Biology subjects

Davis, M. H.

Publications and source records attributed to Davis, M. H..

13 recordsLinked to original sources

bioRxiv2026

Flexible neural encoding predicts the comprehension of degraded speech

How listeners track a variable and continuous acoustic speech signal and parse it into meaningful linguistic representations is a question central to cognitive neuroscience. Moreover, the resilience of this process to acoustic signal degradation is not fully understood. The current study consists of a listening task wherein participants (n = 38) were presented with a naturalistic story whilst undergoing continuous electroencephalography (EEG). Critically, we manipulated access to speech information over two independent dimensions: Spectral clarity, which ranged from unprocessed to severely spectrally degraded; and language, which was either English, spoken by the participants, or Dutch, an incomprehensible language that is closely related to English. All stimuli were produced by the same bilingual speaker. We applied banded regression to model the neural response to a set of acoustic and linguistically derived features. We found that there is no single speech feature for which neural encoding reliably predicted speech understanding in individual listeners or conditions. Yet, differences in feature weights between experimental conditions can be combined into a composite score that strongly predicted individual subjective comprehension of spectrally degraded but linguistically accessible speech in data from held-out participant. Hence, the manner in which neural encoding flexibly adapts to listening context is associated with advantageous perceptual strategies for degraded speech. These findings underscore the complex interplay between low- and high-level features during speech listening and illustrate inter-condition differences in the neural encoding of these properties. Our results highlight natural variation within and between individuals in the encoding of acoustic and linguistic features which provides a potential pathway towards individualised assessment of clinical populations.

neuroscience↗

bioRxiv2025

Tracking visual rhythms: a concert of sensory and motor simulation

When will I see something and what will it be? Temporal predictions are crucial for adaptive interaction with the environment and are typically accompanied by predictions about sensory content, yet these two types of what and when predictions are usually studied separately. Specifically, oscillatory phase-coupling (or entrainment) has been proposed to align our neural sensitivity with likely moments of stimulus appearance, however these accounts ignore that predictions about when something will appear are usually accompanied by predictions about what it will be. Thus, temporal predictions may not enhance all sensory processing but rather modulate particular channels encoding predicted content. We here demonstrate oscillatory phase-coupling in vision and show how it relates to content-specific encoding. In a magnetoencephalography (MEG) study, participants observed rhythmic Gabors at 1.33 or 2 Hz with predictable orientations. They judged the timing or orientation of a delayed probe which manipulated the requirement to covertly maintain the sequence rhythm. We found sustained oscillatory phase-coupling to the entrained rhythm in motor areas specifically when participants judged stimulus timing, where its extent was associated with perceptual performance. Meanwhile, neural decoding revealed content predictions in early visual areas ( what) that fluctuated in line with temporal predictions ( when). These temporally-specific content predictions appeared regardless of task instruction but were correlated and phase-aligned with the motor phase-coupling during timing judgements. These findings suggest that temporal predictions may be derived from motor readouts of temporally-specific sensory predictions, with broad implications for our understanding of entrainment and prediction, and how we represent time more generally.

neuroscience↗

bioRxiv2023

Convergent neural signatures of speech prediction error across space, time and frequency

We used MEG and fMRI to determine how predictions are combined with speech input in superior temporal cortex. We compared neural responses to bisyllabic spoken words in which the first syllable strongly or weakly predicts the form of the second syllable (e.g. "bingo" versus "tango"). We further compared neural responses to the same second syllables when heard in an unfamiliar pseudoword and therefore in a situation in which predictions mismatch with sensory input (e.g. "snigo" and "meago"). Across multiple imaging modalities and analysis approaches (including information-based pattern analysis methods), we show that neural representations of second syllables are suppressed by strong predictions when predictions match sensory input. However, neural representations of the same second syllables show the opposite effect (i.e. enhanced representations following strongly than weakly-predicting syllables) when predictions mismatch with sensory input. Computational simulations show that this interaction between prediction strength and (mis)match is consistent with prediction error but not alternative (sharpened signal) computations. Neural signatures of prediction error are observed early (beginning 200 ms after the onset of the second syllable), localise to early auditory regions (in fMRI, bilateral Heschls gyrus and STG) and are expressed as changes in low-frequency (theta and alpha) power. Our study therefore provides convergent neural evidence that speech perception is supported by the computation of prediction errors in auditory brain regions. These prediction error computations play a central role in the identification of familiar spoken words and perception of unfamiliar pseudowords.

neuroscience↗

bioRxiv2022

Development of an amplicon nanopore sequencing strategy for detection of mutations conferring intermediate resistance to vancomycin in Staphylococcus aureus strains

