A fNIRS Investigation of Speech Planning and Execution in Adults Who Stutter

Flexible-circuit-based 3-D aware modular optical brain imaging system for high-density measurements in natural settings

Significance

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic condition remains a significant challenge.

Aim

The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide real-time probe 3-D shape estimation to improve the use of fNIRS in everyday conditions.

Approach

The MOBI system utilizes bendable and lightweight modular circuit-board design to enhance probe's conformity to head surface and comfort for long-term wearing. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3-D positions in real-time to enable advanced tomographic data analysis and motion tracking.

Results

Optical characterization of the MOBI detector reports a noise equivalence power (NEP) of 8.9 and 7.3 p W / H z at 735 nm and 850 nm, respectively, with a dynamic range of 88 dB. The 3-D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared to positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided.

Conclusions

To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3-D optode position acquisition, combined with lightweight modules (18 g/module) and ergonomic designs, would greatly aid emerging explorations towards brain functions in naturalistic settings.

Examining resting state functional connectivity and frequency power analysis in adults who stutter compared to adults who do not stutter

Introduction

Stuttering is a speech disorder characterized by impaired connections between brain regions involved in speech production. This study aimed to investigate functional connectivity and frequency power during rest in adults who stutter (AWS) compared to fluent adults (AWNS) in the dorsolateral prefrontal cortex (DLPFC), dorsolateral frontal cortex (DLFC), supplementary motor area (SMA), motor speech, angular gyrus (AG), and inferior temporal gyrus (ITG).

Materials and methods

Fifteen AWS (3 females, 12 males) and fifteen age- and sex-matched AWNS (3 females, 12 males) participated in this study. All participants were native Persian speakers. Stuttering severity in the AWS group was assessed using the Persian version of the Stuttering Severity Instrument Fourth Edition (SSI-4). Resting-state electroencephalography (EEG) was recorded for 5 min while participants sat comfortably with their eyes open. We analyzed frequency band power across various frequency bands and investigated functional connectivity within the specified speech region.

Results

Significant between-group differences were found in band powers including alpha, beta, delta, theta, and gamma, specifically in the premotor, SMA, motor speech, and frontal regions. AWS also showed increased coherence between the right motor speech region compared to controls. We demonstrate that the proposed hierarchical false discovery rate (FDR) method is the most effective for both simulations and experimental data. In the expected regions, this method revealed significant synchrony effects at an acceptable error rate of 5%.

Conclusion

The results highlight disrupted functional connectivity in AWS at resting state, particularly in speech-related and associated areas. Given the complex neurological basis of developmental stuttering, robust neural markers are closely linked to this phenomenon. These markers include imbalanced activity within brain regions associated with speech and motor functions, coupled with impaired functional connectivity between these regions. The cortico-basal ganglia-thalamo-cortical system governs the dynamic interplay between cortical regions, with SMA as a key cortical site. It is hypothesized that the aberrant resting state functional connectivity will impact the language planning and motor execution necessary for fluent speech. Examining resting-state metrics as biomarkers could further elucidate the neural underpinnings of stuttering and guide intervention.

A frontal cortical network is critical for language planning during spoken interaction

Many brain areas exhibit activity correlated with language planning, but the impact of these dynamics on spoken interaction remains unclear. Here we use direct electrical stimulation to transiently perturb cortical function in neurosurgical patient-volunteers performing a question-answer task. Stimulating structures involved in speech motor function evoked diverse articulatory deficits, while perturbations of caudal inferior and middle frontal gyri - which exhibit preparatory activity during conversational turn-taking - led to response errors. Perturbation of the same planning-related frontal regions slowed inter-speaker timing, while faster responses could result from stimulation of sites located in other areas. Taken together, these findings further indicate that caudal inferior and middle frontal gyri constitute a critical planning network essential for interactive language use.

fNIRS Studies of Individuals with Speech and Language Impairment Underreport Sociodemographics: A Systematic Review

Functional near-infrared spectroscopy (fNIRS) is a promising tool for scientific discovery and clinical application. However, its utility depends upon replicable reporting. We evaluate reporting of sociodemographics in fNIRS studies of speech and language impairment and asked the following: (1) Do refereed fNIRS publications report participant sociodemographics? (2) For what reasons are participants excluded from analysis? This systematic review was preregistered with PROSPERO (CRD42022342959) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Searches in August 2022 included the terms: (a) fNIRS or functional near-infrared spectroscopy or NIRS or near-infrared spectroscopy, (b) speech or language, and (c) disorder or impairment or delay. Searches yielded 38 qualifying studies from 1997 to present. Eight studies (5%) reported at least partial information on race or ethnicity. Few studies reported SES (26%) or language background (47%). Most studies reported geographic location (100%) and gender/sex (89%). Underreporting of sociodemographics in fNIRS studies of speech and language impairment hinders the generalizability of findings. Replicable reporting is imperative for advancing the utility of fNIRS.

