Horacio G. Rotstein

This study uses models to show cockroach groups use compensatory algorithms and face decision thresholds in multi-attribute, multi-option choices, challenging single-attribute decision paradigms.

This paper uses mathematical modeling to show how synaptic short-term plasticity and cellular time scales shape neuronal frequency filters in a basic feedforward network.

This paper investigates frequency-dependent coupling in electrically coupled networks, analyzing how intrinsic cellular properties and nonlinearities shape coupling coefficients in response to oscillatory inputs.

This paper investigates how neuronal networks process oscillatory inputs using mathematical models and simulations, revealing frequency-dependent communication mechanisms and new phenomena like K-resonance and ΔΦ-phasonance.

The paper analyzes degeneracy in adaptive circuit mechanisms, showing how it leads to adaptation and resonance in response to different input types.

The paper investigates electrical coupling resonance in neurons and finds that coupling coefficient resonance arises from postjunctional neuron resonance, while coupling conductance resonance may originate from other factors.

This study shows that anti-NMDAR encephalitis antibodies cause long-term hippocampal neuronal activity changes that persist after antibody clearance, leading to memory dysfunction.

The paper models how temporal filters in neurons are shaped by presynaptic spike trains and short-term plasticity, showing how different time scales interact to generate filter characteristics.

The paper investigates how rapid fluctuations interact with neuronal dynamics to produce oscillations and variability without requiring stochastic input.

This paper investigates how subthreshold resonant neurons respond to structured and fluctuating inputs, showing that resonance and variability depend on input type and neuronal properties.

The paper investigates structural unidentifiability in dynamic models, focusing on Lambda-Omega models that exhibit infinite parameter sets producing identical oscillations.

The paper analyzes covalent modification cycles under enzyme-in-excess conditions, showing signal termination and frequency preference responses to periodic inputs.

The paper shows that task states reduce neural correlations and variability across cortical areas in both primate and human data, increasing information coding capacity.

The paper demonstrates that resonance in neuronal systems can arise independently at different organizational levels without requiring resonance at other levels.

The paper compares current clamp and voltage clamp techniques for measuring neuronal resonance and shows nonlinearities cause discrepancies between the two methods.

The paper investigates how membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to generate network oscillations in a minimal model.

The paper shows ionic current correlations exist in mouse neurons, extending findings from invertebrates to vertebrates.

This paper investigates how different subthreshold dynamic properties of neurons with the same ionic currents affect spiking resonance and entrainment to oscillatory inputs.

The paper investigates resonance and phasonance in 3D neuronal systems using mathematical modeling and simulations, finding that amplifying currents can modulate, annihilate, or generate antiresonance and antiphasonance depending on their relative time scales to resonant currents.

The paper defines and explains the quadratization process of biophysical models by substituting them with caricature models having parabolic nonlinearities.