Dr. Santamariaâ€™s lab studies the structural properties of dendrites that allow them to implement computational functions to process information and store memories. The influence of dendritic structure on the electrical properties of neurons has been intensely studied over 50 years; however, the question of how dendritic structure affects biochemical computation remains a very open topic of research. For example, from Dr. Santamariaâ€™s work as well as the work of others in the field, it is now clear that not only the physical structure of dendrites, but also their cytostolic structure and organization affect computation. Dr. Santamariaâ€™s research therefore addresses dendritic structure over a wide range of spatial scales, from nanoscopic to the whole dendrite.
At present, work is specifically focused on understanding how dendritic structure controls the reliability and specificity of the biochemical signals that underlie synaptic activity and plasticity. This is an important problem because it is not yet understood how the relatively low numbers of molecules in a synapse can support reliable memory storage especially given the inherently noise nature of biochemical cascades. The labâ€™s recent work has specifically shown that the complexity of dendritic structure, in this case the diversity and density of dendritic spines modifies the environmental diffusion of dendrites breaking down the classical laws of diffusion, named anomalous diffusion. The lab has been able to map spine density to the dendriteâ€™s biochemical environment measured as the level of anomalous diffusion. The biological implications of this break-down are that the reaction rates that were assumed to be noisy at low concentrations may actually be much more efficient than previously expected, resulting in more reliable synapses processes.
Efforts are undertaken using combined and interacting computational, theoretical, and experimental approaches in order to develop a unified framework to understand how dendritic structure affects biochemical processing. The lab believes that this framework can be applied at multiple scales, from glutamate receptors moving in and out of the synapse, to large scale heterogeneous networks of spiking neurons.
Stockton D and Santamaria F (2016). Automating NEURON simulation deployment in cloud resources. In press, Neuroinformatics.
Yang Z and Santamaria F (2016) Purkinje cell intrinsic excitability increases after synaptic long term depression. J Neurophysiology. DOI: 10.1152/jn.00369.2016
Mohapatra N, TÃ¸nnesen J, Vlachos A, Kuner T, Dealers T, NÃ¤gerl UV, Santamaria F, and Jedlicka P (2016) Spines slow down dendritic chloride diffusion and affect short-term ionic plasticity of GABAergic inhibition. Accepted Scientific Reports.
Teka W, Stockton DB, and Santamaria F (2016) Power-law dynamics of membrane conductances increase spiking diversity in a Hodgkin-Huxley model. In press PLoS Computational Biology.
Stockton DB and Santamaria F (2015). NeuroManager: A workflow analysis based simulation management engine for computational neuroscience. Frontiers in Neuroinformatics Vol. 9(24) 10.3389/fninf.2015.00024
Santamaria F. (2015) Cerebellum: Overview. Encyclopedia of Computational Neuroscience. Jung and Jaeger Eds. Springer.
Marinov T and Santamaria F. (2015) Diffusion Equation. Encyclopedia of Computational Neuroscience. Jung and Jaeger Eds. Springer.
Michaelides E and Santamaria F. (2015). Multi-Scale Modeling of Purkinje Cells. Encyclopedia of Computational Neuroscience. Jung and Jaeger Eds. Springer.
Deans H and Santamaria F. (2015). Modeling ion concentrations. Encyclopedia of Computational Neuroscience. Jung and Jaeger Eds. Springer.
Romero VH, Kereselidze Z, Egido W, Michaelides EA, Santamaria F, and Peralta XG. (2014). Nanoparticle assisted photothermal deformation of individual neuronal organelles and cells. Biomedical Optics Express. Vol. 5(11), pp 4002-4012. DOI: http://dx.doi.org/10.1364/BOE.5.004002.
Salinas K, Kereselidze Z, Peralta XG, Santamaria F. (2014). Transient extracellular application of gold nano-stars increases hippocampal neuronal activity. J. of Nanobiotechnology 12(31) DOI: http://dx.doi.org/10.1186/s12951-014-0031-y.
Teka W, Marinov T, Santamaria, F. (2014). Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model. PLoS Comput Biol 10(3): e1003526. DOI: http://dx.doi.org/10.1371/journal.pcbi.1003526.
