Biology subjects

Poeppel, D.

Publications and source records attributed to Poeppel, D..

36 records · Page 2Linked to original sources

bioRxiv2020

Preferred auditory temporal processing regimes and auditory-motor interactions

Decoding the rich temporal dynamics of complex sounds such as speech is constrained by the underlying neuronal processing mechanisms. Oscillatory theories suggest the existence of one optimal perceptual performance regime at auditory stimulation rates in the delta to theta range (<10 Hz), but reduced performance in the alpha range (10-14 Hz) is controversial. Additionally, the widely discussed motor system contribution to timing remains unclear. We measured rate discrimination thresholds between 4-15 Hz, and auditory-motor coupling strength was estimated through auditory-motor synchronization. In a Bayesian model comparison, high auditory-motor synchronizers showed a larger range of constant optimal temporal judgments than low synchronizers, with performance decreasing in the alpha range. This evidence for optimal auditory processing in the theta range is consistent with preferred oscillatory regimes in auditory cortex that compartmentalize stimulus encoding and processing. The findings suggest, remarkably, that increased auditory-motor interaction might extend such an optimal range towards faster rates.

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bioRxiv2020

Overt and covert prosody are reflected in neurophysiological responses previously attributed to grammatical processing

AO_SCPLOWBSTRACTC_SCPLOWRecent neurophysiological research suggests that slow cortical activity tracks hierarchical syntactic structure during online sentence processing (e.g., Ding, Melloni, Zhang, Tian, & Poeppel, 2016). Here we tested an alternative hypothesis: electrophysiological activity peaks at sentence constituent frequencies reflect cortical tracking of overt or covert (implicit) prosodic grouping. In three experiments, participants listened to series of sentences while electroencephalography (EEG) was recorded. First, prosodic cues in the sentence materials were neutralized. We found an EEG spectral power peak elicited at a frequency that only tagged covert prosodic change, but not any major syntactic constituents. In the second experiment, participants listened to a series of sentences with overt prosodic grouping cues that either aligned or misaligned with the syntactic phrasing in the sentences (initial overt prosody trials). Immediately after each overt prosody trial, participants were presented with a second series of sentences (covert prosody trial) with all overt prosodic cues neutralized and asked to imagine the prosodic contour present in the previous, overt prosody trial. The EEG responses reflected an interactive relationship between syntactic processing and prosodic tracking at the frequencies of syntactic constituents (sentences and phrases): alignment of syntax and prosody boosted EEG responses, whereas their misalignment had an opposite effect. This was true for both overt and covert (imagined) prosody. We conclude that processing of both overt and covert prosody is reflected in the frequency tagged neural responses at sentence constituent frequencies, whereas identifying neural markers that are narrowly reflective of syntactic processing remains difficult and controversial.

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bioRxiv2020

Population-level differences in the neural substrates supporting Statistical Learning

The ability to extract regularities from the environment is arguably an adaptive characteristic of intelligent systems. In the context of speech, statistical learning is thought to be an important mechanism for language acquisition. By considering individual differences in speech auditory-motor synchronization, an independent component analysis of fMRI data revealed that the neural substrates of statistical word form learning are not fully shared across individuals. While a network of auditory and superior pre/motor regions is universally activated in the process of learning, a fronto-parietal network is instead additionally and selectively engaged by some individuals, boosting their performance. Furthermore, interfering with the use of this network via articulatory suppression (producing irrelevant speech during learning) normalizes performance across the entire sample. Our work provides novel insights on language-related statistical learning and reconciles previous contrasting findings, while highlighting the need to factor in fundamental individual differences for a precise characterization of cognitive phenomena.

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bioRxiv2020

Acoustically driven cortical delta oscillations underpin perceptual chunking

Oscillation-based models of speech perception postulate a cortical computational principle by which decoding is performed within a window structure derived by a segmentation process. In the syllable level segmentation is realized by a theta oscillator. We provide evidence for an analogous role of a delta oscillator at the phrasal level. We recorded MEG while participants performed a target identification task. Random-digit strings, with phrasal chunks of two digits, were presented at chunk rates inside or outside of the delta range. Strong periodicities were elicited by acoustic-driven chunk rates inside of delta, in superior and middle temporal areas and speech-motor integration areas. Periodicities were diminished or absent for chunk rates outside of the delta range, closely in line with behavioral performance. No periodicities were observed for top-down driven chunking conditions. Our findings show that phrasal chunking is correlated with acoustic-driven delta oscillations, expressing anatomically specific patterns of neuronal periodicities.Competing Interest StatementThe authors have declared no competing interest.View Full Text

