaction between primary auditory cortex, hippocampus, and inferior frontal gyrus in the process of discovering the regularity within the ongoing sound sequence. The results are consistent with precision based predictive coding accounts of perceptual inference and provide compelling neurophysiological evidence of the brains capacity to encode high-order temporal structure in sensory signals.

A Brain System for Auditory Working Memory

The brain basis for auditory working memory, the process of actively maintaining sounds in memory over short periods of time, is controversial. Using functional magnetic resonance imaging in human participants, we demonstrate that the maintenance of single tones in memory is associated with activation in auditory cortex. In addition, sustained activation was observed in hippocampus and inferior frontal gyrus. Multivoxel pattern analysis showed that patterns of activity in auditory cortex and left inferior frontal gyrus distinguished the tone that was maintained in memory. Functional connectivity during maintenance was demonstrated between auditory cortex and both the hippocampus and inferior frontal cortex. The data support a system for auditory working memory based on the maintenance of sound-specific representations in auditory cortex by projections from higher-order areas, including the hippocampus and frontal cortex. SIGNIFICANCE STATEMENT In this work, we demonstrate a system for maintaining sound in working memory based on activity in auditory cortex, hippocampus, and frontal cortex, and functional connectivity among them. Specifically, our work makes three advances from the previous work. First, we robustly demonstrate hippocampal involvement in all phases of auditory working memory (encoding, maintenance, and retrieval): the role of hippocampus in working memory is controversial. Second, using a pattern classification technique, we show that activity in the auditory cortex and inferior frontal gyrus is specific to the maintained tones in working memory. Third, we show long-range connectivity of auditory cortex to hippocampus and frontal cortex, which may be responsible for keeping such representations active during working memory maintenance.

Is predictability salient? A study of attentional capture by auditory patterns

In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention. This article is part of the themed issue ‘Auditory and visual scene analysis’.

Neural Correlates of Auditory Figure-Ground Segregation Based on Temporal Coherence

To make sense of natural acoustic environments, listeners must parse complex mixtures of sounds that vary in frequency, space, and time. Emerging work suggests that, in addition to the well-studied spectral cues for segregation, sensitivity to temporal coherence—the coincidence of sound elements in and across time—is also critical for the perceptual organization of acoustic scenes. Here, we examine pre-attentive, stimulus-driven neural processes underlying auditory figure-ground segregation using stimuli that capture the challenges of listening in complex scenes where segregation cannot be achieved based on spectral cues alone. Signals (“stochastic figure-ground”: SFG) comprised a sequence of brief broadband chords containing random pure tone components that vary from 1 chord to another. Occasional tone repetitions across chords are perceived as “figures” popping out of a stochastic “ground.” Magnetoencephalography (MEG) measurement in naïve, distracted, human subjects revealed robust evoked responses, commencing from about 150 ms after figure onset that reflect the emergence of the “figure” from the randomly varying “ground.” Neural sources underlying this bottom-up driven figure-ground segregation were localized to planum temporale, and the intraparietal sulcus, demonstrating that this area, outside the “classic” auditory system, is also involved in the early stages of auditory scene analysis.”

Sound segregation via embedded repetition is robust to inattention.

The segregation of sound sources from the mixture of sounds that enters the ear is a core capacity of human hearing, but the extent to which this process is dependent on attention remains unclear. This study investigated the effect of attention on the ability to segregate sounds via repetition. We utilized a dual task design in which stimuli to be segregated were presented along with stimuli for a “decoy” task that required continuous monitoring. The task to assess segregation presented a target sound 10 times in a row, each time concurrent with a different distractor sound. McDermott, Wrobleski, and Oxenham (2011) demonstrated that repetition causes the target sound to be segregated from the distractors. Segregation was queried by asking listeners whether a subsequent probe sound was identical to the target. A control task presented similar stimuli but probed discrimination without engaging segregation processes. We present results from 3 different decoy tasks: a visual multiple object tracking task, a rapid serial visual presentation (RSVP) digit encoding task, and a demanding auditory monitoring task. Load was manipulated by using high- and low-demand versions of each decoy task. The data provide converging evidence of a small effect of attention that is nonspecific, in that it affected the segregation and control tasks to a similar extent. In all cases, segregation performance remained high despite the presence of a concurrent, objectively demanding decoy task. The results suggest that repetition-based segregation is robust to inattention.

The Cumulative Effects of Predictability on Synaptic Gain in the Auditory Processing Stream

Stimulus predictability can lead to substantial modulations of brain activity, such as shifts in sustained magnetic field amplitude, measured with magnetoencephalography (MEG). Here, we provide a mechanistic explanation of these effects using MEG data acquired from healthy human volunteers (N = 13, 7 female). In a source-level analysis of induced responses, we established the effects of orthogonal predictability manipulations of rapid tone-pip sequences (namely, sequence regularity and alphabet size) along the auditory processing stream. In auditory cortex, regular sequences with smaller alphabets induced greater gamma activity. Furthermore, sequence regularity shifted induced activity in frontal regions toward higher frequencies. To model these effects in terms of the underlying neurophysiology, we used dynamic causal modeling for cross-spectral density and estimated slow fluctuations in neural (postsynaptic) gain. Using the model-based parameters, we accurately explain the sensor-level sustained field amplitude, demonstrating that slow changes in synaptic efficacy, combined with sustained sensory input, can result in profound and sustained effects on neural responses to predictable sensory streams. SIGNIFICANCE STATEMENT Brain activity can be strongly modulated by the predictability of stimuli it is currently processing. An example of such a modulation is a shift in sustained magnetic field amplitude, measured with magnetoencephalography. Here, we provide a mechanistic explanation of these effects. First, we establish the oscillatory neural correlates of independent predictability manipulations in hierarchically distinct areas of the auditory processing stream. Next, we use a biophysically realistic computational model to explain these effects in terms of the underlying neurophysiology. Finally, using the model-based parameters describing neural gain modulation, we can explain the previously unexplained effects observed at the sensor level. This demonstrates that slow modulations of synaptic gain can result in profound and sustained effects on neural activity.

Detecting auditory changes by pupillary response

Detecting changes is an essential function that helps the organism to constantly monitor and update the information from the environment. In this talk, I will review our recent work, demonstrating that the human pupillary response can be used as a physiological marker for certain aspects of auditory change detection, in both simple and complex acoustic streams. In study 1, using simple repetitive tones with occasionally presented deviants (oddballs), we found that the oddball induces a pupillary dilation response (PDR), that is modulated by the stimulus properties irrespective of whether attention is directed to the sounds (Liao et al. 2016). In study 2, we examined whether PDR also reflects changes in complex acoustic patterns. We adopted the stimuli in Barascud et al. (2016) which contain transitions between random and regular tone-pip patterns. Results revealed an asymmetry: the PDR was observed only to changes from a regular to a random pattern, but not vice-versa. Overall, the results suggest that th...