Huijing Hu
Jingting Li
Sixuan He1
Peng Liu
Hanjun Liu- 1Institute of Medical Research, Northwestern Polytechnical University, Xi'an, China
- 2Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- 3Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
Introduction
Speech production is a complex, neuromotor behavior that involves the physiological, neurological, respiratory, and muscular systems. The decrement in overall function of these systems occurs to advancing age, leading to aging-related changes in speech production. Great efforts have been made to investigate the acoustic changes in the aging speech in the past few decades. For example, changes with aging in voice fundamental frequency (fo) occur through adult life (Ramig and Ringel, 1983; Decoster and Debruyne, 1997; Mueller, 1997; Sataloff et al., 1997). When compared to younger adults, older adults exhibit greater voice fo instability and lower vowel formants (Gorham-Rowan and Laures-Gore, 2006; Torre and Barlow, 2009). Also, decreased speaking rates (Duchin and Mysak, 1987; Wohlert and Smith, 1998) and speech accuracy (Sadagopan and Smith, 2013; Bilodeau-Mercure et al., 2015) represent substantial aging-related deficits in prosody and articulation.
In addition to the acoustic changes in the aging speech, the ability to monitor and correct acoustic changes during speech production that depends on the integration of auditory feedback and motor systems, or speech motor control, is also compromised by normal aging. By unexpectedly perturbing voice fo in auditory feedback during ongoing vocalization, for example, several studies found larger and more variable compensatory vocal responses produced by older adults than by younger adults (Liu et al., 2010; Liu P. et al., 2011; Li et al., 2018). In accordance with abnormally larger vocal compensate responses to pitch perturbations in patients with neurological disorders relative to healthy controls (Liu et al., 2012; Huang et al., 2016; Mollaei et al., 2016; Ranasinghe et al., 2017), enhancement of vocal compensations for perturbed auditory feedback observed in older adults may reflect a decline in speech motor control with normal aging.
In contrast to aging-related changes in speech acoustics, the neuromotor control of speech production with advancing age has received much less attention. Investigations of speech motor control in aging adults can provide significant insights into our understanding of the developmental changes in speech production across the adult lifespan. Speech aging has been attributed to age-related changes in the peripheral and neurological systems and cognitive functions (Ramig et al., 2001; Tucker et al., 2021) as well as sex difference (Torre and Barlow, 2009). Therefore, this review discusses multiple factors that are involved in aging-related neuromotor control of speech production, including laryngeal physiology, brain structure and function, higher-order cognitive functions, and sex-aging interaction.
Laryngeal physiology
Aging-related laryngeal structures accompany with physiological changes, such as decrease and degeneration in thyroarytenoid muscle fiber diameter (Ramig et al., 2001), decreased firing rates (Baker et al., 1998), larger internal stiffness as well as greater mass of vocal folds (Gorham-Rowan and Laures-Gore, 2006). Notably, groups of laryngeal muscles have been identified to be involved in regulating voice fo by controlling the geometry and tension of the vocal folds (Hirano et al., 1970; Ludlow et al., 1992), and our work specified significant contributions of laryngeal cricothyroid and thyroarytenoid muscles to compensatory vocal adjustment (Liu H. et al., 2011). Since the ability to precisely control vocal production declines in older adults (Ballard et al., 2001), excessive vocal compensations when facing pitch errors observed in aging adults (Liu et al., 2010; Liu P. et al., 2011; Li et al., 2018) may be attributed to their deficits in controlling laryngeal muscles to produce the desired speech sounds. Alternatively, aging-related decline in speech production may be related to changes in the use of feedback control strategies with advancing age. Successful control of speech production requires a dynamic balance of auditory and somatosensory feedback (Golfinopoulos et al., 2010), and deficits in somatosensory feedback shifts the balance to auditory feedback (Lametti et al., 2012). Larson et al. (2008) found enhanced vocal compensations for pitch errors induced by anesthetization of the vocal folds when compared to normal kinesthesia, suggesting increased reliance on auditory feedback due to interfered somatosensory feedback. Given impaired kinesthetic function caused by aging-related laryngeal changes (Ramig et al., 2001), older adults may rely more on auditory feedback such that they are more susceptible to errors in vocal output, resulting their reduced accuracy in the neuromotor control of vocal production.