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bioRxiv2020

Neural harmonics reflect grammaticality

Can neural rhythms reflect purely internal syntactic processes in multi-word constructions? To test this controversial conjecture - relevant to language in particular and cognition more broadly - we recorded electroencephalographic and behavioural data as participants listened to isochronously presented sentences of varying in syntactic complexity. Each trial comprised ten concatenated sentences and was either fully grammatical (regular) or rendered ungrammatical via randomly distributed word order violations. We found that attending the regular repetition of abstract syntactic categories (phrases and sentences) generates neural rhythms whose harmonics are mathematically independent of word rate. This permits to clearly separate endogenous syntactic rhythms from exogenous speech rhythms. We demonstrate that endogenous but not exogenous rhythms predict participants grammaticality judgements, and allow for the neural decoding of regular vs. irregular trials. Neural harmonic series constitute a new form of behaviourally relevant evidence for syntactic competence.

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bioRxiv2020

Neural dynamics of phoneme sequencing in real speech jointly encode order and invariant content

Speech consists of a continuously-varying acoustic signal. Yet human listeners experience it as a sequence of discrete units (phonemes and words). To identify how the brain continuously represents and updates speech units, we recorded two-hour magnetoencephalograms from 21 subjects listening to short narratives. Our encoding and decoding analyses show that the human brain uses a dynamic coding scheme to represent approximately three successive phonetic features at each time sample. These dynamic phonetic representations, not directly accessible from the acoustic signal, are active earlier when phonemes are more predictable, and are sustained when lexical identity is uncertain. The results reveal how phoneme sequences in natural speech are neurally represented and shed new light on how the human brain combines them to probe the mental lexicon. One sentence summaryThe human brain keeps track of the relative order of speech sound sequences by jointly encoding content and elapsed processing time

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bioRxiv2019

Crowdsourcing neuroscience: inter-brain coupling during face-to-face interactions outside the laboratory

When we feel connected or engaged during social behavior, are our brains in fact "in sync" in a formal, quantifiable sense? Most studies addressing this question use highly controlled tasks with homogenous subject pools. In an effort to take a more naturalistic approach, we collaborated with art institutions to crowd-source neuroscience data: Over the course of 5 years, we collected electroencephalogram (EEG) data from thousands of museum and festival visitors who volunteered to engage in a 10-minute face-to-face interaction. Pairs of participants with various levels of familiarity sat inside the Mutual Wave Machine--an art/science neurofeedback installation that uses Brain-Computer Interface technology (BCI) to translate real-time correlations of each pairs EEG activity into light patterns. Because such inter-participant EEG correlations are prone to noise contamination, in subsequent offline analyses we computed inter-brain synchrony using Imaginary Coherence and Projected Power Correlations, two synchrony metrics that are largely immune to instantaneous, noise-driven correlations. When applying these methods to two subsets of recorded data with the most consistent protocols, we found that pairs trait empathy, social closeness, engagement, and social behavior (joint action and eye contact) consistently predicted the extent to which their brain activity became synchronized, most prominently in low alpha ([~]7-10 Hz) and beta ([~]20-22 Hz) oscillations. These findings support an account where shared engagement and joint action drive coupled neural activity and behavior during dynamic, naturalistic social interactions. To our knowledge, this work constitutes a first demonstration that an interdisciplinary, real-world, crowdsourcing neuroscience approach may provide a promising method to collect large, rich datasets pertaining to real-life face-to-face interactions. Additionally, it is a demonstration of how the general public can participate and engage in the scientific process outside of the laboratory. Institutions such as museums, galleries, or any other organization where the public actively engages out of self-motivation, can help facilitate this type of citizen science research, and support the collection of large datasets under scientifically controlled experimental conditions. To further enhance the public interest for the out-of-the-lab experimental approach, the data and results of this study are disseminated through a website tailored to the general public (wp.nyu.edu/mutualwavemachine).

