New Developments in Understanding the Complexity of Human Speech Production

Abstract

Speech is one of the most unique features of human communication. Our ability to articulate our thoughts by means of speech production depends critically on the integrity of the motor cortex. Long thought to be a low-order brain region, exciting work in the past years is overturning this notion. Here, we highlight some of major experimental advances in speech motor control research and discuss the emerging findings about the complexity of speech motocortical organization and its large-scale networks. This review summarizes the talks presented at a symposium at the Annual Meeting of the Society of Neuroscience; it does not represent a comprehensive review of contemporary literature in the broader field of speech motor control.

Keywords: ECoG; motor cortex; neuroimaging; speech production.

Figure 1.

Hierarchical organization of the dual pathway of central voice control. The lowest level (subsystem I) is represented by the sensorimotor phonatory nuclei in brainstem and spinal cord, which control laryngeal, articulatory, and respiratory muscles during production of innate vocalizations. The higher level within this system (subsystem II) is represented by the periaqueductal gray, cingulate cortex, and limbic input structures that control vocalization initiation and motivation as well voluntary emotional vocalizations. The highest level (subsystem III) is represented by the laryngeal/orofacial motor cortex in the vSMC with its input and output regions that are responsible for voluntary motor control of speech production. Dotted lines indicate direct connections between different regions within the voice-controlling system. Data from Simonyan and Horwitz (2011).

Figure 2.

A, Schematic view of human body representation within the motor cortex (“motor homunculus”). Data from Penfield and Bordley (1937). B, Probabilistic maps of the vSMC demonstrating the probability of observing a particular motor and sensory response as well as speech arrest to electrical stimulation at a particular cortical site. Color scale represents the probability of each response. Data from Breshears et al. (2015). Ca, Spatial localization of lips, jaw, tongue, and larynx representations within the vSMC. Average magnitude of articulator weightings (color scale) plotted as a function of anteroposterior (AP) distance from the central sulcus and dorsoventral (DV) distance from the Sylvian fissure. Cb, Functional somatotopic organization of speech-articulator representations in the vSMC. Red represents lips. Green represents jaw. Blue represents tongue. Black represents larynx. Yellow represents mixed. D, Timing of correlations between cortical activity and consonant (Da) and vowel (Db) articulator features with (Dc) acoustic landmarks, (Dd) temporal sequence, and range of correlations. Data from Bouchard et al. (2013).

Figure 3.

Differences in voice frequency following response (Aa) and high-gamma response (Ab) between primary auditory cortical areas on posteromedial HG compared with nonprimary areas on anterolateral HG. Data from Behroozmand et al. (2016). B, Changes in speech timing (yellow) versus quality (blue) resulting from focal brain cooling of the IFG and vSMC. Data from Long et al. (2016). C, Average coherence between auditory areas on lateral STG and dorsal premotor cortex (a, c) and IFG (b, d). Data from Kingyon et al. (2015).

Figure 4.

A, Common and distinct functional and structural networks of the laryngeal motor cortex during syllable production and voluntary breathing. Yellow represents functional connections (F) underlying each task. White represents structural connections (S) underlying each task. Red represents overlap between the functional and structural connections (FxS). Data from Simonyan et al. (2009). B, Functional community structure of the group-averaged networks during the resting state, syllable production, sentence production, sequential finger tapping, and auditory discrimination of pure tones. Distinct network communities are shown as circular groups of nodes positioned around the respective connector hubs, which are arranged on horizontal lines. Nodal colors represent module membership. Node lists on the left and right of each graph indicate connector and provincial hubs, respectively. 1, area 1; 17, area 17; 2, area 2; 3a/3b, areas 3a/3b; 44, area 44; 4a/4p, anterior/posterior part of area 4; 5L/5M, area 5L/5M; 6, area 6; 7A/7P/7PC, area 7A/7P/7PC; Cbl-V/VI/VIv/VIIa/Cr1, cerebellar lobules V/VI/VIv/VIIa/Cr1; Cu, cuneus; FG, fusiform gyrus; hIP3, areas hIP3; IL, insula; SOG, superior occipital gyrus; ITG/MTG, inferior/middle temporal gyrus; LG, lingual gyrus; MCC, middle cingulate cortex; OP1–4, operculum; PCu, precuneus; PF/PFm/PFop/PFt/PGa/PGp, areas PF/PFm/PFop/PFt/PGa/PGp in the inferior parietal cortex; MFG, middle frontal gyrus; THp/THpf/THpm/THt, parietal/prefrontal/premotor/temporal part of the thalamus; TP, temporal pole; R, right; L, left. Data from Fuertinger et al. (2015).

Figure 5.

A, The cerebral networks supporting primate-general (gray arrows) and human-specific (black) aspects of vocal communication are assumed to be closely intertwined at the level of the basal ganglia. Dashed lines indicate that the basal ganglia motor loop undergoes a dynamic ontogenetic reorganization during spoken language acquisition in that a left-hemisphere cortical storage site of syllable-sized motor programs gradually emerges. Amygdala etc., Amygdala and other structures of the limbic system; ACC, anterior cingulate cortex; SMA, supplementary motor area; GPi, internal segment of globus pallidus; SNr/SNc, substantia nigra, pars reticulata/pars compacta; PAG, periaqueductal gray; vCPG, vocal central pattern generator. Data from Ackermann et al. (2014). B, Gestural architecture of the word “speaking.” Laryngeal activity (bottom line) is a crucial part of the respective movement sequence and must be adjusted to other vocal tract excursions. Articulatory gestures are assorted into syllabic units; gesture bundles pertaining to strong and weak syllables are rhythmically patterned to form metrical feet. Data from Ziegler (2010).