Brain activity during the preparation and production of spontaneous speech in children with persistent stuttering

Speech production forms the basis for human verbal communication. Though fluent speech production is effortless and automatic for most people, it is disrupted in speakers who stutter, who experience difficulties especially during spontaneous speech and at utterance onsets. Brain areas comprising the basal ganglia thalamocortical (BGTC) motor loop have been a focus of interest in the context of stuttering, given this circuit's critical role in initiating and sequencing connected speech. Despite the importance of better understanding the role of the BGTC motor loop in supporting overt, spontaneous speech production, capturing brain activity during speech has been challenging to date, due to fMRI artifacts associated with severe head motions during speech production. Here, using an advanced technique that removes speech-related artifacts from fMRI signals, we examined brain activity occurring immediately before, and during, overt spontaneous speech production in 22 children with persistent stuttering (CWS) and 18 children who do not stutter (controls) in the 5-to-12-year age range. Brain activity during speech production was compared in two conditions: spontaneous speech (i.e., requiring language formulation) and automatic speech (i.e., overlearned word sequences). Compared to controls, CWS exhibited significantly reduced left premotor activation during spontaneous speech production but not during automatic speech. Moreover, CWS showed an age-related reduction in left putamen and thalamus activation during speech preparation. These results provide further evidence that stuttering is associated with functional deficits in the BGTC motor loop, which are exacerbated during spontaneous speech production.

Functional near-infrared spectroscopy in pediatric clinical research: Different pathophysiologies and promising clinical applications

Over its 30 years of existence, functional near-infrared spectroscopy (fNIRS) has matured into a highly versatile tool to study brain function in infants and young children. Its advantages, amongst others, include its ease of application and portability, the option to combine it with electrophysiology, and its relatively good tolerance to movement. As shown by the impressive body of fNIRS literature in the field of cognitive developmental neuroscience, the method's strengths become even more relevant for (very) young individuals who suffer from neurological, behavioral, and/or cognitive impairment. Although a number of studies have been conducted with a clinical perspective, fNIRS cannot yet be considered as a truly clinical tool. The first step has been taken in this direction by studies exploring options in populations with well-defined clinical profiles. To foster further progress, here, we review several of these clinical approaches to identify the challenges and perspectives of fNIRS in the field of developmental disorders. We first outline the contributions of fNIRS in selected areas of pediatric clinical research: epilepsy, communicative and language disorders, and attention-deficit/hyperactivity disorder. We provide a scoping review as a framework to allow the highlighting of specific and general challenges of using fNIRS in pediatric research. We also discuss potential solutions and perspectives on the broader use of fNIRS in the clinical setting. This may be of use to future research, targeting clinical applications of fNIRS in children and adolescents.

Investigation of functional near-infrared spectroscopy signal quality and development of the hemodynamic phase correlation signal

Significance: There is a longstanding recommendation within the field of fNIRS to use oxygenated (HbO 2 ) and deoxygenated (HHb) hemoglobin when analyzing and interpreting results. Despite this, many fNIRS studies do focus onHbO 2 only. Previous work has shown thatHbO 2 on its own is susceptible to systemic interference and results may mostly reflect that rather than functional activation. Studies using bothHbO 2 and HHb to draw their conclusions do so with varying methods and can lead to discrepancies between studies. The combination ofHbO 2 and HHb has been recommended as a method to utilize both signals in analysis. Aim: We present the development of the hemodynamic phase correlation (HPC) signal to combineHbO 2 and HHb as recommended to utilize both signals in the analysis. We use synthetic and experimental data to evaluate how the HPC and current signals used for fNIRS analysis compare. Approach: About 18 synthetic datasets were formed using resting-state fNIRS data acquired from 16 channels over the frontal lobe. To simulate fNIRS data for a block-design task, we superimposed a synthetic task-related hemodynamic response to the resting state data. This data was used to develop an HPC-general linear model (GLM) framework. Experiments were conducted to investigate the performance of each signal at different SNR and to investigate the effect of false positives on the data. Performance was based on each signal's mean T -value across channels. Experimental data recorded from 128 participants across 134 channels during a finger-tapping task were used to investigate the performance of multiple signals [HbO 2 , HHb, HbT, HbD, correlation-based signal improvement (CBSI), and HPC] on real data. Signal performance was evaluated on its ability to localize activation to a specific region of interest. Results: Results from varying the SNR show that the HPC signal has the highest performance for high SNRs. The CBSI performed the best for medium-low SNR. The next analysis evaluated how false positives affect the signals. The analyses evaluating the effect of false positives showed that the HPC and CBSI signals reflect the effect of false positives onHbO 2 and HHb. The analysis of real experimental data revealed that the HPC and HHb signals provide localization to the primary motor cortex with the highest accuracy. Conclusions: We developed a new hemodynamic signal (HPC) with the potential to overcome the current limitations of usingHbO 2 and HHb separately. Our results suggest that the HPC signal provides comparable accuracy to HHb to localize functional activation while at the same time being more robust against false positives.