Marinov TM and Santamaria F. (2014) Computational modeling of diffusion in the cerebellum. Prog Mol Biol Transl Sci.123:169-89. DOI: http://dx.doi.org/10.1016/B978-0-12-397897-4.00007-3.
Marinov T, Ramirez N, Santamaria F. (2013) Fractional integration toolbox. Fractional Calculus and Applied Analysis. Vol 16(3). DOI: 10.2478/s13540-013-0042-7
Santamaria F, Antunes G, and De Schutter E. Breakdown of mass-action laws in biochemical computation. (2012) Computational Systems Neurobiology, La Novere Bhalla Eds.
Kereselidze Z, Romero VH, Peralta XG, Santamaria F. (2012) Gold Nanostar Synthesis with a Silver Seed Mediated Growth Method. Journal of Visualized Experiments. DOI: 10.3791/3570
Santamaria F, Wils S, De Schutter E, Augustine GJ. (2011). The diffusional properties of dendrites depend on the density of dendritic spines. Eur. J. Neurosci. DOI: 10.1111/j.1460-9568.2011.07785.x.
Commentary: Anomalous diffusion imposed by dendritic spines (Commentary on Santamaria et al.) DOI: 10.1111/j.1460-9568.2011.07809.x
Valdez CM, Smith MA, Perry G, Phelyx DF, Santamaria F (2011) Modeling cholesterol metabolism by gene expression profiling in the hippocampus. Mol. Biosyst., DOI:10.1039/C0MB00282H
Santamaria F, Gonzalez J, Augustine GJ, and Ragavachari S. (2010). Quantifying the effects of elastic collisions and non-covalent binding on glutamate receptor trafficking in the post-synaptic density. PLoS Comp. Bio. 6(5):e1000780. doi:10.1371/journal.pcbi.1000780
Coop AD, Cornelis H, and Santamaria F (2010). Dendritic excitability modulates dendritic information processing in a Purkinje cell model. Front. Comput. Neurosci. 4:6. doi:10.3389/fncom.2010.00006.
Valdez CM , Smith MA, Perry G, Phelyx CF, Santamaria F (2010). Cholesterol homeostasis markers are localized to mouse hippocampal pyramidal and granule layers. Hippocampus. doi: 10.1002/hipo.20743.
Augustine GJ, Santamaria F, Wils S, DeSchutter E (2009) Trapping of diffusing molecules by dendritc spines Journal of Neurochemistry. pp 69-69.
Santamaria F and Bower JM (2008). Theoretical and Computational Neuroscience: Hodgkin-Huxley models. The New Encyclopedia of Neuroscience. Elsevier.
Tanaka K, Khiroug L, Santamaria F, Doi T, Ogasawara H, Ellis-Davies GC, Kawato M, Augustine GJ (2007) Ca2+ requirements for cerebellar long-term synaptic depression: role for a postsynaptic leaky integrator. Neuron54: 787-800.
Santamaria F, Tripp PG, Bower JM (2007) Feedforward inhibition controls the spread of granule cell-induced Purkinje cell activity in the cerebellar cortex. J Neurophysiol97: 248-263.
Santamaria F, Wils S, De Schutter E, Augustine GJ (2006) Anomalous diffusion in Purkinje cell dendrites caused by spines.Neuron52: 635-648.
Santamaria F, Bower JM (2005) Background synaptic activity modulates the response of a modeled purkinje cell to paired afferent input. J Neurophysiol93: 237-250.
Augustine GJ, Santamaria F, Tanaka K (2003) Local calcium signaling in neurons. Neuron40: 331-346.
Santamaria F, Jaeger D, De Schutter E, Bower JM (2002) Modulatory effects of parallel fiber and molecular layer interneuron synaptic activity on purkinje cell responses to ascending segment input: a modeling study. J Comput Neurosci13: 217-235.
Mocanu OD, Oliver J, Santamaria F, Bower JM (2000) Branching point effects on the passive properties of the cerebellar granule cell axon. Neurocomputing. pp 207-212.
Santamaria F, Marsalek P (1998) Investigating spike backpropagation induced Ca2+ influx in models of hippocampal and cortical pyramidal neurons. Biosystems (48)1-3:147-156.