The number of people in risk of developing a neurodegenerative disease increases as the life expectancy grows due to
medical advances. Multiple techniques have been developed to improve patient’s condition, from pharmacological to
invasive electrodes approaches, but no definite cure has yet been discovered.
In this work Optical Neural Stimulation (ONS) has been studied. ONS stimulates noninvasively the outer regions of the
brain, mainly the neocortex. The relationship between the stimulation parameters and the therapeutic response is not
totally clear. In order to find optimal ONS parameters to treat a particular neurodegenerative disease, mathematical
modeling is necessary. Neural networks models have been employed to study the neural spiking activity change induced
by ONS. Healthy and pathological neocortical networks have been considered to study the required stimulation to restore
the normal activity. The network consisted of a group of interconnected neurons, which were assigned 2D spatial
coordinates. The optical stimulation spatial profile was assumed to be Gaussian. The stimulation effects were modeled as
synaptic current increases in the affected neurons, proportional to the stimulation fluence. Pathological networks were
defined as the healthy ones with some neurons being inactivated, which presented no synaptic conductance. Neurons’
electrical activity was also studied in the frequency domain, focusing specially on the changes of the spectral bands
corresponding to brain waves. The complete model could be used to determine the optimal ONS parameters in order to
achieve the specific neural spiking patterns or the required local neural activity increase to treat particular
M. Zverev, F. Fanjul-Vélez, I. Salas-García, N. Ortega-Quijano, and J. L. Arce-Diego, "Analysis of optical neural stimulation effects on neural networks affected by neurodegenerative diseases," Proc. SPIE 9690, Clinical and Translational Neurophotonics; Neural Imaging and Sensing; and Optogenetics and Optical Manipulation, 96901Q (Presented at SPIE BiOS: February 16, 2016; Published: 9 March 2016); https://doi.org/10.1117/12.2208683.
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