Quian Quiroga, Rodrigo
Professor
Life & Medical Sciences
Short biography
Research interests
Given my initial background in Physics and Applied Mathematics, I have developed Signal Processing methods for the analysis of complex electrophysiology data. In particular, I developed a ‘spike sorting’ algorithm to identify the activity of single neurons that outperformed previous algorithms and that is currently used by several laboratories worldwide [Neural Comp 2004, >2000 citations]. I have also presented techniques to improve the quality of the data and the information that can be extracted from it [Nat Neurosci 2016] and have further developed our spike sorting algorithm [J. Neurophys 2018], rendering completely unsupervised and suitable for large-scale recordings and on-chip wireless transmission of the data [J. Neural Eng 2018; international patent PCT/GB2015/050217].
The use of this algorithm allowed me to discover a new type of neuron in the human brain, so called “Concept Cells” or “Jennifer Aniston neurons”, which fire selectively to specific concepts [Nature 2005, ~2000 citations]. For example, one of these neurons fired to different pictures of Jennifer Aniston and not to several dozen pictures of other persons or objects. In following studies, we showed that the firing of these neurons is beyond sensory processing, as it can be triggered by different sensory modalities [Curr Bio 2009; Curr Bio 2020] or by internal thoughts [Nature 2010], representing the subjective meaning attributed to the stimulus rather than the stimulus itself [PNAS 2008; Neuron 2014], among other works [see Cell 2019 for a review]. More recently, we have showed how these neurons form and store memories [Neuron 2015; Nat. Comm. 2016; Nat. Comm. 2018; Cell 2019; Curr Bio 2020], and based on these data, I have proposed that memory coding in the human hippocampus is completely different to what has been described in other species and can be the basis of cognitive abilities uniquely developed in humans [Cell 2017; Science 2019; Cell 2019; Curr Bio 2020; PNAS 2020; TiCS 2020].