Motor speech treatment approaches have been recommended and applied in both adults with aphasia and apraxia of speech and children with speech-sound disorders [1, 2]. There has been a steady increase in the number of studies testing the efficacy of these interventions in these populations and the findings indicate that the effects of these interventions continue to be variable (e.g., [3, 4]) and, in some cases, not maintained long-term (e.g., [5]). Continued progress in the development of more effective motor speech interventions could be achieved by building a better understanding of the “mode of action” (MoA), by which these interventions affect change [6, 7]. A mode of action (MoA) refers to a functional (or anatomical) change in an organism resulting from exposure to a substance or event. This is distinguished from the mechanism of action (MOA), which describes these changes at a molecular level [8]. Identifying links between motor speech intervention techniques and the MoAs they target would improve our understanding of how and why motor speech interventions achieve their effects and what components (or “active ingredients”) are more likely to be effective. The current study focuses on identifying potential MoAs for a specific motor speech intervention technique.

Specific techniques have been utilized within motor speech intervention approaches to aid sensory-motor learning of speech-motor targets, such as the Prompts for Restructuring Oral Muscular Phonetic Targets (PROMPT; e.g., [1, 6]) and Dynamic Temporal and Tactile Cueing (DTTC; e.g., [2, 7]). These techniques aim to enhance somatosensory inputs to facilitate the formation of sensory-motor pathways required for the acquisition and accurate production of speech. In the current study, the broad term “somatosensory information” was chosen because in a clinical motor speech intervention context, there is no empirical data to indicate which specific type of somatosensory information (touch, pressure, pain, temperature, position, movement, and vibration) is activated or specifically contributes to clinical improvements. This is in line with the contemporary use of this term in (non-intervention related) speech motor control research [9, 10]. For a review of somatosensory innervation in humans see Moayedi et al. [11]. Typically, in speech motor interventions somatosensory inputs involve multisensory (tactile, kinesthetic, proprioceptive, auditory and visual) cueing (or exogenous inputs) to emphasize place, voice and manner of speech production and slowing down speech rate to possibly enhance proprioceptive feedback and to highlight movement transitions [1, 7].

There is evidence to suggest that endogenous somatosensory feedback is involved in the acquisition and maintenance of orosensory-to-auditory mapping (DIVA model; [12]) and for stability in speech-motor production [13]. However, there is sparse literature on the importance and role of such inputs delivered via an external agent (e.g., Speech-Language Pathologist [S-LP]) during motor speech interventions. In a study by Dale et al. [14], PROMPT treatment with and without somatosensory inputs was examined in a group of children with Childhood Apraxia of Speech (CAS). Their results demonstrated that PROMPT treatment with tactile input enhanced the production of untreated probe words relative to treatment without tactile input [14]. This finding suggests that somatosensory input can be considered an “active ingredient” (i.e., something that must be present for the intervention to be effective). Nonetheless, very little is known about the underlying mechanisms by which such inputs improve speech production.

PROMPT is a sensory-motor treatment approach often recommended and applied in children with speech sound disorders [15], autism [16], and cerebral palsy [17]. During PROMPT intervention, motor speech goals or treatment priorities are based on the notion of a hierarchical development of speech subsystems known as the Motor Speech Hierarchy [MSH; [1]]. Within this developmental MSH framework, speech production is thought to be the result of interactive development of seven key motor speech subsystems (i.e., Stage I: tone, Stage II: phonatory control, Stage III: mandibular control, Stage IV: labial-facial control, Stage V: lingual control, Stage VI: sequenced movements, and Stage VII: prosody). The PROMPT intervention enables the hierarchical establishment, refinement, and integration of normalized synergistic movement patterns within these speech subsystems through the application of somatosensory inputs or prompts to the client’s face. As PROMPT treatment systematically progresses from the lower- to higher-levels of the hierarchy, speech production variables like place, manner, movement transitions, and timing of speech movements are expected to improve.

In addition to its use in children, PROMPT has also been applied to a limited extent on adults with neurological impairments. Four case studies in the literature suggest that PROMPT may improve the accuracy of words and phrases in acquired apraxia of speech [18, 19, 20, 21]. For example, in both Square et al. [21] and Freed et al. [19] studies, participants with acquired apraxia of speech and aphasia were first presented with an auditory model of a word or functional phrase, and participants were required to repeat the target according to the auditory model. If participants could produce the utterance correctly, the next trial would be initiated. However, if participants were unable to repeat the model accurately, then the participants were first instructed not to respond while the clinician “mapped-in” (or primed) the correct sequence of motor patterns using somatosensory inputs for the target utterance. Following this, the clinician would direct the participants to produce aloud the target phoneme, word, or phrase again, during which the clinician simultaneously used somatosensory inputs to facilitate the appropriate movements. In general, their results indicated improved speech sequencing and precision of speech movements for both trained and untrained target words and sentences.

