The title of the
individual research
project at CBL is:
"Clustered plasticity and network emergent states"
The fellow will
focus on the mathematical
investigation and machine-learning classification of
collective electrical
properties, emerging in neuronal networks coupled to
multielectrode arrays and
neuroelectronic hybrids. Specifically, he/she will first use
patch clamp
recordings to study the passive and active
electrophysiological properties of
neurons in in vitro
neuronal networks
as well as the presence of synaptic currents following
electrical stimulation.
In addition, different stimulation protocols will be applied
to study whether
neuronal networks express specific types of plasticity. We are
mostly
interested in identifying stimuli that are predicted
theoretically to give rise
to highly interconnected neuronal sub-networks.
He/she will then explore the consequences of clustered plasticity rules in conductance-based model neurons. Modeling studies will be performed using the NEURON simulation environment in order to build a network of detailed compartmental models of neurons, where synapses capable of exhibiting plasticity properties like the ones recorded in the physiological experiments will be incorporated. Models will be used to generate predictions about how specific stimuli delivered either to randomly selected neurons in a distributed manner throughout the model system or to nearby neurons in a specific location (clustered) of the model system could alter the electrical and/or structural properties of the network.
He/she will then explore the consequences of clustered plasticity rules in conductance-based model neurons. Modeling studies will be performed using the NEURON simulation environment in order to build a network of detailed compartmental models of neurons, where synapses capable of exhibiting plasticity properties like the ones recorded in the physiological experiments will be incorporated. Models will be used to generate predictions about how specific stimuli delivered either to randomly selected neurons in a distributed manner throughout the model system or to nearby neurons in a specific location (clustered) of the model system could alter the electrical and/or structural properties of the network.
The methodologies to be used in this
project include patch-clamp
recordings and
computational modelling, therefore the fellow should ideally have previous
training in both or either of these
techniques.
According
to the eligibility criteria, the fellow MUST
NOT
1.
be
a Greek citizen,
2.
have
resided or carried out his/her main activity (work, studies,
etc.) in Greece
for more than 12 months in the last 3 years immediately prior
to April 1st 2012.
3.
have
worked in a research position / received research training for
more than 5 years
of his/her undergraduate degree.
Start date:
Immediately
Candidates
that match the required profile will be continuously
interviewed until the
position is filled. Candidates
should send a resume
and two (2)
reference letters to poirazi[at]imbb.forth.gr. If
possible, recommendations
should be send by the referees directly by email at poirazi[at]imbb.forth.gr.
-- Panayiota Poirazi, Ph.D. Research Associate Professor Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton P.O.Box 1385 GR 711 10 Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi@imbb.forth.gr URL: http://www.imbb.forth.gr/personal_page/poirazi.html
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