Brain structure and function
In addition to the peripherical mechanisms, structural and functional changes in the aging brain also contribute to the age-related decline in speech production (Eckert et al., 2008; Harris et al., 2009; Soros et al., 2011; Tremblay et al., 2013, 2017; Tremblay and Deschamps, 2016). When compared to younger adults, for example, older adults exhibited longer speech movement time that was significantly correlated with their structural changes in the bilateral anterior insula, bilateral striatum, rostral supramarginal gyrus, left primary motor area and right inferior frontal sulcus (Tremblay and Deschamps, 2016). As well, older adults showed greater activation in the inferior frontal gyrus, precentral gyrus, anterior insula, and supplementary motor area during overt speech production than younger adults (Soros et al., 2011). In addition, subcortical structures such as the basal ganglia and cerebellum are also involved in the neuromotor control of vocal production, as evidenced by abnormally enhanced vocal compensations for pitch perturbations in aging patients with Parkinson's disease (PD; Liu et al., 2012; Chen et al., 2013; Huang et al., 2016; Mollaei et al., 2016) and spinocerebellar ataxia (SCA; Parrell et al., 2017; Houde et al., 2019; Li et al., 2019).
Note that there is a significant decrease in the number of inhibitory synapses with advancing age (Kovacevic et al., 2005) that limit the capacity to suppress responses to repetitive auditory stimuli (Amenedo and Diaz, 1998), which may be responsible for overcompensation for vocal pitch errors (Liu et al., 2010; Liu P. et al., 2011; Li et al., 2018) and increased cortical responses to pure tones (Stephen et al., 2010) in older adults. On the other hand, previous studies on speech perception has shown aging-related increase in the latency of neural responses to auditory stimuli (Geal-Dor et al., 2006; Matilainen et al., 2010), which has been attributed to the neuronal loss in the aging brain (Jernigan et al., 2001). This delayed temporal processing of speech sounds has been characterized by prolonged event-related potential (ERP) N1 and/or P2 responses in latency in older adults (Tremblay et al., 2003; Martin and Jerger, 2005), which may help explain older adults' slower P2 responses to auditory feedback errors during vocal pitch regulation compared to younger adults (Li et al., 2018).
Higher-order cognitive functions
Previous research has shown that speech changes in older adults only can be partially explained by physiological changes to the speech system (Bilodeau-Mercure and Tremblay, 2016). Cognitive decline in relation to working memory, attentional control, and executive function during aging (Salthouse, 1996; Park et al., 2002) has an impact on language/speech production (Barker et al., 2020). Aging-related declines in working memory, for example, result in the production of inaccurate speech sounds (Sadagopan and Smith, 2013). Inhibitory control deteriorates during aging (Nielson et al., 2002), and deficits of this function have been attributed to off-topic speech in older adults (Gold and Arbuckle, 1995). Also, evidence from people with cognitive impairment suggests a link between cognitive function and speech production. For example, PD patients with motor speech disorders were associated with greater attention/memory dysfunctions (Liu et al., 2019), and individuals with mild cognitive impairment exhibited weaker voice quality and slower articulation rates than healthy controls (Themistocleous et al., 2020). Also, Alzheimer's disease (AD) patients exhibited enhanced and prolonged vocal compensations for pitch perturbations that were significantly related to their dysfunctions in working memory and executive control (Ranasinghe et al., 2017).