The findings from these studies suggest that the somatosensory inputs applied by a trained clinician may increase oro-facial sensory awareness for movement trajectories and sequences, thereby improving spatial-temporal aspects of speech movements [18, 19, 20, 21]. It is unknown whether these somatosensory inputs are also relevant for the cognitive-linguistic system (e.g., during lexical processing). There is some evidence from the speech motor control literature to indicate that somatosensory information may be used by the speech production/perception system beyond the level of simply increasing oro-facial awareness. In fact, somatosensory information may affect the lexicality of phoneme perception [9, 22, 23]. In these studies, modulation of speech perception has been observed because of stretching the facial skin around the mouth area [9] or stimulating mechanoreceptors with air puffs on the back of the hand, the centre of the neck, or on the subject’s ankles [23].

More recently, Ogane et al. [10] demonstrated that somatosensory inputs influence processes at the level of word segmentation and lexical decision. They utilized an auditory identification test using a set of French phrases, which may be segmented differently depending on the placement of accents (i.e., based on acoustic prosodic cues like local pitch increases) within the phrase. They reasoned that since creating an acoustic-prosodic accent may be achieved by hyper-articulation [24], the cues for word segmentation could be obtained from not only acoustic but also from articulatory sensory information. They applied somatosensory stimulation (using a robotic device to stretch the skin at the sides of the participant’s mouth) at different points in the utterance, which had been recorded with neutral accents (i.e., all syllables had a similar emphasis). They found that lexical decisions relating to word segmentation were systematically and significantly biased depending on the timing of the somatosensory stimulation. This effect was not found when somatosensory stimulation was applied to the skin of the participant’s forearm. These findings suggest that neural speech processing broadly integrates event-related information across multiple modalities (i.e., auditory, tactile, visual), and perceptual-sensory-motor relationships may extend to the processing of lexical information in the human brain [10].

Ito et al. [9] have pointed out that such modulation of speech-perception may arise due to connections between facial somatosensory inputs and facial motor and premotor areas [25, 26], or due to bidirectional linkages between the somatosensory and auditory cortices [27, 28, 29, 30], and possibly as a result of auditory-somatosensory interaction at the subcortical superior colliculus level [31]. Other studies have found that multisensory input involving visual, auditory, and somatosensory stimuli show connections into the ventrolateral prefrontal cortex (VLPFC) and specifically converges in areas 47/12, as well as area 45 [32]. Area 45 (and 44) of the inferior frontal gyrus (commonly referred to as Broca’s areas) is thought to be involved in myriad of motor and cognitive functions including lexical processing [33] and has also been associated with word frequency effects [33, 34].

Word frequency effects have been demonstrated to be important in several areas of speech processing. Studies have shown that during the process of lexical (word) selection and encoding of sound structure, high lexical frequency facilitates processing, possibly due to their higher activation levels and strength of neural connections (e.g., [35]). This is reflected in decreased reaction times and higher accuracy (i.e., fewer semantic, phonological, articulatory errors and/or omissions) for high-frequency words relative to low frequency words [36]. In contrast, low-frequency words result in slower response times relative to high-frequency words, which indicates longer processing times for low-frequency words ([37]; for a review in adult aphasia literature, see Kittredge et al. [36]). Other evidence using event-related potentials (ERPs) have also shown larger N400 waves when processing low-frequency words relative to high-frequency words, further suggesting that low-frequency words require more extensive processing [38, 39].

Apart from processing times, studies have also reported word frequency effects on speech articulation (see Bell et al. [40] for a review). For example, low-frequency words are produced with longer durations and more extreme articulatory and acoustic properties [40, 41]. Such durational effects have been explained by models of speech and language processing with proposed interactions between lexical, phonological, and phonetic structures (e.g., [42]). Within these models, its argued that the pace of articulation/speech production may be moderated when processing (e.g., phonological encoding) is slowed as in the case of low-frequency words. It is argued that this facilitates the maintenance of temporal coordination between the lexical and articulatory aspects of speech [40]. Furthermore, under such accounts, word form representations are said to include a specification of the range of phonetic variation associated with the target forms. It is suggested that speakers of a language may learn to associate high-frequency lexical items with a greater degree of phonetic variation relative to low-frequency items, a phenomenon referred to as lexically-conditioned phonetic variation [40]. This results in an activation of a representation specifying a narrow range of phonetic variation during the encoding of the sound structure of low-frequency words. Thus, low-frequency words are said to influence phonetic processing more strongly than high-frequency words [42]. Due to this, it is hypothesized that the processing of low-frequency words may benefit with not only more but also narrowly specified somatosensory input relative to high-frequency words. Such a finding would suggest that part of the effect of these somatosensory cues may occur at a level of cognitive-linguistic processing that involves interactions between lexical access and phonetic processing [40, 42]. Clinically, it is important to understand the level at which exogenous clinician induced somatosensory information is integrated into the speech-production/perception system, as this may have implications for the speech training in children and in the rehabilitation of adult brain-injury patients (e.g., those with word-finding/word-retrieval issues in aphasia). It is likely that somatosensory input may provide a dual benefit wherein it may help improve speech motor patterns and, at the same time, facilitate the retrieval of lexical information.

