Biology subjects

Tahvili, F.

Publications and source records attributed to Tahvili, F..

3 recordsLinked to original sources

bioRxiv2025

A mean-field model of neural networks with PV and SOM interneurons reveals connectivity-based mechanisms of gamma oscillations

Classic theoretical models of cortical oscillations are based on the interactions between two populations of excitatory and inhibitory neurons. Nevertheless, experimental studies and network simulations suggest that interneuron subclasses such as parvalbumin (PV) and somatostatin (SOM) exert distinct control over oscillatory dynamics. Yet, we lack a theoretical understanding of the mechanisms underlying oscillations in E-PV-SOM circuits and of the differences with respect to the classical mechanisms for oscillations in simpler E-I networks. Here, we derive a biologically realistic mean-field model of a canonical three-population E-PV-SOM circuit. This model robustly generates oscillations whose features are consistent with experimental observations, including the relative timing of PV and SOM activity and the effects of optogenetic perturbations. By reducing the model to a linear analytical form, we demonstrate that gamma oscillations emerge directly from the cell-specific connectivity of the three-population circuit. This connectivity motif alone accounts for experimentally observed phase relationships, with PV activity consistently leading that of SOM neurons. Together, this mean field model identifies a distinct structural mechanism giving rise to oscillations in canonical E-PV-SOM circuits and provides theoretical primitives for constructing large-scale, cell-type-specific models of cortical dynamics.

neuroscience↗

bioRxiv2025

A cortical microcircuit model reveals distinct inhibitory mechanisms of network oscillations and stability

We identify a computational mechanism for network oscillations distinct from classic excitatory-inhibitory networks - CAMINOS (Canonical Microcircuit Network Oscillations) - in which different inhibitory-interneuron classes make distinct causal contributions to network oscillations and stability. A computational network model of the canonical microcircuit consisting of SOM, PV and excitatory neurons reproduced key experimental findings, including: Stochastic gamma oscillations with drive-dependent frequency; precise phase-locking of PV interneurons and delayed firing of SOM interneurons; and the distinct effects of optogenetic perturbations of SOM and PV cells. In CAMINOS, the generation of network oscillations depends on both the precise spike timing of SOM and PV interneurons, with PV cells regulating oscillation frequency and network stability, and delayed SOM firing controlling the oscillation amplitude. The asymmetric PV-SOM connectivity is found to be the key source ingredient to generate these oscillations, that naturally establishes distinct PV and SOM-cell spike timing. The CAMINOS model predicts that increased SOM/PV densities along the cortical hierarchy leads to decreased oscillation frequencies (from gamma to alpha/beta) and increased seizure susceptibility, suggesting a unified circuit model for oscillations across different frequency bands.

neuroscience↗

bioRxiv2023

A mean-field model of gamma-frequency oscillations in networks of excitatory and inhibitory neurons

Gamma oscillations are widely seen in the cerebral cortex in different states of the wake-sleep cycle and are thought to play a role in sensory processing and cognition. Here, we study the emergence of gamma oscillations at two levels, in networks of spiking neurons, and a mean-field model. At the network level, we consider two different mechanisms to generate gamma oscillations and show that they are best seen if one takes into account the synaptic delay between neurons. At the mean-field level, we show that, by introducing delays, the mean-field can also produce gamma oscillations. The mean-field matches the mean activity of excitatory and inhibitory populations of the spiking network, as well as their oscillation frequencies, for both mechanisms. This mean-field model of gamma oscillations should be a useful tool to investigate large-scale interactions through gamma oscillations in the brain.

neuroscience↗