Network connectivity of motor control in the ageing brain

Abstract

Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions between brain regions remains scarce. We here investigated the impact of ageing on the interaction of cortical areas during movement selection and initiation using dynamic causal modelling (DCM). We found that age-related psychomotor slowing was accompanied by increases in both regional activity and effective connectivity, especially for 'core' motor coupling targeting primary motor cortex (M1). Interestingly, younger participants within the older group showed strongest connectivity targeting M1, which steadily decreased with advancing age. Conversely, prefrontal influences on the motor system increased with advancing age, and were inversely correlated with reduced parietal influences and core motor coupling. Interestingly, higher net coupling within the prefrontal-premotor-M1 axis predicted faster psychomotor speed in ageing. Hence, as opposed to a uniform age-related decline, our findings are compatible with the idea of different age-related compensatory mechanisms, with an important role of the prefrontal cortex compensating for reduced coupling within the core motor network.

Keywords: Ageing; Effective connectivity; Motor control; fMRI.

Fig. 1

FMRI paradigm. Each block of trials started with the presentation of a fixation cross. ‘Free’- condition: Upon appearance of the fixation cross, subjects were instructed to press the left or right button with the respective index finger at any self-chosen time. Every response was followed by a visual feedback pointing to the side of the button-press. Thereafter, the fixation cross re-appeared until the next response was given by the subject. Thus, subjects were free in terms of both movement lateralization and timing. ‘Intern’- condition: Subjects were instructed to react as fast as possible and press the left or right button upon appearance of a double-headed arrow pointing to both sides. Hence, subjects were restricted with re. to the timing of movement initiation but free in terms of movement lateralization. The fixation cross re-appeared for the time between stimuli. ‘Extern’- condition: Subjects were instructed to react as fast as possible and press the left button upon appearance of an arrow pointing to the left or the right button upon appearance of an arrow pointing to the right. Thus, subjects were restricted with re. to both timing and movement lateralization.

Fig. 2

BOLD activation pattern and between-group activity differences. (I) Conjunction analysis of the neural networks activated by all three higher motor control conditions (‘Free’/‘Intern’/‘Extern’) across all subjects, i.e., n = 24. ROIs used for DCM analysis are highlighted. PFC = prefrontal cortex, PMC = premotor cortex, SMA = supplementary motor area, M1 = primary motor cortex, IPS = intraparietal sulcus. (II) Activity for young (n = 12) and old (n = 12) subjects for each condition separately. (III) Between-group activity differences. Significantly enhanced BOLD activity in old as compared to young individuals for each condition separately. All p < 0.05, family-wise error (FWE) corrected at the cluster level.

Fig. 3

Between-group connectivity differences. Green arrows indicate significantly enhanced endogenous connectivity (DCM-A) between two regions in old as compared to young individuals. Note that all differences between groups remained significant when controlling for structural atrophy as informed by the VBM analysis. PFC = prefrontal cortex, PMC = premotor cortex, SMA = supplementary motor area, M1 = primary motor cortex, IPS = intraparietal sulcus. R = right-hemispheric, L = left-hemispheric. p < 0.05, FDR-corrected for multiple comparisons. Bars represent coupling strength in 1/s. Error bars: SEM.

Fig. 4

Network changes with advancing age. Correlations between advancing age and coupling parameters (DCM-A) in old individuals. Coupling parameters of young subjects are indicated by grey diamonds and shown for illustrative purposes to underline between-group differences for the respective connections. Coupling parameters for older subjects are indicated by red circles for connections displaying a negative correlation with age, and by green circles for connections showing a positive correlation with age. Three different patterns of differential connectivity changes emerged: (I) IPS-PMC: no group difference between young and old subjects, negative correlation with age in old subjects. (II) Coupling targeting M1: enhanced connectivity in older individuals at the group level, negative correlation with age in old subjects. (III) PFC-PMC: enhanced connectivity in older individuals at the group level, positive correlation with age in older subjects. Note that all correlations shown remained significant when controlling for structural atrophy as informed by the VBM analysis. PFC = prefrontal cortex, PMC = premotor cortex, SMA = supplementary motor area, M1 = primary motor cortex, IPS = intraparietal sulcus. *p < 0.05, FDR-corrected for multiple comparisons; n.s. = not significant. Coupling strength in 1/s.

Fig. 5

Association between increased prefrontal coupling and decreased coupling in other parts of the network. Negative correlations between individual PFC-PMC coupling and coupling parameters of other connections displaying a relationship with advancing age in older individuals (cf. Fig. 5). Subjects featuring weaker parietal-premotor-M1 coupling with advancing age show the strongest increase in prefrontal-premotor connectivity. PFC = prefrontal cortex, PMC = premotor cortex, SMA = supplementary motor area, M1 = primary motor cortex, IPS = intraparietal sulcus. *p < 0.05, FDR-corrected for multiple comparisons. Coupling strength in 1/s.

Fig. 6

Association between increased prefrontal-premotor-M1 coupling and behavioural performance. When controlling for grey matter atrophy as informed by the VBM analysis, increased net coupling within the prefrontal-premotor-M1 axis (PFC-PMC + SMA-M1 connectivity) negatively correlates with RTs in both the ‘Intern’ and ‘Extern’ condition. Hence, stronger positive coupling is associated with faster RT, i.e., better behavioural performance. Note that in both panels, data points of two subjects are very close, giving rise to the impression that the plots only contain 11 data points. However, in conformity with previous figures, all 12 data points are displayed in both panels. PFC = prefrontal cortex, PMC = premotor cortex, SMA = supplementary motor area, M1 = primary motor cortex, IPS = intraparietal sulcus. *p < 0.05, FDR-corrected for multiple comparisons.