Tone Sequences Research Articles

Cascades of Periodic Solutions in a Neural Circuit With Delays and Slow-Fast Dynamics

We analyse periodic solutions in a system of four delayed differential equations forced by periodic inputs representing two competing neural populations connected with fast mutual excitation and slow delayed inhibition. The combination of mechanisms generates a rich dynamical structure that we are able to characterize using slow-fast dissection and a binary classification of states. We previously proved the existence conditions of all possible states 1:1 locked to the inputs and applied this analysis to the tracking of the rhythms perceived when listening to alternating sequences of low and high tones. Here we extend this analysis using analytical and computational tools by proving the existence a set of n:1 periodically locked states and their location in parameter space. Firstly we examine cycle skipping states and find that they accumulate in an infinite cascade of period-incrementing bifurcations with increasing periods for decreasing values of the local input strength. Secondly we analyse periodic solutions that alternate between 1:1 locked states that repeat after an integer multiple of the input period (swapping states). We show that such states accumulate in similar bifurcation cascades with decreasing values of the lateral input strength. We report a parameter-dependent scaling constant for the ratio of widths of successive regions in the cascades, which generalises across cycle skipping and swapping states. The periodic states reported here - emergent behaviours in the model - can be linked to known phenomena in auditory perception that are beyond the original scope of the model’s design.

Sensory Attenuation of the Auditory P2 Differentiates Self- from Partner-Produced Sounds during Joint Action.

Successful human interaction relies on people's ability to differentiate between the sensory consequences of their own and others' actions. Research in solo action contexts has identified sensory attenuation, that is, the selective perceptual or neural dampening of the sensory consequences of self-produced actions, as a potential marker of the distinction between self- and externally produced sensory consequences. However, very little research has examined whether sensory attenuation distinguishes self- from partner-produced sensory consequences in joint action contexts. The current study examined whether sensory attenuation of the auditory N1 or P2 ERPs distinguishes self- from partner-produced tones when pairs of people coordinate their actions to produce tone sequences that match a metronome pace. We did not find evidence of auditory N1 attenuation for either self- or partner-produced tones. Instead, the auditory P2 was attenuated for self-produced tones compared to partner-produced tones within the joint action. These findings indicate that self-specific attenuation of the auditory P2 differentiates the sensory consequences of one's own from others' actions during joint action. These findings also corroborate recent evidence that N1 attenuation may be driven by general rather than action-specific processes and support a recently proposed functional dissociation between auditory N1 and P2 attenuation.

Standard Tone Stability as a Manipulation of Precision in the Oddball Paradigm: Modulation of Prediction Error Responses to Fixed-Probability Deviants

Electrophysiological sensory deviance detection signals, such as the mismatch negativity (MMN), have been interpreted from the predictive coding framework as manifestations of prediction error (PE). From a frequentist perspective of the classic oddball paradigm, deviant stimuli are unexpected because of their low probability. However, the amount of PE elicited by a stimulus can be dissociated from its probability of occurrence: when the observer cannot make confident predictions, any event holds little surprise value, no matter how improbable. Here we tested the hypothesis that the magnitude of the neural response elicited to an improbable sound (D) would scale with the precision of the prediction derived from the repetition of another sound (S), by manipulating repetition stability. We recorded the Electroencephalogram (EEG) from 20 participants while passively listening to 4 types of isochronous pure tone sequences differing in the probability of the S tone (880 Hz) while holding constant the probability of the D tone [1,046 Hz; p(D) = 1/11]: Oddball [p(S) = 10/11]; High confidence (7/11); Low confidence (4/11); and Random (1/11). Tones of 9 different frequencies were equiprobably presented as fillers [p(S) + p(D) + p(F) = 1]. Using a mass-univariate non-parametric, cluster-based correlation analysis controlling for multiple comparisons, we found that the amplitude of the deviant-elicited ERP became more negative with increasing S probability, in a time-electrode window consistent with the MMN (ca. 120–200 ms; frontal), suggesting that the strength of a PE elicited to an improbable event indeed increases with the precision of the predictive model.