A top-down inhibitory mechanism that has been proposed to address the neuromotor control of vocal production from a cognitive perspective (Guo et al., 2017; Ranasinghe et al., 2017; Liu et al., 2020) may account for aging-related changes in vocal motor control. Specifically, the left dorsolateral prefrontal cortex (DLPFC) is crucially involved in inhibitory control (Burle et al., 2004), and decreased activity in this region leads to impaired inhibitory control processes (Barber et al., 2013). On the other hand, decreased activity in the left DLPFC was significantly correlated with excessive vocal compensations for pitch perturbations in AD patients (Ranasinghe et al., 2017). Moreover, inhibitory continuous theta burst stimulation (c-TBS) over left DLPFC led to enhanced compensations for vocal pitch errors (Liu et al., 2020). These findings suggest the existence of a top-down inhibitory mechanism mediated by the left DLPFC that underlies auditory-motor control of vocal production, by which the audio-vocal system monitors and corrects feedback errors to produce the desired speech sounds with stability and precision. According to the inhibition deficit hypothesis, deficient inhibitory control occurs to older adults so that they fail to suppress task-irrelevant information (Campbell et al., 2020). Therefore, overcompensation for vocal feedback errors accompanied by decreased cortical activity observed in healthy older adults (Liu P. et al., 2011; Li et al., 2018) and patients with cognitive impairment (Ranasinghe et al., 2017, 2019) can be conceivably attributed to impairment of this top-down mechanism that fails to produce inhibitory control over vocal motor behaviors. These findings support the idea that speech motor control should be viewed as a “cognitive-motor accomplishment” (Kent, 2000), although the precise role of higher-order cognitive functions for speech motor control in older adults is still far from clear.
Sex and aging interaction
During the aging process, the substantial sex differences in speech acoustics are important but often overlooked. For example, men decrease their voice fo slightly until 50 years of age and then increase it afterwards, which is in contrast with women whose voice fo continuously decreases or stays constant until menopause and then decreases (Sataloff et al., 1997; Torre and Barlow, 2009). Our work reveals an aging-related, sex-specific changes in speech motor control, as reflected by decreased P2 amplitudes with aging in men only and men producing increased N1 and P2 responses than women were found in young adults but not in elderly adults (Li et al., 2018). These sex-related changes in speech production with aging have been accounted for by aging-related differences in the laryngeal and brain structures and functions between men and women. For instance, throughout adulthood, women experience more pronounced laryngeal drops and lengthening of the vocal tract than men, leading them to adjust their vowel and speech acoustic differentially to accommodate these changes (Rastatter and Jacques, 1990; Linville and Rens, 2001). Progressive changes in brain structure and function also differ between men and women (Cowell et al., 1994; Kakimoto et al., 2016), as evidenced by greater age-related increase in lateral fissure cerebrospinal fluid volume and greater variation in frontal cortex atrophy in men than in women (Coffey et al., 1998; Kakimoto et al., 2016).
More importantly, both animal and human studies have shown the impact of sex hormonal levels throughout the menstrual cycle or after menopause on controlling vocal production (Walpurger et al., 2004; Wadnerkar et al., 2006; Caras, 2013; Zhu et al., 2016). Specifically, in one study on young women across the menstrual cycle, Zhu et al. (2016) showed that larger vocal compensations for pitch perturbations were correlated with lower levels of estradiol concentration significantly and smaller P2 responses were associated higher levels of progesterone concentration. Although the underlying mechanisms remain largely unknown, sex hormones may modulate vocal motor behavior by activating receptor-coupled effector mechanisms through binding to specific hormone receptors that exist in the larynx and brain (Newman et al., 2000; Goldstein et al., 2001; Gheller et al., 2016). Taken together, these findings shed light on the substantial differences between men and women in elucidating how the aging process affects speech motor behaviors.
Future research
Clarifying the effects of aging on speech motor control not only provides insights into the relationship between the dynamics underlying speech production and neurobiology of aging, but also has important enlightenments for the treatment of motor speech disorders that frequently occur to aging adults. Future work is warranted to investigate the neural mechanisms underlying the effects of aging on speech motor control. On the other hand, abnormal vocal compensation for perturbed auditory feedback has been suggested to be a potential behavioral index of declined or impaired speech motor control (Ranasinghe et al., 2017; Li et al., 2018, 2021). More recently, non-invasive brain stimulation (NIBS) such as continuous theta burst stimulation (cTBS) has been applied over specific brain regions of aging patients with PD and SCA (Dai et al., 2022; Lin et al., 2022), resulting in a normalization of their overcompensation for vocal pitch perturbations. Therefore, NIBS may be a promising strategy that not only improves aging-related decline in the neuromotor control of speech production but also provides novel treatment of motor speech disorders that occur to aging patients with neurological disorders. Further investigations, however, are required to explore this topic in the future.
