학술논문

Effects of Phase-dependent Stimulation on Hippocampal Oscillations: A Computational Modeling Approach
Document Type
Conference
Source
2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Neural Engineering (NER), 2023 11th International IEEE/EMBS Conference on. :1-4 Apr, 2023
Subject
Bioengineering
Signal Processing and Analysis
Neurological diseases
Time-frequency analysis
Computational modeling
Neural activity
Rodents
Neural engineering
Brain modeling
Neuron model
phase-amplitude coupling
phase-dependent stimulation
closed-loop neuromodulation
Language
ISSN
1948-3554
Abstract
The important role of phase-amplitude coupling (PAC) between brain oscillations of different rhythms may imply possibly promising effects for phase-dependent neuromodulation techniques to treat neurological disorders. In particular, the theta-gamma PAC correlates with significant and complex cognitive functions. Computational models serve as convenient tools to overcome in vivo and in vitro limitations. Using a hippocampal computational model in the NEURON and Python environments, we delivered carefully timed current injections to the cells in the network at the harmonics of the network's peak theta band frequency. Each applied stimulus was categorized by its corresponding phase angle, and the stimulation effects on the network activity were analyzed. By analyzing the local field potential and bandpass power amplitudes, we demonstrated enhancement and depression of the theta band depending on the phase of the stimulus. Applying stimulation before the peak phase consistently amplified the the theta band while stimulating immediately after the peak phase consistently suppressed network activity. Further study is required to understand the continuous effects of phase-locked stimulation with a closed-loop stimulator and their implications for human and animal models of rhythmic neural activity. These results demonstrate the capacity of phase-dependent stimulation to modulate neuronal oscillations, which could allow for applications in the treatment of neurological disorders associated with abnormal oscillations, such as Alzheimer's disease. Clinical Relevance- Analyzing the origins of neuronal oscillations and developing a brain stimulation technique for modulating the level of oscillations can facilitate the development of novel treatment methods such as phase-dependent neuromodulation systems for neurological disorders associated with abnormal oscillations.