The provided code modeling attempts to simulate and visualize the activity of Fast-Spiking Interneurons (FSIs) within the striatal microcircuits of the brain, particularly focusing on how dopamine (DA) influences their rhythmic oscillatory activity. This is a part of computational neuroscience, which integrates biological and mathematical concepts to understand brain functions through simulations.

Biological Basis of the Model

1. Fast-Spiking Interneurons (FSIs):

   • FSIs are a class of inhibitory neurons characterized by their ability to fire action potentials at high frequencies. They are essential for modulating the activity of other neurons within the striatum, a critical region for motor control and other cognitive functions. FSIs predominantly release GABA, an inhibitory neurotransmitter.

2. Striatal Microcircuits:

   • The striatum is involved in motor control as well as cognitive processes. Within this region, FSIs play a key role in shaping the activity patterns of medium spiny neurons, the primary output neurons of the striatum. Proper functioning of these circuits is necessary for the execution of smooth, coordinated movements.

3. Dopamine Impact:

   • Dopamine is a vital neuromodulator in the brain, influencing a variety of functions including motor control, motivation, and reward processes. The code explores two levels of dopamine ('lo' and 'hi'), considering its regulatory effect on striatal activity. Dopamine's modulation of striatal microcircuits is known to impact the balance between different oscillating rhythms.

4. Synaptic Currents and Local Field Potentials (LFPs):

   • The code simulates the summed synaptic currents as a surrogate for LFPs, an important measure of neuronal activity that captures synchronized, collective behaviors of neuron populations. LFPs give insight into the oscillatory dynamics of the circuit.

5. Oscillatory Rhythms:

   • The model investigates how delta/theta, gamma, and beta oscillations are interleaved in FSIs and mediate the periodic activity in motor control. Different oscillatory bands contribute to various brain functions, with gamma oscillations often linked to local networking processes and beta oscillations related to motor control.

6. Spectral Analysis:

   • The power spectral density and spectrogram analyses correspond to evaluating the frequency components of the simulated LFPs. This involves understanding how dopamine levels influence these rhythms, contributing to insights into neurophysiological states associated with different dopaminergic conditions.

7. Spiking Activity and Raster Plots:

   • Raster plots illustrate the spiking activity across the network of FSIs, showing temporal dynamics and neuron firing patterns. These plots help visualize how dopamine levels can modulate the synchrony and pattern of neuron firing.

Overall Objective

The main objective of the provided code is to visualize and analyze the dynamic changes in FSI network activity under different levels of dopamine. By examining LFPs, spectrograms, and spiking patterns, researchers aim to understand striatum's role in rhythmically mediated motor control and how dopamine levels modulate these processes, offering insights into movement-related disorders.