The code provided is part of a computational model that simulates and visualizes the electrical activity in neuronal compartments, specifically focusing on the dendritic and somatic membrane potentials in response to injected current steps. This approach is typical in computational neuroscience to study how neurons integrate synaptic inputs and produce output signals.

Biological Basis

1. Neuron Structure and Compartments:

   • Soma and Dendrites: The simulation involves the neuron's soma and apical dendrites, which are critical for the integration of synaptic inputs. The dendrites are distal extensions from the soma and are sites where synaptic inputs predominantly occur. Each compartment (apical dendrite at different distances from the soma) represents a specific location within the neuron where electrical activity is measured or simulated.

2. Membrane Potential:

   • The model is simulating the membrane potential changes, which are critical for understanding neurons' excitable properties. Changes in membrane potential are essential for generating action potentials, also known as spikes, which are the fundamental building blocks of neuronal communication.

3. Current Injection:

   • Somatic and Dendritic Currents: The model incorporates somatic and dendritic current injections, a common experimental and modeling technique used to understand neuronal excitability and integration. This simulates real biological experiments where currents are injected into neurons to study their responses.
   • Different Current Amplitudes: By using different magnitudes of currents (0.3 nA, 0.5 nA, and 1.5 nA), the model explores how different stimulation intensities impact dendritic and somatic membrane potentials. These amplitudes likely simulate physiological or experimental conditions that a neuron encounters.

4. Distance from Soma ((\lambda)):

   • Electrotonic Length: The (\lambda) indicates an electrotonic length, a measure of how far the membrane potentials can spread along the dendrite. It provides insight into the dendritic filtering properties and how signals decay over distance due to the passive cable properties of the neuron.

5. Neuronal Computation and Integration:

   • The separation of somatic and dendritic compartments allows the study of how inputs at different dendritic locations affect the overall excitability of the neuron. This is used to deduce possible roles of dendritic computations in neuron function.

Conclusion

This code effectively models the passive and active electrical properties of neuronal dendrites and soma under varying conditions. Such models aim to deepen the understanding of how inputs are integrated in neurons, potentially influencing computational decision-making processes in the brain. By simulating the effects of different current injections, one can infer the essential role of dendritic and somatic compartments in the complex and nuanced signaling behaviors of neurons.