Predictive top-down integration of prior knowledge during speech perception

Entrainment echoes in the cerebellum

Evidence accumulates that the cerebellum's role in the brain is not restricted to motor functions. Rather, cerebellar activity seems to be crucial for a variety of tasks that rely on precise event timing and prediction. Due to its complex structure and importance in communication, human speech requires a particularly precise and predictive coordination of neural processes to be successfully comprehended. Recent studies proposed that the cerebellum is indeed a major contributor to speech processing, but how this contribution is achieved mechanistically remains poorly understood. The current study aimed to reveal a mechanism underlying cortico-cerebellar coordination and demonstrate its speech-specificity. In a reanalysis of magnetoencephalography data, we found that activity in the cerebellum aligned to rhythmic sequences of noise-vocoded speech, irrespective of its intelligibility. We then tested whether these "entrained" responses persist, and how they interact with other brain regions, when a rhythmic stimulus stopped and temporal predictions had to be updated. We found that only intelligible speech produced sustained rhythmic responses in the cerebellum. During this "entrainment echo," but not during rhythmic speech itself, cerebellar activity was coupled with that in the left inferior frontal gyrus, and specifically at rates corresponding to the preceding stimulus rhythm. This finding represents evidence for specific cerebellum-driven temporal predictions in speech processing and their relay to cortical regions.

Speech Prosody Serves Temporal Prediction of Language via Contextual Entrainment

Temporal prediction assists language comprehension. In a series of recent behavioral studies, we have shown that listeners specifically employ rhythmic modulations of prosody to estimate the duration of upcoming sentences, thereby speeding up comprehension. In the current human magnetoencephalography (MEG) study on participants of either sex, we show that the human brain achieves this function through a mechanism termed entrainment. Through entrainment, electrophysiological brain activity maintains and continues contextual rhythms beyond their offset. Our experiment combined exposure to repetitive prosodic contours with the subsequent presentation of visual sentences that either matched or mismatched the duration of the preceding contour. During exposure to prosodic contours, we observed MEG coherence with the contours, which was source-localized to right-hemispheric auditory areas. During the processing of the visual targets, activity at the frequency of the preceding contour was still detectable in the MEG; yet sources shifted to the (left) frontal cortex, in line with a functional inheritance of the rhythmic acoustic context for prediction. Strikingly, when the target sentence was shorter than expected from the preceding contour, an omission response appeared in the evoked potential record. We conclude that prosodic entrainment is a functional mechanism of temporal prediction in language comprehension. In general, acoustic rhythms appear to endow language for employing the brain's electrophysiological mechanisms of temporal prediction.

Linguistic modulation of the neural encoding of phonemes

Speech comprehension entails the neural mapping of the acoustic speech signal onto learned linguistic units. This acousto-linguistic transformation is bi-directional, whereby higher-level linguistic processes (e.g. semantics) modulate the acoustic analysis of individual linguistic units. Here, we investigated the cortical topography and linguistic modulation of the most fundamental linguistic unit, the phoneme. We presented natural speech and "phoneme quilts" (pseudo-randomly shuffled phonemes) in either a familiar (English) or unfamiliar (Korean) language to native English speakers while recording functional magnetic resonance imaging. This allowed us to dissociate the contribution of acoustic vs. linguistic processes toward phoneme analysis. We show that (i) the acoustic analysis of phonemes is modulated by linguistic analysis and (ii) that for this modulation, both of acoustic and phonetic information need to be incorporated. These results suggest that the linguistic modulation of cortical sensitivity to phoneme classes minimizes prediction error during natural speech perception, thereby aiding speech comprehension in challenging listening situations.

Parallel Encoding of Speech in Human Frontal and Temporal Lobes

Models of speech perception are centered around a hierarchy in which auditory representations in the thalamus propagate to primary auditory cortex, then to the lateral temporal cortex, and finally through dorsal and ventral pathways to sites in the frontal lobe. However, evidence for short latency speech responses and low-level spectrotemporal representations in frontal cortex raises the question of whether speech-evoked activity in frontal cortex strictly reflects downstream processing from lateral temporal cortex or whether there are direct parallel pathways from the thalamus or primary auditory cortex to the frontal lobe that supplement the traditional hierarchical architecture. Here, we used high-density direct cortical recordings, high-resolution diffusion tractography, and hemodynamic functional connectivity to evaluate for evidence of direct parallel inputs to frontal cortex from low-level areas. We found that neural populations in the frontal lobe show speech-evoked responses that are synchronous or occur earlier than responses in the lateral temporal cortex. These short latency frontal lobe neural populations encode spectrotemporal speech content indistinguishable from spectrotemporal encoding patterns observed in the lateral temporal lobe, suggesting parallel auditory speech representations reaching temporal and frontal cortex simultaneously. This is further supported by white matter tractography and functional connectivity patterns that connect the auditory nucleus of the thalamus (medial geniculate body) and the primary auditory cortex to the frontal lobe. Together, these results support the existence of a robust pathway of parallel inputs from low-level auditory areas to frontal lobe targets and illustrate long-range parallel architecture that works alongside the classical hierarchical speech network model.

Isolating Neural Signatures of Conscious Speech Perception with a No-Report Sine-Wave Speech Paradigm

Identifying neural correlates of conscious perception is a fundamental endeavor of cognitive neuroscience. Most studies so far have focused on visual awareness along with trial-by-trial reports of task-relevant stimuli, which can confound neural measures of perceptual awareness with postperceptual processing. Here, we used a three-phase sine-wave speech paradigm that dissociated between conscious speech perception and task relevance while recording EEG in humans of both sexes. Compared with tokens perceived as noise, physically identical sine-wave speech tokens that were perceived as speech elicited a left-lateralized, near-vertex negativity, which we interpret as a phonological version of a perceptual awareness negativity. This response appeared between 200 and 300 ms after token onset and was not present for frequency-flipped control tokens that were never perceived as speech. In contrast, the P3b elicited by task-irrelevant tokens did not significantly differ when the tokens were perceived as speech versus noise and was only enhanced for tokens that were both perceived as speech and relevant to the task. Our results extend the findings from previous studies on visual awareness and speech perception and suggest that correlates of conscious perception, across types of conscious content, are most likely to be found in midlatency negative-going brain responses in content-specific sensory areas.

Neural tracking of continuous acoustics: properties, speech-specificity and open questions

Human speech is a particularly relevant acoustic stimulus for our species, due to its role of information transmission during communication. Speech is inherently a dynamic signal, and a recent line of research focused on neural activity following the temporal structure of speech. We review findings that characterise neural dynamics in the processing of continuous acoustics and that allow us to compare these dynamics with temporal aspects in human speech. We highlight properties and constraints that both neural and speech dynamics have, suggesting that auditory neural systems are optimised to process human speech. We then discuss the speech-specificity of neural dynamics and their potential mechanistic origins and summarise open questions in the field.

