A systems perspective on the effective connectivity of overt speech production

Abstract

The aim of this study was to provide a computational system model of effective connectivity in the human brain underlying overt speech production. Meta-analysis of neuroimaging studies and functional magnetic resonance imaging data acquired during a verbal fluency task revealed a core network consisting of Brodmann's area (BA) 44 in Broca's region, anterior insula, basal ganglia, cerebellum, premotor cortex (PMC, BA 6) and primary motor cortex (M1, areas 4a/4p). Dynamic causal modelling (DCM) indicated the highest evidence for a system architecture featuring the insula in a serial position between BA 44 and two parallel nodes (cerebellum/basal ganglia), from which information converges onto the PMC and finally M1. Parameter inference revealed that effective connectivity from the insular relay into the cerebellum/basal ganglia is primarily task driven (preparation) while the output into the cortical motor system strongly depends on the actual word production rate (execution). DCM hence allowed not only a quantitative characterization of the human speech production network, but also the distinction of a preparatory and an executive subsystem within it. The proposed model of physiological integration during speech production may now serve as a reference for investigations into the neurobiology of pathological states such as dysarthria and apraxia of speech.

Figure 1

Overview of the four hypothesized network architectures underlying overt speech production ((a) model 1, (b) model 2, (c) model 3 and (d) model 4). In all models, each of the defined connections between was allowed to be modulated by any of these conditions. In order to identify the most likely structure of the system given the measured functional magnetic resonance imaging data, a Bayesian model selection procedure based on comparison of the posterior model evidence was employed (cf. table 2).

Figure 2

Localization of the core areas of the cortico-subcortical network overt speech production network as defined by (a) the meta-analysis of previous neuroimaging studies (19 published studies, ALE modelling, p<0.01, FDR; cf. table 1), (b) the fMRI random-effects group analysis (20 subjects, RDFX analysis, p<0.05, FWE) and (c) the location of the activation maxima for the individual subjects (ellipsoids summarize individual maxima: centre, mean location; width, standard deviation) ((i) insula, (ii) BA 44, (iii) PMC/caudate, (iv) M1 and (v) cerebellum).

Figure 3

Correlation analysis between the number of produced words (irrespective of task condition) and the effective connectivity between speech motor areas. (a) Demonstrates that the significant main effect of production rate was due to a higher modulation of effective connectivity in those blocks where more words were produced (r=0.15, p=0.001). (b) Resolves the significant ‘rate×connection’ interaction: only the coupling parameters for the caudate→PMC, cerebellum→PMC and PMC→M1 connections increased significantly with higher word production rates ((i) BA 44→insula; r=−0.07, p=0.509, (ii) insula→caudate; r=0.06, p=0.590, (iii) insula→cerebellum; r=0.10, p=0.378, (iv) caudate→PMC; r=0.39, p<0.001, (v) cerebellum→PMC; r=0.32, p=0.003 and (vi) PMC→M1; r=0.23, p=0.050).

Figure 4

Summary of the system model for overt speech production described in the present study. The numbers refer to the obtained coupling parameters for the displayed model 1 that received the highest model evidence among the four compared hypotheses (figure 1). Coupling parameters are given as rate constants (s⁻¹). Red numbers denote the intrinsic, context-independent connectivity, green ones the task-dependent modulations thereof. For those connections that were significantly modulated by production rate, the respective correlation coefficients are shown in blue.