A speech planning network for interactive language use

During conversation, people take turns speaking by rapidly responding to their partners while simultaneously avoiding interruption1,2. Such interactions display a remarkable degree of coordination, as gaps between turns are typically about 200 milliseconds3-approximately the duration of an eyeblink4. These latencies are considerably shorter than those observed in simple word-production tasks, which indicates that speakers often plan their responses while listening to their partners2. Although a distributed network of brain regions has been implicated in speech planning5-9, the neural dynamics underlying the specific preparatory processes that enable rapid turn-taking are poorly understood. Here we use intracranial electrocorticography to precisely measure neural activity as participants perform interactive tasks, and we observe a functionally and anatomically distinct class of planning-related cortical dynamics. We localize these responses to a frontotemporal circuit centred on the language-critical caudal inferior frontal cortex10 (Broca's region) and the caudal middle frontal gyrus-a region not normally implicated in speech planning11-13. Using a series of motor tasks, we then show that this planning network is more active when preparing speech as opposed to non-linguistic actions. Finally, we delineate planning-related circuitry during natural conversation that is nearly identical to the network mapped with our interactive tasks, and we find this circuit to be most active before participant speech during unconstrained turn-taking. Therefore, we have identified a speech planning network that is central to natural language generation during social interaction.

Imagined speech increases the hemodynamic response and functional connectivity of the dorsal motor cortex

Objective. Decoding imagined speech from brain signals could provide a more natural, user-friendly way for developing the next generation of the brain-computer interface (BCI). With the advantages of non-invasive, portable, relatively high spatial resolution and insensitivity to motion artifacts, the functional near-infrared spectroscopy (fNIRS) shows great potential for developing the non-invasive speech BCI. However, there is a lack of fNIRS evidence in uncovering the neural mechanism of imagined speech. Our goal is to investigate the specific brain regions and the corresponding cortico-cortical functional connectivity features during imagined speech with fNIRS.Approach. fNIRS signals were recorded from 13 subjects' bilateral motor and prefrontal cortex during overtly and covertly repeating words. Cortical activation was determined through the mean oxygen-hemoglobin concentration changes, and functional connectivity was calculated by Pearson's correlation coefficient.Main results. (a) The bilateral dorsal motor cortex was significantly activated during the covert speech, whereas the bilateral ventral motor cortex was significantly activated during the overt speech. (b) As a subregion of the motor cortex, sensorimotor cortex (SMC) showed a dominant dorsal response to covert speech condition, whereas a dominant ventral response to overt speech condition. (c) Broca's area was deactivated during the covert speech but activated during the overt speech. (d) Compared to overt speech, dorsal SMC(dSMC)-related functional connections were enhanced during the covert speech.Significance. We provide fNIRS evidence for the involvement of dSMC in speech imagery. dSMC is the speech imagery network's key hub and is probably involved in the sensorimotor information processing during the covert speech. This study could inspire the BCI community to focus on the potential contribution of dSMC during speech imagery.

Speech planning and execution in children who stutter: Preliminary findings from a fNIRS investigation

Few studies have investigated the neural mechanisms underlying speech production in children who stutter (CWS), despite the critical importance of understanding these mechanisms closer to the time of stuttering onset. The relative contributions of speech planning and execution in CWS therefore are also unknown. Using functional near-infrared spectroscopy, the current study investigated neural mechanisms of planning and execution in a small sample of 9-12 year-old CWS and controls (N = 12) by implementing two tasks that manipulated speech planning and execution loads. Planning was associated with atypical activation in bilateral inferior frontal gyrus and right supramarginal gyrus. Execution was associated with atypical activation in bilateral precentral gyrus and inferior frontal gyrus, as well as right supramarginal gyrus and superior temporal gyrus. The CWS exhibited some activation patterns that were similar to the adults who stutter (AWS) as reported in our previous study: atypical planning in frontal areas including left inferior frontal gyrus and atypical execution in fronto-temporo-parietal regions including left precentral gyrus, and right inferior frontal, superior temporal, and supramarginal gyri. However, differences also emerged. Whereas CWS and AWS both appear to exhibit atypical activation in right inferior and supramarginal gyri during execution, only CWS appear to exhibit this same pattern during planning. In addition, the CWS appear to exhibit atypical activation in left inferior frontal and right precentral gyri related to execution, whereas AWS do not. These preliminary results are discussed in the context of possible impairments in sensorimotor integration and inhibitory control for CWS.

Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm

Significance: Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies may complicate the interpretation of data. Aim: We aim to assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, we determine whether averaging or generalized linear model (GLM)-based analysis generates different experimental conclusions when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach: 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design, comprising sounds of 5 s duration and 10 to 20 s silent intervals, was employed. Results: Both analysis procedures generated similar response morphologies and amplitude estimates, and both indicated that responses to speech were significantly greater than to noise or silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions: Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.

Comparing different pre-processing routines for infant fNIRS data

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Five pre-processing pipelines were compared on synthetic and real infant NIRS data.

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Strict inclusion criteria limit the number of trials, but recover HRF accurately.

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Artifact correction retains larger amounts of data, but may lower HRF amplitude.

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No difference between applying pre-processing to optical density or concentration data.

Functional Near Infrared Spectroscopy (fNIRS) is an important neuroimaging technique in cognitive developmental neuroscience. Nevertheless, there is no general consensus yet about best pre-processing practices. This issue is highly relevant, especially since the development and variability of the infant hemodynamic response (HRF) is not fully known. Systematic comparisons between analysis methods are thus necessary. We investigated the performance of five different pipelines, selected on the basis of a systematic search of the infant NIRS literature, in two experiments. In Experiment 1, we used synthetic data to compare the recovered HRFs with the true HRF and to assess the robustness of each method against increasing levels of noise. In Experiment 2, we analyzed experimental data from a published study, which assessed the neural correlates of artificial grammar processing in newborns. We found that with motion artifact correction (as opposed to rejection) a larger number of trials were retained, but HRF amplitude was often strongly reduced. By contrast, artifact rejection resulted in a high exclusion rate but preserved adequately the characteristics of the HRF. We also found that the performance of all pipelines declined as the noise increased, but significantly less so than if no pre-processing was applied. Finally, we found no difference between running the pre-processing on optical density or concentration change data. These results suggest that pre-processing should thus be optimized as a function of the specific quality issues a give dataset exhibits.

The functional brain networks that underlie visual working memory in the first two years of life

Visual working memory (VWM) is a central cognitive system used to compare views of the world and detect changes in the local environment. This system undergoes dramatic development in the first two years; however, we know relatively little about the functional organization of VWM at the level of the brain. Here, we used image-based functional near-infrared spectroscopy (fNIRS) to test four hypotheses about the spatial organization of the VWM network in early development. Four-month-olds, 1-year-olds, and 2-year-olds completed a VWM task while we recorded neural activity from 19 cortical regions-of-interest identified from a meta-analysis of the adult fMRI literature on VWM. Results showed significant task-specific functional activation near 6 of 19 ROIs, revealing spatial consistency in the brain regions activated in our study and brain regions identified to be part of the VWM network in adult fMRI studies. Working memory related activation was centered on bilateral anterior intraparietal sulcus (aIPS), left temporoparietal junction (TPJ), and left ventral occipital complex (VOC), while visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, left TPJ, and bilateral IPS. Results show that a distributed brain network underlies functional changes in VWM in infancy, revealing new insights into the neural mechanisms that support infants’ improved ability to remember visual information and to detect changes in an on-going visual stream.

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A distributed brain network underlies functional changes in VWM in infancy and toddlerhood.

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This network shows robust engagement of similar brain regions identified in fMRI studies with adults as early as four months.

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Working memory related activation was centered on bilateral anterior intraparietal sulcus, left temporoparietal junction, and left ventral occipital complex

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Visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, bilateral anterior intraparietal sulcus, and left temporoparietal junction.

Theta Modulated Neural Phase Coherence Facilitates Speech Fluency in Adults Who Stutter

Adults who stutter (AWS) display altered patterns of neural phase coherence within the speech motor system preceding disfluencies. These altered patterns may distinguish fluent speech episodes from disfluent ones. Phase coherence is relevant to the study of stuttering because it reflects neural communication within brain networks. In this follow-up study, the oscillatory cortical dynamics preceding fluent speech in AWS and adults who do not stutter (AWNS) were examined during a single-word delayed reading task using electroencephalographic (EEG) techniques. Compared to AWNS, fluent speech preparation in AWS was characterized by a decrease in theta-gamma phase coherence and a corresponding increase in theta-beta coherence level. Higher spectral powers in the beta and gamma bands were also observed preceding fluent utterances by AWS. Overall, there was altered neural communication during speech planning in AWS that provides novel evidence for atypical allocation of feedforward control by AWS even before fluent utterances.