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bioRxiv2019

Brain-to-brain synchrony predicts long-term memory retention more accurately than individual brain measures

Little is known about the brain mechanisms that underpin how humans learn while interacting with one another in ecologically-valid environments (1-3). This is because cognitive neuroscientists typically measure one participant at a time in a highly constrained environment (e.g., inside a brain scanner). In the past few years, researchers have begun comparing brain responses across individuals (4-6) demonstrating that brain-to-brain synchrony can predict subsequent memory retention (7-9). Yet previous research has been constrained to non-interacting individuals. Surprisingly, the one study that was conducted in a group setting found that brain synchrony between students in a classroom predicted how engaged the students were, but not how much information they retained (10). This is unexpected because brain-to-brain synchrony is hypothesized to be driven, at least partially, by shared attention (11, 12), and shared attention has been shown to affect subsequent memory (13). Here we used EEG to simultaneously record brain activity from groups of four students and a teacher in a simulated classroom to investigate whether brain-to-brain synchrony, both between students and between the students and the teacher, can predict learning outcomes (Fig. 1A). We found that brain-to-brain synchrony in the Alpha band (8-12Hz) predicted students delayed memory retention. Further, moment-to-moment variation in alpha-band brain-to-brain synchrony discriminated between content that was retained or forgotten. Whereas student-to-student brain synchrony best predicted delayed memory retention at a zero time lag, student-to-teacher brain synchrony best predicted memory retention when adjusting for a [~]200 millisecond lag in the students brain activity relative to the teachers brain activity. These findings provide key new evidence for the importance of brain data collected simultaneously from groups of individuals in ecologically-valid settings.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC=\"FIGDIR/small/644047v2_fig1.gif\" ALT=\"Figure 1\">\nView larger version (43K):\norg.highwire.dtl.DTLVardef@21b335org.highwire.dtl.DTLVardef@7c9823org.highwire.dtl.DTLVardef@1e84b1dorg.highwire.dtl.DTLVardef@19b6f55_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Experimental setup and timeline. (A) Four students and a teacher were concurrently measured with EEG during a science lesson; (B) The lesson comprised four mini-lectures, each followed by a post-test. Pre-test and delayed post-tests were administered one week prior to and one week following the EEG recording session.\n\nC_FIG HighlightsO_LIElectroencephalogram (EEG) was concurrently recorded in a simulated classroom from groups of four students and a teacher.\nC_LIO_LIAlpha-band (8-12Hz) brain-to-brain synchrony predicted students performance in a delayed post-test.\nC_LIO_LIMoment-to-moment variation in alpha-band brain-to-brain synchrony indicated what specific information was retained by students.\nC_LIO_LIWhereas student-to-student brain synchrony best predicted learning at a zero time lag, student-to-teacher brain synchrony best predicted learning when adjusting for a [~]200 millisecond lag in the students brain activity relative to the teachers brain activity.\nC_LI

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bioRxiv2019

Understanding requires tracking: noise and knowledge interact in bilingual comprehension

Understanding speech in noise is a fundamental challenge for speech comprehension. This perceptual demand is amplified in a second language: it is a common experience in bars, train stations, and other noisy environments that degraded signal quality severely compromises second language comprehension. Through a novel design, paired with a carefully selected participant profile, we independently assessed signal-driven and knowledge-driven contributions to the brain bases of first versus second language processing. We were able to dissociate the neural processes driven by the speech signal from the processes that come from speakers knowledge of their first versus second languages. The neurophysiological data show that in combination with impaired access to top-down linguistic information in the second language, the locus of bilinguals difficulty in understanding second language speech in noisy conditions arises from a failure to successfully perform a basic, low-level process: cortical entrainment to speech signals above the syllabic level. Significance statementOver half of the worlds population is multilingual. Although proficiency in a second language improves over time, even to the point of reaching native-like proficiency, one persistent difficulty is understanding a second language in noisy environments (e.g. in crowds, train stations, etc.). We examined this processing impairment using a novel frequency-tagging paradigm with magnetoencephalography (MEG). We found that the reason underlying bilinguals difficulty in understanding second language speech in noisy conditions is induced by a failure to neurally track the operations reflecting structure (i.e., phrase) building.

