Our research focuses on the biophysical mechanisms underlying neuronal synchronization and the formation of spatiotemporal patterns of neural activity. To this end, we apply a multidisciplinary approach that combines electrophysiology and imaging techniques with mathematical and computational models.

In particular, we primarily investigate how the kinetics of GABA-A receptors regulates the emergence and extension of synchronized spontaneous activity in acute cortical slices of the mouse brain and compare the results with the predictions of theoretical models. In these studies we translate to the cortex the techniques that we have previously used in the study of the neural dynamics in the olfactory bulb. Our goal is to understand the functional consequences of the alterations of GABAergic transmission in the cortex which have been related to the etiology of schizophrenia recently.

From a broader perspective, we are interested in the functional role of brain rhythms. Synchrony and other forms of coherent behavior in neural networks are thought to facilitate the processing of sensory and motor information in the brain. Interestingly, an alteration of neural synchronization and of EEG rhythms in different brain areas correlates with pathologies like epilepsy, Parkinson’s disease (synchrony excess), autism, short-term memory loss and schizophrenia (synchrony deficit). Also, in the absence of stimulation, neural circuits frequently display spatiotemporal patterns of spontaneous activity that, if properly analyzed, inform us about the underlying connectivity and modularity of the circuits. Our lab is developing experimental and computational tools to perform these analyses in brain preparations efficiently.

1. R. F. Galán (2008)
   On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity. PLoS One. 3(5):e2148.
   
2. R. F. Galán, G. B. Ermentrout and N. N. Urban (2008)
   Optimal time scale for spike-time reliability: Theory, simulations and experiments. Journal of Neurophysiology. 99:277-283.
   
3. G. B. Ermentrout, R. F. Galán and N. N. Urban (2008)
   Reliability, synchrony and noise. Trends in Neurosciences. 31(8):428-434.
   
4. R. F. Galán, G. B. Ermentrout and N. N. Urban (2007)
   Stochastic dynamics of uncoupled neural oscillators: Fokker-Planck studies with the finite element method. Physical Review E. 76:056110.
   
5. J. L. Pérez Velázquez, R. F. Galán, L. García Domínguez, Y. Leshchenko, S. Lo, J. Belkas, R. Guevara Erra (2007)
   Phase response curves in the characterization of epileptiform activity. Physical Review E. 76:061912.
   
6. G. B. Ermentrout, R. F. Galán, and N. N. Urban (2007)
   Relating Neural Dynamics to Neural Coding. Physical Review Letters. 99:248103.
   
7. R. F. Galán, G. B. Ermentrout and N. N. Urban (2007)
   Reliability and stochastic synchronization in type I vs. type II neural oscillators. Neurocomputing. 70:2102-2106.
   
8. R. F. Galán, N. Fourcaud, G. B. Ermentrout and N. N. Urban (2006)
   Correlation-induced synchronization of oscillations in olfactory bulb neurons. Journal of Neuroscience. 26(14):3646-3655.
   
9. R. F. Galán, G. B. Ermentrout and N. N. Urban (2006)
   Predicting synchronized neural assemblies from experimentally estimated phase-resetting curves. Neurocomputing. 69(10-12):1112-1115.
   
10. R. F. Galán, G. B. Ermentrout and N. N. Urban (2006)
    Reliability, discriminability and noise-induced synchronization of olfactory neurons. Sensors and Actuators B: Chemical. 116(1-2):168-173.
    
11. R. F. Galán, M. Weidert, R. Menzel, A. V.M. Herz and C. G. Galizia (2006)
    Sensory memory for odors is encoded in spontaneous correlated activity between olfactory glomeruli. Neural Computation. 18(1):10-25.
    
12. R. F. Galán, G. B. Ermentrout and N. N. Urban (2005)
    Efficient estimation of phase-resetting curves in real neurons and its significance for neural-network modeling. Physical Review Letters. 94:158101.
    
13. R. F. Galán, S. Sachse, C. G. Galizia and A.V.M. Herz (2004)
    Odor-Driven Attractor Dynamics in the Antennal Lobe Allow for Simple and Rapid Olfactory Pattern Classification. Neural Computation. 16(5):999-1012.
    
14. R. F. Galán, R. Ritz, P. Szyszka and A.V.M. Herz (2004)
    Uncovering short-time correlations between multichannel recordings of brain activity: A Phase-Space Approach. International Journal of Bifurcations and Chaos. 14(2):585-597.
    
15. R. Ritz, R. F. Galán, P. Szyszka and A.V.M. Herz (2001)
    Analysis of odor processing in the mushroom bodies of the honeybee. Neurocomputing. 38-40:313-318.