Verbal working memory capacity modulates semantic and phonological prediction in spoken comprehension

Mounting evidence suggests that people may use multiple cues to predict different levels of representation (e.g., semantic, syntactic, and phonological) during language comprehension. One question that has been less investigated is the relationship between general cognitive processing and the efficiency of prediction at various linguistic levels, such as semantic and phonological levels. To address this research gap, the present study investigated how working memory capacity (WMC) modulates different kinds of prediction behavior (i.e., semantic prediction and phonological prediction) in the visual world. Chinese speakers listened to the highly predictable sentences that contained a highly predictable target word, and viewed a visual display of objects. The visual display of objects contained a target object corresponding to the predictable word, a semantic or a phonological competitor that was semantically or phonologically related to the predictable word, and an unrelated object. We conducted a Chinese version of the reading span task to measure verbal WMC and grouped participants into high- and low-span groups. Participants showed semantic and phonological prediction with comparable size in both groups during language comprehension, with earlier semantic prediction in the high-span group, and a similar time course of phonological prediction in both groups. These results suggest that verbal working memory modulates predictive processing in language comprehension.

Reaction time for correct identification of vowels in consonant-vowel syllables and of vowel segments

Reaction times for correct vowel identification were measured to determine the effects of intertrial intervals, vowel, and cue type. Thirteen adults with normal hearing, aged 20-38 years old, participated. Stimuli included three naturally produced syllables (/ba/ /bi/ /bu/) presented whole or segmented to isolate the formant transition or static formant center. Participants identified the vowel presented via loudspeaker by mouse click. Results showed a significant effect of intertrial intervals, no significant effect of cue type, and a significant vowel effect-suggesting that feedback occurs, vowel identification may depend on cue duration, and vowel bias may stem from focal structure.

Contra assertions, feedback improves word recognition: How feedback and lateral inhibition sharpen signals over noise

Whether top-down feedback modulates perception has deep implications for cognitive theories. Debate has been vigorous in the domain of spoken word recognition, where competing computational models and agreement on at least one diagnostic experimental paradigm suggest that the debate may eventually be resolvable. Norris and Cutler (2021) revisit arguments against lexical feedback in spoken word recognition models. They also incorrectly claim that recent computational demonstrations that feedback promotes accuracy and speed under noise (Magnuson et al., 2018) were due to the use of the Luce choice rule rather than adding noise to inputs (noise was in fact added directly to inputs). They also claim that feedback cannot improve word recognition because feedback cannot distinguish signal from noise. We have two goals in this paper. First, we correct the record about the simulations of Magnuson et al. (2018). Second, we explain how interactive activation models selectively sharpen signals via joint effects of feedback and lateral inhibition that boost lexically-coherent sublexical patterns over noise. We also review a growing body of behavioral and neural results consistent with feedback and inconsistent with autonomous (non-feedback) architectures, and conclude that parsimony supports feedback. We close by discussing the potential for synergy between autonomous and interactive approaches.

Neural tracking measures of speech intelligibility: Manipulating intelligibility while keeping acoustics unchanged

Neural speech tracking has advanced our understanding of how our brains rapidly map an acoustic speech signal onto linguistic representations and ultimately meaning. It remains unclear, however, how speech intelligibility is related to the corresponding neural responses. Many studies addressing this question vary the level of intelligibility by manipulating the acoustic waveform, but this makes it difficult to cleanly disentangle the effects of intelligibility from underlying acoustical confounds. Here, using magnetoencephalography recordings, we study neural measures of speech intelligibility by manipulating intelligibility while keeping the acoustics strictly unchanged. Acoustically identical degraded speech stimuli (three-band noise-vocoded, ~20 s duration) are presented twice, but the second presentation is preceded by the original (nondegraded) version of the speech. This intermediate priming, which generates a "pop-out" percept, substantially improves the intelligibility of the second degraded speech passage. We investigate how intelligibility and acoustical structure affect acoustic and linguistic neural representations using multivariate temporal response functions (mTRFs). As expected, behavioral results confirm that perceived speech clarity is improved by priming. mTRFs analysis reveals that auditory (speech envelope and envelope onset) neural representations are not affected by priming but only by the acoustics of the stimuli (bottom-up driven). Critically, our findings suggest that segmentation of sounds into words emerges with better speech intelligibility, and most strongly at the later (~400 ms latency) word processing stage, in prefrontal cortex, in line with engagement of top-down mechanisms associated with priming. Taken together, our results show that word representations may provide some objective measures of speech comprehension.

Distinct roles of delta- and theta-band neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing

The brain tracks and encodes multi-level speech features during spoken language processing. It is evident that this speech tracking is dominant at low frequencies (<8 Hz) including delta and theta bands. Recent research has demonstrated distinctions between delta- and theta-band tracking but has not elucidated how they differentially encode speech across linguistic levels. Here, we hypothesised that delta-band tracking encodes prediction errors (enhanced processing of unexpected features) while theta-band tracking encodes neural sharpening (enhanced processing of expected features) when people perceive speech with different linguistic contents. EEG responses were recorded when normal-hearing participants attended to continuous auditory stimuli that contained different phonological/morphological and semantic contents: (1) real-words, (2) pseudo-words and (3) time-reversed speech. We employed multivariate temporal response functions to measure EEG reconstruction accuracies in response to acoustic (spectrogram), phonetic and phonemic features with the partialling procedure that singles out unique contributions of individual features. We found higher delta-band accuracies for pseudo-words than real-words and time-reversed speech, especially during encoding of phonetic features. Notably, individual time-lag analyses showed that significantly higher accuracies for pseudo-words than real-words started at early processing stages for phonetic encoding (<100 ms post-feature) and later stages for acoustic and phonemic encoding (>200 and 400 ms post-feature, respectively). Theta-band accuracies, on the other hand, were higher when stimuli had richer linguistic content (real-words > pseudo-words > time-reversed speech). Such effects also started at early stages (<100 ms post-feature) during encoding of all individual features or when all features were combined. We argue these results indicate that delta-band tracking may play a role in predictive coding leading to greater tracking of pseudo-words due to the presence of unexpected/unpredicted semantic information, while theta-band tracking encodes sharpened signals caused by more expected phonological/morphological and semantic contents. Early presence of these effects reflects rapid computations of sharpening and prediction errors. Moreover, by measuring changes in EEG alpha power, we did not find evidence that the observed effects can be solitarily explained by attentional demands or listening efforts. Finally, we used directed information analyses to illustrate feedforward and feedback information transfers between prediction errors and sharpening across linguistic levels, showcasing how our results fit with the hierarchical Predictive Coding framework. Together, we suggest the distinct roles of delta and theta neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing.

Causal evidence for a coordinated temporal interplay within the language network

Recent neurobiological models on language suggest that auditory sentence comprehension is supported by a coordinated temporal interplay within a left-dominant brain network, including the posterior inferior frontal gyrus (pIFG), posterior superior temporal gyrus and sulcus (pSTG/STS), and angular gyrus (AG). Here, we probed the timing and causal relevance of the interplay between these regions by means of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG). Our TMS-EEG experiments reveal region- and time-specific causal evidence for a bidirectional information flow from left pSTG/STS to left pIFG and back during auditory sentence processing. Adapting a condition-and-perturb approach, our findings further suggest that the left pSTG/STS can be supported by the left AG in a state-dependent manner.