A neural signature of regularity in sound is reduced in older adults

Sensitivity to repetitions in sound amplitude and frequency is crucial for sound perception. As with other aspects of sound processing, sensitivity to such patterns may change with age, and may help explain some age-related changes in hearing such as segregating speech from background sound. We recorded magnetoencephalography to characterize differences in the processing of sound patterns between younger and older adults. We presented tone sequences that either contained a pattern (made of a repeated set of tones) or did not contain a pattern. We show that auditory cortex in older, compared to younger, adults is hyperresponsive to sound onsets, but that sustained neural activity in auditory cortex, indexing the processing of a sound pattern, is reduced. Hence, the sensitivity of neural populations in auditory cortex fundamentally differs between younger and older individuals, overresponding to sound onsets, while underresponding to patterns in sounds. This may help to explain some age-related changes in hearing such as increased sensitivity to distracting sounds and difficulties tracking speech in the presence of other sound.

Towards a unifying basis of auditory thresholds: Thresholds for multicomponent stimuli

Sounds consisting of multiple simultaneous or consecutive components can be detected by listeners when the stimulus levels of the components are lower than those needed to detect the individual components alone. The mechanisms underlying such spectral, spectrotemporal, temporal, or across-ear integration are not completely understood. Here, we report threshold measurements from human subjects for multicomponent stimuli (tone complexes, tone sequences, diotic or dichotic tones) and for their individual sinusoidal components in quiet. We examine whether the data are compatible with the detection model developed by Heil, Matysiak, and Neubauer (HMN model) to account for temporal integration (Heil et al. 2017), and we compare its performance to that of the statistical summation model (Green 1958), the model commonly used to account for spectral and spectrotemporal integration. In addition, we compare the performance of both models with respect to previously published thresholds for sequences of identical tones and for diotic tones. The HMN model is similar to the statistical summation model but is based on the assumption that the decision variable is a number of sensory events generated by the components via independent Poisson point processes. The rate of events is low without stimulation and increases with stimulation. The increase is proportional to the time-varying amplitude envelope of the bandpass-filtered component(s) raised to an exponent of 3. For an ideal observer, the decision variable is the sum of the events from all channels carrying information, for as long as they carry information. We find that the HMN model provides a better account of the thresholds for multicomponent stimuli than the statistical summation model, and it offers a unifying account of spectral, spectrotemporal, temporal, and across-ear integration at threshold.

Dimension-selective attention and dimensional salience modulate cortical tracking of acoustic dimensions

Some theories of auditory categorization suggest that auditory dimensions that are strongly diagnostic for particular categories - for instance voice onset time or fundamental frequency in the case of some spoken consonants - attract attention. However, prior cognitive neuroscience research on auditory selective attention has largely focused on attention to simple auditory objects or streams, and so little is known about the neural mechanisms that underpin dimension-selective attention, or how the relative salience of variations along these dimensions might modulate neural signatures of attention. Here we investigate whether dimensional salience and dimension-selective attention modulate the cortical tracking of acoustic dimensions. In two experiments, participants listened to tone sequences varying in pitch and spectral peak frequency; these two dimensions changed at different rates. Inter-trial phase coherence (ITPC) and amplitude of the EEG signal at the frequencies tagged to pitch and spectral changes provided a measure of cortical tracking of these dimensions. In Experiment 1, tone sequences varied in the size of the pitch intervals, while the size of spectral peak intervals remained constant. Cortical tracking of pitch changes was greater for sequences with larger compared to smaller pitch intervals, with no difference in cortical tracking of spectral peak changes. In Experiment 2, participants selectively attended to either pitch or spectral peak. Cortical tracking was stronger in response to the attended compared to unattended dimension for both pitch and spectral peak. These findings suggest that attention can enhance the cortical tracking of specific acoustic dimensions rather than simply enhancing tracking of the auditory object as a whole.

Network Analysis of Human Brain Connectivity Reveals Neural Fingerprints of a Compositionality Bias in Signaling Systems.

Compositionality is a hallmark of human language and other symbolic systems: a finite set of meaningful elements can be systematically combined to convey an open-ended array of ideas. Compositionality is not uniformly distributed over expressions in a language or over individuals' communicative behavior: at both levels, variation is observed. Here, we investigate the neural bases of interindividual variability by probing the relationship between intrinsic characteristics of brain networks and compositional behavior. We first collected functional resting-state and diffusion magnetic resonance imaging data from a large participant sample (N = 51). Subsequently, participants took part in two signaling games. They were instructed to learn and reproduce an auditory symbolic system of signals (tone sequences) associated with affective meanings (human faces expressing emotions). Signal-meaning mappings were artificial and had to be learned via repeated signaling interactions. We identified a temporoparietal network in which connection length was related to the degree of compositionality introduced in a signaling system by each player. Graph-theoretic analysis of resting-state functional connectivity revealed that, within that network, compositional behavior was associated with integration measures in 2 semantic hubs: the left posterior cingulate cortex and the left angular gyrus. Our findings link individual variability in compositional biases to variation in the anatomy of semantic networks and in the functional topology of their constituent units.

