The motor inhibitory network in patients with asymmetrical Parkinson’s disease: An fMRI study

Recent imaging studies with the stop-signal task in healthy individuals indicate that the subthalamic nucleus, the pre-supplementary motor area and the inferior frontal gyrus are key components of the right hemisphere “inhibitory network”. Limited information is available regarding neural substrates of inhibitory processing in patients with asymmetric Parkinson’s disease. The aim of the current fMRI study was to identify the neural changes underlying deficient inhibitory processing on the stop-signal task in patients with predominantly left-sided Parkinson’s disease. Fourteen patients and 23 healthy controls performed a stop-signal task with the left and right hands. Behaviorally, patients showed delayed response inhibition with either hand compared to controls. We found small imaging differences for the right hand, however for the more affected left hand when behavior was successfully inhibited we found reduced activation of the inferior frontal gyrus bilaterally and the insula. Using the stop-signal delay as regressor, contralateral underactivation in the right dorsolateral prefrontal cortex, inferior frontal and anterior putamen were found in patients. This finding indicates dysfunction of the right inhibitory network in left-sided Parkinson’s disease. Functional connectivity analysis of the left subthalamic nucleus showed a significant increase of connectivity with bilateral insula. In contrast, the right subthalamic nucleus showed increased connectivity with visuomotor and sensorimotor regions of the cerebellum. We conclude that altered inhibitory control in left-sided Parkinson’s disease is associated with reduced activation in regions dedicated to inhibition in healthy controls, which requires engagement of additional regions, not observed in controls, to successfully stop ongoing actions.

Multiple Brain Sources Are Differentially Engaged in the Inhibition of Distinct Action Types

Most studies contributing to identify the brain network for inhibitory control have investigated the cancelation of prepared–discrete actions, thus focusing on an isolated and short-lived chunk of human behavior. Aborting ongoing–continuous actions is an equally crucial ability but remains little explored. Although discrete and ongoing–continuous rhythmic actions are associated with partially overlapping yet largely distinct brain activations, it is unknown whether the inhibitory network operates similarly in both situations. Thus, distinguishing between action types constitutes a powerful means to investigate whether inhibition is a generic function. We, therefore, used independent component analysis (ICA) of EEG data and show that canceling a discrete action and aborting a rhythmic action rely on independent brain components. The ICA showed that a delta/theta power increase generically indexed inhibitory activity, whereas N2 and P3 ERP waves did so in an action-specific fashion. The action-specific components were generated by partially distinct brain sources, which indicates that the inhibitory network is engaged differently when canceling a prepared–discrete action versus aborting an ongoing–continuous action. In particular, increased activity was estimated in precentral gyri and posterior parts of the cingulate cortex for action canceling, whereas an enhanced activity was found in more frontal gyri and anterior parts of the cingulate cortex for action aborting. Overall, the present findings support the idea that inhibitory control is differentially implemented according to the type of action to revise.

Influence of Brain-Derived Neurotrophic Factor Genotype on Short-Latency Afferent Inhibition and Motor Cortex Metabolites

The Met allele of the brain-derived neurotrophic factor (BDNF) gene confers reduced cortical BDNF expression and associated neurobehavioral changes. BDNF signaling influences the survival, development, and synaptic function of cortical networks. Here, we compared gamma-aminobutyric acid (GABA)ergic network activity in the human primary motor cortex (M1) between the Met (Val/Met and Met/Met) and non-Met (Val/Val) genotype groups. Short- and long-interval intracortical inhibition, short-latency afferent inhibition (SAI), and long-latency afferent inhibition were measured using transcranial magnetic stimulation (TMS) as indices of GABAergic activity. Furthermore, the considerable inter-individual variability in inhibitory network activity typically measured by TMS may be affected not only by GABA but also by other pathways, including glutamatergic and cholinergic activities; therefore, we used 3-T magnetic resonance spectroscopy (MRS) to measure the dynamics of glutamate plus glutamine (Glx) and choline concentrations in the left M1, left somatosensory cortex, and right cerebellum. All inhibitory TMS conditions produced significantly smaller motor-evoked potentials than single-pulses. SAI was significantly stronger in the Met group than in the Val/Val group. Only the M1 Glx concentration was significantly lower in the Met group, while the BDNF genotype did not affect choline concentration in any region. Further, a positive correlation was observed between SAI and Glx concentrations only in M1. Our findings provide evidence that the BDNF genotype regulates both the inhibitory and excitatory circuits in human M1. In addition, lower Glx concentration in the M1 of Met carriers may alter specific inhibitory network on M1, thereby influencing the cortical signal processing required for neurobehavioral functions.

Dissociable brain components for inhibitory control: A source separation analysis of cancelling and stopping actions

Previous work has drawn an inhibitory brain network by investigating the cancellation of prepared–discrete actions, thus focusing on an isolated aspect of human behavior. Indeed, ongoing–continuous actions, which have been associated with distinct brain mechanisms for generation, are also crucial to be stopped. Still, it is unknown whether the same inhibitory network generalizes to various situations, including cancelling a prepared–discrete action and stopping an ongoing–continuous action. We used independent component analysis of EEG data to show that cancelling and stopping action rely on independent brain components for inhibition. Indeed, the brain component which best explained inhibition when cancelling action was not involved in stopping action, and reciprocally. The analysis of these components showed that a Delta/Theta power increase generically indexes inhibitory activity, while N2 and P3 event-related potentials do it in a specific way. Sources reconstruction further identified dissociations in the brain areas generating the two inhibitory components. The differences identified between the two source generators underlie some specific activities of the inhibitory network involved in cancelling a prepared–discrete action and stopping an ongoing–continuous action. Thus, increased activity was observed in precentral gyri and posterior parts of the cingulate cortex when action cancelling, while a higher activity was found in more frontal gyri and anterior parts of the cingulate cortex when action stopping. Overall, the present findings support the idea that inhibitory control is differentially implemented according to the type of action to revise.

Spatially localized cluster solutions in inhibitory neural networks

Neurons in the inhibitory network of the striatum display cell assembly firing patterns which recent results suggest may consist of spatially compact neural clusters. Previous computational modeling of striatal neural networks has indicated that non-monotonic, distance-dependent coupling may promote spatially localized cluster firing. Here, we identify conditions for the existence and stability of cluster firing solutions in which clusters consist of spatially adjacent neurons in inhibitory neural networks. We consider simple non-monotonic, distance-dependent connectivity schemes in weakly coupled 1-D networks where cells make strong connections with their kth nearest neighbors on each side. Using the phase model reduction of the network system, we prove the existence of cluster solutions where neurons that are spatially close together are also synchronized in the same cluster, and find stability conditions for these solutions. Our analysis predicts the long-term behavior for networks of neurons, and we confirm our results by numerical simulations of biophysical neuron network models. Additionally, we add weaker coupling between closer neighbors as a perturbation to our network connectivity. We analyze the existence and stability of cluster solutions of the perturbed network and validate our results with numerical simulations. Our results demonstrate that an inhibitory network with non-monotonic, distance-dependent connectivity can exhibit cluster solutions where adjacent cells fire together.