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bioRxiv2019

The Anticipation of Events in Time

Humans use sensory input to anticipate events. The brains capacity to predict cues in time is commonly assumed to be modulated by two uncertainty parameters, the hazard rate (HR) of event probability and the uncertainty in time estimation, which increases with elapsed time. We investigate both assumptions by manipulating event probability density functions (PDF) in three sensory modalities. First we show, contrary to expectation, that perceptual systems use the reciprocal PDF - and not the HR - to model event probability density. Next we demonstrate that temporal uncertainty does not necessarily grow with elapsed time but also diminishes, depending on the event PDF. Finally we show that reaction time (RT) distributions comprise modality-specific and modality-independent components, the latter likely reflecting similarity in processing of probability density across sensory modalities. The results are consistent across vision, audition, and somatosensation, indicating that probability density is more fundamental than hazard rate in terms of the neural operations determining event anticipation and temporal uncertainty. Previous research identified neuronal activitity related to event probability in multiple levels of the cortical hierarchy such as early and higher sensory (V1, V4), association (LIP), motor and other areas. This work proposed that the elementary neuronal computation in estimation of probability across time is the HR. In contrast, our results suggest that the neurobiological implementation of probability estimation is based on a different, much simpler and more stable computation than HR: the reciprocal PDF of events in time.

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bioRxiv2019

Dynamics of functional networks for syllable and word-level processing

Speech comprehension requires the ability to temporally segment the acoustic input for higher-level linguistic analysis. Oscillation-based approaches suggest that low-frequency auditory cortex oscillations track syllable-sized acoustic information and therefore emphasize the relevance of syllabic-level processing for speech segmentation. Most linguistic approaches, however, focus on mapping from acoustic-phonemic representations to the lexical level. How syllabic processing interacts with higher levels of speech processing, beyond segmentation, including the anatomical and neurophysiological characteristics of the networks involved, is debated. Here we investigate the effects of lexical processing and the interactions with (acoustic) syllable processing by examining MEG data recorded in two experiments using a frequency-tagging paradigm. Participants listened to disyllabic words presented at a rate of 4 syllables/sec. Two conjectures were evaluated: (i) lexical processing of words activates a network that interacts with syllable processing; and (ii) syllable transitions contribute to word-level processing. We show that lexical content activated a left-lateralized frontal and superior and middle temporal network and increased the interaction between left middle temporal areas and auditory cortex (phase-phase coupling). Mere syllable-transition information, in contrast, activated a bilateral superior-, middle temporal and inferior frontal network and increased the interaction between those areas. Word and syllable processing interacted in superior and middle temporal areas (cross-frequency coupling), whereas syllable tracking (cerebro-acoustic coherence) decreased when word-level information was present. The data provide a new perspective on speech comprehension by demonstrating a contribution of an acoustic-syllabic to lexical processing route.\n\nSignificance statementThe comprehension of speech requires integrating information at multiple time scales, including phonemic, syllabic, and word scales. Typically, we think of decoding speech in the service of recognizing words as a process that maps from phonemic units to words. Recent neurophysiological evidence, however, has highlighted the relevance of syllable-sized chunks for segmenting speech. Is there more to recognizing spoken language? We provide neural evidence for brain network dynamics that support an interaction of lexical with syllable-level processing. We identify cortical networks that differ depending on whether lexical-semantic information versus low-level syllable-transition information is processed. Word- and syllable-level processing interact within MTG and STG. The data enrich our understanding of comprehension by implicating a mapping from syllabic to lexical representations.

