Predicting speech from a cortical hierarchy of event-based time scales.

How do predictions in the brain incorporate the temporal unfolding of context in our natural environment? We here provide evidence for a neural coding scheme that sparsely updates contextual representations at the boundary of events. This yields a hierarchical, multilayered organization of predictive language comprehension. Training artificial neural networks to predict the next word in a story at five stacked time scales and then using model-based functional magnetic resonance imaging, we observe an event-based "surprisal hierarchy" evolving along a temporoparietal pathway. Along this hierarchy, surprisal at any given time scale gated bottom-up and top-down connectivity to neighboring time scales. In contrast, surprisal derived from continuously updated context influenced temporoparietal activity only at short time scales. Representing context in the form of increasingly coarse events constitutes a network architecture for making predictions that is both computationally efficient and contextually diverse.

Personality captures dissociations of subjective versus objective hearing in noise.

Acoustic noise is pervasive in human environments. Some individuals are more tolerant to noise than others. We demonstrate the explanatory potential of Big-5 personality traits neuroticism (being emotionally unstable) and extraversion (being enthusiastic, outgoing) on subjective self-report and objective psycho-acoustic metrics of hearing in noise in two samples (total N = 1103). Under statistical control for demographics and in agreement with pre-registered hypotheses, lower neuroticism and higher extraversion independently explained superior self-reported noise resistance, speech-hearing ability and acceptable background noise levels. Surprisingly, objective speech-in-noise recognition instead increased with higher levels of neuroticism. In turn, the bias in subjectively overrating one's own hearing in noise decreases with higher neuroticism but increases with higher extraversion. Of benefit to currently underspecified frameworks of hearing in noise and tailored audiological treatments, these results show that personality explains inter-individual differences in coping with acoustic noise, which is a ubiquitous source of distraction and a health hazard.

Temporal selectivity declines in the aging human auditory cortex.

Current models successfully describe the auditory cortical response to natural sounds with a set of spectro-temporal features. However, these models have hardly been linked to the ill-understood neurobiological changes that occur in the aging auditory cortex. Modelling the hemodynamic response to a rich natural sound mixture in N = 64 listeners of varying age, we here show that in older listeners' auditory cortex, the key feature of temporal rate is represented with a markedly broader tuning. This loss of temporal selectivity is most prominent in primary auditory cortex and planum temporale, with no such changes in adjacent auditory or other brain areas. Amongst older listeners, we observe a direct relationship between chronological age and temporal-rate tuning, unconfounded by auditory acuity or model goodness of fit. In line with senescent neural dedifferentiation more generally, our results highlight decreased selectivity to temporal information as a hallmark of the aging auditory cortex.

It can often be difficult for an older person to understand what someone is saying, particularly in noisy environments. Exactly how and why this age-related change occurs is not clear, but it is thought that older individuals may become less able to tune in to certain features of sound. Newer tools are making it easier to study age-related changes in hearing in the brain. For example, functional magnetic resonance imaging (fMRI) can allow scientists to 'see' and measure how certain parts of the brain react to different features of sound. Using fMRI data, researchers can compare how younger and older people process speech. They can also track how speech processing in the brain changes with age. Now, Erb et al. show that older individuals have a harder time tuning into the rhythm of speech. In the experiments, 64 people between the ages of 18 to 78 were asked to listen to speech in a noisy setting while they underwent fMRI. The researchers then tested a computer model using the data. In the older individuals, the brain's tuning to the timing or rhythm of speech was broader, while the younger participants were more able to finely tune into this feature of sound. The older a person was the less able their brain was to distinguish rhythms in speech, likely making it harder to understand what had been said. This hearing change likely occurs because brain cells become less specialised overtime, which can contribute to many kinds of age-related cognitive decline. This new information about why understanding speech becomes more difficult with age may help scientists develop better hearing aids that are individualised to a person's specific needs.

Temporal Sensitivity Measured Shortly After Cochlear Implantation Predicts 6-Month Speech Recognition Outcome.

