The provided code models a network of spiking neurons to study feature selectivity in cortical networks with specific synaptic connectivity. The biological basis revolves around the following key aspects: ### Neuronal Networks and Connectivity - **Neurons and Synapses:** The model simulates networks composed of spiking neurons, mimicking the basic functional units of the brain. The neurons are connected via excitatory and inhibitory synapses, capturing the fundamental excitatory and inhibitory interactions present in neural circuits. - **Specific Connectivity:** The code explores different degrees of feature-specific connectivity, particularly how certain synaptic connections (excitatory-to-excitatory, excitatory-to-inhibitory, etc.) are tailored or modified to exhibit feature selectivity. This reflects the brain's ability to enhance its processing of specific features in sensory stimuli, akin to mechanisms observed in cortical areas such as the primary visual cortex. ### Stimulus Orientation Processing - **Stimulus Orientation:** The model evaluates neuronal responses to varying stimulus orientations. This is representative of how neurons in the visual cortex respond preferentially to specific orientations of visual stimuli—a foundational aspect of visual processing. - **Feature-Specific Modulation (fs_mod):** The model includes parameters for modulating the feature specificity of synaptic connections, exploring how cortical circuits might adjust connectivity to optimize processing for specific orientations or features. ### Biological Relevance - **Cortical Network Dynamics:** The code simulates cortical network dynamics, providing insights into how neurons might be organized and connected to process sensory information efficiently and selectively. - **Orientation Selectivity:** The focus on stimulus orientation reflects a core feature of visual processing in the brain, highlighting the importance of neural mechanisms that enable orientation selectivity—a property well-documented in visual neuroscience. ### Summary Overall, the code seeks to replicate and investigate the principles of feature selectivity in neural circuits, with a particular emphasis on how specific synaptic connectivity can influence this process. By exploring different synaptic configurations and modulating feature-specific connectivity, the model provides a platform for understanding the biological basis of feature processing in cortical networks, as observed in visual perception and other sensory modalities.