Closed-loop paradigms provide us with the opportunity to optimize stimulation protocols for perturbation of pathological oscillatory activity in brain-related disorders. In this vein, spiking activity of motor cortex neurons and beta activity of local field potentials in the subthalamic nucleus have both been used independently of each other as neuronal signals to trigger deep brain stimulation for alleviating Parkinsonism. These approaches were superior to the standard continuous high-frequency stimulation protocols used in daily practice. However, they achieved their effects by bursts of stimulation that were applied at high-frequency as well, i.e., independent of the phase information in the stimulated region. In this context, we propose that, by timing stimulation pulses relative to the ongoing oscillation, an alternative approach, namely the targeted perturbation of pathological rhythms, could be obtained. In this modeling study, we first captured the underlying dynamics of neuronal oscillations in the human subthalamic nucleus by phased coupled neuronal oscillators. We then quantified the nature of the interaction between these coupled oscillators by obtaining a physiologically informed phase response curve from local field potentials. Reconstruction of the phase response curve predicted the sensitivity of the phase oscillator to external stimuli, revealing phase intervals that optimally maximized the degree of perturbation. We conclude that our specifically timed intervention based on the coupled oscillator concept will enable us to identify personalized ways of delivering stimulation pulses in closed-loop paradigms triggered by the phase of pathological oscillations. This will pave the way for novel physiological insights and substantial clinical benefits. In addition, this precisely phased modulation may be capable of modifying the effective interactions between oscillators in an entirely new manner.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for symptomatic Parkinson’s disease (PD); the clinical benefit may not only mirror modulation of local STN activity but also reflect consecutive network effects on cortical oscillatory activity. Moreover, STN-DBS selectively suppresses spatially and spectrally distinct patterns of synchronous oscillatory activity within cortical-subcortical loops. These STN-cortical circuits have been described in PD patients using magnetoencephalography after surgery. This network information, however, is currently not available during surgery to inform the implantation strategy.The authors recorded spontaneous brain activity in 3 awake patients with PD (mean age 67 ± 14 years; mean disease duration 13 ± 7 years) during implantation of DBS electrodes into the STN after overnight withdrawal of dopaminergic medication. Intraoperative propofol was discontinued at least 30 minutes prior to the electrophysiological recordings. The authors used a novel approach for performing simultaneous recordings of STN local field potentials (LFPs) and multichannel electroencephalography (EEG) at rest. Coherent oscillations between LFP and EEG sensors were computed, and subsequent dynamic imaging of coherent sources was performed.The authors identified coherent activity in the upper beta range (21–35 Hz) between the STN and the ipsilateral mesial (pre)motor area. Coherence in the theta range (4–6 Hz) was detected in the ipsilateral prefrontal area.These findings demonstrate the feasibility of detecting frequency-specific and spatially distinct synchronization between the STN and cortex during DBS surgery. Mapping the STN with this technique may disentangle different functional loops relevant for refined targeting during DBS implantation.

There is physiological evidence that Central Pattern Generators (CPG's), at the level of spinal cords, are responsible for generating rhythmic movements in some species of animals like salamanders. There are also other researches suggesting that in human beings there are CPGs at higher levels of the Central Nervous System (CNS) which facilitate the control of rhythmic movements. We proposed a model using the idea of CPG's to mimic human rhythmic arm movement. This model is a neural oscillator which consists of two neurons coupled by reciprocal inhibitions and exhibits different types of bursting and tonic neuronal behaviors. We consider once a one-compartment (the whole neuron or the soma) and then a two-compartment (somadendrite) model to describe the two neurons of the CPG, that describes here the motor control system. Each compartment is described by Hodgkin-Huxley (HH) equations. We show that bursting frequency and the number of action potentials can be controlled by variation of intracellular parameters in both models. In addition, considering dendrite component will allow us to make transition between different neural activities. To describe arm rhythmic movement, the motor control system will be coupled into two motoneurons by inhibitory and excitatory connections. The motoneurons drive the extensor and flexor muscles. We found out that both synaptic coupling and motor control parameters have direct impacts on the spiking frequency of motoneurons which play a critical role in the behavior of arm movement.