Author contributions
HH and HL: conceptualization. HH and JL: writing—original draft preparation. HH, SH, YZ, PL, and HL: writing—review and editing. All authors contributed to the article and approved the submitted version.
Funding
This work was supported by the National Natural Science Foundation of China (Nos. 82172528, 81702227, 82102660, and 82102648), the Natural Science Foundation of Shaanxi province (2022-JM482), and Guangdong Basic and Applied Basic Research Foundation (Nos. 2022A1515011203 and 2023A1515011758).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Amenedo, E., and Diaz, F. (1998). Effects of aging on middle-latency auditory evoked potentials: A cross-sectional study. Biol. Psychiat. 43, 210–219. doi: 10.1016/S0006-3223(97)00255-2
Baker, K. K., Ramig, L. O., Luschei, E. S., and Smith, M. E. (1998). Thyroarytenoid muscle activity associated with hypophonia in Parkinson disease and aging. Neurology 51, 1592–1598. doi: 10.1212/WNL.51.6.1592
Ballard, K. J., Robin, D. A., Woodworth, G., and Zimba, L. D. (2001). Age-related changes in motor control during articulator visuomotor tracking. J. Speech Lang. Hear. Res. 44, 763–777. doi: 10.1044/1092-4388(2001/060)
Barber, A. D., Caffo, B. S., Pekar, J. J., and Mostofsky, S. H. (2013). Effects of working memory demand on neural mechanisms of motor response selection and control. J. Cogn. Neurosci. 25, 1235–1248. doi: 10.1162/jocn_a_00394
Barker, M. S., Nelson, N. L., and Robinson, G. A. (2020). Idea formulation for spoken language production: The interface of cognition and language. J. Int. Neuropsychol. Soc. 26, 226–240. doi: 10.1017/S1355617719001097
Bilodeau-Mercure, M., Kirouac, V., Langlois, N., Ouellet, C., Gasse, I., and Tremblay, P. (2015). Movement sequencing in normal aging: speech, oro-facial, and finger movements. Age 37, 9813. doi: 10.1007/s11357-015-9813-x
Bilodeau-Mercure, M., and Tremblay, P. (2016). Age differences in sequential speech production: Articulatory and physiological factors. J. Am. Geriatr. Soc. 64, e177–e182. doi: 10.1111/jgs.14491
Burle, B., Vidal, F., Tandonnet, C., and Hasbroucq, T. (2004). Physiological evidence for response inhibition in choice reaction time tasks. Brain Cogn. 56, 153–164. doi: 10.1016/j.bandc.2004.06.004
Campbell, K. L., Lustig, C., and Hasher, L. (2020). Aging and inhibition: Introduction to the special issue. Psychol. Aging 35, 605–613. doi: 10.1037/pag0000564
Caras, M. L. (2013). Estrogenic modulation of auditory processing: a vertebrate comparison. Front. Neuroendocrin. 34, 285–299. doi: 10.1016/j.yfrne.2013.07.006
Chen, X., Zhu, X., Wang, E. Q., Chen, L., Li, W., Chen, Z., et al. (2013). Sensorimotor control of vocal pitch production in Parkinson's disease. Brain Res. 1527, 99–107. doi: 10.1016/j.brainres.2013.06.030
Coffey, C. E., Lucke, J. F., Saxton, J. A., Ratcliff, G., Unitas, L. J., Billig, B., et al. (1998). Sex differences in brain aging: A quantitative magnetic resonance imaging study. Arch. Neurol. 55, 169–179. doi: 10.1001/archneur.55.2.169
Cowell, P. E., Turetsky, B. I., Gur, R. C., Grossman, R. I., Shtasel, D. L., and Gur, R. E. (1994). Sex differences in aging of the human frontal and temporal lobes. J. Neurosci. 14, 4748–4755. doi: 10.1523/JNEUROSCI.14-08-04748.1994
Dai, G., Wang, M., Li, Y., Guo, Z., Jones, J. A., Li, T., et al. (2022). Continuous theta burst stimulation over left supplementary motor area facilitates auditory-vocal integration in individuals with Parkinson's disease. Front. Aging Neurosci. 14, 948696. doi: 10.3389/fnagi.2022.948696
Decoster, W., and Debruyne, F. (1997). The ageing voice: changes in fundamental frequency, waveform stability and spectrum. Acta Otorhinolaryngol. Belg. 51, 105–112.