Phonation reaction times (M = 371.1; SD = 67.1) as expected were significantly (t(9) = 5.6, p = 0.0003) shorter than the fastest speech reaction time data (M = 603.3; SD = 92.6) recorded. Means and standard deviations (in parenthesis) for SRT and word-initial phoneme accuracy across congruent and incongruent conditions were calculated and reported in Table 3 for oro-facial somatosensory priming and for forehead control conditions.

The experiment reported in this paper used a cross-modal repetition priming paradigm to examine whether the processing of external S-LP driven somatosensory inputs was modulated by both word-level (lexical frequency) and speech sound articulatory features, suggesting a broader role for speech production information in speech perception. The main effects corroborate data from previous research indicating that the high-frequency words had significantly shorter reaction times than low-frequency words (e.g., [37, 56]; for a review in adult aphasia literature, see Kittredge et al. [36]). Importantly, a statistically significant condition $\times$ word frequency interaction indicated that significant effects of somatosensory priming were found only for low-frequency words as opposed to the high-frequency words.

For phoneme accuracy, the results revealed a main effect of somatosensory input condition. A further exploration of this effect revealed that the percent phoneme accuracy scores were lower for incongruent conditions than congruent conditions for the low-frequency words, but the interaction failed to reach significance. Overall, the results showed significant somatosensory priming effects for the low-frequency words, where the congruent somatosensory condition yielded significantly shorter reaction times and numerically higher phoneme accuracy scores when compared to the incongruent somatosensory condition (see Table 3). In general, for the low-frequency words, incongruent somatosensory input increased SRTs by approximately 45 ms and decreased percentage phoneme accuracy scores by 4–5%. For high-frequency words, SRTs and phoneme accuracy did not differ as a function of somatosensory congruency.

Importantly, data from the control study did not reveal any systematic priming effects from forehead stimulation (non-speech related site), other than a general (and expected) tendency for longer reaction times with low-frequency words. This finding suggests that the perceptual modulation effects in the current study are less likely from simple pattern matching of events between sound stimuli and somatosensory (priming) inputs. Although, reaction time data for forehead stimulation was faster when compared to oral somatosensory condition, readers should note that forehead data was collected from a separate group of control participants at a later date, and thus some differences are expected.

The present findings not only align with contemporary theories of speech perception that support the role of the somatosensory system in speech perception [9, 23] but also extends this to a broader and more integrative role of somatosensory information in lexical access as proposed by Ogane et al. [10]. Specifically, the interaction effects observed between word frequency and type of somatosensory input related to place of articulation suggest that external somatosensory input (as provided by a therapist) may play a role at the level of lexical-phonetic interactions in speech processing [10]. Within interactive activation approaches to word production, such lexical-phonetic interactions may arise in a distributed language network where nodes are bidirectionally (i.e., feedforward and feedback manner) connected across semantic, lexical, and phonetic levels of representation [42]. In some spoken-word recognition models (as discussed in the Introduction section), word frequency is assumed to affect the activation levels during lexical access; thus, it is likely that articulatory place information as stimulated by these somatosensory inputs is one way of raising the activation levels of words which have naturally lower levels of activation (i.e., low-frequency words compared to high-frequency words; [40, 57]).

In the context of restorative neurology, the provision of congruent somatosensory cues may be facilitative for word-finding or naming difficulties (e.g., in anomia, adult apraxia of speech, Broca’s aphasia) in adult aphasia [21, 58, 59]. Typically, phonological cueing techniques have been utilized to improve naming speed and accuracy in individuals with aphasia [58, 59]. In the phonological cueing technique, persons with aphasia are provided with a verbal cue of the first phoneme for an object or picture they are required to name [60]. For example, verbal cue /k/ for the word cat. In such cueing intervention approaches, the addition of somatosensory inputs by a speech therapist [19, 21] or silent observation of visual articulatory gestures [61] has added benefits to improving naming performance in individuals with aphasia. The current findings on healthy control participants, when taken together with the data from multisensory cueing studies in aphasia research [19, 21, 61], suggest that exogenous therapist driven, tightly controlled or specific somatosensory inputs may facilitate rehabilitation of adult brain-injury patients such as those with word-finding/word-retrieval issues in aphasia [18, 19, 20, 21].