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bioRxiv2019

Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy

Speech perception is mediated by both left and right auditory cortices, but with differential sensitivity to specific acoustic information contained in the speech signal. A detailed description of this functional asymmetry is missing, and the underlying models are widely debated. We analyzed cortical responses from 96 epilepsy patients with electrode implantation in left or right primary, secondary, and/or association auditory cortex. We presented short acoustic transients to reveal the stereotyped spectro-spatial oscillatory response profile of the auditory cortical hierarchy. We show remarkably similar bimodal spectral response profiles in left and right primary and secondary regions, with preferred processing modes in the theta ([~]4-8 Hz) and low gamma ([~]25-50 Hz) ranges. These results highlight that the human auditory system employs a two-timescale processing mode. Beyond these first cortical levels of auditory processing, a hemispheric asymmetry emerged, with delta and beta band ([~]3/15 Hz) responsivity prevailing in the right hemisphere and theta and gamma band ([~]6/40 Hz) activity in the left. These intracranial data provide a more fine-grained and nuanced characterization of cortical auditory processing in the two hemispheres, shedding light on the neural dynamics that potentially shape auditory and speech processing at different levels of the cortical hierarchy.\n\nAuthor summarySpeech processing is now known to be distributed across the two hemispheres, but the origin and function of lateralization continues to be vigorously debated. The asymmetric sampling in time (AST) hypothesis predicts that (1) the auditory system employs a two-timescales processing mode, (2) present in both hemispheres but with a different ratio of fast and slow timescales, (3) that emerges outside of primary cortical regions. Capitalizing on intracranial data from 96 epileptic patients we sensitively validated each of these predictions and provide a precise estimate of the processing timescales. In particular, we reveal that asymmetric sampling in associative areas is subtended by distinct two-timescales processing modes. Overall, our results shed light on the neurofunctional architecture of cortical auditory processing.

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bioRxiv2019

Theta and Gamma Bands Encode Acoustic Dynamics over Wide-ranging Timescales

Natural sounds have broadband modulation spectra and contain acoustic dynamics ranging from tens to hundreds of milliseconds. How does the human auditory system encode acoustic information over wide-ranging timescales to achieve sound recognition? Previous work (Teng et al., 2017) demonstrated a temporal coding preference in the auditory system for the theta (4 - 7 Hz) and gamma (30 - 45 Hz) ranges, but it remains unclear how acoustic dynamics between these two ranges is encoded. Here we generated artificial sounds with temporal structures over timescales from ~200 ms to ~30 ms and investigated temporal coding on different timescales in the human auditory cortex. Participants discriminated sounds with temporal structures at different timescales while undergoing magnetoencephalography (MEG) recording. The data show robust neural entrainment in the theta and the gamma bands, but not in the alpha and beta bands. Classification analyses as well as stimulus reconstruction reveal that the acoustic information of all timescales can be differentiated through the theta and gamma bands, but the acoustic dynamics in the theta and gamma ranges are preferentially encoded. We replicate earlier findings of multi-time scale processing and further demonstrate that the theta and gamma bands show generality of temporal coding across all timescales with comparable capacity. The results support the hypothesis that the human auditory cortex primarily encodes auditory information employing neural processes within two discrete temporal regimes. SignificanceNatural sounds contain rich acoustic dynamics over wide-ranging timescales, but perceptually relevant regularities often occupy specific temporal ranges. For instance, speech carries phonemic information on a shorter timescale than syllabic information at ~ 200 ms. How does the brain efficiently sample continuous acoustic input to perceive temporally structured sounds? We presented sounds with temporal structures at different timescales and measured cortical entrainment using magnetoencephalography. We found, unexpectedly, that the human auditory system preserves high temporal coding precision on two non-overlapping timescales, the slower (theta) and faster (gamma) bands, to track acoustic dynamics over all timescales. The results suggest that the acoustic environment which we experience as seamless and continuous is segregated by discontinuous neural processing, or sampled.

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bioRxiv2018

Speech Fine Structure Contains Critical Temporal Cues to Support Speech Segmentation

Segmenting the continuous speech stream into units for further perceptual and linguistic analyses is fundamental to speech recognition. The speech amplitude envelope (SE) has long been considered a fundamental temporal cue for segmenting speech. Does the temporal fine structure (TFS), a significant part of speech signals often considered to contain primarily spectral information, contribute to speech segmentation? Using magnetoencephalography, we show that the TFS entrains cortical oscillatory responses between 3-6 Hz and demonstrate, using mutual information analysis, that (i) the temporal information in the TFS can be reconstructed from a measure of frame-to-frame spectral change and correlates with the SE and (ii) that spectral resolution is key to the extraction of such temporal information. Furthermore, we show behavioural evidence that, when the SE is temporally distorted, the TFS provides cues for speech segmentation and aids speech recognition significantly. Our findings show that it is insufficient to investigate solely the SE to understand temporal speech segmentation, as the SE and the TFS derived from a band-filtering method convey comparable, if not inseparable, temporal information. We argue for a more synthetic view of speech segmentation - the auditory system groups speech signals coherently in both temporal and spectral domains.