Staphylococcus aureus is a major cause of bacteremia and other hospital-acquired infections. The cell-wall active antibiotic vancomycin is commonly used to treat both methicillin-resistant (MRSA) and sensitive (MSSA) infections, but vancomycin intermediate S. aureus (VISA) variants can arise through de novo mutations. Here we performed pilot experiments to develop a combined PCR/long-read sequencing-based method for detection of previously known VISA-causing mutations. We amplified 16 genes (walR, walK, rpoB, graR, graS, vraF, vraG, stpI, vraR, vraS, agrA, sarA, clpP, ccpA, prsA, and yvqF) known from prior studies to be associated with mutations responsible for VISA as 10 amplicons and sequenced amplicon pools as long-reads with Oxford Nanopore adapter ligation on Flongle flow cells. We then detected mutations by mapping reads against a parental consensus or known reference sequence and comparing called variants against a database of known VISA mutations from laboratory selection. There was high (>1000x) coverage of each amplicon in the pool, no relationship between amplicon length and coverage, and the ability to detect the causative mutation (walK 646C>G) in a VISA mutant derived from the USA300 strain (N384-3 from parental strain N384). Mixing mutant (N384-3) and parental (N384) DNA at various ratios from 0 to 1 mutant suggested a mutation detection threshold of roughly the average minor allele frequency of 6.5% at 95% confidence (two standard errors above mean mutation frequency). The study lays the groundwork for direct S. aureus antibiotic phenotype inference using rapid nanopore sequencing from clinical samples. ImportanceBacteremia mortality is known to increase rapidly with time after infection, making rapid diagnostics and treatment necessary. Successful treatment depends on correct administration of antibiotics based on knowledge of strain antibiotic susceptibility. Staphylococcus aureus is a major causative agent of bacteremia and is also increasingly antibiotic resistant. In this work, we develop a method to improve detection of a complex, polygenic antibiotic resistance phenotype in S. aureus, vancomycin-intermediate resistance (VISA) through long-read genomic sequencing of amplicons representing genes most commonly mutated in VISA selection. This method both speeds up VISA determination relative to purely culture-based detection and incorporates the most comprehensive database of VISA genetic determinants known to date.

microbiology↗

bioRxiv2022

Intelligibility improves the perception of speech rhythm

Auditory rhythms are ubiquitous in music, speech, and other everyday sounds. Yet, it is unclear how perceived rhythms arise from the repeating structure of sounds. For speech, it is unclear whether rhythm is solely derived from acoustic properties (e.g., rapid amplitude changes), or if it is also influenced by the linguistic units (syllables, words, etc.) that listeners extract from intelligible speech. Here, we present three experiments in which participants were asked to detect an irregularity in rhythmically spoken speech sequences. In each experiment, we reduce the number of possible stimulus properties that differ between intelligible and unintelligible speech sounds and show that these acoustically-matched intelligibility conditions nonetheless lead to differences in rhythm perception. In Experiment 1, we replicate a previous study showing that rhythm perception is improved for intelligible (16-channel vocoded) as compared to unintelligible (1-channel vocoded) speech - despite near-identical broadband amplitude modulations. In Experiment 2, we use spectrally-rotated 16-channel speech to show the effect of intelligibility cannot be explained by differences in spectral complexity. In Experiment 3, we compare rhythm perception for sine-wave speech signals when they are heard as non-speech (for naive listeners), and subsequent to training, when identical sounds are perceived as speech. In all cases, detection of rhythmic regularity is enhanced when participants perceive the stimulus as speech compared to when they do not. Together, these findings demonstrate that intelligibility enhances the perception of timing changes in speech, which is hence linked to processes that extract abstract linguistic units from sound.

neuroscience↗

bioRxiv2022

Causal contributions of the domain-general (Multiple Demand) and the language-selective brain networks to perceptual and semantic challenges in speech comprehension

1.Listening to spoken language engages domain-general Multiple Demand (MD, fronto-parietal) regions of the human brain, in addition to domain-selective (fronto-temporal) language regions, particularly when comprehension is challenging. However, there is limited evidence that the MD network makes a functional contribution to core aspects of comprehension. In a behavioural study of volunteers (n=19) with chronic brain lesions, but without aphasia, we assessed the causal role of these networks in perceiving, comprehending and adapting to challenging spoken sentences. A first task measured word report for acoustically degraded (noise-vocoded) sentences before and after training. Participants with greater damage to MD but not language regions required more vocoder channels to achieve 50% word report indicating impaired perception. Perception improved following training, reflecting adaptation to acoustic degradation, but perceptual learning was unrelated to lesion location or extent. A second task used sentence coherence judgements to measure the speed and accuracy of comprehension of spoken sentences using lower-frequency meanings of semantically ambiguous words. Comprehension accuracy was high and unaffected by lesion location or extent. The availability of the lower-frequency meaning, as measured in a subsequent word association task, increased following comprehension (word-meaning priming). Word-meaning priming was reduced for participants with greater damage to language but not MD regions. We conclude that language and MD networks make dissociable contributions to challenging speech comprehension: using recent experience to update word meaning preferences depends on language specialised regions, whereas the domain-general MD network plays a causal role in reporting words from degraded speech.

