## Biological Basis of the Code The code provided is part of a computational model designed to simulate neural activity within thalamocortical networks during Non-Rapid Eye Movement (NREM) sleep. This model specifically focuses on the electroencephalogram (EEG) patterns observed during NREM sleep and their response to auditory stimuli. Here are the key biological aspects relevant to the code: ### Thalamocortical Networks in NREM Sleep 1. **Thalamocortical Neural Mass Model**: - The model aims to replicate the dynamics of neural populations, particularly the thalamic and cortical neurons. Thalamocortical circuits play a crucial role in modulating EEG signals during sleep. 2. **NREM Sleep**: - NREM sleep is characterized by slow-wave sleep and is divided into stages, such as N2 and N3, both of which are likely represented by the `"N2"` and `"N3"` mentioned in the code. These stages involve slow oscillatory patterns in the EEG, which the model seeks to simulate. 3. **Membrane Voltages**: - The variables `Vp` and `Vt` represent membrane voltages, likely associated with the cortical and thalamic relay neurons, respectively. Membrane potentials are crucial for understanding the depolarization and hyperpolarization phases of neurons, which underlie the generation of oscillatory patterns observed in EEG during sleep. 4. **Membrane Voltage Dynamics**: - The model investigates the particular behavior of neuron membrane potentials over time (expressed in mV), as rapid fluctuations in these voltages are fundamental to neural signaling and oscillation patterns in brain networks. 5. **EEG Patterns**: - By modeling the membrane voltages over time, the simulation captures key EEG characteristics of NREM sleep, such as slow waves and spindles, which originate from the complex interplay between cortical neurons and thalamic relay and reticular nuclei. ### Plot Parameters - **Time Series Analysis**: - The plots generated are time-series representations of these voltage changes, reflecting the dynamics of neural activity over a 30-second interval. - **Stage-Specific Characteristics**: - The code incorporates conditions that tailor the output based on the NREM stage (N2 or N3), highlighting the distinct oscillatory patterns typical of these sleep stages, which show differences in frequency and amplitude of voltage fluctuations. ### Conclusion Overall, this section of the code is crucial for visualizing the electrical activity in the thalamocortical circuits during NREM sleep stages. It reflects the biological interactions that produce distinct EEG patterns characteristic of different sleep stages and provides a platform for exploring how these patterns are altered by stimuli (though the response to auditory stimulation is not explicitly addressed in the given code). This modeling is foundational for understanding sleep physiology and the role of thalamocortical dynamics in maintaining sleep architecture.