Rodrigo Quian Quiroga

• Head of Bioengineering Research Group
• Ethics Officer

Chair in Bioengineering
Bioengineering Research Group

PhD, (Luebeck, Germany)
T: +44 (0)116 252 2314
F: +44 (0)116 252 2619
E: rqqg1@le.ac.uk

Location: Room 902, Engineering Tower

Main Research Interests:
Professor Rodrigo Quian Quiroga graduated in Physics at the University of Buenos Aires, Argentina, in 1993. After 2 years working at the Department of Physiology of the Institute for
Neurological Investigations – FLENI, Argentina, and one further year at the Department of Epilepsy of the same institute, he moved to Germany and obtained his PhD in Signal  Analysis and Processing at the University of Luebeck in 1998. He was a post-doctoral fellow at the Research Center Juelich, Germany, from 1998 to 2001 and from 2001 to 2004 he was a Sloan fellow at the California Institute of Technology (Caltech), USA.

He was appointed as a Lecturer in Bioengineering at the Department of Engineering of the University of Leicester in 2004 and was promoted to reader in 2006 and to a chair in
Bioengineering and head of the Bioengineering Research Group in 2008. He holds visiting positions at Caltech, the Department of Neurosurgery of the University of California Los
Angeles (UCLA) and the Leibniz Institute of Neurobiology of the University of Magdeburg, Germany.

His research focus is on neuroscience and analysis of electrophysiological data. He studies neural correlates of visual perception and behaviour by analyzing single-cell recordings in
epileptic patients. He is also interested in visuo-motor coordination and the decoding of movement plans from singlecell recordings in monkeys. In collaboration with several clinical
research centres, he studies brain evoked responses and their correlation with learning processes. All these research lines involve the use and development of advanced methods of signal processing, such as wavelets, chaos theory and non-linear synchronization. Professor Quian Quiroga received an award for scientific-technological production from the University of Buenos Aires. He has been given young researcher travel awards for participation at international meetings in Japan and Argentina, and a young investigator award by the American Epilepsy Society. He received a Sloan-Swartz fellowship to work at the Centre for Theoretical Neuroscience in Caltech from 2001 to 2003.

Professor Quian Quiroga has been working on the analysis of electroencephalographic signals, the study of synchronization patterns and the development of advanced methods for the analysis of electrophysiological data. He developed a method based on the Wavelet transform that significantly improved the visualization of single-trial evoked potentials. This was something very difficult to be achieved with previous techniques due to the low amplitude of the single-trial responses in comparison with the ongoing electroencephalogram (EEG). The use of this method opened a wide range of new possibilities to study the correlation of trialby- trial changes of the evoked responses with different cognitive processes. Moreover, he proposed robust synchronization measures that are sensitive to nonlinear interaction and can establish causal relationships between signals. These two approaches had a significant impact for the study of EEG signals and are currently used by several groups.

Current Major Research Projects:
Since his time as a Sloan fellow at Caltech, Professor Quian Quiroga has been working on single-cell recordings; i.e. the study of the firing of neurons recorded from micro-electrodes
implanted in the brain. In particular, he developed an automatic method for processing the neural data recorded from these micro-electrodes that outperformed previous algorithms and particular, he developed an automatic method for processing the neural data recorded from these microelectrodes that outperformed previous algorithms and is currently used by several neurophysiology laboratories (see Figure 1, below).

Fig 1: Algorithm for spike detection and sorting. Spikes corresponding to different neurons are automatically detected and differentiated based on their shapes.

The use of this method allowed the striking finding – in contrast to what most neuroscientists expected – of a new type of ‘abstract’ neuron in the human brain (see Figure 2, below).

Fig 2: The Jennifer Aniston cell. Single neurons in the human brain with an abstract representation of persons of concepts.

This discovery was published in Nature it obtained the first prize at the international meeting on the Cognitive Substrates of Cognition held in 2005 in Madrid and it received worldwide media attention, including articles in the New York Times, Scientific American, Daily Mail, New Scientist, The Independent, etc. It has also been selected as one of the top 100 scientific stories of 2005 by Discover Magazine. This line of research has been the basis of several follow up experiments, including a recent study showing a strong
correlation between the firing of these abstract neurons with conscious perception and another article showing that from the activity of these neurons it is possible to predict what the subjects are seeing far above chance. The possibility to do these predictions is the basis for potential clinical applications, such as the development of brain-machine-interfaces and Neural Prostheses. A Neural Prosthesis device can be, for example, a robotic arm for paralyzed patients that is driven by neural data.

Recent Publications:
• Quian Quiroga R and Panzeri S. Extracting information from neural populations: Information theory and decoding approaches Nature Reviews Neuroscience (in press).
• Quian Quiroga R, Nadasdy Z and Ben-Shaul Y. Unsupervised spike sorting with wavelets and superparamagnetic clustering. Neural Computation, 16: 1661-1687; 2004.
• Quian Quiroga R, Reddy L, Kreiman, G, Koch, C and Fried, I. Invariant visual representation by single neurons in the human brain. Nature, 435: 1102-1107, 2005.
• Quian Quiroga R, Mukamel R, Isham E, Malach R and Fried I. Human single neuron responses at the threshold of conscious recognition. Proc. Natl. Acad. Sci. USA, 105:3599-
3604; 2008.