Duchin, S. W., and Mysak, E. D. (1987). Disfluency and rate characteristics of young adult, middle-aged, and older males. J. Commun. Disord. 20, 245–257. doi: 10.1016/0021-9924(87)90022-0
Eckert, M. A., Walczak, A., Ahlstrom, J., Denslow, S., Horwitz, A., and Dubno, J. R. (2008). Age-related effects on word recognition: reliance on cognitive control systems with structural declines in speech-responsive cortex. J. Assoc. Res. Otolaryngol. 9, 252–259. doi: 10.1007/s10162-008-0113-3
Geal-Dor, M., Goldstein, A., Kamenir, Y., and Babkoff, H. (2006). The effect of aging on event-related potentials and behavioral responses: comparison of tonal, phonologic and semantic targets. Clin. Neurophysiol. 117, 1974–1989. doi: 10.1016/j.clinph.2006.05.024
Gheller, B. J., Riddle, E. S., Lem, M. R., and Thalacker-Mercer, A. E. (2016). Understanding age-related changes in skeletal muscle metabolism: Differences between females and males. Annu. Rev. Nutr. 36, 129–156. doi: 10.1146/annurev-nutr-071715-050901
Gold, D. P., and Arbuckle, T. Y. (1995). A longitudinal study of off-target verbosity. J. Gerontol. B Psychol. Sci. Soc. Sci. 50, 307–315. doi: 10.1093/geronb/50B.6.P307
Goldstein, J. M., Seidman, L. J., Horton, N. J., Makris, N., Kennedy, D. N., Caviness, V. S. Jr., et al. (2001). Normal sexual dimorphism of the adult human brain assessed by in vivo magnetic resonance imaging. Cereb. Cortex 11, 490–497. doi: 10.1093/cercor/11.6.490
Golfinopoulos, E., Tourville, J. A., and Guenther, F. H. (2010). The integration of large-scale neural network modeling and functional brain imaging in speech motor control. NeuroImage 52, 862–874. doi: 10.1016/j.neuroimage.2009.10.023
Gorham-Rowan, M. M., and Laures-Gore, J. (2006). Acoustic-perceptual correlates of voice quality in elderly men and women. J. Commun. Disord. 39, 171–184. doi: 10.1016/j.jcomdis.2005.11.005
Guo, Z., Wu, X., Li, W., Jones, J. A., Yan, N., Sheft, S., et al. (2017). Top-down modulation of auditory-motor integration during speech production: The role of working memory. J. Neurosci. 37, 10323–10333. doi: 10.1523/JNEUROSCI.1329-17.2017
Harris, K. C., Dubno, J. R., Keren, N. I., Ahlstrom, J. B., and Eckert, M. A. (2009). Speech recognition in younger and older adults: A dependency on low-level auditory cortex. J. Neurosci. 29, 6078–6087. doi: 10.1523/JNEUROSCI.0412-09.2009
Hirano, M., Vennard, W., and Ohala, J. (1970). Regulation of register, pitch and intensity of voice. An electromyographic investigation of intrinsic laryngeal muscles. Folia Phoniatr. Logo. 22, 1–20. doi: 10.1159/000263363
Houde, J. F., Gill, J. S., Agnew, Z., Kothare, H., Hickok, G., Parrell, B., et al. (2019). Abnormally increased vocal responses to pitch feedback perturbations in patients with cerebellar degeneration. J. Acoust. Soc. Am. 145, EL372. doi: 10.1121/1.5100910
Huang, X., Chen, X., Yan, N., Jones, J. A., Wang, E. Q., Chen, L., et al. (2016). The impact of Parkinson's disease on the cortical mechanisms that support auditory-motor integration for voice control. Hum. Brain Mapp. 37, 4248–4261. doi: 10.1002/hbm.23306
Jernigan, T. L., Archibald, S. L., Fennema-Notestine, C., Gamst, A. C., Stout, J. C., Bonner, J., et al. (2001). Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiol. Aging 22, 581–594. doi: 10.1016/S0197-4580(01)00217-2
