## Biological Basis of the Code The provided code is designed to generate figures that visualize data produced by simulations of cortical plasticity influenced by neuromodulators. Below are the key biological concepts and mechanisms the code is modeling: ### Synaptic Plasticity - **Spike-Timing-Dependent Plasticity (STDP):** - This is a form of synaptic plasticity whereby the timing difference between pre- and post-synaptic spikes determines the direction and magnitude of synaptic strength changes. The code references different STDP rules ('Rule DP', 'Rule PP', etc.), which are likely different models of synaptic plasticity rules sensitive to the timing of neuronal activity. - **Synaptic Weights:** - The synaptic weights represent the strength of connections between neurons. Changes in these weights, visualized in the figures, reflect the learning and adaptation processes driven by neural activity and potentially influenced by neuromodulation. ### Neuromodulation - **Role of Neuromodulators:** - Neuromodulators are chemical messengers, such as dopamine, serotonin, and acetylcholine, which modulate synaptic transmission and influence plasticity. Although the code does not reveal specific neuromodulators, the reference to neuromodulation suggests that different conditions or rules reflect the impact of these chemicals on synaptic remodeling. ### Cortical Plasticity - **Receptive Field Plasticity:** - The code outputs figures showing the evolution of synaptic weights and presumably receptive field changes over time. Receptive fields in the cortex are dynamic, influenced by both intrinsic neuronal activity and external inputs, reflecting how cortical neurons adapt based on new learning or sensory experiences. ### Input Specificity - **Input Specificity of Synapses:** - The code measures input specificity as the difference between synaptic weights from two distinct inputs. This focuses on how certain synapses, potentially those most frequently activated or associated with specific inputs, strengthen over time compared to others. ### Temporal Dynamics - **Time Evolution:** - The code evaluates synaptic weights and specificity at discrete time intervals (e.g., time(T) = n*5 seconds), capturing the temporal evolution of synaptic changes. This reflects biological time-dependent processes, where changes in neuronal connectivity and plasticity occur over several seconds to minutes in experimental contexts. In summary, the code provided models cortical synaptic plasticity as influenced by multiple STDP rules and illustrates the effects of neuromodulation, underscoring the dynamic nature of neuronal networks in the cortex and their capacity for adaptation and learning through plasticity mechanisms.