On the Significance of Stimulus Waveform in the Modulation of Oscillatory Activity in Excitable Tissues

Abstract

Electrical stimulation can influence the natural rhythms of activity in heart and brain tissue and has numerous applications in the treatment of cardiac and neurological conditions. The design and optimization of electrical stimulus treatments relies on the ability of researchers to predict the physiological responses of the target tissue to external stimulation. These responses vary greatly depending on the stimulus waveform and parameters as well as the state of ongoing activity in the target region, in ways that are not yet fully understood. The objective of this dissertation is to examine the theoretical basis for differential responses to rhythmic external stimulation based on the properties of the stimulus and target tissue and provide insights for future stimulus technique design.Synaptic plasticity plays a key role in neurostimulation as it allows for the effects of stimulus treatments to persist long after the stimulus ends. Rhythmic stimulation can entrain natural neural oscillations and produce persistent changes in the frequency content of neural activity. However, the mechanisms behind these changes are largely unknown. To this end, simple neural oscillator models were constructed in order to examine the role of synaptic plasticity and sinusoidal stimulation on the synchronization between oscillating regions. Sinusoidal stimulation of different frequencies and strengths can disrupt the intrinsic patterns of network activity, causing information to propagate through the network via different synaptic paths. These new pathways are reinforced through spike timing dependent plasticity, fundamentally altering the network behavior post-stimulation. The resulting network activity depends on the stimulus strength and frequency as well as the intrinsic frequencies of the neural oscillators and the strength of inter-oscillator coupling. Additionally, the effects of rhythmic stimulation depend on the spatial properties of the applied stimulus. By applying out-of-phase sinusoidal current to transverse pairs of electrodes, electric fields may be generated which maintain an approximately fixed strength but rotate in space. Rotational fields may provide utility in the modulation of spiral wave dynamics in excitable tissues, which are associated with reentrant cycles in cardiac arrythmias as well as a number of processes within the brain. To explore this, spiral waves were generated in computational models of engineered excitable tissue and were subjected to rotating and sinusoidal electric fields of varying strength and frequency. Rotational fields which match the direction of spiral propagation provide significant efficiency gains in entraining spiral frequency when compared to sinusoidal stimulus, while retrograde rotational fields can reverse the direction of spiral propagation. Even in the absence of spiral wave dynamics, rotational field stimulation may provide utility in the modulation of neural oscillations. The response of a neuron external stimulation depends on its orientation relative to the electric field gradient, which gives rise to orientation-dependent responses to stimulus treatments. Rotational fields may therefore improve neurostimulus efficacy by influencing the excitability of neurons regardless of their orientation. To explore how rotating fields influence neural oscillations, two neural network model architectures were utilized: large-scale bursting networks, and networks of linked idealized oscillators with plastic inter-oscillator connections. Networks were subjected to rotational and sinusoidal fields, and their behaviors were measured as a function of stimulus strength, frequency, and orientation, as well as the degree of axonal alignment within the network. In spatially aligned networks, rotational fields entrain oscillations and promote network synchrony regardless of orientation, whereas the effects of sinusoidal fields exhibit strong orientation-dependence. In spatially disordered networks, however, rotational fields promote activity in different neurons at different stimulus phases, resulting in reduced network synchrony. These findings expand our knowledge on the significance of stimulus waveform in the modulation of electrically excitable tissues. The ability to understand and predict physiological responses to stimulation will open new doors in the design and optimization of stimulus techniques to achieve desired outcomes.