Alexander LerchnerPostdoctoral Research FellowUCL, Gatsby Computational Neuroscience Unit |
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I am working on a systems-level theory of brain function that proposes how the interaction between frontal cortex, posterior cortex, the basal ganglia, and the hippocampal formation gives rise to our cognitive abilities.
My current research within this endeavour is focused on two aspects at different levels of description: systems neuroscience and dynamics of large neural networks.
I
am using experimental methods to address theoretical
concepts in systems neuroscience, in particular the role of prefrontal
cortex
in categorization and rule switching. I am pointing out that many
behavioural tasks that probe higher-level perception
(such as
perceptual categorization or rule switching) are confounded by a
requirement for action selection, and I am suggesting how this
problem can be
overcome in principle. To illustrate my point and to re-assess
prefrontal cortex function, I
have designed an experimental paradigm for testing rule-based
categorization
and switching of category rules without such a confounding element. In
collaboration
with Takafumi Minamimoto and Barry Richmond in the Laboratory for
Neuropsychology
at the NIH, we developed a specific paradigm and tested it in a study
on prefrontal cortex. We have obtained exciting results that
would
have
been difficult to explain in light of previous findings, yet are in
agreement
with my predictions at the outset of the project. We are currently
preparing a
manuscript on the study.
What
can we learn from data obtained by electrophysiology
in living animals? Every neuron in the neocortex is connected
with tens of thousands of other neurons, making even the smallest
conceivable sub-circuits much larger than the number of neurons that we
can observe simultaneously. To get beyond
crude
behavioural correlates of neural activity towards an understanding of
how networks of neurons give rise to function, we need good
theories that predict the dynamics of large neural networks. I am using
mathematical
methods from physics and statistics, combined with numerical
algorithms, to develop and investigate theories of large neural
networks.
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Aug. 2007 - present | Postdoctoral Research
Fellow University College London (UCL) Gatsby Computational Neuroscience Unit London, UK |
Aug. 2004 – July 2007 | Postdoctoral Research
Fellow National Institutes of Health (NIH) Laboratory of Neuropsychology Section on Neural Coding and Computation Bethesda, USA |
June 2004 | Ph.D. Computational Neuroscience DTU and Nordic Institute for Theoretical Physics (NORDITA), Advisor: John Hertz "Dynamics of Large Spiking Neural Networks - Modeling Circuits in the Central Nervous System" Copenhagen, Denmark |
June 1999 | M.Sc. Applied Mathematics - Mathematical Computer Science Vienna University of Technology, Advisor: Kurt Hornik "Analysis of Incomplete Multivariate Data with Computational Neural Networks" Vienna, Austria |
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[ Top ] | [ Research ] | [ Publications ] | [ Short Bio ] | [ Contact ] |