Leading and following: Noise differently affects semantic and acoustic processing during naturalistic speech comprehension

Despite the distortion of speech signals caused by unavoidable noise in daily life, our ability to comprehend speech in noisy environments is relatively stable. However, the neural mechanisms underlying reliable speech-in-noise comprehension remain to be elucidated. The present study investigated the neural tracking of acoustic and semantic speech information during noisy naturalistic speech comprehension. Participants listened to narrative audio recordings mixed with spectrally matched stationary noise at three signal-to-ratio (SNR) levels (no noise, 3 dB, -3 dB), and 60-channel electroencephalography (EEG) signals were recorded. A temporal response function (TRF) method was employed to derive event-related-like responses to the continuous speech stream at both the acoustic and the semantic levels. Whereas the amplitude envelope of the naturalistic speech was taken as the acoustic feature, word entropy and word surprisal were extracted via the natural language processing method as two semantic features. Theta-band frontocentral TRF responses to the acoustic feature were observed at around 400 ms following speech fluctuation onset over all three SNR levels, and the response latencies were more delayed with increasing noise. Delta-band frontal TRF responses to the semantic feature of word entropy were observed at around 200 to 600 ms leading to speech fluctuation onset over all three SNR levels. The response latencies became more leading with increasing noise and decreasing speech comprehension and intelligibility. While the following responses to speech acoustics were consistent with previous studies, our study revealed the robustness of leading responses to speech semantics, which suggests a possible predictive mechanism at the semantic level for maintaining reliable speech comprehension in noisy environments.

Is predictive coding falsifiable?

Predictive-coding has justifiably become a highly influential theory in Neuroscience. However, the possibility of its unfalsifiability has been raised. We argue that if predictive-coding were unfalsifiable, it would be a problem, but there are patterns of behavioural and neuroimaging data that would stand against predictive-coding. Contra (vanilla) predictive patterns are those in which the more expected stimulus generates the largest evoked-response. However, basic formulations of predictive-coding mandate that an expected stimulus should generate little, if any, prediction error and thus little, if any, evoked-response. It has, though, been argued that contra (vanilla) predictive patterns can be obtained if precision is higher for expected stimuli. Certainly, using precision, one can increase the amplitude of an evoked-response, turning a predictive into a contra (vanilla) predictive pattern. We demonstrate that, while this is true, it does not present an absolute barrier to falsification. This is because increasing precision also reduces latency and increases the frequency of the response. These properties can be used to determine whether precision-weighting in predictive-coding justifiably explains a contra (vanilla) predictive pattern, ensuring that predictive-coding is falsifiable.

Immediate neural impact and incomplete compensation after semantic hub disconnection

The human brain extracts meaning using an extensive neural system for semantic knowledge. Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. We report intracranial recordings from two patients during a speech prediction task, obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, we tested hypotheses ranging from solely neural network disruption to complete compensation by the indirectly affected language-related and speech-processing sites. Immediately after ATL disconnection, we observed neurophysiological alterations in the recorded frontal and auditory sites, providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal an immediate impact and capability of the human brain to adjust after losing a brain hub.

Impact of inner ear malformation and cochlear nerve deficiency on the development of auditory-language network in children with profound sensorineural hearing loss

Profound congenital sensorineural hearing loss (SNHL) prevents children from developing spoken language. Cochlear implantation and auditory brainstem implantation can provide partial hearing sensation, but language development outcomes can vary, particularly for patients with inner ear malformations and/or cochlear nerve deficiency (IEM&CND). Currently, the peripheral auditory structure is evaluated through visual inspection of clinical imaging, but this method is insufficient for surgical planning and prognosis. The central auditory pathway is also challenging to examine in vivo due to its delicate subcortical structures. Previous attempts to locate subcortical auditory nuclei using fMRI responses to sounds are not applicable to patients with profound hearing loss as no auditory brainstem responses can be detected in these individuals, making it impossible to capture corresponding blood oxygen signals in fMRI. In this study, we developed a new pipeline for mapping the auditory pathway using structural and diffusional MRI. We used a fixel-based approach to investigate the structural development of the auditory-language network for profound SNHL children with normal peripheral structure and those with IEM&CND under 6 years old. Our findings indicate that the language pathway is more sensitive to peripheral auditory condition than the central auditory pathway, highlighting the importance of early intervention for profound SNHL children to provide timely speech inputs. We also propose a comprehensive pre-surgical evaluation extending from the cochlea to the auditory-language network, showing significant correlations between age, gender, Cn.VIII median contrast value, and the language network with post-implant qualitative outcomes.

Predicting phonological information in language comprehension: evidence from ERP representational similarity analysis and Chinese idioms

Do comprehenders predict the meaning and even the phonological form of upcoming words during language comprehension? With a growing body of evidence suggesting that semantic representations may be predicted, the evidence for phonological prediction is less clear and largely derived from studies conducted in languages utilizing an alphabetic script. In this research, we aim to examine the prediction of phonological information in the processing of Chinese idioms through the use of ERP representational similarity analysis (RSA). The study utilizes four-character Chinese idioms, and phonological overlap was manipulated by varying the syllable at the idiom-final part between idiom pairs so that pairs of idioms share a syllable (i.e. within-pairs) or not (between-pairs). We quantified the similarity between patterns of neural activity of idioms for within- and between-pairs. RSA results revealed greater similarity in neural activity patterns for idioms within-pairs, compared with between-pairs, and critically this similarity effect was observed prior to the presentation of the phonological similarity, providing evidence for the pre-activation of upcoming phonological information, under circumstances that encourage predictive processing.

Delta-Band Neural Responses to Individual Words Are Modulated by Sentence Processing

To understand language, we need to recognize words and combine them into phrases and sentences. During this process, responses to the words themselves are changed. In a step toward understanding how the brain builds sentence structure, the present study concerns the neural readout of this adaptation. We ask whether low-frequency neural readouts associated with words change as a function of being in a sentence. To this end, we analyzed an MEG dataset by Schoffelen et al. (2019) of 102 human participants (51 women) listening to sentences and word lists, the latter lacking any syntactic structure and combinatorial meaning. Using temporal response functions and a cumulative model-fitting approach, we disentangled delta- and theta-band responses to lexical information (word frequency), from responses to sensory and distributional variables. The results suggest that delta-band responses to words are affected by sentence context in time and space, over and above entropy and surprisal. In both conditions, the word frequency response spanned left temporal and posterior frontal areas; however, the response appeared later in word lists than in sentences. In addition, sentence context determined whether inferior frontal areas were responsive to lexical information. In the theta band, the amplitude was larger in the word list condition ∼100 milliseconds in right frontal areas. We conclude that low-frequency responses to words are changed by sentential context. The results of this study show how the neural representation of words is affected by structural context and as such provide insight into how the brain instantiates compositionality in language.SIGNIFICANCE STATEMENT Human language is unprecedented in its combinatorial capacity: we are capable of producing and understanding sentences we have never heard before. Although the mechanisms underlying this capacity have been described in formal linguistics and cognitive science, how they are implemented in the brain remains to a large extent unknown. A large body of earlier work from the cognitive neuroscientific literature implies a role for delta-band neural activity in the representation of linguistic structure and meaning. In this work, we combine these insights and techniques with findings from psycholinguistics to show that meaning is more than the sum of its parts; the delta-band MEG signal differentially reflects lexical information inside and outside sentence structures.

