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 investigate 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.

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. L. García Domínguez, J. L. Pérez Velázquez and R. F. Galán (2013)
   A Model of Functional Brain Connectivity and Background Noise as a Biomarker for Cognitive Phenotypes: Application to Autism. PLoS One. 8(4):e61493.
   
2. R. R. Dhingra, Y. Zhu, F. J. Jacono, D. M. Katz, R. F. Galán and T. E. Dick (2013)
   Decreased Hering–Breuer input-output entrainment in a mouse model of Rett syndrome. Frontiers in Neural Circuits. 7(42):1.
   
3. Y. Zhu, Y-H. Hsieh, R. R. Dhingra, T. E. Dick, F. J. Jacono and R. F. Galán (2013)
   Quantifying interactions between real oscillators with information theory and phase models: Application to cardiorespiratory coupling. Physical Review E. 87:022709.
   
4. N. T. Schmandt and R. F. Galán (2012)
   Stochastic-Shielding Approximation of Markov Chains and its Application to Efficiently Simulate Random Ion-Channel Gating. Physical Review Letters. 109:118101.
   
5. J. Pucilowska, P. A. Puzerey, J. C. Karlo, R. F. Galán and G. E. Landreth (2012)
   Disrupted ERK Signaling during Cortical Development Leads to Abnormal Progenitor Proliferation, Neuronal and Network Excitability and Behavior, Modeling Human Neuro-Cardio-Facial-Cutaneous and Related Syndromes. Journal of Neuroscience. 32(25):8863-8677.
   
6. G. K. Steinke and R. F. Galán (2011)
   Brain rhythms reveal a hierarchical network organization. PLoS Computational Biology. 7(10):e1002207.
   
7. K. C. Daly, R. F. Galán, O. J. Peters and E. M. Staudacher (2011)
   Detailed characterization of local field potential oscillations and their relationship to spike timing in the antennal lobe of the moth Manduca Sexta. Frontiers in Neuroengineering. 4:12.
   
8. S. Hata, K. Arai, R. F. Galán and H. Nakao (2011)
   Optimal phase response curves for stochastic synchronization of limit-cycle oscillators by common Poisson noise. Physical Review E. 84:016229.
   
9. R. F. Galán, T. E. Dick and D. M. Baekey (2010)
   Analysis and modeling of ensemble recordings from respiratory pre-motor neurons indicate changes in functional network architecture after acute hypoxia. Frontiers in Computational Neuroscience. 4:131.
   
10. R. F. Galán (2009)
    Analytical calculation of the frequency shift in phase oscillators driven by colored noise: Implications for electrical engineering and neuroscience. Physical Review E. 80:036113.
    
11. R. F. Galán (2008)
    On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity. PLoS One. 3(5):e2148.
    
12. 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.
    
13. G. B. Ermentrout, R. F. Galán and N. N. Urban (2008)
    Reliability, synchrony and noise. Trends in Neurosciences. 31(8):428-434.
    
14. 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 Letters. 76:056110.
    
15. J. L. Pérez Velázquez, R. F. Galán, L. García Domínguez, Y. Leshchenko, S. Lo, J. Belkas and R. Guevara Erra (2007)
    Phase response curves in the characterization of epileptiform activity. Physical Review E. 76:061912.
    
16. G. B. Ermentrout, R. F. Galán and N. N. Urban (2007)
    Relating Neural Dynamics to Neural Coding. Physical Review Letters. 99:248103.
    
17. 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.
    
18. 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.
    
19. 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.
    
20. 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.
    
21. 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.
    
22. 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.
    
23. 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.
    
24. 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.
    
25. 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.