neuroscience↗

bioRxiv2021

Visual speech is processed differently in auditory and visual cortex: evidence from MEG and partial coherence analysis

Speech perception in noisy environments is enhanced by seeing facial movements of communication partners. However, the neural mechanisms by which audio and visual speech are combined are not fully understood. We explore MEG phase locking to auditory and visual signals in MEG recordings from 14 human participants (6 females, 8 males) that reported words from single spoken sentences. We manipulated the acoustic clarity and visual speech signals such that critical speech information is present in auditory, visual or both modalities. MEG coherence analysis revealed that both auditory and visual speech envelopes (auditory amplitude modulations and lip aperture changes) were phase-locked to 2-6Hz brain responses in auditory and visual cortex, consistent with entrainment to syllable-rate components. Partial coherence analysis was used to separate neural responses to correlated audio-visual signals and showed non-zero phase locking to auditory envelope in occipital cortex during audio-visual (AV) speech. Furthermore, phase-locking to auditory signals in visual cortex was enhanced for AV speech compared to audio-only (AO) speech that was matched for intelligibility. Conversely, auditory regions of the superior temporal gyrus (STG) did not show above-chance partial coherence with visual speech signals during AV conditions, but did show partial coherence in VO conditions. Hence, visual speech enabled stronger phase locking to auditory signals in visual areas, whereas phase-locking of visual speech in auditory regions only occurred during silent lip-reading. Differences in these cross-modal interactions between auditory and visual speech signals are interpreted in line with cross-modal predictive mechanisms during speech perception. Significance StatementVerbal communication in noisy environments is challenging, especially for hearing-impaired individuals. Seeing facial movements of communication partners improves speech perception when auditory signals are degraded or absent. The neural mechanisms supporting lip-reading or audio-visual benefit are not fully understood. Using MEG recordings and partial coherence analysis we show that speech information is used differently in brain regions that respond to auditory and visual speech. While visual areas use visual speech to improve phase-locking to auditory speech signals, auditory areas do not show phase-locking to visual speech unless auditory speech is absent and visual speech is used to substitute for missing auditory signals. These findings highlight brain processes that combine visual and auditory signals to support speech understanding.

neuroscience↗

bioRxiv2020

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 /haid{ezh}/). 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) proposes that spoken word recognition involves comparing heard and predicted speech sounds and using prediction error to update lexical representations. Increased lexical uncertainty in words like 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 neighbouring 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 /haid{ezh}/ 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 StatementEffective speech perception is critical to daily life and involves computations that combine speech signals with prior knowledge of spoken words; that is, 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.

neuroscience↗

bioRxiv2020

Sustained neural rhythms reveal endogenous oscillations supporting speech perception

Rhythmic sensory or electrical stimulation will produce rhythmic brain responses. These rhythmic responses are often interpreted as endogenous neural oscillations aligned (or "entrained") to the stimulus rhythm. However, stimulus-aligned brain responses can also be explained as a sequence of evoked responses, which only appear regular due to the rhythmicity of the stimulus, without necessarily involving underlying neural oscillations. To distinguish evoked responses from true oscillatory activity, we tested whether rhythmic stimulation produces oscillatory responses which continue after the end of the stimulus. Such sustained effects provide evidence for true involvement of neural oscillations. In Experiment 1, we found that rhythmic intelligible, but not unintelligible speech produces oscillatory responses in magnetoencephalography (MEG) which outlast the stimulus at parietal sensors. In Experiment 2, we found that transcranial alternating current stimulation (tACS) leads to rhythmic fluctuations in speech perception outcomes after the end of electrical stimulation. We further report that the phase relation between electroencephalography (EEG) responses and rhythmic intelligible speech can predict the tACS phase that leads to most accurate speech perception. Together, we provide fundamental results for several lines of research - including neural entrainment and tACS - and reveal endogenous neural oscillations as a key underlying principle for speech perception.

neuroscience↗

bioRxiv2020

Rapid computations of spectrotemporal prediction error support perception of degraded speech