Cortical responses correlate with speech performance in pre-lingually deaf cochlear implant children

Introduction

Cochlear implantation is currently the most successful intervention for severe-to-profound sensorineural hearing loss, particularly in deaf infants and children. Nonetheless, there remains a significant degree of variability in the outcomes of CI post-implantation. The purpose of this study was to understand the cortical correlates of the variability in speech outcomes with a cochlear implant in pre-lingually deaf children using functional near-infrared spectroscopy (fNIRS), an emerging brain-imaging technique.

Methods

In this experiment, cortical activities when processing visual speech and two levels of auditory speech, including auditory speech in quiet and in noise with signal-to-noise ratios of 10 dB, were examined in 38 CI recipients with pre-lingual deafness and 36 normally hearing children whose age and sex matched CI users. The HOPE corpus (a corpus of Mandarin sentences) was used to generate speech stimuli. The regions of interest (ROIs) for the fNIRS measurements were fronto-temporal-parietal networks involved in language processing, including bilateral superior temporal gyrus, left inferior frontal gyrus, and bilateral inferior parietal lobes.

Results

The fNIRS results confirmed and extended findings previously reported in the neuroimaging literature. Firstly, cortical responses of superior temporal gyrus to both auditory and visual speech in CI users were directly correlated to auditory speech perception scores, with the strongest positive association between the levels of cross-modal reorganization and CI outcome. Secondly, compared to NH controls, CI users, particularly those with good speech perception, showed larger cortical activation in the left inferior frontal gyrus in response to all speech stimuli used in the experiment.

Discussion

In conclusion, cross-modal activation to visual speech in the auditory cortex of pre-lingually deaf CI children may be at least one of the neural bases of highly variable CI performance due to its beneficial effects for speech understanding, thus supporting the prediction and assessment of CI outcomes in clinic. Additionally, cortical activation of the left inferior frontal gyrus may be a cortical marker for effortful listening.

Temporal lobe perceptual predictions for speech are instantiated in motor cortex and reconciled by inferior frontal cortex

Humans use predictions to improve speech perception, especially in noisy environments. Here we use 7-T functional MRI (fMRI) to decode brain representations of written phonological predictions and degraded speech signals in healthy humans and people with selective frontal neurodegeneration (non-fluent variant primary progressive aphasia [nfvPPA]). Multivariate analyses of item-specific patterns of neural activation indicate dissimilar representations of verified and violated predictions in left inferior frontal gyrus, suggestive of processing by distinct neural populations. In contrast, precentral gyrus represents a combination of phonological information and weighted prediction error. In the presence of intact temporal cortex, frontal neurodegeneration results in inflexible predictions. This manifests neurally as a failure to suppress incorrect predictions in anterior superior temporal gyrus and reduced stability of phonological representations in precentral gyrus. We propose a tripartite speech perception network in which inferior frontal gyrus supports prediction reconciliation in echoic memory, and precentral gyrus invokes a motor model to instantiate and refine perceptual predictions for speech.

A deep hierarchy of predictions enables online meaning extraction in a computational model of human speech comprehension

Understanding speech requires mapping fleeting and often ambiguous soundwaves to meaning. While humans are known to exploit their capacity to contextualize to facilitate this process, how internal knowledge is deployed online remains an open question. Here, we present a model that extracts multiple levels of information from continuous speech online. The model applies linguistic and nonlinguistic knowledge to speech processing, by periodically generating top-down predictions and incorporating bottom-up incoming evidence in a nested temporal hierarchy. We show that a nonlinguistic context level provides semantic predictions informed by sensory inputs, which are crucial for disambiguating among multiple meanings of the same word. The explicit knowledge hierarchy of the model enables a more holistic account of the neurophysiological responses to speech compared to using lexical predictions generated by a neural network language model (GPT-2). We also show that hierarchical predictions reduce peripheral processing via minimizing uncertainty and prediction error. With this proof-of-concept model, we demonstrate that the deployment of hierarchical predictions is a possible strategy for the brain to dynamically utilize structured knowledge and make sense of the speech input.

The channel capacity of multilevel linguistic features constrains speech comprehension

Humans are expert at processing speech but how this feat is accomplished remains a major question in cognitive neuroscience. Capitalizing on the concept of channel capacity, we developed a unified measurement framework to investigate the respective influence of seven acoustic and linguistic features on speech comprehension, encompassing acoustic, sub-lexical, lexical and supra-lexical levels of description. We show that comprehension is independently impacted by all these features, but at varying degrees and with a clear dominance of the syllabic rate. Comparing comprehension of French words and sentences further reveals that when supra-lexical contextual information is present, the impact of all other features is dramatically reduced. Finally, we estimated the channel capacity associated with each linguistic feature and compared them with their generic distribution in natural speech. Our data reveal that while acoustic modulation, syllabic and phonemic rates unfold respectively at 5, 5, and 12 Hz in natural speech, they are associated with independent processing bottlenecks whose channel capacity are of 15, 15 and 35 Hz, respectively, as suggested by neurophysiological theories. They moreover point towards supra-lexical contextual information as the feature limiting the flow of natural speech. Overall, this study reveals how multilevel linguistic features constrain speech comprehension.

Exposure to nonnative-accented speech reduces listening effort and improves social judgments of the speaker

Prior research has revealed a native-accent advantage, whereby nonnative-accented speech is more difficult to process than native-accented speech. Nonnative-accented speakers also experience more negative social judgments. In the current study, we asked three questions. First, does exposure to nonnative-accented speech increase speech intelligibility or decrease listening effort, thereby narrowing the native-accent advantage? Second, does lower intelligibility or higher listening effort contribute to listeners' negative social judgments of speakers? Third and finally, does increased intelligibility or decreased listening effort with exposure to speech bring about more positive social judgments of speakers? To address these questions, normal-hearing adults listened to a block of English sentences with a native accent and a block with nonnative accent. We found that once participants were accustomed to the task, intelligibility was greater for nonnative-accented speech and increased similarly with exposure for both accents. However, listening effort decreased only for nonnative-accented speech, soon reaching the level of native-accented speech. In addition, lower intelligibility and higher listening effort was associated with lower ratings of speaker warmth, speaker competence, and willingness to interact with the speaker. Finally, competence ratings increased over time to a similar extent for both accents, with this relationship fully mediated by intelligibility and listening effort. These results offer insight into how listeners process and judge unfamiliar speakers.

Modeling functional difference between gyri and sulci within intrinsic connectivity networks

Recently, the functional roles of the human cortical folding patterns have attracted increasing interest in the neuroimaging community. However, most existing studies have focused on the gyro-sulcal functional relationship on a whole-brain scale but possibly overlooked the localized and subtle functional differences of brain networks. Actually, accumulating evidences suggest that functional brain networks are the basic unit to realize the brain function; thus, the functional relationships between gyri and sulci still need to be further explored within different functional brain networks. Inspired by these evidences, we proposed a novel intrinsic connectivity network (ICN)-guided pooling-trimmed convolutional neural network (I-ptFCN) to revisit the functional difference between gyri and sulci. By testing the proposed model on the task functional magnetic resonance imaging (fMRI) datasets of the Human Connectome Project, we found that the classification accuracy of gyral and sulcal fMRI signals varied significantly for different ICNs, indicating functional heterogeneity of cortical folding patterns in different brain networks. The heterogeneity may be contributed by sulci, as only sulcal signals show heterogeneous frequency features across different ICNs, whereas the frequency features of gyri are homogeneous. These results offer novel insights into the functional difference between gyri and sulci and enlighten the functional roles of cortical folding patterns.

