Neural Model Current Dynamics Across Six Bursting Neurons

This dataset supports visualization methods for analyzing ionic current dynamics in conductance-based neural models. It contains data from six example bursting model neurons with similar activity but up to a 3-fold difference in conductance densities. The data illustrates changes in membrane potential waveforms and current contributions under perturbations.

Use Cases

• Visualize the percent contribution of ionic currents over time using stacked-area plots for six model neurons.
• Analyze the distribution of membrane potential waveforms across a range of perturbation control parameters.
• Compare the response to perturbations across models with similar bursting behavior but differing conductance densities for Na, K, Ca, and Leak channels.
• Examine the relationship between conductance density variations (up to 3-fold) and changes in current dynamics.

Strengths

• Data is derived from six distinct, computationally simulated bursting neuron models, providing comparative analysis.
• Models are designed with similar activity but differ specifically in conductance densities, isolating that variable for study.
• Includes analysis of multiple ionic current types: Na Channels, K Channels, Ca Channels, and Leak Channels.

Limitations

• The dataset is limited to six specific model examples, which is a small sample size for generalizing findings.
• Data is generated from computational models, not biological recordings, limiting direct applicability to real neural systems.
• The specific data format, size, and structure (e.g., row/column counts) are not provided, complicating immediate usability.

Provenance

Source

Dryad digital repository.

Collection Method

Data generated from computational simulations of conductance-based neural models.

Time Range

null

Freshness

null

Geography

null