Rodrigo Quian Quiroga
Reader in Bioengineering
Tel / Fax: +44 (116) 252-2314/2619
e-mail: rodri at vis dot caltech dot edu
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Spike detection and sorting of extracellular action potentials.
Includes exemplary data and a tutorial on spike sorting.
includes tutorial on wavelets and denoising
Nonlinear synchronization measures
I am a Reader in Bioengineering
at the University of Leicester,
Before joining Leicester University, I was a Sloan post-doctoral fellow at the Sloan Swartz Center of Theoretical Neuroscience at Caltech. There I worked both at Richard Andersen's and Christof Koch's labs, with whom I keep an active collaboration. With Christof we study neural correlates of visual perception. For this we analyze single cell recordings in awake humans in collaboration with Itzhak Fried at UCLA. These recordings are from epileptic patients, which are studied with intracranial electrodes in order to localize the epileptic focus and evaluate the feasibility of epilepsy surgery. We found a remarkable type of cells responding selectively to different pictures of the same individual or object. For analyzing these data, it is crucial the use of an optimal spike sorting method in order to identify the firing of the different cells. I developed – wave_clus- an unsupervised algorithm for spike detection and sorting that seems to do a good job. These codes, some exemplary data and a tutorial on spike sorting are available here. One of Richard’s main interests is the function of the posterior parietal cortex (PPC) and its correlation with movement planning. We have been working on single-trial decoding of movement plans and showed that it is possible to reliably predict saccades and reach plans from two segregated areas in PCC. These results have implications for the development of neuronal prostheses, which is an active field of research at Richard’s lab.
Before joining Caltech, I was a post-doc at Peter
Grassberger's group in Juelich,
I have also been studying EEGs and evoked potentials (i.e. alterations of the EEG due to stimulation) with time-frequency methods. The time-frequency analysis ranges from elementary tools such as the Fourier Transform to more complex ones such as the Gabor Transform, Wavelets and further quantitative measures derived from them. With these methods it is possible to correlate spontaneous and evoked oscillations with different brain processes. I have also been working on the analysis of single-stimulus evoked potentials (without need of ensemble averaging of several trials), something very difficult to be done with previous approaches due to the low amplitude of the evoked responses in comparison with the ongoing EEG. This allows the study of functional processes, such as habituation, sensitization, learning, etc. and contributes new information that can have high clinical relevance (see the tutorial on wavelet decomposition and denoising).
Invariant visual representation by single-neurons
in the human brain.
Unsupervised spike sorting with wavelets and superparamagnetic clustering.
Single-trial event-related potentials with
Performance of different synchronization measures in
real data: a case study on electroencephalographic signals.