Cortical speech tracking is related to individual prediction tendencies

Listening can be conceptualized as a process of active inference, in which the brain forms internal models to integrate auditory information in a complex interaction of bottom-up and top-down processes. We propose that individuals vary in their "prediction tendency" and that this variation contributes to experiential differences in everyday listening situations and shapes the cortical processing of acoustic input such as speech. Here, we presented tone sequences of varying entropy level, to independently quantify auditory prediction tendency (as the tendency to anticipate low-level acoustic features) for each individual. This measure was then used to predict cortical speech tracking in a multi speaker listening task, where participants listened to audiobooks narrated by a target speaker in isolation or interfered by 1 or 2 distractors. Furthermore, semantic violations were introduced into the story, to also examine effects of word surprisal during speech processing. Our results show that cortical speech tracking is related to prediction tendency. In addition, we find interactions between prediction tendency and background noise as well as word surprisal in disparate brain regions. Our findings suggest that individual prediction tendencies are generalizable across different listening situations and may serve as a valuable element to explain interindividual differences in natural listening situations.

Cortical tracking of lexical speech units in a multi-talker background is immature in school-aged children

Children have more difficulty perceiving speech in noise than adults. Whether this difficulty relates to an immature processing of prosodic or linguistic elements of the attended speech is still unclear. To address the impact of noise on linguistic processing per se, we assessed how babble noise impacts the cortical tracking of intelligible speech devoid of prosody in school-aged children and adults. Twenty adults and twenty children (7-9 years) listened to synthesized French monosyllabic words presented at 2.5 Hz, either randomly or in 4-word hierarchical structures wherein 2 words formed a phrase at 1.25 Hz, and 2 phrases formed a sentence at 0.625 Hz, with or without babble noise. Neuromagnetic responses to words, phrases and sentences were identified and source-localized. Children and adults displayed significant cortical tracking of words in all conditions, and of phrases and sentences only when words formed meaningful sentences. In children compared with adults, the cortical tracking was lower for all linguistic units in conditions without noise. In the presence of noise, the cortical tracking was similarly reduced for sentence units in both groups, but remained stable for phrase units. Critically, when there was noise, adults increased the cortical tracking of monosyllabic words in the inferior frontal gyri and supratemporal auditory cortices but children did not. This study demonstrates that the difficulties of school-aged children in understanding speech in a multi-talker background might be partly due to an immature tracking of lexical but not supra-lexical linguistic units.

Decoding subject's own name in the primary auditory cortex

Current studies have shown that perception of subject's own name (SON) involves multiple multimodal brain regions, while activities in unimodal sensory regions (i.e., primary auditory cortex) and their interaction with multimodal regions during the self-processing remain unclear. To answer this, we combined multivariate pattern analysis and dynamic causal modelling analysis to explore the regional activation pattern and inter-region effective connection during the perception of SON. We found that SON and other names could be decoded from the activation pattern in the primary auditory cortex. In addition, we found an excitatory effect of SON on connections from the anterior insula/inferior frontal gyrus to the primary auditory cortex, and to the temporoparietal junction. Our findings extended the current knowledge of self-processing by showing that primary auditory cortex could discriminate SON from other names. Furthermore, our findings highlighted the importance of influence of the insula on the primary auditory cortex during self-processing.

Neural dynamics of phoneme sequences reveal position-invariant code for content and order

Speech consists of a continuously-varying acoustic signal. Yet human listeners experience it as sequences of discrete speech sounds, which are used to recognise discrete words. To examine how the human brain appropriately sequences the speech signal, we recorded two-hour magnetoencephalograms from 21 participants listening to short narratives. Our analyses show that the brain continuously encodes the three most recently heard speech sounds in parallel, and maintains this information long past its dissipation from the sensory input. Each speech sound representation evolves over time, jointly encoding both its phonetic features and the amount of time elapsed since onset. As a result, this dynamic neural pattern encodes both the relative order and phonetic content of the speech sequence. These representations are active earlier when phonemes are more predictable, and are sustained longer when lexical identity is uncertain. Our results show how phonetic sequences in natural speech are represented at the level of populations of neurons, providing insight into what intermediary representations exist between the sensory input and sub-lexical units. The flexibility in the dynamics of these representations paves the way for further understanding of how such sequences may be used to interface with higher order structure such as lexical identity.

Under-resourced or overloaded? Rethinking working memory deficits in developmental language disorder

Dominant theoretical accounts of developmental language disorder (DLD) commonly invoke working memory capacity limitations. In the current report, we present an alternative view: That working memory in DLD is not under-resourced but overloaded due to operating on speech representations with low discriminability. This account is developed through computational simulations involving deep convolutional neural networks trained on spoken word spectrograms in which information is either retained to mimic typical development or degraded to mimic the auditory processing deficits identified among some children with DLD. We assess not only spoken word recognition accuracy and predictive probability and entropy (i.e., predictive distribution spread), but also use mean-field-theory based manifold analysis to assess; (a) internal speech representation dimensionality and (b) classification capacity, a measure of the networks' ability to isolate any given internal speech representation that is used as a proxy for attentional control. We show that instantiating a low-level auditory processing deficit results in the formation of internal speech representations with atypically high dimensionality, and that classification capacity is exhausted due to low representation separability. These representation and control deficits underpin not only lower performance accuracy but also greater uncertainty even when making accurate predictions in a simulated spoken word recognition task (i.e., predictive distributions with low maximum probability and high entropy), which replicates the response delays and word finding difficulties often seen in DLD. Overall, these simulations demonstrate a theoretical account of speech representation and processing deficits in DLD in which working memory capacity limitations play no causal role. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effect of aging on audiovisual integration: Comparison of high- and low-intensity conditions in a speech discrimination task

Audiovisual integration is an essential process that influences speech perception in conversation. However, it is still debated whether older individuals benefit more from audiovisual integration than younger individuals. This ambiguity is likely due to stimulus features, such as stimulus intensity. The purpose of the current study was to explore the effect of aging on audiovisual integration, using event-related potentials (ERPs) at different stimulus intensities. The results showed greater audiovisual integration in older adults at 320–360 ms. Conversely, at 460–500 ms, older adults displayed attenuated audiovisual integration in the frontal, fronto-central, central, and centro-parietal regions compared to younger adults. In addition, we found older adults had greater audiovisual integration at 200–230 ms under the low-intensity condition compared to the high-intensity condition, suggesting inverse effectiveness occurred. However, inverse effectiveness was not found in younger adults. Taken together, the results suggested that there was age-related dissociation in audiovisual integration and inverse effectiveness, indicating that the neural mechanisms underlying audiovisual integration differed between older adults and younger adults.

Prediction Cannot Be Directly Trained: An Extension to Jones and Westermann (2021)

In January 2021, we published an article titled "Predictive Processing and Developmental Language Disorder" in the Journal of Speech, Language, and Hearing Research. The current commentary provides an important extension to this work. Specifically, we aim to head off the suggestion that a child's "predictive capacity" may be trained independently of improving the quality of their long-term speech representations.