Kakimoto, A., Ito, S., Okada, H., Nishizawa, S., Minoshima, S., and Ouchi, Y. (2016). Age-related sex-specific changes in brain metabolism and morphology. J. Nucl. Med. 57, 221–225. doi: 10.2967/jnumed.115.166439
Kent, R. D. (2000). Research on speech motor control and its disorders: a review and prospective. J. Commun. Disord. 33, 391–427. doi: 10.1016/S0021-9924(00)00023-X
Kovacevic, S., Qualls, C., Adair, J. C., Hudson, D., Woodruff, C. C., Knoefel, J., et al. (2005). Age-related effects on superior temporal gyrus activity during an auditory oddball task. Neuroreport 16, 1075–1079. doi: 10.1097/00001756-200507130-00009
Lametti, D. R., Nasir, S. M., and Ostry, D. J. (2012). Sensory preference in speech production revealed by simultaneous alteration of auditory and somatosensory feedback. J. Neurosci. 32, 9351–9358. doi: 10.1523/JNEUROSCI.0404-12.2012
Larson, C. R., Altman, K. W., Liu, H., and Hain, T. C. (2008). Interactions between auditory and somatosensory feedback for voice F (0) control. Exp. Brain Res. 187, 613–621. doi: 10.1007/s00221-008-1330-z
Li, J., Hu, H., Chen, N., Jones, J. A., Wu, D., Liu, P., et al. (2018). Aging and sex influence cortical auditory-motor integration for speech control. Front. Neurosci. 12, 749. doi: 10.3389/fnins.2018.00749
Li, W., Zhuang, J., Guo, Z., Jones, J. A., Xu, Z., and Liu, H. (2019). Cerebellar contribution to auditory feedback control of speech production: Evidence from patients with spinocerebellar ataxia. Hum. Brain Mapp. 40, 4748–4758. doi: 10.1002/hbm.24734
Li, Y., Tan, M., Fan, H., Wang, E. Q., Chen, L., Li, J., et al. (2021). Neurobehavioral effects of LSVT® LOUD on auditory-vocal Integration in Parkinson's disease: A preliminary study. Front. Neurosci. 15, 624801. doi: 10.3389/fnins.2021.624801
Lin, Q., Chang, Y., Liu, P., Jones, J. A., Chen, X., Peng, D., et al. (2022). Cerebellar continuous theta burst stimulation facilitates auditory-vocal integration in spinocerebellar ataxia. Cereb. Cortex 32, 455–466. doi: 10.1093/cercor/bhab222
Linville, S. E., and Rens, J. (2001). Vocal tract resonance analysis of aging voice using long-term average spectra. J. Voice. 15, 323–330. doi: 10.1016/S0892-1997(01)00034-0
Liu, D., Dai, G., Liu, C., Guo, Z., Xu, Z., Jones, J. A., et al. (2020). Top-down inhibitory mechanisms underlying auditory-motor integration for voice control: Evidence by TMS. Cereb. Cortex 30, 4515–4527. doi: 10.1093/cercor/bhaa054
Liu, H., Behroozmand, R., Bove, M., and Larson, C. R. (2011). Laryngeal electromyographic responses to perturbations in voice pitch auditory feedback. J. Acoust. Soc. Am. 129, 3946–3954. doi: 10.1121/1.3575593
Liu, H., Russo, N., and Larson, C. R. (2010). Age-related differences in vocal responses to pitch feedback perturbations: A preliminary study. J. Acoust. Soc. Am. 127, 1042–1046. doi: 10.1121/1.3273880
Liu, H., Wang, E. Q., Verhagen Metman, L., and Larson, C. R. (2012). Vocal responses to perturbations in voice auditory feedback in individuals with Parkinson's disease. PLoS ONE 7, e33629. doi: 10.1371/journal.pone.0033629
Liu, P., Chen, Z., Jones, J. A., Huang, D., and Liu, H. (2011). Auditory feedback control of vocal pitch during sustained vocalization: A cross-sectional study of adult aging. PLoS ONE 6, e22791. doi: 10.1371/journal.pone.0022791
