Diego Martin Mateos

This study uses Lempel-Ziv Complexity metrics to analyze EEG data from preterm infants, showing how sleep state complexity and maturation change with postmenstrual age.

The paper analyzes equal and cross-frequency connectivity in brain states to explore integration-segregation dynamics in sensory-motor processing.

This study uses ordinal-pattern quantifiers to analyze hippocampal dynamics after TBI and pharmacological treatment, revealing time-dependent dynamical changes and treatment effects.

This study examines how modafinil affects brain activity in rats during wakefulness and sleep, finding increased gamma-band power and altered sleep patterns.

This study examines how trazodone affects brain dynamics in dogs during sleep cycles using EEG analysis, finding changes in sleep structure, power distribution, and connectivity.

This paper applies hypergraph models to analyze multidimensional neuroscience data, revealing distinct connectivity patterns in sleep stages and epilepsy types.

This study examines changes in hippocampal granule cell excitability and synaptic transmission after TBI, finding biphasic alterations in synaptic input patterns over time.

This study examines how subanesthetic ketamine affects high-frequency cortical oscillations in cats, finding state-dependent changes and respiratory coupling.

The paper introduces a novel perspective on equal and cross-frequency neural coupling, showing that cross-frequency coupling partitions brain synchrony states and favors information segregation, while equal frequency coupling favors integration.

This paper uses Transfer Entropy to analyze information flow between brain hemispheres during eyes-open and eyes-closed resting states, finding increased information transfer in EC for alpha, beta1, and beta2 bands.

The paper uses non-linear metrics to differentiate firing dynamics between dorsal and median raphe neurons in rats, finding that OP Entropy is effective in distinguishing these neurons.

This study compares electroencephalographic signatures of urethane anesthesia and natural sleep-wake states in rats, finding distinct neurophysiological features in urethane that differentiate it from sleep.

This study shows that low-frequency brain oscillations drive changes in EEG complexity during sleep and wakefulness in rats.

This study measures brain activity complexity in anaesthetized monkeys to correlate with consciousness levels, finding changes in complexity with different anaesthetics.

The paper identifies the edge-of-chaos critical point as the state of cortical dynamics during conscious states and shows it is disrupted during unconsciousness.

The paper uses five information theory-based measures to quantify and classify sleep stages from EEG signals, showing that combined measures improve differentiation of sleep states.

The paper proposes a framework to understand brain organization and dynamics in conscious and unconscious states by emphasizing energy gradient creation and dissipation in neural networks.

This paper introduces a complexity-entropy map method to analyze EEG data from patients on psychotropic drugs, showing it can detect subtle changes in clinical response to treatment.

This paper compares functional connectivity in eyes closed and eyes open resting states using intracranial EEG, finding reduced alpha band connectivity in eyes open conditions.