A Theoretical Framework for Human and Nonhuman Vocal Interaction

Vocal communication is a critical feature of social interaction across species; however, the relation between such behavior in humans and nonhumans remains unclear. To enable comparative investigation of this topic, we review the literature pertinent to interactive language use and identify the superset of cognitive operations involved in generating communicative action. We posit these functions comprise three intersecting multistep pathways: (a) the Content Pathway, which selects the movements constituting a response; (b) the Timing Pathway, which temporally structures responses; and (c) the Affect Pathway, which modulates response parameters according to internal state. These processing streams form the basis of the Convergent Pathways for Interaction framework, which provides a conceptual model for investigating the cognitive and neural computations underlying vocal communication across species.

Event-Related Potential Evidence for Involuntary Consciousness During Implicit Memory Retrieval

Classical notion claims that a memory is implicit if has nothing to do with consciousness during the information retrieval from storage, or is otherwise explicit. Here, we demonstrate event-related potential evidence for involuntary consciousness during implicit memory retrieval. We designed a passive oddball paradigm for retrieval of implicit memory in which an auditory stream of Shepard tones with musical pitch interval contrasts were delivered to the subjects. These contrasts evoked a mismatch negativity response, which is an event-related potential and a neural marker of implicit memory, in the subjects with long-term musical training, but not in the subjects without. Notably, this response was followed by a salient P3 component which implies involvement of involuntary consciousness in the implicit memory retrieval. Finally, source analysis of the P3 revealed moving dipoles from the frontal lobe to the insula, a brain region closely related to conscious attention. Our study presents a case of involvement of involuntary consciousness in the implicit memory retrieval and suggests a potential challenge to the classical definition of implicit memory.

Prefrontal cortex supports speech perception in listeners with cochlear implants

Cochlear implants are neuroprosthetic devices that can restore hearing in people with severe to profound hearing loss by electrically stimulating the auditory nerve. Because of physical limitations on the precision of this stimulation, the acoustic information delivered by a cochlear implant does not convey the same level of acoustic detail as that conveyed by normal hearing. As a result, speech understanding in listeners with cochlear implants is typically poorer and more effortful than in listeners with normal hearing. The brain networks supporting speech understanding in listeners with cochlear implants are not well understood, partly due to difficulties obtaining functional neuroimaging data in this population. In the current study, we assessed the brain regions supporting spoken word understanding in adult listeners with right unilateral cochlear implants (n=20) and matched controls (n=18) using high-density diffuse optical tomography (HD-DOT), a quiet and non-invasive imaging modality with spatial resolution comparable to that of functional MRI. We found that while listening to spoken words in quiet, listeners with cochlear implants showed greater activity in the left prefrontal cortex than listeners with normal hearing, specifically in a region engaged in a separate spatial working memory task. These results suggest that listeners with cochlear implants require greater cognitive processing during speech understanding than listeners with normal hearing, supported by compensatory recruitment of the left prefrontal cortex.

Lipreading: A Review of Its Continuing Importance for Speech Recognition With an Acquired Hearing Loss and Possibilities for Effective Training

PURPOSE

The goal of this review article is to reinvigorate interest in lipreading and lipreading training for adults with acquired hearing loss. Most adults benefit from being able to see the talker when speech is degraded; however, the effect size is related to their lipreading ability, which is typically poor in adults who have experienced normal hearing through most of their lives. Lipreading training has been viewed as a possible avenue for rehabilitation of adults with an acquired hearing loss, but most training approaches have not been particularly successful. Here, we describe lipreading and theoretically motivated approaches to its training, as well as examples of successful training paradigms. We discuss some extensions to auditory-only (AO) and audiovisual (AV) speech recognition.

METHOD

Visual speech perception and word recognition are described. Traditional and contemporary views of training and perceptual learning are outlined. We focus on the roles of external and internal feedback and the training task in perceptual learning, and we describe results of lipreading training experiments.

RESULTS

Lipreading is commonly characterized as limited to viseme perception. However, evidence demonstrates subvisemic perception of visual phonetic information. Lipreading words also relies on lexical constraints, not unlike auditory spoken word recognition. Lipreading has been shown to be difficult to improve through training, but under specific feedback and task conditions, training can be successful, and learning can generalize to untrained materials, including AV sentence stimuli in noise. The results on lipreading have implications for AO and AV training and for use of acoustically processed speech in face-to-face communication.

CONCLUSION

Given its importance for speech recognition with a hearing loss, we suggest that the research and clinical communities integrate lipreading in their efforts to improve speech recognition in adults with acquired hearing loss.

EXPRESS: Orthographic and feature-level contributions to letter identification

Word recognition is facilitated by primes containing visually similar letters (dentjst-dentist, Marcet & Perea, 2017), suggesting that letter identities are encoded with initial uncertainty. Orthographic knowledge also guides letter identification, as readers are more accurate at identifying letters in words compared to pseudowords (Reicher, 1969; Wheeler, 1970). We investigated how higher-level orthographic knowledge and low-level visual feature analysis operate in combination during letter identification. We conducted a Reicher-Wheeler task to compare readers' ability to discriminate between visually similar and dissimilar letters across different orthographic contexts (words, pseudowords, and consonant strings). Orthographic context and visual similarity had independent effects on letter identification, and there was no interaction between these factors. The magnitude of these effects indicated that higher-level orthographic information plays a greater role than lower-level visual feature information in letter identification. We propose that readers use orthographic knowledge to refine potential letter candidates while visual feature information is accumulated. This combination of higher-level knowledge and low-level feature analysis may be essential in permitting the flexibility required to identify visual variations of the same letter (e.g. N-n) whilst maintaining enough precision to tell visually similar letters apart (e.g. n-h). These results provide new insights on the integration of visual and linguistic information and highlight the need for greater integration between models of reading and visual processing. This study was pre-registered on the Open Science Framework. Pre-registration, stimuli, instructions, trial-level data, and analysis scripts are openly available (https://osf.io/p4q9u/).

Processing of an Audiobook in the Human Brain Is Shaped by Cultural Family Background

Perception of the same narrative can vary between individuals depending on a listener’s previous experiences. We studied whether and how cultural family background may shape the processing of an audiobook in the human brain. During functional magnetic resonance imaging (fMRI), 48 healthy volunteers from two different cultural family backgrounds listened to an audiobook depicting the intercultural social life of young adults with the respective cultural backgrounds. Shared cultural family background increased inter-subject correlation of hemodynamic activity in the left-hemispheric Heschl’s gyrus, insula, superior temporal gyrus, lingual gyrus and middle temporal gyrus, in the right-hemispheric lateral occipital and posterior cingulate cortices as well as in the bilateral middle temporal gyrus, middle occipital gyrus and precuneus. Thus, cultural family background is reflected in multiple areas of speech processing in the brain and may also modulate visual imagery. After neuroimaging, the participants listened to the narrative again and, after each passage, produced a list of words that had been on their minds when they heard the audiobook during neuroimaging. Cultural family background was reflected as semantic differences in these word lists as quantified by a word2vec-generated semantic model. Our findings may depict enhanced mutual understanding between persons who share similar cultural family backgrounds.

