Frances K. Skinner

The paper develops MATLAB-based software to automatically identify and analyze theta rhythms in hippocampal EEG/LFP data, showing it can robustly detect feature changes during seizures and post-seizure periods.

The paper develops a mathematical model of hippocampal circuits to identify cell-type specific mechanisms underlying theta-gamma coupled rhythms.

This study identifies chirp patterns in ictal discharges as a potential biomarker for tracking seizure progression in a mouse epilepsy model.

The paper investigates the role of hyperpolarization-activated currents in shaping spiking frequency preference of human cortical layer 5 neurons using computational models and experimental validation.

This paper introduces an adaptive unscented Kalman filter for neuronal state and parameter estimation, showing improved accuracy and robustness compared to standard variants.

The paper develops a reduced OLM cell model to identify biophysical current balances enabling theta frequency spiking resonance in vivo.

The paper uses biophysical models to show that CCK+ basket cells have a greater role in theta-gamma coupling than PV+ basket cells in the hippocampus.

The paper uses computational modeling to show how I-S3 interneurons suppress OLM cell spiking and contribute to theta frequency resonance in simulated scenarios.

The paper compares minimal and detailed models of CA1 microcircuits to show how theta rhythms are generated and controlled by pyramidal and inhibitory cells.

The paper investigates how intrinsic neuronal properties and external inhibition influence theta rhythm frequencies in CA1 microcircuits using computational models.

The paper integrates computational models and experiments to show that hippocampal OLM cells have dendritic HCN2 channels, supporting theta spiking resonance.

The paper develops a biophysically detailed human layer 5 cortical neuron model showing slower h-current kinetics compared to rodents, leading to differences in resonance and post-inhibitory rebound.

The paper uses computational models to show that hyper-excitable inhibitory networks can transition from asynchronous to synchronous activity, potentially explaining seizure initiation.

The paper identifies synaptic mechanisms controlling VIP-expressing interneurons' firing and their recruitment during theta oscillations and ripples in the hippocampus.

The paper uses computational models to predict balanced synaptic states in hippocampal circuits during rhythmic activities.

The paper uses biophysical LFP models to show that OLM cells contribute to theta rhythms through specific connectivity patterns with BiCs and PYR cells.

The paper develops computational models of hippocampal networks to understand theta rhythm generation, finding that spike frequency adaptation and post-inhibitory rebound are key mechanisms.