OBJECTIVES: Psychoacoustic tests assessed shortly after cochlear implantation are useful predictors of the rehabilitative speech outcome. While largely independent, both spectral and temporal resolution tests are important to provide an accurate prediction of speech recognition. However, rapid tests of temporal sensitivity are currently lacking. Here, we propose a simple amplitude modulation rate discrimination (AMRD) paradigm that is validated by predicting future speech recognition in adult cochlear implant (CI) patients. DESIGN: In 34 newly implanted patients, we used an adaptive AMRD paradigm, where broadband noise was modulated at the speech-relevant rate of ~4 Hz. In a longitudinal study, speech recognition in quiet was assessed using the closed-set Freiburger number test shortly after cochlear implantation (t0) as well as the open-set Freiburger monosyllabic word test 6 months later (t6). RESULTS: Both AMRD thresholds at t0 (r = -0.51) and speech recognition scores at t0 (r = 0.56) predicted speech recognition scores at t6. However, AMRD and speech recognition at t0 were uncorrelated, suggesting that those measures capture partially distinct perceptual abilities. A multiple regression model predicting 6-month speech recognition outcome with deafness duration and speech recognition at t0 improved from adjusted R = 0.30 to adjusted R = 0.44 when AMRD threshold was added as a predictor. CONCLUSIONS: These findings identify AMRD thresholds as a reliable, nonredundant predictor above and beyond established speech tests for CI outcome. This AMRD test could potentially be developed into a rapid clinical temporal-resolution test to be integrated into the postoperative test battery to improve the reliability of speech outcome prognosis.

Homology and Specificity of Natural Sound-Encoding in Human and Monkey Auditory Cortex.

Understanding homologies and differences in auditory cortical processing in human and nonhuman primates is an essential step in elucidating the neurobiology of speech and language. Using fMRI responses to natural sounds, we investigated the representation of multiple acoustic features in auditory cortex of awake macaques and humans. Comparative analyses revealed homologous large-scale topographies not only for frequency but also for temporal and spectral modulations. In both species, posterior regions preferably encoded relatively fast temporal and coarse spectral information, whereas anterior regions encoded slow temporal and fine spectral modulations. Conversely, we observed a striking interspecies difference in cortical sensitivity to temporal modulations: While decoding from macaque auditory cortex was most accurate at fast rates (> 30 Hz), humans had highest sensitivity to ~3 Hz, a relevant rate for speech analysis. These findings suggest that characteristic tuning of human auditory cortex to slow temporal modulations is unique and may have emerged as a critical step in the evolution of speech and language.

Thalamic and parietal brain morphology predicts auditory category learning.

Auditory categorization is a vital skill involving the attribution of meaning to acoustic events, engaging domain-specific (i.e., auditory) as well as domain-general (e.g., executive) brain networks. A listener's ability to categorize novel acoustic stimuli should therefore depend on both, with the domain-general network being particularly relevant for adaptively changing listening strategies and directing attention to relevant acoustic cues. Here we assessed adaptive listening behavior, using complex acoustic stimuli with an initially salient (but later degraded) spectral cue and a secondary, duration cue that remained nondegraded. We employed voxel-based morphometry (VBM) to identify cortical and subcortical brain structures whose individual neuroanatomy predicted task performance and the ability to optimally switch to making use of temporal cues after spectral degradation. Behavioral listening strategies were assessed by logistic regression and revealed mainly strategy switches in the expected direction, with considerable individual differences. Gray-matter probability in the left inferior parietal lobule (BA 40) and left precentral gyrus was predictive of "optimal" strategy switch, while gray-matter probability in thalamic areas, comprising the medial geniculate body, co-varied with overall performance. Taken together, our findings suggest that successful auditory categorization relies on domain-specific neural circuits in the ascending auditory pathway, while adaptive listening behavior depends more on brain structure in parietal cortex, enabling the (re)direction of attention to salient stimulus properties.