Lexical Effects on the Perceived Clarity of Noise-Vocoded Speech in Younger and Older Listeners

When listening to degraded speech, such as speech delivered by a cochlear implant (CI), listeners make use of top-down linguistic knowledge to facilitate speech recognition. Lexical knowledge supports speech recognition and enhances the perceived clarity of speech. Yet, the extent to which lexical knowledge can be used to effectively compensate for degraded input may depend on the degree of degradation and the listener's age. The current study investigated lexical effects in the compensation for speech that was degraded via noise-vocoding in younger and older listeners. In an online experiment, younger and older normal-hearing (NH) listeners rated the clarity of noise-vocoded sentences on a scale from 1 ("very unclear") to 7 ("completely clear"). Lexical information was provided by matching text primes and the lexical content of the target utterance. Half of the sentences were preceded by a matching text prime, while half were preceded by a non-matching prime. Each sentence also consisted of three key words of high or low lexical frequency and neighborhood density. Sentences were processed to simulate CI hearing, using an eight-channel noise vocoder with varying filter slopes. Results showed that lexical information impacted the perceived clarity of noise-vocoded speech. Noise-vocoded speech was perceived as clearer when preceded by a matching prime, and when sentences included key words with high lexical frequency and low neighborhood density. However, the strength of the lexical effects depended on the level of degradation. Matching text primes had a greater impact for speech with poorer spectral resolution, but lexical content had a smaller impact for speech with poorer spectral resolution. Finally, lexical information appeared to benefit both younger and older listeners. Findings demonstrate that lexical knowledge can be employed by younger and older listeners in cognitive compensation during the processing of noise-vocoded speech. However, lexical content may not be as reliable when the signal is highly degraded. Clinical implications are that for adult CI users, lexical knowledge might be used to compensate for the degraded speech signal, regardless of age, but some CI users may be hindered by a relatively poor signal.

Expectations boost the reconstruction of auditory features from electrophysiological responses to noisy speech

Online speech processing imposes significant computational demands on the listening brain, the underlying mechanisms of which remain poorly understood. Here, we exploit the perceptual "pop-out" phenomenon (i.e. the dramatic improvement of speech intelligibility after receiving information about speech content) to investigate the neurophysiological effects of prior expectations on degraded speech comprehension. We recorded electroencephalography (EEG) and pupillometry from 21 adults while they rated the clarity of noise-vocoded and sine-wave synthesized sentences. Pop-out was reliably elicited following visual presentation of the corresponding written sentence, but not following incongruent or neutral text. Pop-out was associated with improved reconstruction of the acoustic stimulus envelope from low-frequency EEG activity, implying that improvements in perceptual clarity were mediated via top-down signals that enhanced the quality of cortical speech representations. Spectral analysis further revealed that pop-out was accompanied by a reduction in theta-band power, consistent with predictive coding accounts of acoustic filling-in and incremental sentence processing. Moreover, delta-band power, alpha-band power, and pupil diameter were all increased following the provision of any written sentence information, irrespective of content. Together, these findings reveal distinctive profiles of neurophysiological activity that differentiate the content-specific processes associated with degraded speech comprehension from the context-specific processes invoked under adverse listening conditions.

Arousal States as a Key Source of Variability in Speech Perception and Learning

The human brain exhibits the remarkable ability to categorize speech sounds into distinct, meaningful percepts, even in challenging tasks like learning non-native speech categories in adulthood and hearing speech in noisy listening conditions. In these scenarios, there is substantial variability in perception and behavior, both across individual listeners and individual trials. While there has been extensive work characterizing stimulus-related and contextual factors that contribute to variability, recent advances in neuroscience are beginning to shed light on another potential source of variability that has not been explored in speech processing. Specifically, there are task-independent, moment-to-moment variations in neural activity in broadly-distributed cortical and subcortical networks that affect how a stimulus is perceived on a trial-by-trial basis. In this review, we discuss factors that affect speech sound learning and moment-to-moment variability in perception, particularly arousal states—neurotransmitter-dependent modulations of cortical activity. We propose that a more complete model of speech perception and learning should incorporate subcortically-mediated arousal states that alter behavior in ways that are distinct from, yet complementary to, top-down cognitive modulations. Finally, we discuss a novel neuromodulation technique, transcutaneous auricular vagus nerve stimulation (taVNS), which is particularly well-suited to investigating causal relationships between arousal mechanisms and performance in a variety of perceptual tasks. Together, these approaches provide novel testable hypotheses for explaining variability in classically challenging tasks, including non-native speech sound learning.

Audiovisual incongruence differentially impacts left and right hemisphere sensorimotor oscillations: Potential applications to production

Speech production gives rise to distinct auditory and somatosensory feedback signals which are dynamically integrated to enable online monitoring and error correction, though it remains unclear how the sensorimotor system supports the integration of these multimodal signals. Capitalizing on the parity of sensorimotor processes supporting perception and production, the current study employed the McGurk paradigm to induce multimodal sensory congruence/incongruence. EEG data from a cohort of 39 typical speakers were decomposed with independent component analysis to identify bilateral mu rhythms; indices of sensorimotor activity. Subsequent time-frequency analyses revealed bilateral patterns of event related desynchronization (ERD) across alpha and beta frequency ranges over the time course of perceptual events. Right mu activity was characterized by reduced ERD during all cases of audiovisual incongruence, while left mu activity was attenuated and protracted in McGurk trials eliciting sensory fusion. Results were interpreted to suggest distinct hemispheric contributions, with right hemisphere mu activity supporting a coarse incongruence detection process and left hemisphere mu activity reflecting a more granular level of analysis including phonological identification and incongruence resolution. Findings are also considered in regard to incongruence detection and resolution processes during production.

Reduced Semantic Context and Signal-to-Noise Ratio Increase Listening Effort As Measured Using Functional Near-Infrared Spectroscopy

OBJECTIVES

Understanding speech-in-noise can be highly effortful. Decreasing the signal-to-noise ratio (SNR) of speech increases listening effort, but it is relatively unclear if decreasing the level of semantic context does as well. The current study used functional near-infrared spectroscopy to evaluate two primary hypotheses: (1) listening effort (operationalized as oxygenation of the left lateral PFC) increases as the SNR decreases and (2) listening effort increases as context decreases.

DESIGN

Twenty-eight younger adults with normal hearing completed the Revised Speech Perception in Noise Test, in which they listened to sentences and reported the final word. These sentences either had an easy SNR (+4 dB) or a hard SNR (-2 dB), and were either low in semantic context (e.g., "Tom could have thought about the sport") or high in context (e.g., "She had to vacuum the rug"). PFC oxygenation was measured throughout using functional near-infrared spectroscopy.

RESULTS

Accuracy on the Revised Speech Perception in Noise Test was worse when the SNR was hard than when it was easy, and worse for sentences low in semantic context than high in context. Similarly, oxygenation across the entire PFC (including the left lateral PFC) was greater when the SNR was hard, and left lateral PFC oxygenation was greater when context was low.