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bioRxiv2018

Reading at the speed of speech: the rate of eye movements aligns with auditory language processing

Across languages, the speech signal is characterized by a predominant modulation of the amplitude spectrum between about 4.3-5.5Hz, reflecting the production and processing of linguistic information chunks (syllables, words) every [~]200ms. Interestingly, [~]200ms is also the typical duration of eye fixations during reading. Prompted by this observation, we demonstrate that German readers sample written text at [~]5Hz. A subsequent meta-analysis with 142 studies from 14 languages replicates this result, but also shows that sampling frequencies vary across languages between 3.9Hz and 5.2Hz, and that this variation systematically depends on the complexity of the writing systems (character-based vs. alphabetic systems, orthographic transparency). Finally, we demonstrate empirically a positive correlation between speech spectrum and eye-movement sampling in low-skilled readers. Based on this convergent evidence, we propose that during reading, our brains linguistic processing systems imprint a preferred processing rate, i.e., the rate of spoken language production and perception, onto the oculomotor system.

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bioRxiv2018

Electrocorticographic responses to time-compressed speech vary across the cortical auditory hierarchy

Human listeners understand spoken language across a variety of rates, but when speech is presented three times or more faster than its usual rate, it becomes unintelligible. How the brain achieves such tolerance and why speech becomes unintelligible above certain rates is still unclear. We addressed these questions using electrocorticography (ECoG) recordings in 7 epileptic patients (two female). Patients rated the intelligibility of sentences presented at the original rate (100%), speeded rates (33% or 66% of the original sentence duration) and a slowed rate (150%). We then examined which parameters of the neural response covary with the transition from intelligible to unintelligible speech. Specifically, we asked whether neural responses: 1) track the acoustic envelope of the incoming speech; 2) \"scale\" with speech rate, i.e. whether neural responses elicited by slowed and speeded sentences can be linearly scaled to match the responses to the original sentence. Behaviorally, intelligibility was at ceiling for speech rates of 66% and above, but dropped significantly for the 33% rate. At the neural level, Superior Temporal Gyrus regions (STG) in close proximity to A1 ( low-level) tracked the acoustic envelope and linearly scaled with the input across all speech rates, irrespective of intelligibility. In contrast, secondary auditory areas in the STG as well as the inferior frontal gyrus and angular gyrus ( high-level) tracked the acoustic envelope and linearly scaled with input only for intelligible speech. These results help reconcile seemingly contradictory previous findings and provide better understanding of how information processing unfolds along the cortical auditory hierarchy.

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bioRxiv2017

In spoken word recognition the future predicts the past

Speech is an inherently noisy and ambiguous signal. In order to fluently derive meaning, a listener must integrate contextual information to guide interpretations of the sensory input. While many studies have demonstrated the influence of prior context, the neural mechanisms supporting the integration of subsequent information remain unknown. Using magnetoencephalography, we analysed responses to spoken words with a varyingly ambiguous onset phoneme, the identity of which is later disambiguated at the lexical uniqueness point1. Our results uncover a three-level processing network. Subphonemic detail is preserved in primary auditory cortex over long timescales, and re-evoked at subsequent phoneme positions. Commitments to phonological categories occur in parallel, resolving on the shorter time-scale of ~450 ms. Finally, predictions are formed over likely lexical items. These findings provide evidence that future input determines the perception of earlier speech sounds by maintaining sensory features until they can be optimally integrated with top-down information.

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bioRxiv2017

Listening to speech induces coupling between auditory and motor cortices in an unexpectedly rate-restricted manner

The relation between perception and action remains a fundamental question for neuroscience. In the context of speech, existing data suggest an interaction between auditory and speech-motor cortices, but the underlying mechanisms remain incompletely characterized. We fill a basic gap in our understanding of the sensorimotor processing of speech by examining the synchronization between auditory and speech-motor regions over different speech rates, a fundamental parameter delimiting successful perception. First, using MEG we measure synchronization between auditory and speech-motor regions while participants listen to syllables at various rates. We show, surprisingly, that auditory-motor synchrony is significant only over a restricted range and is enhanced at ~4.5 Hz, a value compatible with the mean syllable rate across languages. Second, neural modeling reveals that this modulated coupling plausibly emerges as a consequence of the underlying neural architecture. The findings suggest that the auditory-motor interaction should be interpreted rather conservatively when considering phase space.

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