The code provided models the spatiotemporal dynamics of neuronal activity, specifically focusing on the oscillatory behavior and phase relationships of spikes in neural circuits. Here's a breakdown of the biological basis for this code: ### Biological Context 1. **Olfactory Bulb Network**: - The code models neurons within the olfactory bulb, a critical brain region for processing olfactory (smell) information. The main neuronal populations considered are: - **Mitral Cells (MCs)**: Principal output neurons of the olfactory bulb that relay processed sensory information to higher brain regions. - **Periglomerular Cells (PGs)** and **Granule Cells (GCs)**: Interneurons that modulate the activity of mitral cells through inhibitory interactions and synaptic plasticity. 2. **Oscillations and Phase Synchronization**: - Neuronal oscillations and phase locking are fundamental for efficient coding and transferring of sensory information. In the olfactory bulb, gamma oscillations (~40-120 Hz) are prominently involved in odor discrimination and sensory processing. 3. **Spike Phases**: - The phase of the spike refers to its timing relative to the oscillatory cycle. This code measures and analyzes spike phases to understand their synchronization across the network. - The calculation of the **phase-locking index (Ksyn)** is a measure of how tightly spiking activity of neurons is synchronized with the network oscillations. ### Key Biological Implementations - **Sampling and Frequency Analysis**: - The code uses techniques like Fast Fourier Transform (FFT) and band-pass filtering to isolate and analyze specific frequency bands relevant to neuronal oscillations (especially those in the gamma range). - **Phase Calculation**: - Peaks (and troughs) of the subthreshold local field potential (LFP) are detected to determine reference points for calculating spike phases. - A custom computation assigns a phase based on where each spike falls within the oscillatory cycle (0 to 360 degrees). - **Phase Distributions**: - Histograms and distributions are created to visualize how neuronal spikes are distributed across the oscillatory cycle, reflecting on the population-level synchronization. - **Raster Plots**: - The timing of spikes relative to the oscillation cycle is plotted, providing insight into the temporal structure of spike firing across different neurons in the population. ### Biological Insights - The framework highlights the role of specific neuronal populations in shaping the olfactory bulb's response to stimuli. - By focusing on the phase relationships of spikes, this model can explore how sensory information is encoded not just by the timing of spikes but by their precise alignment with ongoing network oscillations. - Such models allow us to infer how changes in synaptic strength or network connectivity might affect sensory processing capabilities, particularly in conditions that involve disrupted oscillatory activity. This code exemplifies the use of computational models to bridge the gap between abstract neuronal dynamics and tangible physiological functions, such as sensory information processing.