Human speech perception can be described as Bayesian perceptual inference but how are these Bayesian computations instantiated neurally? We use magnetoencephalographic recordings of brain responses to degraded spoken words as a function of signal quality and prior knowledge to demonstrate that spectrotemporal modulations in speech are more clearly represented in neural responses than alternative speech representations (e.g. spectrogram or articulatory features). We found an interaction between speech signal quality and expectations from prior written text on the quality of neural representations; increased signal quality enhanced neural representations of speech that mismatched with prior expectations, but led to greater suppression of speech that matched prior expectations. This interaction is a unique neural signature of prediction error computations and already apparent in neural responses within 250 ms of speech input. Our findings contribute towards the detailed specification of a computational model of speech perception based on predictive coding frameworks.

neuroscience↗

bioRxiv2019

Perception of rhythmic speech is modulated by focal bilateral tACS

Several recent studies have used transcranial alternating stimulation (tACS) to demonstrate a causal role of neural oscillatory activity in speech processing. In particular, it has been shown that the ability to understand speech in a multi-speaker scenario or background noise depends on the timing of speech presentation relative to simultaneously applied tACS. However, it is possible that tACS did not change actual speech perception but rather auditory stream segregation. In this study, we tested whether the phase relation between tACS and the rhythm of degraded words, presented in silence, modulates word report accuracy. We found strong evidence for a tACS-induced modulation of speech perception, but only if the stimulation was applied bilaterally using ring electrodes (not for unilateral left hemisphere stimulation with square electrodes). These results were only obtained when data was analyzed using a statistical approach that was identified as optimal in a previous simulation study. The effect was driven by a phasic disruption of word report scores. Our results suggest a causal role of neural entrainment for speech perception and emphasize the importance of optimizing stimulation protocols and statistical approaches for brain stimulation research.

neuroscience↗

bioRxiv2019

How to test for oscillatory modulation of neural function and behaviour

Research on whether perception or other processes depend on the phase of neural oscillations is rapidly gaining popularity. However, it is unknown which methods are optimally suited to evaluate the hypothesized phase effect. Using a simulation approach, we here test the ability of different methods to detect such an effect on dichotomous (e.g., \"hit\" vs \"miss\") and continuous (e.g., scalp potentials) response variables. We manipulated parameters that characterise the phase effect or define the experimental approach to test for this effect. For each parameter combination and response variable, we identified an optimal method. We found that methods regressing single-trial responses on circular (sine and cosine) predictors perform best for all of the simulated parameters, regardless of the nature of the response variable (dichotomous or continuous). In sum, our study lays a foundation for optimized experimental designs and analyses in future studies investigating the role of phase for neural and behavioural responses. We provide MATLAB code for the statistical methods tested.

neuroscience↗

bioRxiv2017

Neural decoding of bistable sounds reveals an effect of intention on perceptual organization

Auditory signals arrive at the ear as a mixture that the brain must decompose into distinct sources, based to a large extent on acoustic properties of the sounds. An important question concerns whether listeners have voluntary control over how many sources they perceive. This has been studied using pure tones H and L presented in the repeating pattern HLH-HLH-, which can form a bistable percept, heard either as an integrated whole (HLH-) or as segregated into high (H-H-) and low (-L--) sequences. Although instructing listeners to try to integrate or segregate sounds affects reports of what they hear, this could reflect a response bias rather than a perceptual effect. We had human listeners (15 males, 12 females) continuously report their perception of such sequences and recorded neural activity using magneto-encephalography. During neutral listening, a classifier trained on patterns of neural activity distinguished between periods of integrated and segregated perception. In other conditions, participants tried to influence their perception by allocating attention either to the whole sequence, or to a subset of the sounds. They reported hearing the desired percept for a greater proportion of time than when listening neutrally. Critically, neural activity supported these reports; stimulus-locked brain responses in auditory cortex were more likely to resemble the signature of segregation when participants tried to hear segregation than when attempting to perceive integration. These results indicate that listeners can influence how many sound sources they perceive, as reflected in neural responses that track both the input and its perceptual organization.\n\nSignificance StatementCan we consciously influence our perception of the external world? We address this question using sound sequences that can be heard either as coming from a single source, or as two distinct auditory streams. Listeners reported spontaneous changes in their perception between these two interpretations while we recorded neural activity to identify signatures of such integration and segregation. They also indicated that they could, to some extent, choose between these alternatives. This claim was supported by corresponding changes in responses in auditory cortex. By linking neural and behavioral correlates of perception we demonstrate that the number of objects we perceive can depend not only on the physical attributes of our environment, but also on how we intend to experience it.

neuroscience↗