| | Models | Description |
| 1. |
Biophysically Realistic Network Model of the Wild-Type and Degenerate Retina (Ly et al 2022)
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Please read the readme.txt file before running any code.
Objective: A major reason for poor visual outcomes provided by existing retinal prostheses is the limited knowledge of the impact of photoreceptor loss on retinal remodelling and its subsequent impact on neural responses to electrical stimulation. Computational network models of the neural retina assist in the understanding of normal retinal function but can be also useful for investigating diseased retinal responses to electrical stimulation.
Approach: We developed and validated a biophysically detailed discrete neuronal network model of the retina in the software package NEURON. The model includes rod and cone photoreceptors, ON and OFF bipolar cell pathways, amacrine and horizontal cells and finally, ON and OFF retinal ganglion cells with detailed network connectivity and neural intrinsic properties. By accurately controlling the network parameters, we simulated the impact of varying levels of degeneration on retinal electrical function.
Main results: Our model was able to reproduce characteristic monophasic and biphasic oscillatory patterns seen in ON and OFF neurons during retinal degeneration. Oscillatory activity occurred at 3 Hz with partial photoreceptor loss and at 6 Hz when all photoreceptor input to the retina was removed. Oscillations were found to gradually weaken, then disappear when synapses and gap junctions were destroyed in the inner retina. Without requiring any changes to intrinsic cellular properties of individual inner retinal neurons, our results suggest that changes in connectivity alone were sufficient to give rise to neural oscillations during photoreceptor degeneration, and significant network connectivity destruction in the inner retina terminated the oscillations.
Significance: Our results provide a platform for further understanding physiological retinal changes with progressive photoreceptor and inner retinal degeneration. Furthermore, our model can be used to guide future stimulation strategies for retinal prostheses to benefit patients at different stages of disease progression, particularly in the early and mid-stages of retinal degeneration. |
| 2. |
Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)
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"Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. ..." |
| 3. |
Ca2+-activated I_CAN and synaptic depression promotes network-dependent oscil. (Rubin et al. 2009)
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"... the preBotzinger complex...
we present and analyze a
mathematical model demonstrating an unconventional mechanism
of rhythm generation in which glutamatergic synapses and the
short-term depression of excitatory transmission play key rhythmogenic
roles.
Recurrent synaptic excitation triggers postsynaptic Ca2+-
activated nonspecific cation current (ICAN) to initiate a network-wide
burst.
Robust depolarization due to ICAN also causes voltage-dependent
spike inactivation, which diminishes recurrent excitation and
thus attenuates postsynaptic Ca2+ accumulation.
..." |
| 4. |
Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016)
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" ... We developed a multiscale model of primary motor cortex, ranging from molecular, up to cellular, and network levels, containing 1715 compartmental model neurons with multiple ion channels and intracellular molecular dynamics. We wired the model based on electrophysiological data obtained from mouse motor cortex circuit mapping experiments. We used the model to reproduce patterns of heightened activity seen in dystonia by applying independent random variations in parameters to identify pathological parameter sets. ..." |