Switching perception of musical meters by listening to different acoustic cues of biphasic sound stimulus.

Meter is one of the core features of music perception. It is the cognitive grouping of regular sound sequences, typically for every 2, 3, or 4 beats. Previous studies have suggested that one can not only passively perceive the meter from acoustic cues such as loudness, pitch, and duration of sound elements, but also actively perceive it by paying attention to isochronous sound events without any acoustic cues. Studying the interaction of top-down and bottom-up processing in meter perception leads to understanding the cognitive system’s ability to perceive the entire structure of music. The present study aimed to demonstrate that meter perception requires the top-down process (which maintains and switches attention between cues) as well as the bottom-up process for discriminating acoustic cues. We created a “biphasic” sound stimulus, which consists of successive tone sequences designed to provide cues for both the triple and quadruple meters in different sound attributes, frequency, and duration. Participants were asked to focus on either frequency or duration of the stimulus, and to answer how they perceived meters on a five-point scale (ranged from “strongly triple” to “strongly quadruple”). As a result, we found that participants perceived different meters by switching their attention to specific cues. This result adds evidence to the idea that meter perception involves the interaction between top-down and bottom-up processes.

Predictive Uncertainty Underlies Auditory Boundary Perception

Anticipating the future is essential for efficient perception and action planning. Yet the role of anticipation in event segmentation is understudied because empirical research has focused on retrospective cues such as surprise. We address this concern in the context of perception of musical-phrase boundaries. A computational model of cognitive sequence processing was used to control the information-dynamic properties of tone sequences. In an implicit, self-paced listening task (N = 38), undergraduates dwelled longer on tones generating high entropy (i.e., high uncertainty) than on those generating low entropy (i.e., low uncertainty). Similarly, sequences that ended on tones generating high entropy were rated as sounding more complete (N = 31 undergraduates). These entropy effects were independent of both the surprise (i.e., information content) and phrase position of target tones in the original musical stimuli. Our results indicate that events generating high entropy prospectively contribute to segmentation processes in auditory sequence perception, independently of the properties of the subsequent event.

Context Sensitivity across Multiple Time scales with a Flexible Frequency Bandwidth.

Everyday auditory streams are complex, including spectro-temporal content that varies at multiple timescales. Using EEG, we investigated the sensitivity of human auditory cortex to the content of past stimulation in unattended sequences of equiprobable tones. In 3 experiments including 82 participants overall, we found that neural responses measured at different latencies after stimulus onset were sensitive to frequency intervals computed over distinct timescales. Importantly, early responses were sensitive to a longer history of stimulation than later responses. To account for these results, we tested a model consisting of neural populations with frequency-specific but broad tuning that undergo adaptation with exponential recovery. We found that the coexistence of neural populations with distinct recovery rates can explain our results. Furthermore, the adaptation bandwidth of these populations depended on spectral context-it was wider when the stimulation sequence had a wider frequency range. Our results provide electrophysiological evidence as well as a possible mechanistic explanation for dynamic and multiscale context-dependent auditory processing in the human cortex.

Atypical beta power fluctuation while listening to an isochronous sequence in dyslexia

ObjectiveDevelopmental dyslexia is a reading disorder that features difficulties in perceiving and tracking rhythmic regularities in auditory streams, such as speech and music. Studies on typical healthy participants have shown that power fluctuations of neural oscillations in beta band (15–25 Hz) reflect an essential mechanism for tracking rhythm or entrainment and relate to predictive timing and attentional processes. Here we investigated whether adults with dyslexia have atypical beta power fluctuation. MethodsThe electroencephalographic activities of individuals with dyslexia (n = 13) and typical control participants (n = 13) were measured while they passively listened to an isochronous tone sequence (2 Hz presentation rate). The time–frequency neural activities generated from auditory cortices were analyzed. ResultsThe phase of beta power fluctuation at the 2 Hz stimulus presentation rate differed and appeared opposite between individuals with dyslexia and controls. ConclusionsAtypical beta power fluctuation might reflect deficits in perceiving and tracking auditory rhythm in dyslexia. SignificanceThese findings extend our understanding of atypical neural activities for tracking rhythm in dyslexia and could inspire novel methods to objectively measure the benefits of training, and predict potential benefit of auditory rhythmic rehabilitation programs on an individual basis.

Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge

Humans are highly attuned to patterns in the environment. This ability to detect environmental patterns, referred to as statistical learning, plays a key role in many diverse aspects of cognition. However, the spatiotemporal neural mechanisms underlying implicit statistical learning, and how these mechanisms may relate or give rise to explicit learning, remain poorly understood. In the present study, we investigated these different aspects of statistical learning by using an auditory nonlinguistic statistical learning paradigm combined with magnetoencephalography. Twenty-four healthy volunteers were exposed to structured and random tone sequences, and statistical learning was quantified by neural entrainment. Already early during exposure, participants showed strong entrainment to the embedded tone patterns. A significant increase in entrainment over exposure was detected only in the structured condition, reflecting the trajectory of learning. While source reconstruction revealed a wide range of brain areas involved in this process, entrainment in areas around the left pre-central gyrus as well as right temporo-frontal areas significantly predicted behavioral performance. Sensor level results confirmed this relationship between neural entrainment and subsequent explicit knowledge. These results give insights into the dynamic relation between neural entrainment and explicit learning of triplet structures, suggesting that these two aspects are systematically related yet dissociable. Neural entrainment reflects robust, implicit learning of underlying patterns, whereas the emergence of explicit knowledge, likely built on the implicit encoding of structure, varies across individuals and may depend on factors such as sufficient exposure time and attention.

Neural Encoding of Auditory Statistics.

The human brain extracts statistical regularities embedded in real-world scenes to sift through the complexity stemming from changing dynamics and entwined uncertainty along multiple perceptual dimensions (e.g., pitch, timbre, location). While there is evidence that sensory dynamics along different auditory dimensions are tracked independently by separate cortical networks, how these statistics are integrated to give rise to unified objects remains unknown, particularly in dynamic scenes that lack conspicuous coupling between features. Using tone sequences with stochastic regularities along spectral and spatial dimensions, this study examines behavioral and electrophysiological responses from human listeners (male and female) to changing statistics in auditory sequences and uses a computational model of predictive Bayesian inference to formulate multiple hypotheses for statistical integration across features. Neural responses reveal multiplexed brain responses reflecting both local statistics along individual features in frontocentral networks, together with global (object-level) processing in centroparietal networks. Independent tracking of local surprisal along each acoustic feature reveals linear modulation of neural responses, while global melody-level statistics follow a nonlinear integration of statistical beliefs across features to guide perception. Near identical results are obtained in separate experiments along spectral and spatial acoustic dimensions, suggesting a common mechanism for statistical inference in the brain. Potential variations in statistical integration strategies and memory deployment shed light on individual variability between listeners in terms of behavioral efficacy and fidelity of neural encoding of stochastic change in acoustic sequences.SIGNIFICANCE STATEMENT The world around us is complex and ever changing: in everyday listening, sound sources evolve along multiple dimensions, such as pitch, timbre, and spatial location, and they exhibit emergent statistical properties that change over time. In the face of this complexity, the brain builds an internal representation of the external world by collecting statistics from the sensory input along multiple dimensions. Using a Bayesian predictive inference model, this work considers alternative hypotheses for how statistics are combined across sensory dimensions. Behavioral and neural responses from human listeners show the brain multiplexes two representations, where local statistics along each feature linearly affect neural responses, and global statistics nonlinearly combine statistical beliefs across dimensions to shape perception of stochastic auditory sequences.

Groupitizing Improves Estimation of Numerosity of Auditory Sequences.

Groupitizing is a recently described phenomenon of numerosity perception where clustering items of a set into smaller “subitizable” groups improves discrimination. Groupitizing is thought to be rooted on the subitizing system, with which it shares several properties: both phenomena accelerate counting and decrease estimation thresholds irrespective of stimulus format (for both simultaneous and sequential numerosity perception) and both rely on attention. As previous research on groupitizing has been almost completely limited to vision, the current study investigates whether it generalizes to other sensory modalities. Participants estimated the numerosity of a series of tones clustered either by proximity in time or by similarity in frequency. We found that compared with unstructured tone sequences, grouping lowered auditory estimation thresholds by up to 20%. The groupitizing advantage was similar across different grouping conditions, temporal proximity and tone frequency similarity. These results mirror the groupitizing effect for visual stimuli, suggesting that, like subitizing, groupitizing is an a-modal phenomenon.