Liu, Y., Gui, Y., Hu, J., Liang, S., Mo, S., Zhou, Y., et al. (2019). Attention/memory complaint is correlated with motor speech disorder in Parkinson's disease. BMC Neurol. 19, 309. doi: 10.1186/s12883-019-1535-8
Ludlow, C., Van Pelt, F., and Koda, J. (1992). Characteristics of late responses to superior laryngeal nerve stimulation in humans. Ann. Oto. Rhinol. Laryngol. 101, 127–134. doi: 10.1177/000348949210100204
Martin, J. S., and Jerger, J. F. (2005). Some effects of aging on central auditory processing. J. Rehabil. Res. Dev. 42, 25–44. doi: 10.1682/JRRD.2004.12.0164
Matilainen, L. E., Talvitie, S. S., Pekkonen, E., Alku, P., May, P. J., and Tiitinen, H. (2010). The effects of healthy aging on auditory processing in humans as indexed by transient brain responses. Clin. Neurophysiol. 121, 902–911. doi: 10.1016/j.clinph.2010.01.007
Mollaei, F., Shiller, D. M., Baum, S. R., and Gracco, V. L. (2016). Sensorimotor control of vocal pitch and formant frequencies in Parkinson's disease. Brain Res. 1646, 269–277. doi: 10.1016/j.brainres.2016.06.013
Mueller, P. B. (1997). The aging voice. Semin. Speech Lang. 18, 159–169. doi: 10.1055/s-2008-1064070
Newman, S. R., Butler, J., Hammond, E. H., and Gray, S. D. (2000). Preliminary report on hormone receptors in the human vocal fold. J. Voice. 14, 72–81. doi: 10.1016/S0892-1997(00)80096-X
Nielson, K. A., Langenecker, S. A., and Garavan, H. (2002). Differences in the functional neuroanatomy of inhibitory control across the adult life span. Psychol. Aging 17, 56–71. doi: 10.1037/0882-7974.17.1.56
Park, D. C., Lautenschlager, G., Hedden, T., Davidson, N. S., Smith, A. D., and Smith, P. K. (2002). Models of visuospatial and verbal memory across the adult life span. Psychol. Aging 17, 299–320. doi: 10.1037/0882-7974.17.2.299
Parrell, B., Agnew, Z., Nagarajan, S., Houde, J., and Ivry, R. B. (2017). Impaired feedforward control and enhanced feedback control of speech in patients with cerebellar degeneration. J. Neurosci. 37, 9249–9258. doi: 10.1523/JNEUROSCI.3363-16.2017
Ramig, L. A., and Ringel, R. L. (1983). Effects of physiological aging on selected acoustic characteristics of voice. J. Speech Hear. Res. 26, 22–30. doi: 10.1044/jshr.2601.22
Ramig, L. O., Gray, S., Baker, K., Corbin-Lewis, K., Buder, E., Luschei, E., et al. (2001). The aging voice: A review, treatment data and familial and genetic perspectives. Folia Phoniatr. Logo. 53, 252–265. doi: 10.1159/000052680
Ranasinghe, K. G., Gill, J. S., Kothare, H., Beagle, A. J., Mizuiri, D., Honma, S. M., et al. (2017). Abnormal vocal behavior predicts executive and memory deficits in Alzheimer's disease. Neurobiol. Aging 52, 71–80. doi: 10.1016/j.neurobiolaging.2016.12.020
Ranasinghe, K. G., Kothare, H., Kort, N., Hinkley, L. B., Beagle, A. J., Mizuiri, D., et al. (2019). Neural correlates of abnormal auditory feedback processing during speech production in Alzheimer's disease. Sci. Rep. 9, 5686. doi: 10.1038/s41598-019-41794-x
Rastatter, M. P., and Jacques, R. D. (1990). Formant frequency structure of the aging male and female vocal tract. Folia Phoniatr. 42, 312–319. doi: 10.1159/000266088
Sadagopan, N., and Smith, A. (2013). Age differences in speech motor performance on a novel speech task. J. Speech Lang. Hear. Res. 56, 1552–1566. doi: 10.1044/1092-4388(2013/12-0293)
Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychol. Rev. 103, 403–428. doi: 10.1037/0033-295X.103.3.403
