intra craneal EEG
Intractable epilepsy
Alzheimer's disease
Personalized health care
Preventive and Predicitve Medicine
Coordination Dynamics
Network Theory
Category Theory
Diffusion Model

 Gomez-Ramírez research is focused on multi-scale mathematical modelling of brain networks. An original aspect of his work is the use of the mathematical thery of categories. Working as a mathematical neuroscientist, he is interested in foster our understanding of brain complex networks dynamics and the development of network metrics that could be used as biomarkers for early diagnosis in neurodegenerative disoprders such as Alzheimer's Disease. He has a broad training as a experimental and clinical neuroscientist in neuroimaging (fMRI) and electrophysiology (iEEG).
Gomez-Ramírez is also interested in Neuroaesthetics and the Arts. Neuroaesthetics can be seen as a way of bridging the interdisciplinary gap between art and science; a recent scientific discipline that can help to finally dissolve the "two cultures."

A short description of the main projects in which I am working right now.

The somewhat limited success in the pharmacological treatment of some
neuropsychiatric syndromes, specially epilepsy and addiction, has aroused an increasing
interest in the possibility of using brief direct electrical intracerebral stimulation to alter the deviant behavior associated with those syndromes. The idea substantiating the possible success of electrical perturbations is based on the assumption that if the dynamics of the abnormal brain coordination dynamics associated with the syndromes is perturbed by stimulations then the aberrant behaviours may not appear, or will be interrupted if already initiated. Evidence gathered in both animal models and in patients, indicate that it is feasible to alter the transitions towards abnormal brain synchrony patterns, by means of minimal (short duration, low frequencies and intensities) closed-loop, or feedback, stimulation.
 The project  proposes to perform similar dynamical analysis of brain activity associated with reward-seeking and addictive behaviours, using a closed-loop algorithm able to first, identify abnormal brain coordinated patterns of activity that correlate with the compulsions and other actions associated with addiction, and second, perturb these aberrant synchrony patterns in a way that is effective in ameliorating the addictive syndrome.  

In this project we study resting-state functional connectivity networks dynamics to understand how network connectivity changes during both ictal and interictal. Mesial temporal lobe epilepsy (MTLE) is the most common form of human epilepsy. MTLE is a focal for of epilepsy with hippocampal sclerosis as a common underlying pathology. In MTLE  the epileptogenic area is confined to mesial temporal lobe but subcortical and cortical areas are also affected. We will explore the hypothesis that the dynamic,time-dependant, nature of functional connectivity is an adaptive compensatory mechanism in chronic epilepsy. A result that justifies the assumption is interhemispheric hippocampal connectivity incrases linearly with disease duration when epilepsy progresses beyond ten years. The view of epilepsy as a network disorder challenges the classification of epilepsy and other neurological disorders being either local or global.