Deficits in multi-scale top-down processes distorting auditory perception in schizophrenia

Cognitive models postulate that impaired source monitoring incorrectly weights the top-down prediction and bottom-up sensory processes and causes hallucinations. However, the underlying mechanisms of the interaction, such as whether the incorrectly weighting is ubiquitously on all levels of sensory features and whether different top-down processes have distinct effects in subgroups of schizophrenia are still unclear. This study investigates how multi-scale predictions influence perception of basic tonal features in schizophrenia. Sixty-three schizophrenia patients with and without symptoms of auditory verbal hallucinations (AVHs), and thirty healthy controls identified target tones in noise at the end of tone sequences. Predictions of different timescales were manipulated by either an alternating pattern in the preceding tone sequences (long-term regularity) or a repetition between the target tone and the tone immediately before (short-term repetition). The sensitivity index, d prime (d’), was obtained to assess the modulation of predictions on tone identification. Patients with AVHs showed higher d’ when the target tones conformed to the long-term regularity of alternating pattern in the preceding tone sequence than when the target tones were inconsistent with the pattern. Whereas, the short-term repetition modulated the tone identification in patients without AVHs. Predictions did not influence tone identification in healthy controls. Our results suggest that impaired source monitoring in schizophrenia patients with AVHs heavily weights top-down predictions over bottom-up perceptual processes to form incorrect perception. The weighting function in source monitoring can extend to the processes of basic tonal features, and predictions at multiple timescales could differentially modulate perception in different clinical populations. The impaired interaction between top-down and bottom-up processes might underlie the development of hallucination symptoms in schizophrenia.

Distinct Neural Representations of Content and Ordinal Structure in Auditory Sequence Memory.

Two forms of information, frequency (content) and ordinal position (structure), have to be stored when retaining a sequence of auditory tones in working memory (WM). However, the neural representations and coding characteristics of content and structure, particularly during WM maintenance, remain elusive. Here, in two EEG studies in human participants (both sexes), by transiently perturbing the "activity-silent" WM retention state and decoding the reactivated WM information, we demonstrate that content and structure are stored in a dissociative manner with distinct characteristics throughout WM process. First, each tone in the sequence is associated with two codes in parallel, characterizing its frequency and ordinal position, respectively. Second, during retention, a structural retrocue successfully reactivates structure but not content, whereas a following white noise triggers content but not structure. Third, structure representation remains stable, whereas content code undergoes a dynamic transformation through memory progress. Finally, the noise-triggered content reactivations during retention correlate with subsequent WM behavior. Overall, our results support distinct content and structure representations in auditory WM and provide an efficient approach to access the silently stored WM information in the human brain. The dissociation of content and structure could facilitate efficient memory formation via generalizing stable structure to new auditory contents.SIGNIFICANCE STATEMENT In memory experiences, contents do not exist independently but are linked with each other via ordinal structure. For instance, recalling a piece of favorite music relies on correct ordering (sequence structure) of musical tones (content). How are the structure and content for an auditory temporally structured experience maintained in working memory? Here, by using impulse-response approach and time-resolved representational dissimilarity analysis on human EEG recordings in an auditory working memory task, we reveal that content and structure are stored in a dissociated way, which would facilitate efficient and rapid memory formation through generalizing stable structure knowledge to new auditory inputs.

Sustained Pupil Responses Are Modulated by Predictability of Auditory Sequences.

