Gorka Zamora‐López

This study links receptor profiles and cortical excitability to acute and long-term stroke outcomes using patient-specific whole-brain models.

This study compares brain responses to psilocybin and escitalopram in depression using the Fluctuation-Dissipation Theorem, finding distinct non-equilibrium dynamics and responder differentiation.

This paper shows that Hebbian and anti-Hebbian inhibitory STDP rules enable stable memory encoding and modularity in spiking neural networks without control mechanisms.

This study introduces a framework using game theory to characterize optimal communication in brain networks, finding that broadcasting models best describe communication efficiency, with rich-club regions playing a key role.

This paper reveals the structural connectivity architecture of the human brain, showing that subcortical regions are central hubs critical for global signal propagation.

The paper shows inhibitory neurons are essential for forming and maintaining modular neural structures after learning through synaptic adaptation.

The paper identifies integrated and segregated brain states during rest and tasks using graph theory and deep learning, finding integration correlates with information compression and segregation with specialization.

This study identifies impaired neural propagation and responsiveness in disorders of consciousness using resting-state fMRI and links these deficits to glucose metabolism and specific circuit failures.

This study examines how brain dynamics change during low-level states of consciousness, finding reduced stability in brain hubs and decreased heterogeneity in synchronization patterns.

This paper introduces MOU-EC, a whole-brain effective connectivity model for fMRI data to study brain cognition in health and disease, showing its application in extracting task-specific biomarkers and interpreting connectivity changes.

This paper introduces a dynamic network framework for analyzing whole-brain fMRI data, showing functional communities merge over time and networks shift from segregated to integrated activity.