The provided code is part of a computational model in neuroscience focusing on the real-time simulation of neural activity, particularly in the context of transcranial alternating current stimulation (tACS) targeted at the thalamic Vim (ventral intermediate nucleus) region. This type of simulation can be used to explore the interaction between neuronal oscillations and external electrical stimulation, a relevant topic in understanding and potentially treating tremor disorders such as Parkinson's Disease and Essential Tremor. ### Biological Basis 1. **Neuronal Network and Synaptic Connections:** - The code initializes a network of neurons and establishes synaptic connections (via `createConnections`), which is crucial for simulating realistic neural network behavior. Synapses are the biological structures that allow neurons to communicate with each other through electrical or chemical signals. 2. **Stimulation and Oscillations:** - The model uses a sinusoidal current to simulate transcranial alternating current stimulation (tACS), a non-invasive brain stimulation technique. The parameters define the amplitude and phase of the stimulus, which correspond to the intensity and timing of electrical signals applied to the brain. 3. **Membrane Potentials and Neural Activity:** - The code reads the instantaneous membrane potentials of neurons in the Vim region, which reflects their electrical activity. Membrane potentials are crucial as they determine whether a neuron will fire an action potential, the fundamental unit of communication in the nervous system. 4. **Phase Adaptation and Spike Timing:** - Real-time phase adaptation is implemented to track and influence the neural oscillations. This involves analyzing spike timing and phase estimation through methods such as the empirical cumulative Hilbert Transform (ecHT). Precise phase alignment of tACS with endogenous neural oscillations can potentially synchronize or desynchronize neural activity, which is a target mechanism in treating neurological disorders. 5. **Random Number Generation for Noise:** - Random number seeds are used to introduce synaptic and membrane noise, mimicking the stochastic nature of neuronal firing and synaptic transmission. This reflects the variability and inherent noise present in biological neuronal systems. Overall, the code models the dynamic behavior of neuronal populations under oscillatory stimulation, providing insights into how external electric fields interact with neural circuits, particularly in regions implicated in movement disorders. The approach highlights the role of electrical phase relationships in modulating neuronal activity, which is a key aspect of neuromodulation therapies.