The brain is highly sensitive to auditory regularities and exploits the predictable order of sounds in many situations, from parsing complex auditory scenes, to the acquisition of language. To understand the impact of stimulus predictability on perception, it is important to determine how the detection of predictable structure influences processing and attention. Here, we use pupillometry to gain insight into the effect of sensory regularity on arousal. Pupillometry is a commonly used measure of salience and processing effort, with more perceptually salient or perceptually demanding stimuli consistently associated with larger pupil diameters. In two experiments we tracked human listeners' pupil dynamics while they listened to sequences of 50-ms tone pips of different frequencies. The order of the tone pips was either random, contained deterministic (fully predictable) regularities (experiment 1, n = 18, 11 female) or had a probabilistic regularity structure (experiment 2, n = 20, 17 female). The sequences were rapid, preventing conscious tracking of sequence structure thus allowing us to focus on the automatic extraction of different types of regularities. We hypothesized that if regularity facilitates processing by reducing processing demands, a smaller pupil diameter would be seen in response to regular relative to random patterns. Conversely, if regularity is associated with heightened arousal and attention (i.e., engages processing resources) the opposite pattern would be expected. In both experiments we observed a smaller sustained (tonic) pupil diameter for regular compared with random sequences, consistent with the former hypothesis and confirming that predictability facilitates sequence processing.SIGNIFICANCE STATEMENT The brain is highly sensitive to auditory regularities. To appreciate the impact that the presence of predictability has on perception, we need to better understand how a predictable structure influences processing and attention. We recorded listeners' pupil responses to sequences of tones that followed either a predictable or unpredictable pattern, as the pupil can be used to implicitly tap into these different cognitive processes. We found that the pupil showed a smaller sustained diameter to predictable sequences, indicating that predictability eased processing rather than boosted attention. The findings suggest that the pupil response can be used to study the automatic extraction of regularities, and that the effects are most consistent with predictability helping the listener to efficiently process upcoming sounds.

The dynamics of auditory stream segregation: Effects of sudden changes in frequency, level, or modulation.

Three experiments explored the effects of abrupt changes in stimulus properties on streaming dynamics. Listeners monitored 20-s-long low- and high-frequency (LHL-) tone sequences and reported the number of streams heard throughout. Experiments 1 and 2 used pure tones and examined the effects of changing triplet base frequency and level, respectively. Abrupt changes in base frequency (±3-12 semitones) caused significant magnitude-related falls in segregation (resetting), regardless of transition direction, but an asymmetry occurred for changes in level (±12 dB). Rising-level transitions usually decreased segregation significantly, whereas falling-level transitions had little or no effect. Experiment 3 used pure tones (unmodulated) and narrowly spaced (±25 Hz) tone pairs (dyads); the two evoke similar excitation patterns, but dyads are strongly modulated with a distinctive timbre. Dyad-only sequences induced a strongly segregated percept, limiting scope for further build-up. Alternation between groups of pure tones and dyads produced large, asymmetric changes in streaming. Dyad-to-pure transitions caused substantial resetting, but pure-to-dyad transitions sometimes elicited even greater segregation than for the corresponding interval in dyad-only sequences (overshoot). The results indicate that abrupt changes in timbre can strongly affect the likelihood of stream segregation without introducing significant peripheral-channeling cues. These asymmetric effects of transition direction are reminiscent of subtractive adaptation in vision.

Auditory streaming emerges from fast excitation and slow delayed inhibition

In the auditory streaming paradigm, alternating sequences of pure tones can be perceived as a single galloping rhythm (integration) or as two sequences with separated low and high tones (segregation). Although studied for decades, the neural mechanisms underlining this perceptual grouping of sound remains a mystery. With the aim of identifying a plausible minimal neural circuit that captures this phenomenon, we propose a firing rate model with two periodically forced neural populations coupled by fast direct excitation and slow delayed inhibition. By analyzing the model in a non-smooth, slow-fast regime we analytically prove the existence of a rich repertoire of dynamical states and of their parameter dependent transitions. We impose plausible parameter restrictions and link all states with perceptual interpretations. Regions of stimulus parameters occupied by states linked with each percept match those found in behavioural experiments. Our model suggests that slow inhibition masks the perception of subsequent tones during segregation (forward masking), whereas fast excitation enables integration for large pitch differences between the two tones.

A Constraint-based Analysis of Obligatory Contour Principle in Anaang Morphological Constructions

The obligatory contour principle forbids identical consecutive features in the underlying representation. This work undertakes a description of the Anaang tonal structure, the tonal behaviour of compounds and reduplicates in the language, bearing in mind their sensitivity to the OCP and the environments that trigger the adherence. An adapted Ibadan wordlist of 400 Basic Items (Trial) English version was used via interview for data collection from six men and six women within Abak Local Government Area in Akwa Ibom State. The data were analysed using optimality theoretical framework. The analysis shows that Anaang compounds as well as reduplicates exhibit cases of tonal modifications in line with OCP. For compounds, the tone of the second noun changes depending on the tonal sequence. In the HH noun base, the second-high tone of the second noun changes to a low tone, in the LH noun base, the tone of the second noun is raised to a down-stepped high tone, the LL noun base sees the tone of the second noun being raised to a high tone. For reduplication, the tone of the L verb base changes when the redup
 lication is partial. When the reduplication is complete, the high tone of the second noun is down-stepped.