The question remains whether specific exogenous S-LP driven somatosensory inputs in clinical rehabilitation settings constitute an “active ingredient” underlying MoAs in motor speech interventions such as the PROMPT approach. As described in Hayden et al. [1] recent research studies from independent laboratories have demonstrated changes in cortical spatial-temporal neural activity and brain structure following PROMPT intervention [62, 63, 64]. A magnetic resonance imaging study by Kadis et al. [63] revealed that PROMPT intervention induced thinning of the left posterior superior temporal gyrus (Wernicke’s area) in eight of nine children with CAS. Similarly, in Yu et al. [64] study, participants demonstrated significant differences in cortical neural activity during speech tasks as a function of PROMPT intervention on magnetoencephalography recordings. In both these studies, significant improvements in speech motor control and speech articulation were also observed following the intervention. More recently, Fiori et al. [62] studied PROMPT intervention-related brain structural connectivity changes in white matter fiber tracts using diffusion-weighted imaging (diffusion tractography) in a group of 10 children with CAS. Five CAS children received the PROMPT intervention, while the other five received Language and Non-speech Oral Motor (LNSOM) treatment. Their results revealed significant and positive changes in the standardized assessment of speech motor control in the group that received PROMPT intervention relative to the LNSOM-treated group. Although in both PROMPT- and LNSOM-treated groups, the speech improvements paralleled changes in the ventral corticobulbar tracts (innervates tongue/larynx), only the PROMPT intervention group showed additional neuroplastic changes such as an increase in connectivity in the left dorsal corticobulbar tracts (i.e., those associated with lip/facial muscles). The authors argue that this may be an intervention-specific response as jaw control and labial-facial control were priority speech motor goals for children receiving PROMPT therapy.

Importantly, such discoveries of experience-dependent neuroplasticity in children receiving somatosensory based motor speech intervention (e.g., PROMPT) for speech sound disorders demonstrate a mode of action and improves our understanding of how motor speech intervention produces its effects. For federal agencies such as the U.S. Food and Drug Administration (FDA), identifying MoA’s is a key component of discovering and developing therapeutic interventions. The discovery of MoAs of motor speech intervention will hopefully permit the development of future research directed at modifying existing techniques to replicate such neural effects, adjust the dosage to elicit systematic effects in targeted neural pathways and potentially discover populations that are responsive to motor speech interventions [1]. Thus, converging evidence from behavioural data in children [14], adults [18, 19, 20, 21], perceptual data from cross-modal research [9, 10], and neuroimaging studies [62, 63, 64] seem to reinforce the notion that somatosensory inputs may be a potential active ingredient in motor speech interventions.

These findings provide preliminary support for the notion that speech production information is represented in the mental lexicon and can be accessed through exogenous S-LP-driven somatosensory inputs related to place of articulation. Low-frequency words usually take longer to be recognized, and the additional information provided by somatosensory input can facilitate this process. Our findings suggest that the way somatosensory inputs influence lexical selection is biased by the usage sensitivity of how lexical information is stored in the mental lexicon [70, 71]. The study results highlight a broader and more integrative role of somatosensory information in lexical access, as proposed by Ogane et al. [10].

AKN conceived and obtained the funding. AKN was the principal investigator who was responsible for the study conceptualization, recruitment of study personnel and co-led the data collection process with DH and TY. AKN and TY conducted the final data analysis and drafted the manuscript. TY and RB assisted with literature search, study design, development of stimuli, noise mixing, software programming. PvL participated in the design of the study and offered in-kind support (research lab and research staff), as well as provided critical feedback throughout the study and on the draft of the manuscript. DH contributed to theoretical foundations and clinical applications in the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.

The study was approved by the University of Toronto’s Health Sciences Research Ethics Board (Protocol # 31524), and all participants provided written informed consent prior to participation.

We thank all of the participants in the study, and all of the staff, including more than 6 research assistants, independent contractors (speech–language pathologists), four anonymous reviewers and volunteers from the University of Toronto, who assisted with the study. We gratefully acknowledge the research support of Anna Huynh and Vina Law during the design and data collection phase.

This study was funded by an international competitive Clinical Trials Research Grant (2013–2019) awarded to the first author by the PROMPT Institute, Santa Fe, NM, USA. The first author (ANK) also received project completion top-up funds from The PROMPT Institute in 2021.

This study was funded in-part by an international competitive Clinical Trials Research Grant (2013–2019; NIH Trial Registration NCT02105402) awarded to the first author (ANK) by The PROMPT Institute, Santa Fe, NM, USA. However, the funding agency was not involved in the study design, analysis or interpretation of the data. The first author (ANK) also received project completion top-up funds from The PROMPT Institute in 2021. The fourth author DH is a salaried employee (Research Director) of The PROMPT Institute, SF, NM, USA.