Wulfram Gerstner - Research
My research is generously funded by the
by the European Community in the projects
as well as by an
ERC Advanced Investigator Grant.
Current research projects in my group cover
the following areas:
Temporal Coding in Networks of Spiking Neurons .
At the LCN, as in many other labs, we have routinely
used integrate-and-fire neurons and variants
thereof to study temporal coding properties of spiking neurons.
We have developed the Spike Response Model that emphasizes
refractory properties of the neuron, as well as
the adaptive exponential integrate-and-fire model (AdEx).
Recently, we explored whether these neuron models can be used
to predict neuronal activity in slice experiments
on a spike-by-spike basis under random-current or random-conductance
Research in this area is persued by
my PhD students and PostDocs
Richard Naud, Christian Pozzorini, Felipe Gerhard, Skander Mensi
and Tim Vogels
See also our
book on Spiking Neuron Models
as well as the recent papers
Badel et al. (2008) and
Jolivet et al. (2006)
or the short review from 2009
Spike-timing dependent plasticity (STDP) and learning.
I have been interest in the precise temporal
conditions for synaptic plasticity since
1993 when we published a first paper
in Biological Cybernetics.
An STDP function with two phases (LTP for
pre- before post and LTD for inverse timing)
has been studied for the first time
in a model of the barn owl auditory system -
published in a Nature paper in 1996,
slightly before the first experimental results on STDP
In view of the wealth of experimental results,
we have developed modern version of STDP models
that emphasize triplets of spikes and the relation
to BCM learning rules, as well as the relation
to reinforcement learning.
PhD students and PostDocs
Lorric Ziegler, Guillaume Hennequin,
and Tim Vogels
continue this modeling effort.
See our early papers in
Biological Cybernetics (1993)
as well as the recent articles of
Pfister et al. (2006) in Neural Computation
Toyoizumi et al. (2005) in Proc. Natl. Acad. Sciences
Clopath et al. (2010) in Nature Neuroscience .
See also the short review of
STDP in Scholapedia
as well as the recent work on
Reward-modulated STDP in J. Neuroscience (2010)
Link to Behavior and Psychophysics.
On a different line of research, I have been interested
for many years in how
spatial representation by place cells
can be implememted in a biologically plausible
model. Many models
only look at the problem of navigation,
given an existing representation by
a set of hippocampal place cells.
Together with my former PhD-student
we have developed a method to automatically create
place fields with unsupervised growing networks
while a robot moving around in an environment.
My current PhD students Ricardo Chavariaga, Tomas Stroesslin,
and Denis Sheynikhovich have persued this research further.
In particular we have focused on questions of how
the geometrical and non-geometrical features
of the environment influence different navigational strategies.
The model is learning using combinations
of unsupervised Hebbian learning for the place cells
and reinforcement learning for the choice of actions.
See the papers of
Arleo and Gerstner 2000
Sheynikhovich et al. 2005
as well as the recent article of
Sheynikhovich et al. 2009 in Psychological Reviews .
The project is finished.
Together with my colleague Carmen Sandi at EPFL
I have co-supervised Gedi Luksys as a PhD studetns
so as to explain
behavioral learning data in rodents under different
stress conditions with a reinforcement learning model.
See Luksys, Gerstner, and Sandi (2009) in
Nature Neuroscience 12:1180-1186
Together with my colleague Olaf Blanke I co-supervise
Danilo Jimenez Rezende to explore models that would
explain the bodily self.
Together with my colleague Michael Herzog
we work on psychophysics of decision making
with ultra-short stimuli.
Back to home page of Wulfram Gerstner.
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