Sataloff, R. T., Rosen, D. C., Hawkshaw, M., and Spiegel, J. R. (1997). The aging adult voice. J. Voice. 11, 156–160. doi: 10.1016/S0892-1997(97)80072-0
Soros, P., Bose, A., Sokoloff, L. G., Graham, S. J., and Stuss, D. T. (2011). Age-related changes in the functional neuroanatomy of overt speech production. Neurobiol. Aging 32, 1505–1513. doi: 10.1016/j.neurobiolaging.2009.08.015
Stephen, J. M., Knoefel, J. E., Adair, J., Hart, B., and Aine, C. J. (2010). Aging-related changes in auditory and visual integration measured with MEG. Neurosci. Lett. 484, 76–80. doi: 10.1016/j.neulet.2010.08.023
Themistocleous, C., Eckerstrom, M., and Kokkinakis, D. (2020). Voice quality and speech fluency distinguish individuals with Mild Cognitive Impairment from Healthy Controls. PLoS ONE 15, e0236009. doi: 10.1371/journal.pone.0236009
Torre, P. 3rd., and Barlow, J. A. (2009). Age-related changes in acoustic characteristics of adult speech. J. Commun. Disord. 42, 324–333. doi: 10.1016/j.jcomdis.2009.03.001
Tremblay, K. L., Piskosz, M., and Souza, P. (2003). Effects of age and age-related hearing loss on the neural representation of speech cues. Clin. Neurophysiol. 114, 1332–1343. doi: 10.1016/S1388-2457(03)00114-7
Tremblay, P., and Deschamps, I. (2016). Structural brain aging and speech production: A surface-based brain morphometry study. Brain Struct. Funct. 221, 3275–3299. doi: 10.1007/s00429-015-1100-1
Tremblay, P., Dick, A. S., and Small, S. L. (2013). Functional and structural aging of the speech sensorimotor neural system: Functional magnetic resonance imaging evidence. Neurobiol. Aging 34, 1935–1951. doi: 10.1016/j.neurobiolaging.2013.02.004
Tremblay, P., Sato, M., and Deschamps, I. (2017). Age differences in the motor control of speech: An fMRI study of healthy aging. Hum. Brain Mapp. 38, 2751–2771. doi: 10.1002/hbm.23558
Tucker, B. V., Ford, C., and Hedges, S. (2021). Speech aging: Production and perception. Wiley Interdiscip Rev Cogn Sci 12, e1557. doi: 10.1002/wcs.1557
Wadnerkar, M. B., Cowell, P. E., and Whiteside, S. P. (2006). Speech across the menstrual cycle: A replication and extension study. Neurosci. Lett. 408, 21–24. doi: 10.1016/j.neulet.2006.07.032
Walpurger, V., Pietrowsky, R., Kirschbaum, C., and Wolf, O. T. (2004). Effects of the menstrual cycle on auditory event-related potentials. Horm. Behav. 46, 600–606. doi: 10.1016/j.yhbeh.2004.07.002
Wohlert, A. B., and Smith, A. (1998). Spatiotemporal stability of lip movements in older adult speakers. J. Speech Lang. Hear. Res. 41, 41–50. doi: 10.1044/jslhr.4101.41
Keywords: speech production, aging, neuromotor control, auditory feedback, voice
Citation: Hu H, Li J, He S, Zhao Y, Liu P and Liu H (2023) Aging-related decline in the neuromotor control of speech production: current and future. Front. Aging Neurosci. 15:1172277. doi: 10.3389/fnagi.2023.1172277
Received: 23 February 2023; Accepted: 05 April 2023;
Published: 20 April 2023.
Edited by:
Xiaoyan Li, Medical College of Wisconsin, United StatesReviewed by:
Xing Tian, New York University Shanghai, ChinaAllison Hilger, University of Colorado Boulder, United States
Copyright © 2023 Hu, Li, He, Zhao, Liu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hanjun Liu, bGhhbmp1biYjeDAwMDQwO21haWwuc3lzdS5lZHUuY24=
†These authors have contributed equally to this work