The brain dynamics of rapid perceptual adaptation to adverse listening conditions.

Listeners show a remarkable ability to quickly adjust to degraded speech input. Here, we aimed to identify the neural mechanisms of such short-term perceptual adaptation. In a sparse-sampling, cardiac-gated functional magnetic resonance imaging (fMRI) acquisition, human listeners heard and repeated back 4-band-vocoded sentences (in which the temporal envelope of the acoustic signal is preserved, while spectral information is highly degraded). Clear-speech trials were included as baseline. An additional fMRI experiment on amplitude modulation rate discrimination quantified the convergence of neural mechanisms that subserve coping with challenging listening conditions for speech and non-speech. First, the degraded speech task revealed an "executive" network (comprising the anterior insula and anterior cingulate cortex), parts of which were also activated in the non-speech discrimination task. Second, trial-by-trial fluctuations in successful comprehension of degraded speech drove hemodynamic signal change in classic "language" areas (bilateral temporal cortices). Third, as listeners perceptually adapted to degraded speech, downregulation in a cortico-striato-thalamo-cortical circuit was observable. The present data highlight differential upregulation and downregulation in auditory-language and executive networks, respectively, with important subcortical contributions when successfully adapting to a challenging listening situation.

Upregulation of cognitive control networks in older adults' speech comprehension.

Speech comprehension abilities decline with age and with age-related hearing loss, but it is unclear how this decline expresses in terms of central neural mechanisms. The current study examined neural speech processing in a group of older adults (aged 56-77, n = 16, with varying degrees of sensorineural hearing loss), and compared them to a cohort of young adults (aged 22-31, n = 30, self-reported normal hearing). In a functional MRI experiment, listeners heard and repeated back degraded sentences (4-band vocoded, where the temporal envelope of the acoustic signal is preserved, while the spectral information is substantially degraded). Behaviorally, older adults adapted to degraded speech at the same rate as young listeners, although their overall comprehension of degraded speech was lower. Neurally, both older and young adults relied on the left anterior insula for degraded more than clear speech perception. However, anterior insula engagement in older adults was dependent on hearing acuity. Young adults additionally employed the anterior cingulate cortex (ACC). Interestingly, this age group × degradation interaction was driven by a reduced dynamic range in older adults who displayed elevated levels of ACC activity for both degraded and clear speech, consistent with a persistent upregulation in cognitive control irrespective of task difficulty. For correct speech comprehension, older adults relied on the middle frontal gyrus in addition to a core speech comprehension network recruited by younger adults suggestive of a compensatory mechanism. Taken together, the results indicate that older adults increasingly recruit cognitive control networks, even under optimal listening conditions, at the expense of these systems' dynamic range.

Auditory skills and brain morphology predict individual differences in adaptation to degraded speech.

Noise-vocoded speech is a spectrally highly degraded signal, but it preserves the temporal envelope of speech. Listeners vary considerably in their ability to adapt to this degraded speech signal. Here, we hypothesised that individual differences in adaptation to vocoded speech should be predictable by non-speech auditory, cognitive, and neuroanatomical factors. We tested 18 normal-hearing participants in a short-term vocoded speech-learning paradigm (listening to 100 4-band-vocoded sentences). Non-speech auditory skills were assessed using amplitude modulation (AM) rate discrimination, where modulation rates were centred on the speech-relevant rate of 4 Hz. Working memory capacities were evaluated (digit span and nonword repetition), and structural MRI scans were examined for anatomical predictors of vocoded speech learning using voxel-based morphometry. Listeners who learned faster to understand degraded speech also showed smaller thresholds in the AM discrimination task. This ability to adjust to degraded speech is furthermore reflected anatomically in increased grey matter volume in an area of the left thalamus (pulvinar) that is strongly connected to the auditory and prefrontal cortices. Thus, individual non-speech auditory skills and left thalamus grey matter volume can predict how quickly a listener adapts to degraded speech.