CONCLUSIONS

These results suggest that activation of the left lateral PFC (interpreted here as reflecting listening effort) increases to compensate for acoustic and linguistic challenges. This may reflect the increased engagement of domain-general and domain-specific processes subserved by the dorsolateral prefrontal cortex (e.g., cognitive control) and inferior frontal gyrus (e.g., predicting the sensory consequences of articulatory gestures), respectively.

COSMO-Onset: A Neurally-Inspired Computational Model of Spoken Word Recognition, Combining Top-Down Prediction and Bottom-Up Detection of Syllabic Onsets

Recent neurocognitive models commonly consider speech perception as a hierarchy of processes, each corresponding to specific temporal scales of collective oscillatory processes in the cortex: 30-80 Hz gamma oscillations in charge of phonetic analysis, 4-9 Hz theta oscillations in charge of syllabic segmentation, 1-2 Hz delta oscillations processing prosodic/syntactic units and the 15-20 Hz beta channel possibly involved in top-down predictions. Several recent neuro-computational models thus feature theta oscillations, driven by the speech acoustic envelope, to achieve syllabic parsing before lexical access. However, it is unlikely that such syllabic parsing, performed in a purely bottom-up manner from envelope variations, would be totally efficient in all situations, especially in adverse sensory conditions. We present a new probabilistic model of spoken word recognition, called COSMO-Onset, in which syllabic parsing relies on fusion between top-down, lexical prediction of onset events and bottom-up onset detection from the acoustic envelope. We report preliminary simulations, analyzing how the model performs syllabic parsing and phone, syllable and word recognition. We show that, while purely bottom-up onset detection is sufficient for word recognition in nominal conditions, top-down prediction of syllabic onset events allows overcoming challenging adverse conditions, such as when the acoustic envelope is degraded, leading either to spurious or missing onset events in the sensory signal. This provides a proposal for a possible computational functional role of top-down, predictive processes during speech recognition, consistent with recent models of neuronal oscillatory processes.

Predictive Neural Computations Support Spoken Word Recognition: Evidence from MEG and Competitor Priming

Human listeners achieve quick and effortless speech comprehension through computations of conditional probability using Bayes rule. However, the neural implementation of Bayesian perceptual inference remains unclear. Competitive-selection accounts (e.g., TRACE) propose that word recognition is achieved through direct inhibitory connections between units representing candidate words that share segments (e.g., hygiene and hijack share /haidʒ/). Manipulations that increase lexical uncertainty should increase neural responses associated with word recognition when words cannot be uniquely identified. In contrast, predictive-selection accounts (e.g., Predictive-Coding) propose that spoken word recognition involves comparing heard and predicted speech sounds and using prediction error to update lexical representations. Increased lexical uncertainty in words, such as hygiene and hijack, will increase prediction error and hence neural activity only at later time points when different segments are predicted. We collected MEG data from male and female listeners to test these two Bayesian mechanisms and used a competitor priming manipulation to change the prior probability of specific words. Lexical decision responses showed delayed recognition of target words (hygiene) following presentation of a neighboring prime word (hijack) several minutes earlier. However, this effect was not observed with pseudoword primes (higent) or targets (hijure). Crucially, MEG responses in the STG showed greater neural responses for word-primed words after the point at which they were uniquely identified (after /haidʒ/ in hygiene) but not before while similar changes were again absent for pseudowords. These findings are consistent with accounts of spoken word recognition in which neural computations of prediction error play a central role.SIGNIFICANCE STATEMENT Effective speech perception is critical to daily life and involves computations that combine speech signals with prior knowledge of spoken words (i.e., Bayesian perceptual inference). This study specifies the neural mechanisms that support spoken word recognition by testing two distinct implementations of Bayes perceptual inference. Most established theories propose direct competition between lexical units such that inhibition of irrelevant candidates leads to selection of critical words. Our results instead support predictive-selection theories (e.g., Predictive-Coding): by comparing heard and predicted speech sounds, neural computations of prediction error can help listeners continuously update lexical probabilities, allowing for more rapid word identification.

Brain electrical dynamics in speech segmentation depends upon prior experience with the language

It remains unclear whether the process of speech tracking, which facilitates speech segmentation, reflects top-down mechanisms related to prior linguistic models or stimulus-driven mechanisms, or possibly both. To address this, we recorded electroencephalography (EEG) responses from native and non-native speakers of English that had different prior experience with the English language but heard acoustically identical stimuli. Despite a significant difference in the ability to segment and perceive speech, our EEG results showed that theta-band tracking of the speech envelope did not depend significantly on prior experience with language. However, tracking in the theta-band did show changes across repetitions of the same sentence, suggesting a priming effect. Furthermore, native and non-native speakers showed different phase dynamics at word boundaries, suggesting differences in segmentation mechanisms. Finally, we found that the correlation between higher frequency dynamics reflecting phoneme-level processing and perceptual segmentation of words might depend on prior experience with the spoken language.

Neural attentional-filter mechanisms of listening success in middle-aged and older individuals

Successful listening crucially depends on intact attentional filters that separate relevant from irrelevant information. Research into their neurobiological implementation has focused on two potential auditory filter strategies: the lateralization of alpha power and selective neural speech tracking. However, the functional interplay of the two neural filter strategies and their potency to index listening success in an ageing population remains unclear. Using electroencephalography and a dual-talker task in a representative sample of listeners (N = 155; age=39-80 years), we here demonstrate an often-missed link from single-trial behavioural outcomes back to trial-by-trial changes in neural attentional filtering. First, we observe preserved attentional-cue-driven modulation of both neural filters across chronological age and hearing levels. Second, neural filter states vary independently of one another, demonstrating complementary neurobiological solutions of spatial selective attention. Stronger neural speech tracking but not alpha lateralization boosts trial-to-trial behavioural performance. Our results highlight the translational potential of neural speech tracking as an individualized neural marker of adaptive listening behaviour.

Sensorimotor contributions to working memory differ between the discrimination of Same and Different syllable pairs

Sensorimotor activity during speech perception is both pervasive and highly variable, changing as a function of the cognitive demands imposed by the task. The purpose of the current study was to evaluate whether the discrimination of Same (matched) and Different (unmatched) syllable pairs elicit different patterns of sensorimotor activity as stimuli are processed in working memory. Raw EEG data recorded from 42 participants were decomposed with independent component analysis to identify bilateral sensorimotor mu rhythms from 36 subjects. Time frequency decomposition of mu rhythms revealed concurrent event related desynchronization (ERD) in alpha and beta frequency bands across the peri- and post-stimulus time periods, which were interpreted as evidence of sensorimotor contributions to working memory encoding and maintenance. Left hemisphere alpha/beta ERD was stronger in Different trials than Same trials during the post-stimulus period, while right hemisphere alpha/beta ERD was stronger in Same trials than Different trials. A between-hemispheres contrast revealed no differences during Same trials, while post-stimulus alpha/beta ERD was stronger in the left hemisphere than the right during Different trials. Results were interpreted to suggest that predictive coding mechanisms lead to repetition suppression effects in Same trials. Mismatches arising from predictive coding mechanisms in Different trials shift subsequent working memory processing to the speech-dominant left hemisphere. Findings clarify how sensorimotor activity differentially supports working memory encoding and maintenance stages during speech discrimination tasks and have potential to inform sensorimotor models of speech perception and working memory.