David Angulo‐García

This paper studies slow relaxation oscillations in neural mass models with spike frequency adaptation, identifying chaotic behaviors and their relation to Up and Down states.

This paper proposes a mechanism for sustained balanced neural activity through short-term synaptic depression, showing it can maintain irregular activity without external inputs.

This study examines how spike-frequency adaptation affects macroscopic neural dynamics in excitatory and inhibitory networks, revealing new collective dynamical regimes and cross-frequency coupling patterns.

This study identifies spatially organized neuronal assemblies in the nucleus reuniens during slow oscillations and shows their role in stabilizing prefrontal cortex and hippocampal sequences.

The paper identifies early-born GABA neurons in the hippocampus as lifelong hubs with unique functional properties.

This study investigates cross-frequency coupling in inhibitory neural mass models, showing how different synaptic parameters can generate theta-gamma rhythms and their coupling mechanisms.

The paper shows that hippocampal network activity represents a combination of space and time with tunable degrees across days, using calcium imaging and network modeling in mice.

The paper develops a spiking network model to identify two types of driver cells in developing neuronal networks and explains their roles in synchronization dynamics.

The paper analyzes the firing time statistics of neurons under inhibitory noise, deriving exact results for firing rate, coefficient of variation, and spike train spectrum.

The paper investigates how inhibition in sparse neural networks can both suppress and promote neural activity, revealing a transition between different firing regimes.